less_retarded_wiki

by drummyfish, generated on 10/21/23, available under CC0 1.0 (public domain)

21st Century

21st century, known as the Age Of Shit, is already one of the worst centuries in history despite only being around shortly.

3D Modeling

The topic of 3D modeling will be part of article about 3D models.

3D Model

In the world of computers (especially in computer graphics, but also e.g. in physics simulations etc.) 3D model is a representation of a three dimensional object, for example of a real life object such as a car, tree or a dog, but also possibly something more abstract like a fractal or function plot surface. 3D models can be displayed using various 3D rendering techniques and are used mostly to simulate real world on computers (e.g. games), as real world is, as we know, three dimensional. 3D models can be created in several ways, e.g. manually with 3D modelling software (such as Blender) by 3D artists, by 3D scanning real world objects, or automatically by procedural generation.

3D models can be represented in many ways -- the mainstream "game" 3D models that most people are used to seeing are polygonal (made of triangles) boundary-representation (recording only surface, not volume) textured (with "pictures" on their surface) 3D models, but keep in mind many different ways are possible and used too, for example various volume representations, voxel models, point clouds, implicit surfaces, spline surfaces, constructive solid geometry, wireframe etc. Models may also bear additional extra information and features, e.g. bone rigs for animation, animation key frames, density information, LODs and so on.

TODO: classification, operations (subdivision, booleans, ...), texturing, animation, formats, ...

3D Modeling: Learning It And Doing It Right

WORK IN PROGRESS

Do you want to start 3D modeling? Or do you already know a bit about it and just want some advice to get better? Then let us share a few words of advice here.

Nowadays as a FOSS user you will most likely do 3D modeling with Blender -- we recommended it to start learning 3D modeling as it is powerful, free, gratis, has many tutorials etc. Do NOT use anything proprietary no matter what anyone tells you! Once you know a bit about the art, you may play around with alternative programs or approaches (such as writing programs that generate 3D models etc.). However as a beginner just start with Blender, which is from now on in this article the software we'll suppose you're using.

Start extremely simple and learn bottom-up, i.e. learn about fundamentals and low level concepts and start with very simple models (e.g. simple untextured low-poly shape of a house, box with a roof), keep creating more complex models by small steps. Do NOT fall into the trap of "quick and easy magic 3D modeling" such as sculpting or some "smart apps" without knowing what's going on at the low level, you'll end up creating extremely ugly, inefficient models in bad formats, like someone wanting to create space rockets without learning anything about math or physics first. Remember to practice, practice, practice -- eventually you learn by doing, so try to make small projects and share your results on sites such as opengameart to get feedback and some mental satisfaction and reward for your effort. The following is an outline of possible steps you may take towards becoming an alright 3D artist:

1. Learn what 3D model actually is, basic technical details about how a computer represents it and roughly how 3D rendering works. It is EXTREMELY important to have at least some idea about the fundamentals, i.e. you should learn at least the following:

• 3D models that are used today consist of vertices and triangles (though higher polygons are usually supported in modeling software, everything is broken down to triangles eventually), computers usually store arrays of vertices and triangles as indices pointing to the array of vertices. Triangles have facing (front and back side, determined by the order of its vertices). These 3D models only represent the boundary (not the volume). All this is called the model's geometry.
• Normals are vectors "perpendicular to the surface", they can be explicitly modified and stored or computed automatically and they are extremely important because they say how the model interacts with light (they are used in shading of the model), i.e. which edges appear sharp or smooth. Normal maps are textures that can be used to modify normals to make the surface seem rough or otherwise deformed without actually modifying the geometry. You HAVE TO understand normals.
• Textures are images (or similar image-like data) that can be mapped to the model surface to "paint it" (or give it other material properties). They are mapped to models by giving vertices texturing UV coordinates. To make textures you'll need some basics of 2D image editing (see e.g. GIMP).
• 3D rendering (and also modeling) works with the concept of a scene in which a number of models reside, as well as a virtual camera (or multiple ones), lights and other objects. These objects have transformations (normally translation, rotation and scale, represented by matrices) and may form a hierarchy, so called scene graph (some objects may be parents of other objects, meaning the child transformations are relative to parents) etc.
• A 3D renderer will draw the triangles the model consists of by applying shading to determine color of each pixel of the rasterized triangle. Shading takes into account besides others texture(s) of the model, its material properties and light falling on the model (in which the model normals play a big role). Shading can be modified by creating shaders (if you don't create custom shaders, some default one will be used).
• Briefly learn about other concepts such as low/high poly modeling and basic 3D formats such as OBJ and COLLADA (which features they support etc.), possible other models representations (voxels, point clouds, ...) etc.

2. Manually create a few extremely simple low-poly untextured models, e.g. that of a simple house, laptop, hammer, bottle etc. Keep the vertex and triangle count very low (under 100), make the model by MANUALLY creating every vertex and triangle and focus only on learning this low level geometry manipulation well (how to create a vertex, how to split an edge, how to rotate a triangle, ...), making the model conform to good practice and get familiar with tools you're using, i.e. learn the key binds, locking movement direction to principal axes, learn manipulating your 3D view, setting up the free/side/front/top view with reference images etc. Make the model nice! I.e. make it have correctly facing triangles (turn backface culling on to check this), avoid intersecting triangles, unnecessary triangles and vertices, remove all duplicate vertices (don't have multiple vertices with the same position), connect all that should be connected, avoid badly shaped triangles (e.g. extremely acute/long ones) etc. Also learn about normals and make them nice! I.e. try automatic normal generation (fiddle e.g. with angle thresholds for sharp/smooth edges), see how they affect the model look, try manually marking some edges sharp, try out smoothing groups etc. Save your final models in OBJ format (one of the simplest and most common formats supporting all you need at this stage). All this will be a lot to learn, that's why you must not try to create a complex model at this stage. You can keep yourself "motivated" e.g. by aiming for creating a low-poly model collection you can share at opengameart or somewhere :)
3. Learn texturing -- just take the models you have and try to put a simple texture on them by drawing a simple image, then unwrapping the UV coordinates and MANUALLY editing the UV map to fit on the model. Again the goal is to get familiar with the tools and concepts now; experiment with helpers such as unwrapping by "projecting from 3D view", using "smart" UV unwrap etc. Make the UV map nice! Just as model geometry, UV maps also have good practice -- e.g. you should utilize as many texture pixels as possible (otherwise you're wasting space in the image), watch out for color bleeding, the mapping should have kind of "uniform pixel density" (or possibly increased density on triangles where more details is supposed to be), some pixels of the texture may be mapped to multiple triangles if possible (to efficiently utilize them) etc. Only make a simple diffuse texture (don't do PBR, material textures etc., that's too advanced now). Try out texture painting and manual texture creation in a 2D image program, get familiar with both.
4. Learn modifiers and advanced tools. Modifiers help you e.g. with the creation of symmetric models: you only model one side and the other one gets mirrored. Subdivide modifier will automatically create a higher poly version of your model (but you need to help it by telling it which sides are sharp etc.). Boolean operations allow you to apply set operations like unification or subtraction of shapes (but usually create a messy geometry you have to repair!). There are many tools, experiment and learn about their pros and cons, try to incorporate them to your modeling.
5. Learn retopology and possibly sculpting. Topology is an extremely important concept -- it says what the structure of triangles/polygons is, how they are distributed, how they are connected, which curves their edges follow etc. Good topology has certain rules (e.g. ideally only being composed of quads, being denser where the shape has more detail and sparser where it's flat, having edges so that animation won't deform the model badly etc.). Topology is important for efficiency (you utilize your polygon budget well), texturing and especially animation (nice deformation of the model). Creating more complex models is almost always done in the following two steps:

• Creating the shape while ignoring topology, for example with sculpting (but also other techniques, e.g. just throwing shapes together). The goal is to just make the desired shape.
• Retopology: creating a nice topology for the shape while keeping the shape unchanged. This is done by starting modeling from the start with the "stick to surface" option, i.e. whenever you create or move a vertex, it sticks to the nearest surface (surface of the created shape). Here you just try to create a new "envelope" on the existing shape while focusing on making the envelope's topology nice.

6. Learn about materials and shaders. At this point you may learn about how to create custom shaders, how to create transparent materials, apply multiple textures, how to make realistic skin, PBR shaders etc. You should at least be aware of basic shading concepts and commonly encountered techniques such as Phong shading, subsurface scattering, screen space effects etc. because you'll encounter them in shader editors and you should e.g. know what performance penalties to expect.
7. Learn animation. First learn about keyframes and interpolation and try to animate basic transformations of a model, e.g. animate a car driving through a city by keyframing its position and rotation. Then learn about animating the model's geometry -- first the simple, old way of morphing between different shapes (shape keys in Blender). Finally learn the hardest type of animation: skeletal animation. Learn about bones, armatures, rigging, inverse kinematics etc.
8. Now you can go crazy and learn all the uber features such as hair, physics simulation, NURBS surfaces, boob physics etc.

Don't forget to stick to LRS principles! This is important so that your models are friendly to good technology. I.e. even if "modern" desktops don't really care about polygon count anymore, still take the effort to optimize your model so as to not use more polygons that necessary! Your models may potentially be used on small, non-consumerist computers with software renderers and low amount of RAM. Low-poly is better than high-poly (you can still prepare your model for automatic subdivision so that obtaining a higher poly model from it automatically is possible). Don't use complex stuff such as PBR or skeletal animation unless necessary -- you should mostly be able to get away with a simple diffuse texture and simple keyframe morphing animation, just like in old games! If you do use complex stuff, make it optional (e.g. make a normal map but don't rely on it being used in the end).

Good luck with your modeling!

3D Rendering

In computer graphics 3D rendering is concerned with computing images that represent a projected view of 3D objects through a virtual camera.

There are many methods and algorithms for doing so differing in many aspects such as computation complexity, implementation complexity, realism of the result, representation of the 3D data, limitations of viewing and so on. If you are just interested in the realtime 3D rendering used in gaymes nowadays, you are probably interested in GPU-accelerated 3D rasterization with APIs such as OpenGL and Vulkan.

LRS has a 3D rendering library called small3dlib.

Methods

As most existing 3D "frameworks" are harmful, a LRS programmer is likely to write his own 3D rendering system that suits his program best, therefore we should list some common methods of achieving 3D. Besides that, it's just pretty interesting to see what there is in the store.

Rendering spectrum: The book Real-Time Rendering mentions that methods for 3D rendering can be seen as lying on a spectrum, one extreme of which is appearance reproduction and the other physics simulation. Methods closer to trying to imitate the appearance try to simply focus on imitating the look of an object on the monitor that the actual 3D object would have in real life, without being concerned with how that look arises in real life -- these may e.g. use image data such as photographs; these methods may rely on lightfields, photo textures etc. The physics simulation methods try to replicate the behavior of light in real life -- their main goal is to solve the rendering equation, usually only approximately -- and so, through internally imitating the same processes, come to similar visual results that arise in real world: these methods rely on creating 3D geometry (e.g. that made of triangles or voxels), computing light reflections and global illumination. Most methods lie somewhere in between these two extremes: for example billboards and particle systems may use a texture to represent an object while at the same time using 3D quads (very simple 3D models) to correctly deform the textures by perspective and solve their visibility. The classic polygonal 3D models are also usually somewhere in between: the 3D geometry and shading are trying to simulate the physics, but e.g. a photo texture mapped on such 3D model is the opposite appearance-based approach (PBR further tries to shift the use of textures more towards the physics simulation end).

A table of some common 3D rendering methods follows, including the most simple, most advanced and some unconventional ones. Note that here we talk about methods and techniques rather than algorithms, i.e. general approaches that are often modified and combined into a specific rendering algorithm. For example the traditional triangle rasterization is sometimes combined with raytracing to add e.g. realistic reflections. The methods may also be further enriched with features such as texturing, antialiasing and so on. The table below should help you choose the base 3D rendering method for your specific program.

The methods may be tagged with the following:

• 2.5D: primitive 3D, often called pseudo 3D or fake 3D, having significant limitations e.g. in degrees of freedom of the camera
• off: slow method usually used for offline (non-realtime) rendering (even though they indeed may run in real time e.g. with the help of powerful GPUs)
• IO vs OO: image order (rendering by pixels) vs object order (rendering by objects)

TODO: Rescue On Fractalus!

TODO: find out how build engine/slab6 voxel rendering worked and possibly add it here (from http://advsys.net/ken/voxlap.htm seems to be based on raycasting)

TODO: VoxelQuest has some innovative voxel rendering, check it out (https://www.voxelquest.com/news/how-does-voxel-quest-work-now-august-2015-update)

3D Rendering Basics For Nubs

If you're a complete noob and are asking what the essence of 3D is or just how to render simple 3Dish pictures for your game without needing a PhD, here's the very basics. Yes, you can use some 3D engine such as Godot that has all the 3D rendering preprogrammed, but you you'll surrender to bloat, you won't really know what's going on and your ability to tinker with the rendering or optimizing it will be basically zero... AND you'll miss on all the fun :) So here we just foreshadow some concepts you should start with if you want to program your own 3D rendering.

The absolute basic thing in 3D is probably perspective, or the concept which says that "things further away look smaller". This is basically the number one thing you need to know and with which you can make simple 3D pictures, even though there are many more effects and concepts that "make pictures look 3D" and which you can potentially study later (lighting, shadows, focus and blur, stereoscopy, parallax, visibility/obstruction etc.). { It's probably possible to make something akin "3D" even without perspective, just with orthographic projection, but that's just getting to details now. Let's just suppose we need perspective. ~drummyfish }

If you don't have rotating camera and other fancy things, perspective is actually mathematically very simple, you basically just divide the object's size by its distance from the viewer, i.e. its Z coordinate (you may divide by some multiple of Z coordinate, e.g. by 2 * Z to get different field of view) -- the further away it is, the bigger number its size gets divided by so the smaller it becomes. This "dividing by distance" ultimately applies to all distances, so in the end even the details on the object get scaled according to their individual distance, but as a first approximation you may just consider scaling objects as a whole. Just keep in mind you should only draw objects whose Z coordinate is above some threshold (usually called a near plane) so that you don't divide by 0! With this "dividing by distance" trick you can make an extremely simple "3Dish" renderer that just draws sprites on the screen and scales them according to the perspective rules (e.g. some space simulator where the sprites are balls representing planets). There is one more thing you'll need to handle: visibility, i.e. nearer objects have to cover the further away objects -- you can do this by simply sorting the objects by distance and drawing them back-to-front (painter's algorithm).

Here is some "simple" C code that demonstrates perspective and draws a basic animated wireframe cuboid as ASCII in terminal:

#include <stdio.h>

#define SCREEN_W 50       // ASCII screen width
#define SCREEN_H 22       // ASCII screen height
#define LINE_POINTS 64    // how many points for drawing a line
#define FOV 8             // affects "field of view"
#define FRAMES 30         // how many animation frames to draw

char screen[SCREEN_W * SCREEN_H];

void showScreen(void)
{
  for (int y = 0; y < SCREEN_H; ++y)
  {
    for (int x = 0; x < SCREEN_W; ++x)
      putchar(screen[y * SCREEN_W + x]);

    putchar('\n');
  }
}

void clearScreen(void)
{
  for (int i = 0; i < SCREEN_W * SCREEN_H; ++i)
    screen[i] = ' ';
}

// Draws point to 2D ASCII screen, [0,0] means center.
int drawPoint2D(int x, int y, char c) 
{
  x = SCREEN_W / 2 + x;
  y = SCREEN_H / 2 + y;

  if (x >= 0 && x < SCREEN_W && y >= 0 && y <= SCREEN_H)
    screen[y * SCREEN_W + x] = c;
}

// Divides coord. by distance taking "FOV" into account => perspective.
int perspective(int coord, int distance)
{
  return (FOV * coord) / distance;
}

void drawPoint3D(int x, int y, int z, char c)
{
  if (z <= 0)
    return; // at or beyond camera, don't draw

  drawPoint2D(perspective(x,z),perspective(y,z),c);
}

int interpolate(int a, int b, int n)
{
  return a + ((b - a) * n) / LINE_POINTS;
}

void drawLine3D(int x1, int y1, int z1, int x2, int y2, int z2, char c)
{
  for (int i = 0; i < LINE_POINTS; ++i) // draw a few points to form a line
    drawPoint3D(interpolate(x1,x2,i),interpolate(y1,y2,i),interpolate(z1,z2,i),c);
}

int main(void)
{
  int shiftX, shiftY, shiftZ;

  #define N 12  // side length
  #define C '*'

  // cuboid points:
  //      X                   Y            Z
  #define PA -2 * N + shiftX, N + shiftY,  N + shiftZ
  #define PB 2 * N + shiftX,  N + shiftY,  N + shiftZ
  #define PC 2 * N + shiftX,  N + shiftY,  2 * N + shiftZ
  #define PD -2 * N + shiftX, N + shiftY,  2 * N + shiftZ
  #define PE -2 * N + shiftX, -N + shiftY, N + shiftZ
  #define PF 2 * N + shiftX,  -N + shiftY, N + shiftZ
  #define PG 2 * N + shiftX,  -N + shiftY, 2 * N + shiftZ
  #define PH -2 * N + shiftX, -N + shiftY, 2 * N + shiftZ

  for (int i = 0; i < FRAMES; ++i) // render animation
  {
    clearScreen();

    shiftX = -N + (i * 4 * N) / FRAMES; // animate
    shiftY = -N / 3 + (i * N) / FRAMES;
    shiftZ = 0; 

    // bottom:
    drawLine3D(PA,PB,C); drawLine3D(PB,PC,C); drawLine3D(PC,PD,C); drawLine3D(PD,PA,C);

    // top:
    drawLine3D(PE,PF,C); drawLine3D(PF,PG,C); drawLine3D(PG,PH,C); drawLine3D(PH,PE,C);

    // sides:
    drawLine3D(PA,PE,C); drawLine3D(PB,PF,C); drawLine3D(PC,PG,C); drawLine3D(PD,PH,C);

    drawPoint3D(PA,'A'); drawPoint3D(PB,'B'); // corners
    drawPoint3D(PC,'C'); drawPoint3D(PD,'D');
    drawPoint3D(PE,'E'); drawPoint3D(PF,'F');
    drawPoint3D(PG,'G'); drawPoint3D(PH,'H');

    showScreen();

    puts("press key to animate");
    getchar();
  }

  return 0;
}

One frame of the animation should look like this:

                 E*******************************F
                 * *                       ***   *
                 *  **                 ***       *
                 *   H***************G*          *
                 *   *               *           *
                 *   *               *           *
                 *   *               *           *
                 *   *               *           *
                 *   *               *           *
                 *   *               *           *
                 *   D***************C           *
                 *  **                ***        *
                 *  *                    *       *
                 * *                       **    *
                 ***                         * * *
                 A*******************************B

press key to animate

Mainstream Realtime 3D

You may have come here just to learn about the typical realtime 3D rendering used in today's games because aside from research and niche areas this kind of 3D is what we normally deal with in practice. This is what this section is about.

Nowadays "game 3D" means a GPU accelerated 3D rasterization done with rendering APIs such as OpenGL, Vulkan, Direct3D or Metal (the last two being proprietary and therefore shit) and higher level engines above them, e.g. Godot, OpenSceneGraph etc. The methods seem to be evolving to some kind of rasterization/pathtracing hybrid, but rasterization is still the basis.

This mainstream rendering uses an object order approach (it blits 3D objects onto the screen rather than determining each pixel's color separately) and works on the principle of triangle rasterization, i.e. 3D models are composed of triangles (or higher polygons which are however eventually broken down into triangles) and these triangles are projected onto the screen according to the position of the virtual camera and laws of perspective. Projecting the triangles means finding the 2D screen coordinates of each of the triangle's three vertices -- once we have thee coordinates, we draw (rasterize) the triangle to the screen just as a "normal" 2D triangle (well, with some asterisks).

Furthermore things such as z-buffering (for determining correct overlap of triangles) and double buffering are used, which makes this approach very memory (RAM/VRAM) expensive -- of course mainstream computers have more than enough memory but smaller computers (e.g. embedded) may suffer and be unable to handle this kind of rendering. Thankfully it is possible to adapt and imitate this kind of rendering even on "small" computers -- even those that don't have a GPU, i.e. with pure software rendering. For this we e.g. replace z-buffering with painter's algorithm (triangle sorting), drop features like perspective correction, MIP mapping etc. (of course quality of the output will go down).

Also additionally there's a lot of bloat added in such as complex screen space shaders, pathtracing (popularly known as raytracing), megatexturing, shadow rendering, postprocessing, compute shaders etc. This may make it difficult to get into "modern" 3D rendering. Remember to keep it simple.

On PCs the whole rendering process is hardware-accelerated with a GPU (graphics card). GPU is a special hardware capable of performing many operations in parallel (as opposed to a CPU which mostly computes sequentially with low level of parallelism) -- this is ideal for graphics because we can for example perform mapping and drawing of many triangles at once, greatly increasing the speed of rendering (FPS). However this hugely increases the complexity of the whole rendering system, we have to have a special API and drivers for communication with the GPU and we have to upload data (3D models, textures, ...) to the GPU before we want to render them. Debugging gets a lot more difficult. So again, this is bloat, consider avoiding GPUs.

GPUs nowadays are no longer just focusing on graphics, but are kind of a general device that can be used for more than just 3D rendering (e.g. crypto mining, training AI etc.) and can no longer even perform 3D rendering completely by themselves -- for this they have to be programmed. I.e. if we want to use a GPU for rendering, not only do we need a GPU but also some extra code. This code is provided by "systems" such as OpenGL or Vulkan which consist of an API (an interface we use from a programming language) and the underlying implementation in a form of a driver (e.g. Mesa3D). Any such rendering system has its own architecture and details of how it works, so we have to study it a bit if we want to use it.

The important part of a system such as OpenGL is its rendering pipeline. Pipeline is the "path" through which data go through the rendering process. Each rendering system and even potentially each of its version may have a slightly different pipeline (but generally all mainstream pipelines somehow achieve rasterizing triangles, the difference is in details of how they achieve it). The pipeline consists of stages that follow one after another (e.g. the mentioned mapping of vertices and drawing of triangles constitute separate stages). A very important fact is that some (not all) of these stages are programmable with so called shaders. A shader is a program written in a special language (e.g. GLSL for OpenGL) running on the GPU that processes the data in some stage of the pipeline (therefore we distinguish different types of shaders based on at which part of the pipeline they reside). In early GPUs stages were not programmable but they became so as to give a greater flexibility -- shaders allow us to implement all kinds of effects that would otherwise be impossible.

Let's see what a typical pipeline might look like, similarly to something we might see e.g. in OpenGL. We normally simulate such a pipeline also in software renderers. Note that the details such as the coordinate system handedness and presence, order, naming or programmability of different stages will differ in any particular pipeline, this is just one possible scenario:

1. Vertex data (e.g. 3D model space coordinates of triangle vertices of a 3D model) are taken from a vertex buffer (a GPU memory to which the data have been uploaded).
2. Stage: vertex shader: Each vertex is processed with a vertex shader, i.e. one vertex goes into the shader and one vertex (processed) goes out. Here the shader typically maps the vertex 3D coordinates to the screen 2D coordinates (or normalized device coordinates) by:

• multiplying the vertex by a model matrix (transforms from model space to world space, i.e. applies the model move/rotate/scale operations)
• multiplying by view matrix (transforms from world space to camera space, i.e. takes into account camera position and rotation)
• multiplying by projection matrix (applies perspective, transforms from camera space to screen space in homogeneous coordinates)

3. Possible optional stages that follow are tessellation and geometry processing (tessellation shaders and geometry shader). These offer possibility of advanced vertex processing (e.g. generation of extra vertices which vertex shaders are unable to do).
4. Stage: vertex post processing: Usually not programmable (no shaders here). Here the GPU does things such as clipping (handling vertices outside the screen space), primitive assembly and perspective divide (transforming from [homogeneous coordinates](homogeneous coordinates.md) to traditional cartesian coordinates).
5. Stage: rasterization: Usually not programmable, the GPU here turns triangles into actual pixels (or fragments), possibly applying backface culling, perspective correction and things like stencil test and depth test (even though if fragment shaders are allowed to modify depth, this may be postpones to later).
6. Stage: pixel/fragment processing: Each pixel (fragment) produced by rasterization is processed here by a pixel/fragment shader. The shader is passed the pixel/fragment along with its coordinates, depth and possibly other attributes, and outputs a processed pixel/fragment with a specific color. Typically here we perform shading and texturing (pixel/fragment shaders can access texture data which are again stored in texture buffers on the GPU).
7. Now the pixels are written to the output buffer which will be shown on screen. This can potentially be preceded by other operations such as depth tests, as mentioned above.

TODO: example of specific data going through the pipeline

42

"HAHAHAHAHAHAHAHAHAHHHHAAA BAZINGA" --Sheldon fan

42 is an even integer with prime factorization of 2 * 3 * 7. This number was made kind of famous (and later overused in pop culture to the point of completely destroying the joke) by Douglas Adams' book The Hitchhiker's Guide to the Galaxy in which it appears as the answer to the ultimate question of life, the Universe and everything (the point of the joke was that this number was the ultimate answer computed by a giant supercomputer over millions of years, but it was ultimately useless as no one knew the question to which this number was the answer).

If you make a 42 reference in front of a TBBT fan, he will shit himself.

4chan

{ haha https://lolwut.info/comp/4chan/4chan-g.html ~drummyfish }

4chan (https://4chan.org/) is the most famous image board. As most image boards, 4chan has a nice, oldschool minimalist look, even though it contains shitty captchas for posting and the site's code is proprietary. The site tolerates a great amount of free speech up to the point of being regularly labeled "right-wing extremist site" (although bans for stupid reasons such as harmless pedo jokes are very common, speaking from experience). Being a "rightist paradise" it is commonly seen as a rival to reddit, aka the pseudoleftist paradise -- both forums hate each other to death. The discussion style is pretty nice, there are many nice stories and memes (e.g. the famous greentexts) coming from 4chan but it can also be a hugely depressing place just due to the shear number of retards with incorrect opinions.

The site consists of multiple boards, each with given discussion topic and rules. The most (in)famous boards are likely politically incorrect AKA /pol/, where most of the american school shooters hang around, and random AKA /b/ which is just a shitton of meme shitposting, porn, toxicity, fun, trolling and retardedness.

For us the most important part of 4chan is the technology board known as /g/ (for technoloGEE). Browsing /g/ can bring all kinds of emotion, it's a place of relative freedom and somewhat beautiful chaos where all people from absolute retards to geniuses argue about important and unimportant things, brands, tech news and memes, and constantly advise each other to kill themselves. Sometimes the place is pretty toxic and not good for mental health, actually it is more of a rule than an exception.

As of 2022 /g/ became unreadable, ABANDON SHIP. The board became flooded with capitalists, cryptofascists, proprietary shills, productivity freaks and other uber retards, it's really not worth reading anymore. You can still read good old threads on archives such as https://desuarchive.org/g/page/280004/.

See Also

• something awful

Aaron Swartz

"I think all censorship should be deplored." --Aaron Swartz

TODO

Abstraction

Abstraction is an important concept in programming, mathematics and other fields of science, philosophy and art, which in simple words can be described as "viewing an issue from a distance", thinking in higher-level concepts, i.e. paying less attention to fine detail so that one can see the bigger picture. In programming for example we distinguish programming languages of high and low level of abstraction, depending on how close they are "to the hardware" (e.g. assembly being low level, JavaScript being high level); in art high abstraction means portraying and capturing things such as ideas, feelings and emotions with shapes that may seem "distant", not resembling anything concrete or familiar. We usually talk about different levels of abstraction, depending on the "distance" we take in vieweing the issue at hand -- this concept may very well be demonstrated on sciences: particle physics researches the world at the lowest level of abstraction, in extreme close-up, for example by examining individual atoms that make up our brains, while biology resides at a higher level of abstraction, viewing the brain at the level of individual cells, and finally psychology shows a very high level of abstraction because it looks at the brain from great distance and just studies its behavior.

In mainstream programming education it is generally taught to "abstract as much as possible" because that's aligned with the capitalist way of technology -- high abstraction is easy to handle for incompetent programming monkeys, it helps preventing them from making damage by employing billions of safety mechanisms, it also perpetuates the cult of never stopping layering of the abstraction sandwich, creating bloat, bullshit jobs, it makes computers slower, constantly outdated and so drives software consumerism. This is extremely wrong. LRS advocates to employ only as little abstraction as needed, so as to support minimalism, i.e. too much abstraction is bad. For example a widely used general purpose programming language should basically only have as much abstraction as to allow portability, it should definitely NOT succumb high abstraction such as object obsessed programming.

In a more detailed view abstraction is not one-dimensional, we may abstract in different directions ("look at the issue from different angles"); for example functional, logic and object paradigms are different ways of abstracting from the low level, each one in different way. So the matter of abstracting is further complicated by trying to choose the right abstraction -- one kind of abstraction may work well for certain kinds of problems (i.e. solving these problems will become simple when applying this abstraction) but badly for other kinds of problems.

Let's take a look at a possible division of a computer to different levels of abstraction, from lowest to highest (keep in mind it's also possible to define the individual levels differently):

• physics: Computer is a collection of atoms and subatomic particles such as electrons, operating with terms such as energy, charge, spin or quantum effects.
• electronic circuit: Computer is an analog circuit in which electricity flows through wires and electronic components, operating with terms such as voltage, current, transistor, resistor or electronic interference.
• logic circuit: Computer is a binary digital circuit; this is abstracting electricity away, now we are only considering two possible values carried by the wires: 1s and 0s. Operating with terms such as logic gate, logic function, multiplexer or sequential circuit.
• machine code/assembly: Computer is a machine with a specific instruction architecture, executing an algorithm encoded as simple binary instructions, such as "add two numbers" or "write a number to memory", in a specific format that's different for different types of computers. Operating with terms such as CPU cycle, opcode, register, memory or interrupt.
• low level portable language: Computer is a machine capable of performing algorithms written in a structured language resembling human language and it's a machine that's essentially the same as other computers, even of different types, i.e. all computers can understand the same language (programs are portable), typically e.g. C. Operating with terms such as structured data type, procedure, signed/unsigned type, memory management etc.
• high level language: Computer is a machine capable of performing algorithms while handling many things (such as memory allocation or ensuring safety) automatically and dynamically (on-the-go) and understanding more complex and abstract descriptions of problems, allowing for very fast and comfortable programming in languages like Python or JavaScript. Operating with terms such as objects, dictionaries, pure functions and polymorphism.
• very high level, artificial intelligence: Computer is a machine capable of simulating human thinking and therefore able to lead a conversation with human, it can perform commands given in natural language and even reason and create on its own. Operating with terms such as training, data sets and ethics.

Acronym

Acronym is an abbreviation of a multiple word term by usually appending the starting letters of each word to form a new word.

Here is a list of some acronyms:

• AA (anti aliasing)
• AC (alternating current, air conditioning)
• AD (anno domini)
• ACID (atomicity consistency isolation durability)
• ACK (acknowledgement)
• ADSL (asymmetric digital subscriber line)
• AF (as fuck)
• AFAIK (as far as I know)
• AJAX (asynchronous JavaScript and XML)
• AFK (away from keyboard)
• ALU (arithmetic logic unit)
• AM (amplitude modulation)
• ANCAP (anarcho capitalist)
• ANPAC (anarcho pacifist)
• ANSI (american national standards institute)
• AO (ambient occlusion)
• API (application programming interface)
• ARM (advanced RISC machines)
• ARPANET (advanced research projects agency network)
• ASAP (as soon as possible)
• ASCII (American standard code for information interchange)
• ASM (assembly)
• ATM (at the moment, automated teller machine)
• B (byte, bit)
• B4 (before)
• BASH (bourne again shell)
• BASIC (beginner all purpose symbolic instruction code)
• BBC (big black cock)
• BBS (bulletin board system)
• BC (bytecode, before Christ)
• BCD (binary coded decimal)
• BDFL (benevolent dictator for life)
• BDSM (bondage domination sadism masochism)
• BF (brainfuck)
• BG (background, bad game)
• BGR (blue green red)
• BIOS (basic input/output system)
• BJ (blow job)
• BJT (bipolar junction transistor)
• BS (bullshit)
• BSD (Berkeley software distribution)
• BTFO (blown the fuck out)
• CAD (computer aided design)
• CAPTCHA (completely automated public Turing test to tell computers and humans apart)
• CC (creative commons)
• CC0 (creative commons zero)
• CD (compact disc, change directory)
• CEO (chief executive officer)
• CGI (computer generated imagery)
• CISC (complex instruction set computer)
• CLI (command line interface)
• CMOS (complementary metal oxide semiconductor)
• CMS (content management system)
• CMYK (cyan magenta yellow key)
• COMPSCI (computer science)
• CP (child porn, copy)
• CPU (central processing unit)
• CRC (cyclic redundancy check)
• CRT (cathode ray tube)
• CSG (constructive solid geometry)
• CSS (cascading style sheet)
• CSV (comma separated values)
• DAC (digital analog converter)
• DB (database)
• DC (direct current)
• DDOS (distributed denial of service)
• DDR (double data rate)
• DE (desktop environment)
• DHCP (dynamic host configuration protocol)
• DL (download)
• DMA (direct memory access)
• DMCA (digital millennium copyright act)
• DND (dungeons & dragons, do not disturb)
• DNS (domain name system)
• DOM (document object model)
• DOS (disk operating system, denial of service)
• DOTADIW (do one thing and do it well)
• DPI (dots per inch)
• DRAM (dynamic RAM)
• DRM (digital restrictions management)
• DRY (don't repeat yourself)
• DVD (digital versatile disc)
• EEPROM (electronically erasable programmable ROM)
• ELF (executable and linkable format)
• EMCAS (editor macros)
• ENIAC (electronic numerical integrator and computer)
• EOF (end of file)
• EOL (end of line, end of life)
• ERP (erotic role play)
• ESR (Erik Steven Raymond)
• EULA (end user license agreement)
• FAQ (frequently asked questions)
• FE (frontend)
• FET (field effect transistor)
• FFS (for fuck's sake)
• FIFO (first in first out)
• FLAC (free lossless audio codec)
• FLOSS (free libre open source software)
• FM (frequency modulation)
• FML (fuck my life)
• FORTRAN (formula translation)
• FOSH (free and open source hardware)
• FOSS (free and open source software)
• FSF (free software foundation)
• FP (floating point)
• FPGA (field programmable gate array)
• FPS (frames per second, first person shooter)
• FQA (frequently questioned answers)
• FS (file system)
• FTL (faster than light)
• FTP (file transfer protocol)
• FU (fuck you)
• FXAA (full screen anti aliasing)
• FYI (for your information)
• GB (gigabyte/gigabit, GameBoy)
• GBPS (GB per second)
• GCC (GNU compiler collection)
• GDB (GNU debugger)
• GI (global illumination)
• GIB (gibibyte)
• GIF (graphics interchange format)
• GIGO (garbage in garbage out)
• GIMP (GNU image manipulation program)
• GLUT (OpenGL utility toolkit)
• GNOME (GNU network object model environment)
• GNU (GNU's Not Unix)
• GOAT (greatest of all time)
• GPG (GNU privacy guard)
• GPGPU (general purpose GPU)
• GPL (GNU General Public License)
• GPLv2 (GPL version 2)
• GPLv3 (GPL version 3)
• GPS (global positioning system)
• GPU (graphics processing unit)
• GRUB (grand unified boot loader)
• GSM (global system for mobile communication)
• GTK+ (GIMP toolking)
• GUI (graphical user interface)
• H8 (hate)
• HD (high definition)
• HDD (hard disc drive)
• HDMI (HD multimedia interface)
• HW (hardware)
• HTML (hypertext markup language)
• HTTP (hypertext transfer protocol)
• HTTPS (HTTP secure)
• HURD (hird of unix replacing demons)
• HQ (high quality)
• HZ (hertz)
• IANA (internet assigned number authority)
• IANAL (I am not a lawyer)
• ICMP (internet control message protocol)
• IDC (I don't care)
• IDE (integrated development environment)
• IEEE (institute for electrical and electronic
• IM (instant messaging)
• IMAP (internet message access protocol)
• IMHO (in my honest opinion)
• IMO (in my opinion)
• INB4 (in before)
• IO (input/output)
• IOT (internet of things)
• IPS (instructions per second)
• IP (internet protocol, intellectual property)
• IPV4 (IP version 4)
• IPV6 (IP version 6)
• IRC (internet relay chat)
• IRL (in real life)
• ISA (instruction set architecture)
• ISO (international organization for standardization)
• ISP (internet service provider)
• ISS (international space station)
• IS (information system)
• IT (information technology)
• J2ME (java 2 micro edition)
• JB (jailbait)
• JDK (java development kit)
• JIT (just in time)
• JK (just kidding)
• JPEG/JPG (joint photographic expert group)
• JS (JavaScript)
• JSON (JavaScript object notation)
• K&R (Kernighan and Ritchie)
• KB (kilobyte/kilobit)
• KBPS (KB per second)
• KDE (K desktop environment)
• KEK (a meme version of LOL coming from World Of Warcraft)
• KHZ (kilohertz)
• KIB (kibibyte)
• KILL (keep it Linux loser)
• KISS (keep it simple stupid)
• KLOC (kilo LOC)
• KKK (ku klux klan)
• KYS (kill yourself)
• LAMP (linux apache mysql php)
• LARP (live action role play)
• LAN (local area network)
• LCD (liquid crystal display)
• LED (light emitting diode)
• LER (light emitting resistor)
• LGBT (lesbian gay bisexual trans)
• LGBTQ (lesbian gay bisexual trans queer)
• LGPL (lesser GPL)
• LIFO (last in first out)
• LISP (list processing)
• LMAO (laughing my ass off)
• LOC (lines of code)
• LOL (laughing out loud)
• LQ (low quality)
• LRS (less retarded software/society)
• LSB (least significant bit)
• LUT (lookup table)
• MBR (master boot record)
• MHZ (megahertz)
• MIB (mebibyte)
• MIME (multipurpose internet mail extension)
• MIP (multum in parvo)
• MIPS (millions of instructions per second)
• MBPS (MB per second)
• MCU (microcontroller unit)
• MD (markdown)
• MFW (my face when)
• MMO (massively multiplayer online)
• MMX (multimedia extension)
• MMORPG (MMO RPG)
• MOSFET (metal oxide semiconductor field effect transistor)
• MPEG (motion pictures experts group)
• MR (merge request)
• MS/M$ (Micro$oft)
• MSB (most significant bit)
• MSC (master of science)
• MSG (message)
• MUD (multi user dungeon)
• NAN (not a number)
• NASA (national aeronautic and space administration)
• NAT (network address translation)
• NC (non commercial)
• NEET (not in education, employment or training)
• NFT (non-fungible token)
• NGL (not gonna lie)
• NOP (no operation)
• NP (nondeterministic polynomial)
• NTFS (NT file system)
• OEM (original equipment manufacturers)
• OGL (OpenGL)
• OMG (oh my god)
• OO (object oriented, object obsessed, object obfuscated)
• OOP (object oriented/obsessed programming)
• OS (operating system, open source)
• OSS (open source software)
• OSI (open source initiative)
• P2P (peer to peer)
• PB (petabyte, petabit, personal best)
• PBR (physically based rendering)
• PC (personal computer, political correctness)
• PD (public domain)
• PDF (portable document format)
• PCM (pulse code modulation)
• PGP (pretty good privacy)
• PHD (doctor of philosophy)
• PID (process ID)
• PIN (personal identification number)
• PNG (portable network graphics)
• POP3 (post office protocol version 3)
• POSIX (portable operating system interface)
• PPC (power PC)
• PR (pull request)
• PS (Photoshop, Postscript, PlayStation)
• PS2 (personal system 2)
• PTHC (preteen hardcore)
• QOS (quality of service)
• RAID (redundant array of inexpensive discs)
• RAM (random access memory)
• RC (release candidate)
• RCL (raycastlib)
• REGEX (regular expression)
• RFC (request for comments)
• RGB (red green blue)
• RGBA (red green blue alpha)
• RISC (reduced instruction set computer)
• RIP (rest in piece)
• RLE (run length encoding)
• RMS (Richard Matthew Stallman)
• RN (right now)
• ROFL (rolling on floor laughing)
• ROM (read-only memory)
• RPG (role playing game)
• RPI (Raspberry Pi)
• RT (real time)
• RTFM (read the fucking manual)
• RTOS (real time operating system)
• S3L (small3dlib)
• SAAS (software as a service)
• SAASS (service as a software substitute)
• SAF (smallabstractfish)
• SBC (single board computer)
• SCL (smallchesslib)
• SD (standard definition, secure digital)
• SDF (signed distance function)
• SDK (software development kit)
• SDL (simple directmedia layer)
• SED (smoke emitting diode)
• SEO (search engine optimization)
• SFX (sound effects)
• SGML (standard generalized markup language)
• SHA (secure hash algorithm)
• SIG (special interest group)
• SIM (subscriber identity module)
• SIMD (single instruction multiple data)
• SLOC (source lines of code)
• SMS (short message service)
• SMTP (simple mail transfer protocol)
• SNTP (simple network time protocol)
• SOC (system on a chip)
• SQL (structured query language)
• SRAM (static RAM)
• SSAO (screen space ambient occlusion)
• SSD (solid state drive)
• SSH (secure shell)
• SSL (secure socket layer)
• STFU (shut the fuck up)
• SVG (scalable vector graphics)
• SW (software)
• TAS (tool assisted speedrun)
• TB (terabyte, terabit)
• TCC (tiny C compiler)
• TCP (transmission control protocol)
• TFT (thin filter transistor)
• TFW (that face when)
• TLA (three letter acronym)
• TM (trademark, Turing machine)
• TOS (terms of service)
• TTY (teletype)
• TUI (text user interface)
• UBI (universal basic income)
• UDP (user datagram protocol)
• UI (user interface)
• UML (unified modeling language)
• URI (uniform resource identifier)
• URL (uniform resource locator)
• USA (united states of america)
• USB (universal serial bus)
• UTC (coordinated universal time)
• UTF (unicode transformation format)
• UX (user experience)
• VCS (version control system)
• VOD (video on demand)
• VHS (video home system)
• VIM (vi improved)
• VFX (visual effects)
• VLAN (virtual LAN)
• VLIW (very long instruction word)
• VM (virtual machine)
• VPN (virtual private network)
• VPS (virtual private server)
• VRAM (video RAM)
• W3C (world wide web consortium)
• WAN (wide area network)
• WAP (wireless application protocol)
• WIFI (wireless fidelity)
• WOW (World Of Warcraft)
• WPA (WIFI protected access)
• WTF (what the fuck)
• WTFPL (do what the fuck you want to public license)
• WYSIWYG (what you see is what you get)
• WM (window manager)
• WWW (world wide web)
• XAML (extensible application markup language)
• XHTML (extensible HTML)
• XML (extensible markup language)
• YOLO (you only live once)
• ZOMG (when you want to write OMG but accidentally also hit Z)

See Also

• LRS dictionary

Artificial Intelligence

Artificial intelligence (AI) is an area of computer science whose effort lies in making computers simulate thinking of humans and possibly other biologically living beings. This may include making computers play games such as chess, compose music, paint pictures, understand and processing audio, images and text on high level of abstraction (e.g. translation between natural languages), making predictions about complex systems such as stock market or weather or even exhibit a general human-like behavior. Even though today's focus in AI is on machine learning and especially neural networks, there are many other usable approaches and models such as "hand crafted" state tree searching algorithms that can simulate and even outperform the behavior of humans in certain specialized areas.

There's a concern that's still a matter of discussion about the dangers of developing a powerful AI, as that could possibly lead to a technological singularity in which a super intelligent AI might take control over the whole world without humans being able to seize the control back. Even though it's still likely a far future and many people say the danger is not real, the question seems to be about when rather than if.

By about 2020, "AI" has become a capitalist buzzword. They try to put machine learning into everything just for that AI label -- and of course, for a bloat monopoly.

By 2023 neural network AI has become extremely advanced in processing visual, textual and audio information and is rapidly marching on. Networks such as stable diffusion are now able to generate images (or modify existing ones) with results mostly indistinguishable from real photos just from a short plain language textual description. Text to video AI is emerging and already giving nice results. AI is able to write computer programs from plain language text description. Chatbots, especially the proprietary chatGPT, are scarily human-like and can already carry on conversation mostly indistinguishable from real human conversation while showing extraordinary knowledge and intelligence -- the chatbot can for example correctly reason about advanced mathematical concepts on a level much higher above average human. AI has become mainstream and is everywhere, normies are downloading "AI apps" on their phones that do funny stuff with their images while spying on them. In games such as chess or even strategy video games neural AI has already been for years far surpassing the best of humans by miles.

Algorithm

Algorithm (from the name of Persian mathematician Muhammad ibn Musa al-Khwarizmi) is an exact step-by-step description of how to solve some type of a problem. Algorithms are basically what programming is all about: we tell computers, in very exact ways (with programming languages), how to solve problems -- we write algorithms. But algorithms don't have to be just computer programs, they are simply instruction for solving problems.

Cooking recipes are commonly given as an example of a non-computer algorithm, though they rarely contain branching ("if then...") and loops ("while a condition holds do ..."), the key features of algorithms. The so called wall-follower is a simple algorithm to get out of any maze: you just pick either a left-hand or right-hand wall and then keep following it. You may write a crazy algorithm basically for any kind of problem, e.g. for how to clean a room or how to get a girl to bed, but it has to be precise so that anyone can execute the algorithm just by blindly following the steps; if there is any ambiguity, it is not considered an algorithm; a vague, imprecise "hint" on how to find a solution (e.g. "to get to the airport head somewhere in this direction.") we rather call a heuristic. Heuristics are useful too and they may be utilized by an algorithm, e.g. to find a precise solution faster, but from programmer's point of view algorithms, the PRECISE ways of finding solutions, are the basic of everything.

Interesting fact: contrary to intuition there are problems that are mathematically proven to be unsolvable by any algorithm, see undecidability, but for most practically encountered problems we can write an algorithm (though for some problems even our best algorithms can be unusably slow).

Algorithms are mostly (possibly not always, depending on exact definition of the term) written as a series of steps (or instructions); these steps may be specific actions (such as adding two numbers or drawing a pixel to the screen) or conditional jumps to other steps ("if condition X holds then jump to step N, otherwise continue"). At the lowest level (machine code, assembly) computers can do just that: execute instructions (expressed as 1s and 0s) and perform conditional jumps. These jumps can be used to create branches (in programming known as if-then-else) and loops. Branches and loops are together known as control structures -- they don't express a direct action but control which steps in the algorithm will follow. All in all, any algorithm can be written with only these three constructs:

• sequence: A series of steps, one after another. E.g. "write prompt, read number from input, store than number to memory".
• selection (branches, if-then-else): Two branches (sequences of steps) preceded by a condition; the first branch is executed only if the condition holds, the second ("else") branch is executed only if the condition doesn't hold (e.g. "If user password is correct, log the user in, otherwise print out an error.").
• iteration (loops, repetition): Sequence of steps that's repeated as long as certain condition holds (e.g. "As long as end of file is not reached, read and print out next character from the file.").

Note: in a wider sense algorithms may be expressed in other ways than sequences of steps (non-imperative ways, see declarative languages), even mathematical equations are often called algorithms because they imply the steps towards solving a problem. But we'll stick to the common meaning of algorithm given above.

Additional constructs can be introduced to make programming more comfortable, e.g. subroutines/functions (kind of small subprograms that the main program uses for solving the problem), macros (shorthand commands that represent multiple commands) or switch statements (selection but with more than two branches). Loops are also commonly divided into several types such as: counted loops, loops with condition and the beginning, loops with condition at the end and infinite loops (for, while, do while and while (1) in C, respectively) -- in theory there can only be one generic type of loop but for convenience programming languages normally offer different "templates" for commonly used loops. Similarly to mathematical equations, algorithms make use of variables, i.e. values which can change and which have a specific name (such as x or myVariable).

Practical programming is based on expressing algorithms via text, but visual programming is also possible: flowcharts are a way of visually expressing algorithms, you have probably seen some. Decision trees are special cases of algorithms that have no loops, you have probably seen some too. Even though some languages (mostly educational such as Snap) are visual and similar to flow charts, it is not practical to create big algorithms in this way -- serious programs are written as a text in programming languages.

Example

Let's write a simple algorithm that counts the number of divisors of given number x and checks if the number is prime along the way. (Note that we'll do it in a naive, educational way -- it can be done better). Let's start by writing the steps in plain English:

1. Read the number x from the input.
2. Set the divisor counter to 0.
3. Set currently checked number to 1.
4. While currently checked number is lower or equal than x:

• a: If currently checked number divides x, increase divisor counter by 1.
• b: Increase currently checked number.

5. Write out the divisor counter.
6. If divisor counter is equal to 2, write out the number is a prime.

Notice that x, divisor counter and currently checked number are variables. Step 4 is a loop (iteration) and steps a and 6 are branches (selection). The flowchart of this algorithm is:

               START
                 |
                 V
               read x
                 |
                 V
       set divisor count to 0
                 |
                 V
       set checked number to 1
                 |
    .----------->|
    |            |
    |            V                no
    |    checked number <= x ? ------.
    |            |                   |
    |            | yes               |
    |            V                   |
    |     checked number    no       |
    |       divides x ? -------.     |
    |            |             |     |
    |            | yes         |     |
    |            V             |     |
    |     increase divisor     |     |
    |       count by 1         |     |
    |            |             |     |
    |            |             |     |
    |            |<------------'     |
    |            |                   |
    |            V                   |
    |     increase checked           V
    |       number by 1     print divisor count
    |            |                   |
    '------------'                   |
                                     V             no
                             divisor count = 2 ? -----.
                                     |                |
                                     | yes            |
                                     V                |
                           print "number is prime"    |
                                     |                |
                                     |<---------------'
                                     V
                                    END

This algorithm would be written in Python as:

x = int(input("enter a number: "))

divisors = 0

for i in range(1,x + 1):
  if x % i == 0: # i divides x?
    divisors = divisors + 1

print("divisors: " + str(divisors))
 
if divisors == 2:
  print("It is a prime!")

in C as:

#include <stdio.h>                                                              
                                                                                 
int main(void)
{
  int x, divisors = 0;
                                                                
  scanf("%d",&x); // read a number

  for (int i = 1; i <= x; ++i)
    if (x % i == 0) // i divides x?
      divisors = divisors + 1;

  printf("number of divisors: %d\n",divisors);
 
  if (divisors == 2)
    puts("It is a prime!");

  return 0;
} 

and in comun as (for simplicity only works for numbers up to 9):

<- "0" -  # read X and convert to number
0         # divisor count
1         # checked number

@@
  $0 $3 > ?     # checked num. > x ?
    !@
  .

  $2 $1 % 0 = ? # checked num. divides x ?
    $1 ++ $:2   # increase divisor count
  .

  ++      # increase checked number
.

0 "divisors: " -->   # write divisor count
$1 "0" + -> 10 ->

$1 2 = ?
  0 "It is a prime" --> 10 ->
.

This algorithm is however not very efficient and could be optimized -- for example there is no need to check divisors higher than the square root of the checked value (mathematically above square root the only divisor left is the number itself) so we could lower the number of the loop iterations and so make the algorithm finish faster.

Study of Algorithms

Algorithms are the essence of computer science, there's a lot of theory and knowledge about them.

Turing machine, a kind of mathematical bare-minimum computer, created by Alan Turing, is the traditional formal tool for studying algorithms, though many other models of computation exist. From theoretical computer science we know not all problems are computable, i.e. there are problems unsolvable by any algorithm (e.g. the halting problem). Computational complexity is a theoretical study of resource consumption by algorithms, i.e. how fast and memory efficient algorithms are (see e.g. P vs NP). Mathematical programming is concerned, besides others, with optimizing algorithms so that their time and/or space complexity is as low as possible which gives rise to algorithm design methods such as dynamic programming (practical optimization is a more pragmatic approach to making algorithms more efficient). Formal verification is a field that tries to mathematically (and sometimes automatically) prove correctness of algorithms (this is needed for critical software, e.g. in planes or medicine). Genetic programming and some other methods of artificial intelligence try to automatically create algorithms (algorithms that create algorithms). Quantum computing is concerned with creating new kinds of algorithms for quantum computers (a new type of still-in-research computers). Programming language design is the art and science of creating languages that express computer algorithms well.

Specific Algorithms

Following are some common algorithms classified into groups.

• graphics
  • DDA: line drawing algorithm
  • Bresenham's algorithm: another line drawing algorithm
  • Midpoint algorithm: circle drawing algorithm
  • flood fill: algorithm for coloring continuous areas
  • FXAA
  • Hough transform: finds shapes in pictures
  • painter's algorithm
  • path tracing
  • ray tracing
• math
  • Boot'h algorithm: algorithm for multiplication
  • Dijkstra's algorithm
  • Euclidean algorithm: computes greatest common divisor
  • numerical algorithms: approximate mathematical functions
  • sieve of Eratosthenes: computes prime numbers
• sorting
  • bogosort (stupid sort)
  • bubble sort: simple, kind of slow but still usable sorting algorithm
  • heap sort
  • insertion sort
  • merge sort
  • shaker sort
  • selection sort
  • slow sort
  • quick sort: one of the fastest sorting algorithms
• searching
  • binary search
  • linear search
• other
  • A*: path searching algorithm, used by AI in many games
  • backpropagation: training of neural networks
  • fizzbuzz: problem/simple algorithm given in job interviews to filter out complete noobs
  • FFT: quickly converts signal (audio, image, ...) to its representation in frequencies, one of the most famous and important algorithms
  • Huffman coding: compression algorithm
  • Kalman filter
  • k-means: clustering algorithm
  • MD5: hash function
  • backtracking
  • minimax plus alpha-beta pruning: used by many AIs that play turn based games
  • proof of work algorithms: used by some cryptocurrencies
  • RSA
  • Shor's algorithm: quantum factorization algorithm
  • YouTube algorithm: secret algorithm YouTube uses to suggest videos to viewers, a lot of people hate it :)

See Also

• programming
• design pattern
• recursion

Aliasing

Aliasing is a certain typically undesirable phenomenon that distorts signals (such as sounds or images) when they are sampled discretely (captured at single points, usually at periodic intervals) -- this can happen e.g. when capturing sound with digital recorders or when rendering computer graphics. There exist antialiasing methods for suppressing or even eliminating aliasing. Aliasing can be often seen on small checkerboard patterns as a moiré pattern (spatial aliasing), or maybe more famously on rotating wheels or helicopter rotor blades that in a video look like standing still or rotating the other way (temporal aliasing, caused by capturing images at intervals given by the camera's FPS).

A simple example showing how sampling at discrete points can quite dramatically alter the recorded result:

|      .|-'-'.' '           .--.           |   |''''
|  . '  |      ' .        .'    '.         |   |    
'|- - -O+ - -O- - .|     |  O  O  |        '---+---.
 |     \|_ _ /    ||     |  \__/  |            |   |
_ _'_._ |      . '|       '.    .'         ____|   |
       ' ' ' '              ''''
  original image    taking even columns  taking odd columns

The following diagram shows the principle of aliasing with a mathematical function:

^       original                     sampling period                       
|   |               |               |<------------->|
|   |             _ |           _   |         _     |
| .'|'.         .' '|         .' '. |       .' '.   |
|/__|__\_______/____|\_______/_____\|______/_____\__|___
|   |   \     /     | \     /       \     /       \ |
|   |    '._.'      |  '._.'        |'._.'         '|_.'
|   |               |               |               |
|   :               :               :               :
V   :               :               :               :
    :               :               :               :
^   :               :               :               :
|   :               :               :               :
|---o---...____     :               :               :
|   |          '''''o...____        :               :
|___|_______________|______ ''''----o_______________:___
|                                     '''----___    |        
|                                               ''''o---
|     reconstructed                                              
|
V

The top signal is a sine function of a certain frequency. We are sampling this signal at periodic intervals indicated by the vertical lines (this is how e.g. digital sound recorders record sounds from the real world). Below we see that the samples we've taken make it seem as if the original signal was a sine wave of a much lower frequency. It is in fact impossible to tell from the recorded samples what the original signal looked like.

Let's note that signals can also be two and more dimensional, e.g. images can be viewed as 2D signals. These are of course affected by aliasing as well.

The explanation above shows why a helicopter's rotating blades look to stand still in a video whose FPS is synchronized with the rotation -- at any moment the camera captures a frame (i.e. takes a sample), the blades are in the same position as before, hence they appear to not be moving in the video.

Of course this doesn't only happen with perfect sine waves. Fourier transform shows that any signal can be represented as a sum of different sine waves, so aliasing can appear anywhere.

Nyquist–Shannon sampling theorem says that aliasing can NOT appear if we sample with at least twice as high frequency as that of the highest frequency in the sampled signal. This means that we can eliminate aliasing by using a low pass filter before sampling which will eliminate any frequencies higher than the half of our sampling frequency. This is why audio is normally sampled with the rate of 44100 Hz -- from such samples it is possible to correctly reconstruct frequencies up to about 22000 Hz which is about the upper limit of human hearing.

Aliasing is also a common problem in computer graphics. For example when rendering textured 3D models, aliasing can appear in the texture if that texture is rendered at a smaller size than its resolution (when the texture is enlarged by rendering, aliasing can't appear because enlargement decreases the frequency of the sampled signal and the sampling theorem won't allow it to happen). (Actually if we don't address aliasing somehow, having lower resolution textures can unironically have beneficial effects on the quality of graphics.) This happens because texture samples are normally taken at single points that are computed by the texturing algorithm. Imagine that the texture consists of high-frequency details such as small checkerboard patterns of black and white pixels; it may happen that when the texture is rendered at lower resolution, the texturing algorithm chooses to render only the black pixels. Then when the model moves a little bit it may happen the algorithm will only choose the white pixels to render. This will result in the model blinking and alternating between being completely black and completely white (while it should rather be rendered as gray).

The same thing may happen in ray tracing if we shoot a single sampling ray for each screen pixel. Note that interpolation/filtering of textures won't fix texture aliasing. What can be used to reduce texture aliasing are e.g. by mipmaps which store the texture along with its lower resolution versions -- during rendering a lower resolution of the texture is chosen if the texture is rendered as a smaller size, so that the sampling theorem is satisfied. However this is still not a silver bullet because the texture may e.g. be shrink in one direction but enlarged in other dimension (this is addressed by anisotropic filtering). However even if we sufficiently suppress aliasing in textures, aliasing can still appear in geometry. This can be reduced by multisampling, e.g. sending multiple rays for each pixel and then averaging their results -- by this we increase our sampling frequency and lower the probability of aliasing.

Why doesn't aliasing happen in our eyes and ears? Because our senses don't sample the world discretely, i.e. in single points -- our senses integrate. E.g. a rod or a cone in our eyes doesn't just see exactly one point in the world but rather an averaged light over a small area (which is ideally right next to another small area seen by another cell, so there is no information to "hide" in between them), and it also doesn't sample the world at specific moments like cameras do, its excitation by light falls off gradually which averages the light over time, preventing temporal aliasing (instead of aliasing we get motion blur).

So all in all, how to prevent aliasing? As said above, we always try to satisfy the sampling theorem, i.e. make our sampling frequency at least twice as high as the highest frequency in the signal we're sampling, or at least get close to this situation and lower the probability of aliasing. This can be done by either increasing sampling frequency (which can be done smart, some methods try to detect where sampling should be denser), or by preprocessing the input signal with a low pass filter or otherwise ensure there won't be too high frequencies (e.g. using lower resolution textures).

Altruism

Not to be confused with autism.

Anal Bead

To most people anal beads are just sex toys they stick in their butts, however anal beads with with remotely controlled vibration can also serve as a well hideen one-way communication device. Use of an anal bead for cheating in chess has been the topic of a great cheat scandal in 2022 (Niemann vs Carlsen).

Analog

Analog is the opposite of digital.

Analytic Geometry

Analytic geometry is part of mathematics that solves geometric problems with algebra; for example instead of finding an intersection of a line and a circle with ruler and compass, analytic geometry finds the intersection by solving an equation. In other words, instead of using pen and paper we use numbers. This is very important in computing as computers of course just work with numbers and aren't normally capable of drawing literal pictures and drawing results from them -- that would be laughable (or awesome?). Analytic geometry finds use especially in such fields as physics simulations (collision detections) and computer graphics, in methods such as raytracing where we need to compute intersections of rays with various mathematically defined shapes in order to render 3D images. Of course the methods are used in other fields, for example rocket science and many other physics areas. Analytic geometry reflects the fact that geometric and algebraic problem are often analogous, i.e. it is also the case that many times problems we encounter in arithmetic can be seen as geometric problems and vice versa (i.e. solving an equation is the same as e.g. finding an intersection of some N-dimensional shapes).

Fun fact: approaches in the opposite direction also exist, i.e. solving mathematical problems physically rather than by computation. For example back in the day when there weren't any computers to compute very difficult integrals and computing them by hand would be immensely hard, people literally cut physical function plots out of paper and weighted them in order to find the integral. Awesome oldschool hacking.

Anyway, how does it work? Typically we work in a 2D or 3D Euclidean space with Cartesian coordinates (but of course we can generalize to more dimensions etc.). Here, geometric shapes can be described with equations (or inequalities); for example a zero-centered circle in 2D with radius r has the equation x^2 + y^2 = r^2 (Pythagorean theorem). This means that the circle is a set of all points [x,y] such that when substituted to the equation, the equation holds. Other shapes such as lines, planes, ellipses, parabolas have similar equations. Now if we want to find intersections/unions/etc., we just solve systems of multiple equations/inequalities and find solutions (coordinates) that satisfy all equations/inequalities at once. This allows us to do basically anything we could do with pen and paper such as defining helper shapes and so on. Using these tools we can compute things such as angles, distances, areas, collision points and much more.

Analytic geometry is closely related to linear algebra.

Examples

Nub example:

Find the intersection of two lines in 2D: one is a horizontal line with y position 2, the other is a 45 degree line going through the [0,0] point in the positive x and positive y direction, like this:

  y
  :        _/ line 2
  :      _/
_2:_____/_______ line 1
  :  _/
  :_/
--:----------x
_/:
  :

The equation of line 1 is just y = 2 (it consists of all points [x,2] where for x we can plug in any number to get a valid point on the line).

The equation of line 2 is x = y (all points that have the same x and y coordinate lie on this line).

We find the intersection by finding such point [x,y] that satisfies both equations. We can do this by plugging the first equation, y = 2, to the second equation, x = y, to get the x coordinate of the intersection: x = 2. By plugging this x coordinate to any of the two line equations we also get the y coordinate: 2. I.e. the intersection lies at coordinates [2,2].

Advanced nub example:

Let's say we want to find, in 2D, where a line L intersects a circle C. L goes through points A = [-3,0.5] and B = [3,2]. C has center at [0,0] and radius r = 2.

The equation for the circle C is x^2 + y^2 = 2^2, i.e. x^2 + y^2 = 4. This is derived from Pythagorean theorem, you can either check that or, if lazy, just trust this. Equations for common shapes can be looked up.

One possible form of an equation of a 2D line is a "slope + offset" equation: y = k * x + q, where k is the tangent (slope) of the line and q is an offset. To find the specific equation for our line L we need to first find the numbers k and q. This is done as follows.

The tangent (slope) k is (B.y - A.y) / (B.x - A.x). This is the definition of a tangent, see that if you don't understand this. So for us k = (2 - 0.5) / (3 - -3) = 0.25.

The number q (offset) is computed by simply substituting some point that lies on the line to the equation and solving for q. We can substitute either A or B, it doesn't matter. Let's go with A: A.y = k * A.x + q, with specific numbers this is 0.5 = 0.25 * -3 + q from which we derive that q = 1.25.

Now we have computed both k and q, so we now have equations for both of our shapes:

• circle C: x^2 + y^2 = 4
• line L: y = 0.25 * x + 1.25

Feel free to check the equations, substitute a few points and plot them to see they really represent the shapes (e.g. if you substitute a specific x shape to the line equation you will get a specific y for it).

Now to find the intersections we have to solve the above system of equations, i.e. find such couples (coordinates) [x,y] that will satisfy both equations at once. One way to do this is to substitute the line equation into the circle equation. By this we get:

x^2 + (0.25 * x + 1.25)^2 = 4

This is a quadratic equation, let's get it into the standard format so that we can solve it:

x^2 + 0.0625 * x^2 + 0.625 * x + 1.5625 = 4

1.0625 * x^2 + 0.625 * x - 2.4375 = 0

Note that this makes perfect sense: a quadratic equation can have either one, two or no solution (in the realm of real numbers), just as there can either be one, two or no intersection of a line and a circle.

Solving quadratic equation is simple so we skip the details. Here we get two solutions: x1 = 1.24881 and x2 = -1.83704. These are the x position of our intersections. We can further find also the y coordinates by simply substituting these into the line equation, i.e. we get the final result:

• intersection 1: [1.24881, 1.5622025]
• intersection 2: [-1.83704, 0.79074]

See Also

• linear algebra

Anarchism

Anarchism (from Greek an, no and archos, ruler) is a socialist political philosophy rejecting any social hierarchy and oppression. Anarchism doesn't mean without rules, but without rulers; despite popular misconceptions anarchism is not chaos -- on the contrary, it strives for a stable, ideal society of equal people that live in peace. It means order without power. The symbols of anarchism include the letter A in a circle and a black flag that for different branches of anarchism is diagonally split from bottom left to top right and the top part is filled with a color specific for that branch.

A great many things about anarchism are explained in the text An Anarchist FAQ, which is free licensed and can be accessed e.g. at https://theanarchistlibrary.org/library/the-anarchist-faq-editorial-collective-an-anarchist-faq-full.

Anarchism is a wide term and encompasses many flavors such as anarcho communism, anarcho pacifism, anarcho syndicalism, anarcho primitivism or anarcho mutualism. Some of the branches disagree on specific questions, e.g. about whether violence is ever justifiable, or propose different solutions to issues such as organization of society, however all branches of anarchism are socialist and all aim for elimination of social hierarchy such as social classes created by wealth, jobs and weapons, i.e. anarchism opposes state (e.g. police having power over citizens) and capitalism (employers exploiting employees, corporations exploiting consumers etc.).

There exist fake, pseudoanarchist ideologies such as "anarcho" capitalism (which includes e.g. so caleed crypto "anarchism") that deceive by their name despite by their very definition NOT fitting the definition of anarchism (just like Nazis called themselves socialists despite being the opposite). Also such shit as "anarcha" feminism are just fascist bullshit. The propaganda also tries to deceive the public by calling various violent criminals anarchists, even though they very often can't fit the definition of a true anarchist.

LRS is an anarchist movement, specifically anarcho pacifist and anarcho communist one.

Anarch

Anarch is a LRS/suckless, free as in freedom first person shooter game similar to Doom, written by drummyfish. It has been designed to follow the LRS principles very closely and set an example of how games, and software in general, should be written. It also tries to be compatible with principles of less retarded society, i.e. it promotes anarchism, anti-capitalism, pacifism etc.

The repo is available at https://codeberg.org/drummyfish/Anarch or https://gitlab.com/drummyfish/anarch. Some info about the game can also be found at the libregamewiki: https://libregamewiki.org/Anarch.

{ Though retrospectively I can of course see many mistakes and errors about the game, I am overall quite happy about how it turned out, it got some attention among the niche of suckless lovers and many people have written me they liked the game and its philosophy. Many people have ported it to their favorite platforms, some have even written me their own expansion of the game lore, tricks they found etc. If you're among them, thank you :) ~drummyfish }

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screenshot from the terminal version

Anarch has these features:

• It is completely public domain free software/free culture under CC0, including all code and assets which were all made from scratch by drummyfish.
• It has extremely low hardware demands, fitting into 256 kb (WITH assets, with mods and compression even 60 kb) and requiring only about 32 kb of RAM and 50 MHz CPU. GPUs need not apply.
• It is written in pure C99 without any dependencies (not even the standard library). It uses no dynamic heap allocation and no floating point.
• It is extremely portable, written against a very tiny I/O layer. As such it has been ported to many platforms such as GNU/Linux, BSD, Pokitto, browser JavaScript, Raspberry Pi and many others.
• It is written in a single compilation unit and without any build system.
• It is created with only free software.
• It is well documented.
• Mods and configs follow suckless philosophy: mods are just diffs, config is part of source code.
• Gameplay-wise Anarch offers 10 levels and multiple enemy and weapon types. It supports mouse where available.

Technical Details

Anarch's engine uses raycastlib, a LRS library for advanced 2D ray casting which is often called a "pseudo 3D". This method was used by Wolf3D, but Anarch improves it to allow different levels of floor and ceiling which makes it look a little closer to Doom (which however used a different methods called BSP rendering).

The music in the game is procedurally generated using bytebeat.

All images in the game (textures, sprites, ...) are 32x32 pixels, compressed by using a 16 color subpalette of the main 256 color palette, and are stored in source code itself as simple arrays of bytes -- this eliminates the need for using files and allows the game to run on platforms without a file system.

The game uses a tiny custom-made 4x4 bitmap font to render texts.

Saving/loading is optional, in case a platform doesn't have persistent storage. Without saving all levels are simply available from the start.

In the suckless fashion, mods are recommended to be made and distributed as patches.

"Anarcho" Capitali$m

Not to be confused with anarchism.

So called "anarcho capitalism" (ancap for short, not to be confused with anpac or any form of anarchism) is probably the worst, most retarded and most dangerous idea in the history of ever, and that is the idea of supporting capitalism absolutely unrestricted by a state or anything else. No one with at least 10 brain cells and/or anyone who has spent at least 3 seconds observing the world could come up with such a stupid, stupid idea. We, of course, completely reject this shit.

It has to be noted that "anarcho capitalism" is not real anarchism, despite its name. Great majority of anarchists strictly reject this ideology as any form of capitalism is completely incompatible with anarchism -- anarchism is defined as opposing any social hierarchy and oppression, while capitalism is almost purely based on many types of hierarchies (internal corporate hierarchies, hierarchies between companies, hierarchies of social classes of different wealth etc.) and oppression (employee by employer, consumer by corporation etc.). Why do they call it anarcho capitalism then? Well, partly because they're stupid and don't know what they're talking about (otherwise they couldn't come up with such an idea in the first place) and secondly, as any capitalists, they want to deceive and ride on the train of the anarchist brand -- this is not new, Nazis also called themselves socialists despite being the complete opposite.

The colors on their flag are black and yellow (this symbolizes shit and piss).

It is kind of another bullshit kind of "anarchism" just like "anarcha feminism" etc.

The Worst Idea In History

As if capitalism wasn't extremely bad already, "anarcho" capitalists want to get rid of the last mechanisms that are supposed to protect the people from corporations -- states. We, as anarchists ourselves, of course see states as eventually harmful, but they cannot go before we get rid of capitalism first. Why? Well, imagine all the bad things corporations would want to do but can't because there are laws preventing them -- in "anarcho" capitalism they can do them.

Firstly this means anything is allowed, any unethical, unfair business practice, including slavery, physical violence, blackmailing, rape, worst psychological torture, nuclear weapons, anything that makes you the winner in the jungle system. Except that this jungle is not like the old, self-regulating jungle in which you could only reach limited power, this jungle offers, through modern technology, potentially limitless power with instant worldwide communication and surveillance technology, with mass production, genetic engineering, AI and weapons capable of destroying the planet.

Secondly the idea of getting rid of a state in capitalism doesn't even make sense because if we get rid of the state, the strongest corporation will become the state, only with the difference that state is at least supposed to work for the people while a corporation is only by its very definition supposed to care solely about its own endless profit on the detriment of people. Therefore if we scratch the state, McDonalds or Coca Cola or Micro$oft -- whoever is the strongest -- hires a literal army and physically destroys all its competition, then starts ruling the world and making its own laws -- laws that only serve the further growth of that corporation such as that everyone is forced to work 16 hour shifts every day until he falls dead. Don't like it? They kill your whole family, no problem. 100% of civilization will experience the worst kind of suffering, maybe except for the CEO of McDonald's, the world corporation, until the planet's environment is destroyed and everyone hopefully dies, as death is what we'll wish for.

All in all, "anarcho" capitalism is advocated mostly by children who don't know a tiny bit about anything, by children who are being brainwashed daily in schools by capitalist propaganda, with no education besides an endless stream of ads from their smartphones, or capability of thinking on their own. However, these children are who will run the world soon. It is sad, it's not really their fault, but through them the system will probably come into existence. Sadly "anarcho" capitalism is already a real danger and a very likely future. It will likely be the beginning of our civilization's greatest agony. We don't know what to do against it other than provide education.

God be with us.

Anarcho Pacifism

Anarcho pacifism (anpac) is a form of anarchism that completely rejects any violence. Anarcho pacifists argue that since anarchism opposes hierarchy and oppression, we have to reject violence which is a tool of oppression and establishing hierarchy. This would make it the one true purest form of anarchism. Anarcho pacifists use a black and white flag.

Historically anarcho pacifists such as Leo Tolstoy were usually religiously motivated for rejecting violence, however this stance may also come from logic and other than religious beliefs, e.g. the simple belief that violence will only spawn more violence ("eye for an eye will only make the whole world blind"), or pure unconditional love of life.

We, LRS, advocate anarcho pacifism. We see how violence can be a short term solution, even to preventing a harm of many, however from the long term perspective we only see the complete delegitimisation of violence as leading to a truly mature society. We realize a complete, 100% non violent society may be never achieved, but with enough education and work it will be possible to establish a society with absolute minimum of violence, a society in which firstly people grow up in a completely non violent environment so that they never accept violence, and secondly have all needs secured so that they don't even have a reason for using violence. We should at least try to get as close to this ideal as possible.

Antialiasing

Antialiasing (AA) means preventing aliasing, i.e. distortion of signal (images, audio, video, ...) caused by discrete sampling. Most people think antialiasing stands for "smooth edges in video game graphics", however that's a completely inaccurate understanding of antialiasing: yes, one of the most noticeable effects of 3D graphics antialiasing for a common human is that of having smooth edges, but smooth edges are not the primary goal, they are not the only effect and they are not even the most important effect of antialisng. Understanding antialiasing requires understanding what aliasing is, which is not a completely trivial thing to do (it's not the most difficult thing in the world either, but most people are just afraid of mathematics, so they prefer to stick with "antialiasing = smooth edges" simplification).

The basic sum up is following: aliasing is a negative effect which may arise when we try to sample (capture) continuous signals potentially containing high frequencies (the kind of "infinitely complex" data we encounter in real world such as images or sounds) in discrete (non-continuous) ways by capturing the signal values at specific points in time (as opposed to capturing integrals of intervals), i.e. in ways native and natural to computers. Note that the aliasing effect is mathematical and is kind of a "punishment" for our "cheating" which we do by trying to simplify capturing of very complex signals, i.e. aliasing has nothing to do with noise or recording equipment imperfections, and it may occur not only when recording real world data but also when simulating real world, for example during 3D graphics rendering (which simulates capturing real world with a camera). A typical example of such aliasing effect is a video of car wheels rotating very fast (with high frequency) with a relatively low FPS camera, which then seem to be rotating very slowly and in opposite direction -- a high frequency signal (fast rotating wheels) caused a distortion (illusion of wheels rotating slowly in opposite direction) due to simplified discrete sampling (recording video as a series of photographs taken at specific points in time in relatively low FPS). Similar undesirable effects may appear e.g. on high resolution textures when they're scaled down on a computer screen (so called Moiré effect), but also in sound or any other data. Antialiasing exploits the mathematical Nyquist–Shannon sampling theorem that says that aliasing cannot occur when the sampling frequency is high enough relatively to the highest frequency in the sampled data, i.e. antialising tries to prevent aliasing effects typically by either preventing high frequency from appearing in the sampled data (e.g. blurring textures, see MIP mapping) or by increasing the sampling frequency (e.g. multisampling). As a side effect of better sampling we also get things such as smoothly rendered edges etc.

Note that the word anti in antialising means that some methods may not prevent aliasing completely, they may just try to suppress it somehow. For example the FXAA (fast approximate antialiasing) method is a postprocessing algorithm which takes an already rendered image and tries to make it as if it was properly rendered in ways preventing aliasing, however it cannot be 100% successful as it doesn't know the original signal, all it can do is try to give us a good enough approximation.

How to do antialiasing? There are many ways, depending on the kind of data (e.g. the number of dimensions of the signal or what frequencies you expect in it) or required quality (whether you want to prevent aliasing completely or just suppress it). As stated above, most methods make use of the Nyquist–Shannon sampling theorem which states that aliasing cannot occur if the sampling frequency is at least twice as high as the highest frequency in the sampled signal. I.e. if you can make sure your sampling frequency is high enough relatively to the highest frequency in the signal, you will completely prevent aliasing -- you can do this by either processing the input signal with a low pass filter (e.g. blurring an image) or by increasing your sampling frequency (e.g. rendering at higher resolution). Some specific antialiasing methods include:

• avoiding aliasing: A pretty straightforward way :) Aliasing can be avoided e.g. simply by using low resolution textures as opposed to high resolution ones.
• multisampling (MSAA), supersampling (SSAA) etc.: Increasing sampling frequency, typically in computer graphics rendering. The specific methods differ by where and how they increase the number of samples (some methods increase sampling uniformly everywhere, some try to detect aliasing areas and only put more samples there etc). A simple (but expensive) way of doing this is rendering the image at higher resolution and then scaling it back down.
• FXAA: Cheating, approximation of antialiasing by postprocessing, usually in shaders, cheap but can be imperfect.
• MIP mapping: Way of preventing aliasing in rendering of scaled-down textures by having precomputed scaled-down antialiased versions of it.
• anisotrpic filtering: Improved version of MIP mapping.
• motion blur: Temporal antialiasing in video, basically increasing the number of samples in the time domain.
• ...

Antivirus Paradox

{ I think this paradox must have had another established name even before antiviruses, but I wasn't able to find anything. If you know it, let me know. ~drummyfish }

Antivirus paradox is the paradox of someone who's job it is to eliminate certain undesirable phenomenon actually having an interest in keeping this phenomenon existing so as to keep his job. A typical example is an antivirus company having an interest in the existence of dangerous viruses and malware so as to keep their business running; in fact antivirus companies themselves secretly create and release viruses and malware.

Cases of this behavior are common, e.g. the bind-torture-kill serial killer used to work as a seller of home security alarms who installed alarms for people who were afraid about being invaded by the bind-torture-killer, and then used his knowledge of the alarms to break into the houses -- a typical capitalist business. It is also a known phenomenon that many firefighters are passionate arsonists because society simply rewards them for fighting fires (as opposed to rewarding them for the lack of fires).

In capitalism and similar systems requiring people to have jobs this paradox prevents progress, i.e. actual elimination of undesirable phenomena, hence capitalism and similar systems are anti-progress. And not only that, the system pressures people to artificially creating new undesirable phenomena (e.g. lack of women in tech and similar bullshit) just to create new bullshit jobs that "fight" this phenomena. In a truly good society where people are not required to have jobs and in which people aim to eliminate work this paradox largely disappears.

Apple

See also http://techrights.org/wiki/Apple%27s_Dark_Side.

Apple is a terrorist organization and one of the biggest American computer fashion corporations, infamously founded by Steve Job$, it creates and sells overpriced, abusive, highly consumerist proprietary electronic devices.

App

App is a retarded capitalist name for application; it is used by soydevs, corporations and normalfaggots (similarly to how "coding" is used for programming). This word is absolutely unacceptable and is only to be used to mock these retards.

Anything called an "app" is expected to be bloat, badly designed and, at best, of low quality (and, at worst, malicious).

Approximation

Approximating means calculating or representing something with lesser than best possible precision -- estimating -- purposefully allowing some margin of error in results and using simpler mathematical models than the most accurate ones: this is typically done in order to save resources (CPU cycles, memory etc.) and reduce complexity so that our projects and analysis stay manageable. Simulating real world on a computer is always an approximation as we cannot capture the infinitely complex and fine nature of the real world with a machine of limited resources, but even withing this we need to consider how much, in what ways and where to simplify.

Using approximations however doesn't have to imply decrease in precision of the final result -- approximations very well serve optimization. E.g. approximate metrics help in heuristic algorithms such as A*. Another use of approximations in optimization is as a quick preliminary check for the expensive precise algorithms: e.g. using bounding spheres helps speed up collision detection (if bounding spheres of two objects don't collide, we know they can't possibly collide and don't have to expensively check this).

Examples of approximations:

• Distances: instead of expensive Euclidean distance (sqrt(dx^2 + dy^2)) we may use Chebyshev distance (dx + dy) or Taxicab distance (max(dx,dy)).
• Engineering approximations ("guesstimations"): e.g. sin(x) = x for "small" values of x or pi = 3 (integer instead of float).
• Physics engines: complex triangle meshes are approximated with simple analytical shapes such as spheres, cuboids and capsules or at least convex hulls which are much easier and faster to deal with. They also approximate relativistic physics with Newtonian.
• Addition/subtraction can sometimes be approximates with OR/AND operation, as they behave a bit similarly. This can be used e.g. for brightening/darkening of pixel colors in 332 or 565 format -- without the approximation addition of colors in these formats is very expensive (basically requires conversion to RGB, addition, clamping and a conversion back).
• Real time graphics engines, on the other hand, normally approximate all shapes with triangle meshes.
• Ray tracing neglects indirect lighting. Computer graphics in general is about approximating the solution of the rendering equation.
• Real numbers are practically always approximated with floating point or fixed point (rational numbers).
• Numerical methods offer generality and typically yield approximate solutions while their precision vs speed can be adjusted via parameters such as number of iterations.
• Taylor series approximates given mathematical function and can be used to e.g. estimate solutions of differential equations.
• ...

Arch Linux

"BTW I use Arch"

Arch Linux is a rolling-release Linux distribution for the "tech-savvy", mostly fedora-wearing weirdos.

Arch is shit at least for two reasons: it has proprietary packages (such as discord) and it uses systemd. Artix Linux is a fork of Arch without systemd.

Art

Art is an endeavor that seeks discovery and creation of beauty and primarily relies on intuition. While the most immediate examples of art that come to mind are for example music and painting, even the most scientific and rigorous effort like math and programming becomes art when pushed to the highest level, to the boundaries of current knowledge where intuition becomes important for further development.

See Also

• beauty

ASCII Art

ASCII art is the art of manually creating graphics and images only out of fixed-width ASCII characters. This means no unicode or extended ASCII characters are allowed, of course. ASCII art is also, strictly speaking, separate from mere ASCII rendering, i.e. automatically rendering a bitmap image with ASCII characters in place of pixels, and ASCII graphics that utilizes the same techniques as ASCII art but can't really be called art (e.g. computer generated diagrams). Pure ASCII art should make no use of color.

This kind of art used to be a great part of the culture of earliest Internet communities for a number of reasons imposed largely by the limitations of old computers -- it could be created easily with a text editor and saved in pure text format, it didn't take much space to store or send over a network and it could be displayed on text-only displays and terminals. The principle itself predates computers, people were already making this kind of images with type writers. Nevertheless the art survives even to present day and lives on in the hacker culture, in Unix communities, on the Smol Internet etc. ASCII diagram may very well be embedded e.g. in a comment in a source code to explain some spatial concept -- that's pretty KISS. We, LRS, highly advocate use of ASCII art whenever it's good enough.

Here is a simple 16-shade ASCII palette (but watch out, whether it works will depend on your font): #OVaxsflc/!;,.- . Another one can be e.g.: WM0KXkxocl;:,'. .

            _,,_  
           /    ';_  
    .     (  0 _/  "-._
    |\     \_ /_==-"""'
    | |:---'   (
     \ \__."    ) Steamer
      '--_ __--'    Duck!
          |L_
          

      []  [][][][][]
      [][][]      [][]
      [][]          []
      []    XX    XX[]
      []      XXXX  []
      [][]          []
      [][][]      [][]
      []  [][][][][]
        
          SAF FTW
          
^
|
|   _.--._                  _.--._
| .'      '.              .'      '.
|/__________\____________/__________\______
|            \          /            \
|             '.      .'              '.
|               `'--'`                  `'-
|
V

   ("\/") ("\/") ("\/")
   \    / \    / \    /
    \  /   \  /   \  /
     \/     \/     \/

See Also

• ANSI art
• pixel art
• plain text
• cowsay
• figlet

ASCII

ASCII (American standard code for information interchange) is a relatively simple standard for digital encoding of text that's one of the most basic and probably the most common format used for this purpose. For its simplicity and inability to represent characters of less common alphabets it is nowadays quite often replaced with more complex encodings such as UTF-8 who are however almost always backwards compatible with ASCII (interpreting UTF-8 as ASCII will give somewhat workable results), and ASCII itself is also normally supported everywhere. ASCII is the suckless/LRS/KISS character encoding, recommended and good enough for most programs.

The ASCII standard assigns a 7 bit code to each basic text character which gives it a room for 128 characters -- these include lowercase and uppercase English alphabet, decimal digits, other symbols such as a question mark, comma or brackets, plus a few special control characters that represent instructions such as carriage return which are however often obsolete nowadays. Due to most computers working with 8 bit bytes, most platforms store ASCII text with 1 byte per character; the extra bit creates a room for extending ASCII by another 128 characters (or creating a variable width encoding such as UTF-8). These extensions include unofficial ones such as VISCII (ASCII with additional Vietnamese characters) and more official ones, most notably ISO 8859: a group of standards by ISO for various languages, e.g. ISO 88592-1 for western European languages, ISO 8859-5 for Cyrillic languages etc.

The ordering of characters has been kind of cleverly designed to make working with the encoding easier, for example digits start with 011 and the rest of the bits correspond to the digit itself (0000 is 0, 0001 is 1 etc.). Corresponding upper and lower case letters only differ in the 6th bit, so you can easily convert between upper and lower case by negating it as letter ^ 0x20. { I think there is a few missed opportunities though, e.g. in not putting digits right before letters. That way it would be very easy to print hexadecimal (and all bases up to a lot) simply as putchar('0' + x). ~drummyfish }

ASCII was approved as an ANSI standard in 1963 and since then underwent many revisions every few years. The current one is summed up by the following table:

See Also

• Unicode
• PETSCII
• ATASCII
• ASCII art
• base64

Assembly

Assembly (also ASM) is, for any given hardware computing platform (ISA, basically a CPU architecture), the lowest level programming language that expresses typically a linear, unstructured sequence of CPU instructions -- it maps (mostly) 1:1 to machine code (the actual binary CPU instructions) and basically only differs from the actual machine code by utilizing a more human readable form (it gives human friendly nicknames, or mnemonics, to different combinations of 1s and 0s). Assembly is converted by assembler into the the machine code. Assembly is similar to bytecode, but bytecode is meant to be interpreted or used as an intermediate representation in compilers while assembly represents actual native code run by hardware. In ancient times when there were no higher level languages (like C or Fortran) assembly was used to write computer programs -- nowadays most programmers no longer write in assembly (majority of zoomer "coders" probably never even touch anything close to it) because it's hard (takes a long time) and not portable, however programs written in assembly are known to be extremely fast as the programmer has absolute control over every single instruction (of course that is not to say you can't fuck up and write a slow program in assembly).

Assembly is NOT a single language, it differs for every architecture, i.e. every model of CPU has potentially different architecture, understands a different machine code and hence has a different assembly (though there are some standardized families of assembly like x86 that work on wide range of CPUs); therefore assembly is not portable (i.e. the program won't generally work on a different type of CPU or under a different OS)! And even the same kind of assembly language may have several different syntax formats which may differ in comment style, order of writing arguments and even instruction abbreviations (e.g. x86 can be written in Intel and AT&T syntax). For the reason of non-portability (and also for the fact that "assembly is hard") you shouldn't write your programs directly in assembly but rather in a bit higher level language such as C (which can be compiled to any CPU's assembly). However you should know at least the very basics of programming in assembly as a good programmer will come in contact with it sometimes, for example during hardcore optimization (many languages offer an option to embed inline assembly in specific places), debugging, reverse engineering, when writing a C compiler for a completely new platform or even when designing one's own new platform. You should write at least one program in assembly -- it gives you a great insight into how a computer actually works and you'll get a better idea of how your high level programs translate to machine code (which may help you write better optimized code) and WHY your high level language looks the way it does.

The most common assembly languages you'll encounter nowadays are x86 (used by most desktop CPUs) and ARM (used by most mobile CPUs) -- both are used by proprietary hardware and though an assembly language itself cannot (as of yet) be copyrighted, the associated architectures may be "protected" (restricted) e.g. by patents. RISC-V on the other hand is an "open" alternative, though not yet so wide spread. Other assembly languages include e.g. AVR (8bit CPUs used e.g. by some Arduinos) and PowerPC.

To be precise, a typical assembly language is actually more than a set of nicknames for machine code instructions, it may offer helpers such as macros (something aking the C preprocessor), pseudoinstructions (commands that look like instructions but actually translate to e.g. multiple instructions), comments, directives, named labels for jumps (as writing literal jump addresses would be extremely tedious) etc.

Assembly is extremely low level, so you get no handholding or much programming "safety" (apart from e.g. CPU operation modes), you have to do everything yourself -- you'll be dealing with things such as function call conventions, interrupts, syscalls and their conventions, how many CPU cycles different instructions take, memory segments, endianness, raw addresses/goto jumps, call frames etc.

Note that just replacing assembly mnemonics with binary machine code instructions is not yet enough to make an executable program! More things have to be done such as linking libraries and converting the result to some executable format such as elf which contains things like header with metainformation about the program etc.

Typical Assembly Language

Assembly languages are usually unstructured, i.e. there are no control structures such as if or while statements: these have to be manually implemented using labels and jump (goto) instructions. There may exist macros that mimic control structures. The typical look of an assembly program is however still a single column of instructions with arguments, one per line, each representing one machine instruction.

The working of the language reflects the actual hardware architecture -- most architectures are based on registers so usually there is a small number (something like 16) of registers which may be called something like R0 to R15, or A, B, C etc. Sometimes registers may even be subdivided (e.g. in x86 there is an eax 32bit register and half of it can be used as the ax 16bit register). These registers are the fastest available memory (faster than the main RAM memory) and are used to perform calculations. Some registers are general purpose and some are special: typically there will be e.g. the FLAGS register which holds various 1bit results of performed operations (e.g. overflow, zero result etc.). Some instructions may only work with some registers (e.g. there may be kind of a "pointer" register used to hold addresses along with instructions that work with this register, which is meant to implement arrays). Values can be moved between registers and the main memory (with instructions called something like move, load or store).

Writing instructions works similarly to how you call a function in high level language: you write its name and then its arguments, but in assembly things are more complicated because an instruction may for example only allow certain kinds of arguments -- it may e.g. allow a register and immediate constant (kind of a number literal/constant), but not e.g. two registers. You have to read the documentation for each instruction. While in high level language you may write general expressions as arguments (like myFunc(x + 2 * y,myFunc2())), here you can only pass specific values.

There are also no complex data types, assembly only works with numbers of different size, e.g. 16 bit integer, 32 bit integer etc. Strings are just sequences of numbers representing ASCII values, it is up to you whether you implement null terminated strings or Pascal style strings. Pointers are just numbers representing addresses. It is up to you whether you interpret a number as signed or unsigned (some instructions treat numbers as unsigned, some as signed).

Instructions are typically written as three-letter abbreviations and follow some unwritten naming conventions so that different assembly languages at least look similar. Common instructions found in most assembly languages are for example:

• MOV (move): move a number between registers and/or main memory (RAM).
• JMP (jump): unconditional jump to far away instruction.
• BEQ (branch if equal): jump if result of previous comparison was equality.
• ADD (add): add two numbers.
• NOP (no operation): do nothing (used e.g. for delays or as placeholders).
• CMP (compare): compare two numbers and set relevant flags (typically for a subsequent conditional jump).

How To

On Unices the objdump utility from GNU binutils can be used to disassemble compiled programs, i.e view the instructions of the program in assembly (other tools like ndisasm can also be used). Use it e.g. as:

objdump -d my_compiled_program

Let's now write a simple Unix program in x86 assembly (AT&T syntax). Write the following source code into a file named e.g. program.s:

.global   _start         # include the symbol in object file

str:
.ascii    "it works\n"   # the string data

.text 
_start:                  # execution starts here
  mov     $5,   %rbx     # store loop counter in rbx

.loop:
  # make a Linux "write" syscall:
                         # args to syscall will be passed in regs.
  mov     $1,   %rax     # says syscalls type (1 = write)
  mov     $1,   %rdi     # says file to write to (1 = stdout)
  mov     $str, %rsi     # says the address of the string to write
  mov     $9,   %rdx     # says how many bytes to write
  syscall                # makes the syscall

  sub     $1,   %rbx     # decrement loop counter
  cmp     $0,   %rbx     # compare it to 0
  jne     .loop          # if not equal, jump to start of the loop

  # make an "exit" syscall to properly terminate:
  mov     $60,  %rax     # says syscall type (60 = exit)
  mov     $0,   %rdi     # says return value (0 = success)
  syscall                # makes the syscall

The program just writes out it works five times: it uses a simple loop and a Unix system call for writing a string to standard output (i.e. it won't work on Windows and similar shit).

Now assembly source code can be manually assembled into executable by running assemblers like as or nasm to obtain the intermediate object file and then linking it with ld, but to assemble the above written code simply we may just use the gcc compiler which does everything for us:

gcc -nostdlib -no-pie -o program program.s

Now we can run the program with

./program

And we should see

it works
it works
it works
it works
it works

As an exercise you can objdump the final executable and see that the output basically matches the original source code. Furthermore try to disassemble some primitive C programs and see how a compiler e.g. makes if statements or functions into assembly.

Example

Let's take the following C code:

#include <stdio.h>

char incrementDigit(char d)
{
  return // remember this is basically an if statement
    d >= '0' && d < '9' ?
    d + 1 :
    '?';
}

int main(void)
{
  char c = getchar();
  putchar(incrementDigit(c));
  return 0;
}

We will now compile it to different assembly languages (you can do this e.g. with gcc -S my_program.c). This assembly will be pretty long as it will contain boilerplate and implementations of getchar and putchar from standard library, but we'll only be looking at the assembly corresponding to the above written code. Also note that the generated assembly will probably differ between compilers, their versions, flags such as optimization level etc. The code will be manually commented.

{ I used this online tool: https://godbolt.org. ~drummyfish }

The x86 assembly may look like this:

incrementDigit:
  pushq   %rbp                   # save base pointer
  movq    %rsp, %rbp             # move base pointer to stack top
  movl    %edi, %eax             # move argument to eax
  movb    %al, -4(%rbp)          # and move it to local var.
  cmpb    $47, -4(%rbp)          # compare it to '0'
  jle     .L2                    # if <=, jump to .L2
  cmpb    $56, -4(%rbp)          # else compare to '9'
  jg      .L2                    # if >, jump to .L4
  movzbl  -4(%rbp), %eax         # else get the argument
  addl    $1, %eax               # add 1 to it
  jmp     .L4                    # jump to .L4
.L2:
  movl    $63, %eax              # move '?' to eax (return val.)
.L4:
  popq    %rbp                   # restore base pointer
  ret
  
main:
  pushq   %rbp                   # save base pointer
  movq    %rsp, %rbp             # move base pointer to stack top
  subq    $16, %rsp              # make space on stack
  call    getchar                # push ret. addr. and jump to func.
  movb    %al, -1(%rbp)          # store return val. to local var.
  movsbl  -1(%rbp), %eax         # move with sign extension
  movl    %eax, %edi             # arg. will be passed in edi
  call    incrementDigit
  movsbl  %al, %eax              # sign extend return val.
  movl    %eax, %edi             # pass arg. in edi again
  call    putchar
  movl    $0, %eax               # values are returned in eax
  leave
  ret

The ARM assembly may look like this:

incrementDigit:
  sub   sp, sp, #16              // make room on stack
  strb  w0, [sp, 15]             // load argument from w0 to local var.
  ldrb  w0, [sp, 15]             // load back to w0
  cmp   w0, 47                   // compare to '0'
  bls   .L2                      // branch to .L2 if <
  ldrb  w0, [sp, 15]             // load argument again to w0
  cmp   w0, 56                   // compare to '9'
  bhi   .L2                      // branch to .L2 if >=
  ldrb  w0, [sp, 15]             // load argument again to w0
  add   w0, w0, 1                // add 1 to it
  and   w0, w0, 255              // mask out lowest byte
  b     .L3                      // branch to .L3
.L2:
  mov   w0, 63                   // set w0 (ret. value) to '?'
.L3:
  add   sp, sp, 16               // shift stack pointer back
  ret
  
main:
  stp   x29, x30, [sp, -32]!     // shift stack and store x regs
  mov   x29, sp
  bl    getchar
  strb  w0, [sp, 31]             // store w0 (ret. val.) to local var. 
  ldrb  w0, [sp, 31]             // load it back to w0
  bl    incrementDigit
  and   w0, w0, 255              // mask out lowest byte
  bl    putchar
  mov   w0, 0                    // set ret. val. to 0
  ldp   x29, x30, [sp], 32       // restore x regs
  ret

The RISC-V assembly may look like this:

incrementDigit:
  addi    sp,sp,-32              # shift stack (make room)
  sw      s0,28(sp)              # save frame pointer
  addi    s0,sp,32               # shift frame pointer
  mv      a5,a0                  # get arg. from a0 to a5
  sb      a5,-17(s0)             # save to to local var.
  lbu     a4,-17(s0)             # get it to a4
  li      a5,47                  # load '0' to a4
  bleu    a4,a5,.L2              # branch to .L2 if a4 <= a5
  lbu     a4,-17(s0)             # load arg. again
  li      a5,56                  # load '9' to a5
  bgtu    a4,a5,.L2              # branch to .L2 if a4 > a5
  lbu     a5,-17(s0)             # load arg. again
  addi    a5,a5,1                # add 1 to it
  andi    a5,a5,0xff             # mask out the lowest byte
  j       .L3                    # jump to .L3
.L2:
  li      a5,63                  # load '?'
.L3:
  mv      a0,a5                  # move result to ret. val.
  lw      s0,28(sp)              # restore frame pointer
  addi    sp,sp,32               # pop stack
  jr      ra                     # jump to addr in ra
  
main:
  addi    sp,sp,-32              # shift stack (make room)
  sw      ra,28(sp)              # store ret. addr on stack
  sw      s0,24(sp)              # store stack frame pointer on stack
  addi    s0,sp,32               # shift frame pointer
  call    getchar
  mv      a5,a0                  # copy return val. to a5
  sb      a5,-17(s0)             # move a5 to local var
  lbu     a5,-17(s0)             # load it again to a5
  mv      a0,a5                  # move it to a0 (func. arg.)
  call    incrementDigit
  mv      a5,a0                  # copy return val. to a5
  mv      a0,a5                  # get it back to a0 (func. arg.)
  call    putchar
  li      a5,0                   # load 0 to a5
  mv      a0,a5                  # move it to a0 (ret. val.)
  lw      ra,28(sp)              # restore return addr.
  lw      s0,24(sp)              # restore frame pointer
  addi    sp,sp,32               # pop stack
  jr      ra                     # jump to addr in ra

Assertiveness

Assertiveness is an euphemism for being a dick.

Arcus Tangent

Arcus tangent, written as atan or tan^-1, is the inverse function to the tangent function. For given argument x (any real number) it returns a number y (from -pi/2 to pi/2) such that tan(y) = x.

Approximation: Near 0 atan(x) can very rougly be approximated simply by x. For a large argument atan(x) can be approximated by pi/2 - 1/x (as atan's limit is pi/2). The following formula { created by me ~drummyfish } approximates atan with a poylnomial for non-negative argument with error smaller than 2%:

atan(x) ~= (x * (2.96088 + 4.9348 * x))/(3.2 + 3.88496 * x + pi * x^2)

            | y
       pi/2 +                  
            |       _..---''''''
            |   _.''
            | .'
-----------.+'-+--+--+--+--+--> x
        _.' |0 1  2  3  4  5
     _-'    |
.--''       |
      -pi/2 +
            |

plot of atan(x)

Atheism

"In this moment I am euphoric ..." --some retarded atheist

An atheist is someone who doesn't believe in god or any other similar supernatural beings.

An especially annoying kind is the reddit atheist who will DESTROY YOU WITH FACTS AND LOGIC^(TM). These atheists are 14 year old children who think they've discovered the secret of the universe and have to let the whole world know they're atheists who will destroy you with their 200 IQ logic and knowledge of all 10 cognitive biases and argument fallacies, while in fact they reside at the mount stupid and many times involuntarily appear on other subreddits such as r/iamverysmart and r/cringe. They masturbate to Richard Dawkins, love to read soyentific studiiiiiies about how race has no biological meaning and think that religion is literally Hitler. They like to pick easy targets such as flatearthers and cyberbully them on YouTube with the power of SCIENCE and their enormously large thesaurus (they will never use a word that's among the 100000 most common English words). They are so cringe you want to kill yourself, but their discussions are sometimes entertaining to read with a bowl of popcorn.

Such a specimen of atheist is one of the best quality examples of a pseudosceptic. See also this: https://www.debunkingskeptics.com/Contents.htm.

On a bit more serious note: we've all been there, most people in their teens think they're literal Einsteins and then later in life cringe back on themselves. However, some don't grow out of it and stay arrogant, ignorant fucks for their whole lives. The principal mistake of the stance they retain is they try to apply "science" (or whatever it means in their world) to EVERYTHING and reject any other approach to solving problems -- of course, science (the real one) is great, but it's just a tool, and just like you can't fix every problem with a hammer, you can't approach every problem with science. In your daily life you make a million of unscientific decisions and it would be bad to try to apply science to them; you cross the street not because you've read a peer-reviewed paper about it being the most scientifically correct thing to do, but because you feel like doing it, because you believe the drivers will stop and won't run you over. Beliefs, intuition, emotion, non-rationality and even spirituality are and have to be part of life, and it's extremely stupid to oppose these concepts just out of principle. With that said, there's nothing wrong about being a well behaved man who just doesn't feel a belief in any god in his heart, just you know, don't be an idiot.

Among the greatest minds it is hard to find true atheists, even though they typically have a personal and not easy to describe faith. Newton was a Christian. Einstein often used the word "God" instead of "nature" or "universe"; even though he said he didn't believe in the traditional personal God, he also said that the laws of physics were like books in a library which must have obviously been written by someone or something we can't comprehend. Nikola Tesla said he was "deeply religious, though not in the orthodox sense". There are also very hardcore religious people such as Larry Wall, the inventor of Perl language, who even planned to be a Christian missionary. The "true atheists" are mostly second grade "scientists" who make career out of the pose and make living by writing books about atheism rather than being scientists.

See Also

• stupidity

Audiophilia

Audiophilia is a mental disorder, similar to other diseases such as distrohopping and chronic ricing, that makes one scared of low or normal quality audio. Audiophiles are scared of lossy compression and so harm society by wasting storage space. Audiophilia, similarly to e.g. the business with mechanical keyboards, is the astrology of technology, it is an arbitrarily invented bullshit business creating an artificial need that makes people wanna buy golden cables and similar shit in belief that it will make their life happier, perpetuation consumerism and capitalism.

Autoupdate

Autoupdate is a malicious software feature that frequently remotely modifies software on the user's device without asking, sometimes silently and many times in a forced manner without the possibility to refuse this modification (typically in proprietary software). This is a manifestation of update culture. These remote software modifications are called "updates" to make the user think they are a good thing, but in fact they usually introduce more bugs, bloat, security vulnerabilities, annoyance (forced reboots etc.) and malware (even in "open source", see e.g. the many projects on GitHub that introduced intentional malware targeted at Russian users during the Russia-Ukraine war).

Avoidant Personality Disorder

TODO

In many cases avoiding the problem really is the objectively best solution.

Axiom Of Choice

In mathematics (specifically set theory) axiom of choice is a possible axiom which basically states we can arbitrarily choose elements of sets and which is famous for being controversial and problematic because it causes trouble both when we accept or reject it. Note that this topic can go to a great depth and lead to philosophical debates, there is a huge rabbit hole and mathematicians can talk about this for hours; here we'll only state the very basic and quite simplified things, mostly for those who aren't professional mathematicians but need some overview of mathematics (e.g. programmers).

Indeed, what really IS the axiom of choice? It is an axiom, i.e. something that we can't prove but can either accept or reject as a basic fact so that we can use it to prove things. Informally it says that given any collection of sets (even an infinite collection of infinitely large sets), we can make an arbitrary selection of one element from each set. More mathematically it says: if we have a collection of sets, there always exists a function f such that for any set S from the collection f(S) is an element of S.

This doesn't sound weird, does it? Well, in many normal situations it isn't. For example if we have finitely many sets, we can simply write out each element of the set, we don't need to define any selection function, so we don't need axiom of choice to make our choice of elements here. But also if we have infinitely many sets that are well ordered (we can compare elements), for example infinitely many sets of natural numbers, we can simply define a function that takes e.g. the smallest number from each set -- here we don't need axiom of choice either. The issues start if we have e.g. infinitely many sets of real numbers (which can't be well ordered without the axiom of choice, consider that e.g. open intervals don't have lowest number) -- here we can't say how a function should select one element from each set, so we have to either accept axiom of choice (we say it simply can be done "somehow", e.g. by writing each element out on an infinitely large paper) or reject it (we say it can't be done). Here it is again the case that what's normally completely non-problematic starts to get very weird once you involve infinity.

Why is it problematic? Once you learn about axiom of choice, your first question will probably be why should it pose any problems if it just seems like an obvious fact. Well, it turns out it leads to strange things. If we accept axiom of choice, then some weird things happen, most famously e.g. the Banach-Tarski paradox which uses the axiom of choice to prove that you can disassemble a sphere into finitely many pieces, then move and rotate them so that they create TWO new spheres, each one identical to the original (i.e. you duplicate the original sphere). But if we reject the axiom of choice, other weird things happen, for example we can't prove that every vector space has a basis -- it seems quite elementary that every vector space should have a basis, but this can't be proven without the axiom of choice and in fact accepting this implies the axiom of choice is true. Besides this great many number of proofs simply don't work without axiom of choice. So essentially either way things get weird, whether we accept axiom of choice or not.

So what do mathematicians do? How do they deal with this and why don't they kill themselves? Well, in reality most of them are pretty chill and don't really care, they try avoid it if they can (their proof is kind of stronger if it relies on fewer axioms) but they accept it if they really need it for a specific proof. Many elementary things in mathematics actually rely on axiom of choice, so there's no fuzz when someone uses it, it's very normal. Turns out axiom of choice is more of something they argue over a beer, they usually disagree about whether it is INTUITIVELY true or false, but that doesn't really affect their work.

Backgammon

Backgammon is an old, very popular board game of both skill and chance (dice rolling). It often involves betting and is especially popular in countries of Near East such as Egypt, Syria etc. (where it is kind of what chess is to our western world or what shogi and go are to Asia). Similartly to chess, go, shogi and other traditional board games backgammon is considered by us to be one of the best games as it is owned by no one, highly free, cheap, simple yet deep and entertaining and can be played even without a computer, just with a bunch of rocks; compared to the other mentioned board games backgammon is unique by involving an element of chance and being only played on 1 dimensional board; it is also relatively simple and therefore noob-friendly and possibly more relaxed (if you lose you can just blame it on rolling bad numbers).

TODO

Backpropagation

{ Dunno if this is completely correct, I'm learning this as I'm writing it. There may be errors. ~drummyfish }

Backpropagation, or backprop, is an algorithm, based on the chain rule of derivation, used in training neural networks; it computes the partial derivative (or gradient) of the function of the network's error so that we can perform a gradient descent, i.e. update the weights towards lowering the network's error. It computes the analytical derivative (theoretically you could estimate a derivative numerically, but that's not so accurate and can be too computationally expensive). Backpropagation is one of the most common methods for training neural networks but it is NOT the only possible one -- there are many more such as evolutionary programming. It is called backpropagation because it works backwards and propagates the error from the output towards the input, due to how the chain rule works, and it's efficient by reusing already computed values.

Details

Consider the following neural network:

     w000     w100
  x0------y0------z0
    \    /  \    /  \
     \  /    \  /    \
      \/w010  \/w11O  \_E
      /\w001  /\w1O1  /
     /  \    /  \    /
    /    \  /    \  /
  x1------y1------z1
     w011     w111

It has an input layer (neurons x0, x1), a hidden layer (neurons y0, y1) and an output layer (neurons z0, z1). For simplicity there are no biases (biases can easily be added as input neurons that are always on). At the end there is a total error E computed from the networks's output against the desired output (training data).

Let's say the total error is computed as the squared error: E = squared_error(z0) + squared_error(z1) = 1/2 * (z0 - z0_desired)^2 + 1/2 * (z1 - z1_desired)^2.

We can see each non-input neuron as a function. E.g. the neuron z0 is a function z0(x) = z0(a(z0s(x))) where:

• z0s is the sum of inputs to the neuron, in this case z0s(x) = w100 * y0(x) + +110 * y1(x)
• a is the activation function, let's suppose the normally used logistic function a(x) = 1/(1 + e^x).

If you don't know what the fuck is going on see neural networks first.

What is our goal now? To find the partial derivative of the whole network's total error function (at the current point defined by the weights), or in other words the gradient at the current point. I.e. from the point of view of the total error (which is just a number output by this system), the network is a function of 8 variables (weights w000, w001, ...) and we want to find a derivative of this function in respect to each of these variables (that's what a partial derivative is) at the current point (i.e. with current values of the weights). This will, for each of these variables, tell us how much (at what rate and in which direction) the total error changes if we change that variable by certain amount. Why do we need to know this? So that we can do a gradient descent, i.e. this information is kind of a direction in which we want to move (change the weights and biases) towards lowering the total error (making the network compute results which are closer to the training data). So all in all the goal is to find derivatives (just numbers, slopes) with respect to w000, w001, w010, ... w111.

Could we do this without backpropagation? Yes -- we can use numerical algorithms to estimate derivatives, the simplest one would be to just try to change each weight, one by one, by some small number, let's say dw, and see how much such change changes the output error. I.e. we would sample the error function in all directions which could give us an idea of the slope in each direction. However this would be pretty slow, we would have to reevaluate the whole neural network as many times as there are weights. Backpropagation can do this much more efficiently.

Backpropagation is based on the chain rule, a rule of derivation that equates the derivative of a function composition (functions inside other functions) to a product of derivatives. This is important because by converting the derivatives to a product we will be able to reuse the individual factors and so compute very efficiently and quickly.

Let's write derivative of f(x) with respect to x as D{f(x),x}. The chain rule says that:

D{f(g(x)),x} = D{f(g(x)),g(x)} * D{g(x),x}

Notice that this can be applied to any number of composed functions, the product chain just becomes longer.

Let's get to the computation. Backpropagation work by going "backwards" from the output towards the input. So, let's start by computing the derivative against the weight w100. It will be a specific number; let's call it 'w100. Derivative of a sum is equal to the sum of derivatives:

'w100 = D{E,w100} = D{squared_error(z0),w100} + D{squared_error(z0),w100} = D{squared_error(z0),w100} + 0

(The second part of this sum became 0 because with respect to w100 it is a constant.)

Now we can continue and utilize the chain rule:

'w100 = D{E,w100} = D{squared_error(z0),w100} = D{squared_error(z0(a(z0s))),w100} = D(squared_error(z0),z0) * D{a(z0s),z0s} * d{z0s,w100}

We'll now skip the intermediate steps, they should be easy if you can do derivatives. The final results is:

'w100 = (z0_desired - z0) * (z0s * (1 - z0s)) * y0

Now we have computed the derivative against w100. In the same way can compute 'w101, 'w110 and 'w111 (weights leading to the output layer).

Now let's compute the derivative in respect to w000, i.e. the number 'w000. We will proceed similarly but the computation will be different because the weight w000 affects both output neurons ('z0' and 'z1'). Again, we'll use the chain rule.

w000 = D{E,w000} = D(E,y0) * D{a(y0s),y0s} * D{y0s,w000}

D(E,y0) = D{squared_error(z0),y0} + D{squared_error(z1),y0}

Let's compute the first part of the sum:

D{squared_error(z0),y0} = D{squared_error(z0),z0s} * D{squared_error(z0s),y0}

D{squared_error(z0),z0s} = D{squared_error(z0),z0} * D{a(z0s)),z0s}

Note that this last equation uses already computed values which we can reuse. Finally:

D{squared_error(z0s),y0} = D{squared_error(w100 * y0 + w110 * y1),y0} = w100

And we get:

D{squared_error(z0),y0} = D{squared_error(z0),z0} * D{a(z0s)),z0s} * w100

And so on until we get all the derivatives.

Once we have them, we multiply them all by some value (learning rate, a distance by which we move in the computed direction) and subtract them from the current weights by which we perform the gradient descent and lower the total error.

Note that here we've only used one training sample, i.e. the error E was computed from the network against a single desired output. If more example are used in a single update step, they are usually somehow averaged.

BBS

{ I am too young to remember this shit so I'm just writing what I've read on the web. ~drummyfish }

Bulletin board system (BBS) is, or rather used to be, a kind of server that hosts a community of users who connect to it via terminal, who exchange messages, files, play games and otherwise interact -- BBSes were mainly popular before the invention of web, i.e. from about 1978 to mid 1990s, however some still exist today. BBSes are powered by special BBS software and the people who run them are called sysops.

Back then people connected to BBSes via dial-up modems and connecting was much more complicated than connecting to a server today: you had to literally dial the number of the BBS and you could only connect if the BBS had a free line. Early BBSes weren't normally connected through Internet but rather through other networks like UUCP working through phone lines. I.e. a BBS would have a certain number of modems that defined how many people could connect at once. It was also expensive to make calls into other countries so BBSes were more of a local thing, people would connect to their local BBSes. Furthermore these things ran often on non-multitasking systems like DOS so allowing multiple users meant the need for having multiple computers. The boomers who used BBSes talk about great adventure and a sense of intimacy, connecting to a BBS meant the sysop would see you connecting, he might start chatting with you etc. Nowadays the few existing BBSes use protocols such as telnet, nevertheless there are apparently about 20 known dial-up ones in north America. Some BBSes evolved into more modern communities based e.g. on public access Unix systems -- for example SDF.

A BBS was usually focused on a certain topic such as technology, fantasy roleplay, dating, warez etc., they would typically greet the users with a custom themed ANSI art welcome page upon login -- it was pretty cool.

{ There's some documentary on BBS that's upposed to give you an insight into this shit, called literally BBS: The documentary. It's about 5 hours long tho. ~drummyfish }

The first BBS was CBBS (computerized bulletin board system) created by Ward Christensen and Randy Suess in 1978 during a blizzard storm -- it was pretty primitive, e.g. it only allowed one user to be connected at the time. After publication of their invention, BBSes became quite popular and the number of them grew to many thousands -- later there was even a magazine solely focused on BBSes (BBS Magazine). BBSes would later group into larger networks that allowed e.g. interchange of mail. The biggest such network was FidoNet which at its peak hosted about 35000 nodes.

{ Found some list of BBSes at http://www.synchro.net/sbbslist.html. ~drummyfish }

See Also

• public access Unix
• Usenet
• modem world
• tildeverse

Beauty

Beauty is the quality of being extremely appealing and pleasing. Though the word will likely invoke association with traditional art, in technology, engineering, mathematics and other science beauty is, despite it's relative vagueness and subjectivity, an important aspect of design, and in fact this "mathematical beauty" has lots of times some clearly defined shapes -- for example simplicity is mostly considered beautiful. Beauty is similar to and many times synonymous with elegance.

Beauty can perhaps be seen as a heuristic, a touch of intuition that guides the expert in exploration of previously unknown fields, as we have come to learn that the greatest discoveries tend to be very beautiful (however there is also an opposite side: some people, such as Sabine Hossenfelder, criticize e.g. the pursuit of beautiful theories in modern physics as this approach seems to be have led to stagnation). Indeed, beginners and noobs are mostly concerned with learning hard facts, learning standards and getting familiar with already known ways of solving known problems, they often aren't able to recognize what's beautiful and what's ugly. But as one gets more and more experienced and finds himself near the borders of current knowledge, there is suddenly no guidance but intuition, beauty, to suggest ways forward, and here one starts to get the feel for beauty. At this point the field, even if highly exact and rigorous, has become an art.

What is beautiful then? As stated, there is a lot of subjectivity, but generally the following attributes are correlated with beauty:

• simplicity, typically finding simplicity in complexity, e.g. a very short formula or algorithm that describes an infinitely complex fractal shape, a simple but valuable equation in physics (e = m * c^2), a short computer program that yields rich results (demoscene, code golfing, suckless, ...).
• generality, i.e. if a simple equation can describe many problems, not just a specific case.
• lack of exceptions, i.e. when our equation works without having to deal with special cases (in programming represented by if-then branches).
• symmetry, i.e. when we can e.g. swap variables in the equation and get some kind of opposite result.
• unification, i.e. if multiple nice things meet, for example the Euler's identity brings together into one equation the most important numbers in mathematics: i, pi, 1 and 0.
• aesthetics, either of the equation itself or the generated thing (fractals, attractors, ...).
• TODO

Examples of beautiful things include:

• Euler's identity, an equation often cited as the most beautiful in mathematics: e^{ipi} + 1 = 0*. It is simple and contains many of the most important numbers: e, pi, i 1 and 0.
• minimalist software, Unix philosophy
• fractals TODO
• bytebeat

Bilinear Interpolation

Bilinear interpolation (also bilinear filtering) is a simple way of creating a smooth transition (interpolation) between discrete samples (values) in 2D, it is a generalization of linear interpolation to 2 dimensions. It is used in many places, popularly e.g. in 3D computer graphics for texture filtering; bilinear interpolation allows to upscale textures to higher resolutions (i.e. compute new pixels between existing pixels) while keeping their look smooth and "non-blocky" (even though blurry). On the scale of quality vs simplicity it is kind of a middle way between a simpler nearest neighbour interpolation (which creates the "blocky" look) and more complex bicubic interpolation (which uses yet smoother curves but also requires more samples). Bilinear interpolation can further be generalized to trilinear interpolation (in computer graphics trilinear interpolation is used to also additionally interpolate between different levels of a texture's mipamap) and perhaps even bilinear extrapolation. Many frameworks/libraries/engines have bilinear filtering built-in (e.g. GL_LINEAR in OpenGL).

####OOOOVVVVaaaaxxxxssssffffllllcccc////!!!!;;;;,,,,....----    
####OOOOVVVVaaaaxxxxxssssffffllllcccc////!!!!;;;;,,,,.....----  
####OOOOVVVVaaaaaxxxxssssfffflllllcccc////!!!!!;;;;,,,,....-----
###OOOOOVVVVaaaaaxxxxsssssfffflllllcccc////!!!!!;;;;,,,,,....---
###OOOOVVVVVaaaaaxxxxsssssfffffllllccccc/////!!!!!;;;;,,,,,.....
##OOOOOVVVVVaaaaaxxxxxsssssffffflllllcccc/////!!!!!;;;;;,,,,,...
##OOOOOVVVVVaaaaaxxxxxsssssfffffflllllccccc/////!!!!!;;;;;,,,,,.
#OOOOOOVVVVVaaaaaxxxxxxsssssfffffflllllccccc//////!!!!!;;;;;;,,,
OOOOOOVVVVVVaaaaaaxxxxxssssssfffffflllllcccccc//////!!!!!;;;;;;,
OOOOOOVVVVVVaaaaaaxxxxxxssssssffffffllllllcccccc//////!!!!!!;;;;
OOOOOVVVVVVVaaaaaaxxxxxxsssssssfffffflllllllcccccc///////!!!!!!;
OOOOOVVVVVVaaaaaaaxxxxxxxsssssssffffffflllllllccccccc//////!!!!!
OOOOVVVVVVVaaaaaaaaxxxxxxxsssssssfffffffflllllllccccccc////////!
OOOVVVVVVVVaaaaaaaaxxxxxxxxssssssssffffffffllllllllcccccccc/////
OOVVVVVVVVVaaaaaaaaaxxxxxxxxsssssssssfffffffflllllllllcccccccc//
OVVVVVVVVVVaaaaaaaaaxxxxxxxxxssssssssssffffffffflllllllllccccccc
VVVVVVVVVVaaaaaaaaaaaxxxxxxxxxxssssssssssfffffffffffllllllllllcc
VVVVVVVVVVaaaaaaaaaaaxxxxxxxxxxxxsssssssssssffffffffffffllllllll
VVVVVVVVVVaaaaaaaaaaaaxxxxxxxxxxxxxsssssssssssssffffffffffffflll
VVVVVVVVVaaaaaaaaaaaaaaaxxxxxxxxxxxxxxsssssssssssssssfffffffffff
VVVVVVVVaaaaaaaaaaaaaaaaaxxxxxxxxxxxxxxxxxxsssssssssssssssssffff
VVVVVVVaaaaaaaaaaaaaaaaaaaaaxxxxxxxxxxxxxxxxxxxxssssssssssssssss
VVVVVVaaaaaaaaaaaaaaaaaaaaaaaaaxxxxxxxxxxxxxxxxxxxxxxxxxxsssssss
VVVaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaxxxxxxxxxxxxxxxxxxxxxxxxxxx
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaxxxxxxxxxxxxxxx
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaVVVVVVVVVVVVVVVVVVV
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVV
aaaaaaaaaaaaaaaaaaaaaaaaVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVOOOOOO
aaaaaaaaaaaaaaaaaaaaaVVVVVVVVVVVVVVVVVVVVVVVVVVOOOOOOOOOOOOOOOOO
aaaaaaaaaaaaaaaaaaaaVVVVVVVVVVVVVVVVVVVVOOOOOOOOOOOOOOOOOOOOO###

The above image is constructed by applying bilinear interpolation to the four corner values.

The principle is simple: first linearly interpolate in one direction (e.g. horizontal), then in the other (vertical). Mathematically the order in which we take the dimensions doesn't matter (but it may matter practically due to rounding errors etc.).

Example: let's say we want to compute the value x between the four following given corner values:

1 . . . . . . 5
. . . . . . . .
. . . . . . . . 
. . . . . . . .
. . . . . . . .
. . . . x . . .
. . . . . . . .
8 . . . . . . 3

Let's say we first interpolate horizontally: we'll compute one value, a, on the top (between 1 and 5) and one value, b, at the bottom (between 8 and 3). When computing a we interpolate between 1 and 5 by the horizontal position of x (4/7), so we get a = 1 + 4/7 * (5 - 1) = 23/7. Similartly b = 8 + 4/7 * (3 - 8) = 36/7. Now we interpolate between a and b vertically (by the vertical position of x, 5/7) to get the final value x = 23/7 + 5/7 * (36/7 - 23/7) = 226/49 ~= 4.6. If we first interpolate vertically and then horizontally, we'd get the same result (the value between 1 and 8 would be 6, the value between 5 and 3 would be 25/7 and the final value 226/49 again).

Here is a C code to compute all the inbetween values in the above, using fixed point (no float):

#include <stdio.h>

#define GRID_RESOLUTION 8

int interpolateLinear(int a, int b, int t)
{
  return a + (t * (b - a)) / (GRID_RESOLUTION - 1);
}

int interpolateBilinear(int topLeft, int topRight, int bottomLeft, int bottomRight,
  int x, int y)
{
#define FPP 16 // we'll use fixed point to prevent rounding errors
    
#if 1 // switch between the two versions, should give same results:
  // horizontal first, then vertical
  int a = interpolateLinear(topLeft * FPP,topRight * FPP,x);
  int b = interpolateLinear(bottomLeft * FPP,bottomRight * FPP,x);
  return interpolateLinear(a,b,y) / FPP;
#else
  // vertical first, then horizontal
  int a = interpolateLinear(topLeft * FPP,bottomLeft * FPP,y);
  int b = interpolateLinear(topRight * FPP,bottomRight * FPP,y);
  return interpolateLinear(a,b,x) / FPP;
#endif
}

int main(void)
{
  for (int y = 0; y < GRID_RESOLUTION; ++y)
  {
    for (int x = 0; x < GRID_RESOLUTION; ++x)
      printf("%d ",interpolateBilinear(1,5,8,3,x,y));

    putchar('\n');
  }
    
  return 0;
}

The program outputs:

1 1 2 2 3 3 4 5 
2 2 2 3 3 4 4 5 
3 3 3 3 4 4 4 5 
4 4 4 4 4 4 4 5 
5 5 5 5 5 5 5 4 
6 6 6 6 5 5 5 4 
7 7 7 6 6 5 5 4 
8 8 7 6 6 5 4 3

Billboard

In 3D computer graphics billboard is a flat image placed in the scene that rotates so that it's always facing the camera. Billboards used to be greatly utilized instead of actual 3D models in old games thanks to being faster to render (and possibly also easier to create than full 3D models), but we can still encounter them even today and even outside retro games, e.g. particle systems are normally rendered with billboards (each particle is one billboard). Billboards are also commonly called sprites, even though that's not exactly accurate.

There are two main types of billboards:

• Ones rotating only about vertical axis, i.e. billboards that change only their yaw, they only face the camera in a top-down view of the scene. Such sprite may deform on the screen (when the camera is at different height level) just like 3D models do and when viewed completely from above will disappear completely. This may in some situations look better than other options (e.g. in games enemies won't appear lying on their back when seen from above).
• Freely rotating ones, i.e. ones that change all three Euler angles so that they ALWAYS face the camera from any possible angle. There may further be other two subtypes: billboards that align themselves with the camera's projection plane (they simply rotate themselves in the same way as the camera) which always end up on the screen as an undeformed and unrotated image, and billboards that face themselves towards the camera's position and copy the camera's roll (though these may seem like two same things, they are not, for the latter we need to know the camera and billboard's positions, for the former we only need the camera's rotation). For simplicity we usually choose to implement the former, though the latter may result in look closer to that which would be produced by an actual 3D model of the object (e.g. a sphere projected to an ellipse by perspective).

Some billboards also choose their image based on from what angle they're viewed (e.g. an enemy in a game viewed from the front will use a different image than when viewed from the side, as seen e.g. in Doom). Also some billboards intentionally don't scale and keep the same size on the screen, for example health bars in some games.

In older software billboards were implemented simply as image blitting, i.e. the billboard's scaled image would literally be copied to the screen at the appropriate position (this would implement the freely rotating billboard). Nowadays when rendering 3D models is no longer really considered harmful to performance and drawing pixels directly is less convenient, billboards are more and more implemented as so called textured quads, i.e. they are really a flat square 3D model that may pass the same pipeline as other 3D models (even though in some frameworks they may actually have different vertex shaders etc.) and that's simply rotated to face the camera in each frame (in modern frameworks there are specific functions for this).

Fun fact: in the old games such as Doom the billboard images were made from photographs of actual physical models from clay. It was easier and better looking than using the primitive 3D software that existed back then.

Implementation Details

The following are some possibly useful things for implementing billboards.

The billboard's position on the screen can be computed by projecting its center point in world coordinates with modelview and projection matrices, just as we project vertices of 3D models.

The billboard's size on the screen shall due to perspective be multiplied by 1 / (tan(FOV / 2) * z) where FOV is the camera's field of view and z is the billboard's distance from camera's projection plane (which is NOT equal to the mere distance from the camera's position, that would create a fisheye lens effect -- the distance from the projection plane can be obtained from the above mentioned projection matrix). (If the camera's FOV is different in horizontal and vertical directions, then also the billboard's size will change differently in these directions.)

For billboards whose images depends on viewing angle we naturally need to compute the angle. We may do this either in 2D or 3D -- most games resort to the simpler 2D case (only considering viewing angle in a single plane parallel to the floor), in which case we may simply use the combination of dot product and cross product between the normalized billboard's direction vector and a normalized vector pointing from the billboard's position towards the camera's position (dot product gives the cosine of the angle, the sign of cross product's vertical component will give the rest of the information needed for determining the exact angle). Once we have the angle, we quantize (divide) it, i.e. drop its precision depending on how many directional images we have, and then e.g. with a switch statement pick the correct image to display. For the 3D case (possible different images from different 3D positions) we may first transform the sprite's 3D facing vector to camera space with appropriate matrix, just like we transform 3D models, then this transformed vector will (again after quantization) directly determine the image we should use.

When implementing the free rotating billboard as a 3D quad that's aligning with the camera projection plane, we can construct the model matrix for the rotation from the camera's normalized directional vectors: R is camera's right vector, U is its up vector and F is its forward vector. The matrix simply transforms the quad's vertices to the coordinate system with bases R, U and F, i.e. rotates the quad in the same way as the camera. When using row vectors, the matrix is following:

R.x R.y R.z 0
U.x U.y U.z 0
F.x F.y F.z 0
0   0   0   1

Bill Gate$

"Some people are so poor that all they've got is money."

William "Bill" Gaytes (28.10.1955 -- TODO) is a mass murderer and rapist (i.e. capitalist) who established and led the terrorist organization Micro$oft. He is one of the most rich and evil individuals in history who took over the world by force establishing the malware "operating system" Window$ as the common operating system, nowadays being dangerous especially by hiding behind his "charity organization" (see charitywashing) which has been widely criticized (see e.g. http://techrights.org/wiki/Gates_Foundation_Critique, even such mainstream media as Wikipedia present the criticism) but which nevertheless makes him look as someone doing "public good" in the eyes of the naive brainless NPC masses.

     \__.,.
   -."     "./
   /,/---"""\\
   ; __   __ ;
  (=[0 ]"[ 0]=)
  \| ""._,"" |/
   |  .___,  |
    \_,   ._/
      "---"
  dead or alive

ASCII portrait of Bill Gaytes

He is really dumb, only speaks one language and didn't even finish university. He also has no moral values, but that goes without saying for any rich businessman. He was owned pretty hard in chess by Magnus Carlsen on some shitty TV show.

When Bill was born, his father was just busy counting dollar bills, so he named him Bill. Bill was mentally retarded as a child and as such had to attend a private school. He never really understood programming but with a below average intelligence he had a good shot at succeeding in business. Thanks to his family connections he got to Harvard where he met Steve Ballmer.L ater he dropped out of the school due to his low intelligence.

In 1975 he founded Micro$oft, a malware company named after his dick. By a sequence of extremely lucky events combined with a few dick moves by Bill the company then became successful: when around the year 1980 IBM was creating the IBM PC, they came to Bill because they needed an operating system. He lied to them that he had one and sold them a license even though at the time he didn't have any OS (lol). After that he went to a programmer named Tim Paterson and basically stole (bought for some penny) his OS named QDOS and gave it to IBM, while still keeping ownership of the OS (he only sold IBM a license to use it, not exclusive rights for it). He basically fucked everyone for money and got away with it, the American way. For this he is admired by Americans.

When Bill Gates and Steve Jobs saw how enormously rich they got by abusing the whole world, they got horny and had gay sex together, after which Bill legally changed his name to Bill Gaytes. This however gave Jobs ass cancer and he died.

Binary

The word binary in general refers to having two choices; in computer science binary refers to the base 2 numeral system, i.e. a system of writing numbers with only two symbols, usually 1s and 0s. We can write any number in binary just as we can with our everyday decimal system, but binary is more convenient for computers because this system is easy to implement in electronics (a switch can be on or off, i.e. 1 or 0; systems with more digits were tried but unsuccessful, they failed miserably in reliability -- see e.g. ternary computers). The word binary is also by extension used for non-textual computer files such as native executable programs or asset files for games.

One binary digit can be used to store exactly 1 bit of information. So the number of places we have for writing a binary number (e.g. in computer memory) is called a number of bits or bit width. A bit width N allows for storing 2^N values (e.g. with 2 bits we can store 4 values: 0, 1, 2 and 3, in binary 00, 01, 10 and 11).

At the basic level binary works just like the decimal (base 10) system we're used to. While the decimal system uses powers of 10, binary uses powers of 2. Here is a table showing a few numbers in decimal and binary:

Conversion to decimal: let's see an example that utilizes the facts mentioned above. Let's have a number that's written as 10135 in decimal. The first digit from the right (5) says the number of 10^(0)s (1s) in the number, the second digit (3) says the number of 10^(1)s (10s), the third digit (1) says the number of 10^(2)s (100s) etc. Similarly if we now have a number 100101 in binary, the first digit from the right (1) says the number of 2^(0)s (1s), the second digit (0) says the number of 2^(1)s (2s), the third digit (1) says the number of 2^(2)s (4s) etc. Therefore this binary number can be converted to decimal by simply computing 1 * 2^0 + 0 * 2^1 + 1 * 2^2 + 0 * 2^3 + 0 * 2^4 + 1 * 2^5 = 1 + 4 + 32 = 37.

100101 = 1 + 4 + 32 = 37
||||||
\\\\\\__number of 2^0s (= 1s)
 \\\\\__number of 2^1s (= 2s)
  \\\\__number of 2^2s (= 4s)
   \\\__number of 2^3s (= 8s)
    \\__number of 2^4s (= 16s)
     \__number of 2^5s (= 32s)

To convert from decimal to binary we can use a simple algorithm that's again derived from the above. Let's say we have a number X we want to write in binary. We will write digits from right to left. The first (rightmost) digit is the remainder after integer division of X by 2. Then we divide the number by 2. The second digit is again the remainder after division by 2. Then we divide the number by 2 again. This continues until the number is 0. For example let's convert the number 22 to binary: first digit = 22 % 2 = 0; 22 / 2 = 11, second digit = 11 % 2 = 1; 11 / 2 = 5; third digit = 5 % 2 = 1; 5 / 2 = 2; 2 % 2 = 0; 2 / 2 = 1; 1 % 2 = 1; 1 / 2 = 0. The result is 10110.

TODO: operations in binary

In binary it is very simple and fast to divide and multiply by powers of 2 (1, 2, 4, 8, 16, ...), just as it is simply to divide and multiple by powers of 10 (1, 10, 100, 1000, ...) in decimal (we just shift the radix point, e.g. the binary number 1011 multiplied by 4 is 101100, we just added two zeros at the end). This is why as a programmer you should prefer working with powers of two (your programs can be faster if the computer can perform basic operations faster).

Binary can be very easily converted to and from hexadecimal and octal because 1 hexadecimal (octal) digit always maps to exactly 4 (3) binary digits. E.g. the hexadeciaml number F0 is 11110000 in binary (1111 is always equaivalent to F, 0000 is always equivalent to 0). This doesn't hold for the decimal base, hence programmers often tend to avoid base 10.

We can work with the binary representation the same way as with decimal, i.e. we can e.g. write negative numbers such as -110101 or rational numbers (or even real numbers) such as 1011.001101. However in a computer memory there are no other symbols than 1 and 0, so we can't use extra symbols such as - or . to represent such values. So if we want to represent more numbers than non-negative integers, we literally have to only use 1s and 0s and choose a specific representation/format/encoding of numbers -- there are several formats for representing e.g. signed (potentially negative) or rational (fractional) numbers, each with pros and cons. The following are the most common number representations:

• two's complement: Allows storing integers, both positive, negative and zero. It is probably the most common representation of integers because of its great advantages: basic operations (+, -, *) are performed exactly the same as with "normal" binary numbers, and there is no negative zero (which would be an inconvenience and waste of memory). Inverting a number (from negative to positive and vice versa) is done simply by inverting all the bits and adding 1. The leftmost bit signifies the number's sign (0 = +, 1 = -).
• sign-magnitude: Allows storing integers, both positive, negative and zero. It's pretty straightforward: the leftmost bit in a number serves as a sign (0 means +, 1 means -) and the rest of the number is the distance from zero in "normal" representation. So e.g. a 4 bit number 0011 is 3 while 1011 is -3 (note that we have to know the bit width of the number here, e.g. on 8 bits -3 would be 10000011). The disadvantage is there are two values for zero (positive, 0000 and negative, 1000) which wastes a value and presents a computational inconvenience, and operations with these numbers are more complicated and slower (checking the sign requires extra code).
• one's complement: Allows storing integers, both positive, negative and zero. The leftmost bit signifies a sign, in the same way as with sign-magnitude, but numbers are inverted differently: a positive number is turned into negative (and vice versa) by inverting all bits. So e.g. 0011 is 3 while 1100 is -3 (again, bit width matters). The disadvantage is there are two values for zero (positive, 0000 and negative, 1111) which wastes a value and presents a computational inconvenience, and some operations with these numbers may be more complex.
• fixed point: Allows storing rational numbers (fractions), i.e. numbers with a radix point (such as 1101.011), which can also be positive, negative or zero. It works by imagining a radix point at some fixed position in the binary representation, e.g. if we have an 8 bit number, we may consider 5 leftmost bits to represent the whole part and 3 rightmost bits to be the fractional part (so e.g the number 11010110 represents 11010.110). The advantage here is extreme simplicity (we can use normal integer numbers as fixed point simply by imagining a radix point). The disadvantage may be low precision and small range of representable values.
• floating point: Allows storing rational numbers in great ranges, both positive, negative and zero, plus some additional values such as infinity and not a number. It allows the radix point to be shifted which gives a potential for storing extremely big and extremely small numbers at the same time. The disadvantage is that float is extremely complex, bloated, wastes some values and for fast execution requires a special hardware unit (which most "normal" computers nowadays have, but are missing e.g. in some embedded systems).

As anything can be represented with numbers, binary can be used to store any kind of information such as text, images, sounds and videos. See data structures and file formats.

See Also

• unary
• ternary
• bit
• hexadecimal
• De Morgan's laws
• data structure
• data type

Bit Hack

Bit hacks or bit tricks are simple clever formulas for performing useful operations with binary numbers. Some operations, such as checking if a number is power of two or reversing bits in a number, can be done very efficiently with these hacks, without using loops, branching and other undesirably slow operations, potentially increasing speed and/or decreasing size and/or memory usage of code -- this can help us optimize. Many of these can be found on the web and there are also books such as Hacker's Delight which document such hacks.

Basics

Basic bit manipulation techniques are common and part of general knowledge so they won't be listed under hacks, but for sake of completeness and beginners reading this we should mention them here. Let's see the basic bit manipulation operators in C:

• | (bitwise OR): Performs the logical OR on all corresponding bits of two operands, e.g. 0b0110 | 0b1100 gives 1110 (14 in decimal). This is used to set bits and combine flags (options) into a single numeric value that can easily be passed to function etc. For example to set the lowest bit of a number to 1 just do myNumber | 1. Now consider e.g. #define OPTION_A 0b0001, #define OPTION_B 0b0010 and #define OPTION_C 0b0100, now we can make a single number that represents a set of selected options e.g. as OPTION_C | OPTION_B (the value will be 0101 and says that options B and C have been selected).
• & (bitwise AND): Performs the logical AND on all corresponding bits of two operands, e.g. 0b0110 & 0b1100 gives 0100 (4 in decimal). This may be used to mask out specific bits, to check if specific bits are set (useful to check the set flags as mentioned above) or to clear (set to zero) specific bits. Consider the flag example from above, if we want to check if value x has e.g. the option B set, we simply do x & OPTION_B which results in non-zero value if the option is set. Another example may be myNumber & 0b00001111 (in practice you'll see hexadecimal values, i.e. myNumber & 0x0F) which masks out the lowest 4 bits of myNumber (which is equivalent to the operation modulo 16).
• ~ (bitwise NOT): Flips every bit of the number -- pretty straightforward. This is used e.g. for clearing bits as x & ~(1 << 3) (clear 3rd bit of x).
• ^ (bitwise XOR): Performs the logical XOR on all corresponding bits of two operands, e.g. 0b0110 ^ 0b1100 gives 1010 (10 in decimal). This is used to e.g. flip specific bits.
• << and >> (binary shift left/right): Performs bitwise shift left or right (WATCH OUT: shifting by data type width or more is undefined behavior in C). This is typically used to perform fast multiplication (left) and division (right) by powers of two (2, 4, 8, 16, ...), just as we can quickly multiply/divide by 10 in decimal by shifting the decimal point. E.g. 5 << 3 is the same as 5 * 2^3 = 5 * 8 = 40.

Specific Bit Hacks

{ Work in progress. I'm taking these from various sources such as the Hacker's Delight book or web and rewriting them a bit, always testing. Some of these are my own. ~drummyfish }

Unless noted otherwise we suppose C syntax and semantics and integer data types. Keep in mind all potential dangers, for example it may sometimes be better to write an idiomatic code and let compiler do the optimization that's best for given platform, also of course readability will worsen etc. Nevertheless as a hacker you should know about these tricks, it's useful for low level code etc.

2^N: 1 << N

absolute value of x (two's complement):

  int t = x >> (sizeof(x) * 8 - 1);
  x = (x + t) ^ t;

average x and y without overflow: (x & y) + ((x ^ y) >> 1) { TODO: works with unsigned, not sure about signed. ~drummyfish }

clear (to 0) Nth bit of x: x & ~(1 << N)

clear (to 0) rightmost 1 bit of x: x & (x - 1)

conditionally add (subtract etc.) x and y based on condition c (c is 0 or 1): x + ((0 - c) & y), this avoids branches AND ALSO multiplication by c, of course you may replace + by another operators.

count 0 bits of x: Count 1 bits and subtract from data type width.

count 1 bits of x (8 bit): We add neighboring bits in parallel, then neighboring groups of 2 bits, then neighboring groups of 4 bits.

  x = (x & 0x55) + ((x >> 1) & 0x55);
  x = (x & 0x33) + ((x >> 2) & 0x33);
  x = (x & 0x0f) + (x >> 4);

count 1 bits of x (32 bit): Analogous to 8 bit version.

  x = (x & 0x55555555) + ((x >> 1) & 0x55555555);
  x = (x & 0x33333333) + ((x >> 2) & 0x33333333);
  x = (x & 0x0f0f0f0f) + ((x >> 4) & 0x0f0f0f0f);
  x = (x & 0x00ff00ff) + ((x >> 8) & 0x00ff00ff);
  x = (x & 0x0000ffff) + (x >> 16);

count leading 0 bits in x (8 bit):

  int r = (x == 0);
  if (x <= 0x0f) { r += 4; x <<= 4; }
  if (x <= 0x3f) { r += 2; x <<= 2; }
  if (x <= 0x7f) { r += 1; }

count leading 0 bits in x (32 bit): Analogous to 8 bit version.

  int r = (x == 0);
  if (x <= 0x0000ffff) { r += 16; x <<= 16; }
  if (x <= 0x00ffffff) { r += 8; x <<= 8; }
  if (x <= 0x0fffffff) { r += 4; x <<= 4; }
  if (x <= 0x3fffffff) { r += 2; x <<= 2; }
  if (x <= 0x7fffffff) { r += 1; }

divide x by 2^N: x >> N

divide x by 3 (unsigned at least 16 bit, x < 256): ((x + 1) * 85) >> 8, we use kind of a fixed point multiplication by reciprocal (1/3), on some platforms this may be faster than using the divide instruction, but not always (also compilers often do this for you). { I checked this particular trick and it gives exact results for any x < 256, however this may generally not be the case for other constants than 3. Still even if not 100% accurate this can be used to approximate division. ~drummyfish }

divide x by 5 (unsigned at least 16 bit, x < 256): ((x + 1) * 51) >> 8, analogous to divide by 3.

get Nth bit of x: (x >> N) & 0x01

is x a power of 2?: x && ((x & (x - 1)) == 0)

is x even?: (x & 0x01) == 0

is x odd?: (x & 0x01)

isolate rightmost 0 bit of x: ~x & (x + 1)

isolate rightmost 1 bit of x: x & (~x + 1) (in two's complement equivalent to x & -x)

log base 2 of x: Count leading 0 bits, subtract from data type width - 1.

maximum of x and y: x ^ ((0 - (x < y)) & (x ^ y))

minimum of x and y: x ^ ((0 - (x > y)) & (x ^ y))

multiply x by 2^N: x << N

multiply by 7 (and other numbers close to 2^N): (x << 3) - x

next higher or equal power of 2 from x (32 bit):

  x--;
  x |= x >> 1;
  x |= x >> 2;
  x |= x >> 4;
  x |= x >> 8;
  x |= x >> 16;
  x = x + 1 + (x == 0);

parity of x (8 bit):

  x ^= x >> 1;
  x ^= x >> 2;
  x = (x ^ (x >> 4)) & 0x01;

reverse bits of x (8 bit): We switch neighboring bits, then switch neighboring groups of 2 bits, then neighboring groups of 4 bits.

  x = ((x >> 1) & 0x55) | ((x & 0x55) << 1);
  x = ((x >> 2) & 0x33) | ((x & 0x33) << 2);
  x = ((x >> 4) & 0x0f) | (x << 4);

reverse bits of x (32 bit): Analogous to the 8 bit version.

  x = ((x >> 1) & 0x55555555) | ((x & 0x55555555) << 1);
  x = ((x >> 2) & 0x33333333) | ((x & 0x33333333) << 2);
  x = ((x >> 4) & 0x0f0f0f0f) | ((x & 0x0f0f0f0f) << 4);
  x = ((x >> 8) & 0x00ff00ff) | ((x & 0x00ff00ff) << 8);
  x = ((x >> 16) & 0x0000ffff) | (x << 16);

rotate x left by N (8 bit): (x << N) | (x >> (8 - N)) (watch out, in C: N < 8, if storing in wider type also do & 0xff)

rotate x right by N (8 bit): analogous to left rotation, (x >> N) | (x << (8 - N))

set (to 1) Nth bit of x: x | (1 << N)

set (to 1) the rightmost 0 bit of x: x | (x + 1)

set or clear Nth bit of x to b: (x & ~(1 << N)) | (b << N)

sign of x (returns 1, 0 or -1): (x > 0) - (x < 0)

swap x and y (without tmp var.): x ^= y; y ^= x; x ^= y; or x -= y; y += x; x = y - x;

toggle Nth bit of x: x ^ (1 << N)

toggle x between A and B: (x ^ A) ^ B

x and y have different signs?: (x > 0) == (y > 0), (x <= 0) == (y <= 0) etc. (differs on 0:0 behavior)

TODO: the ugly hacks that use conversion to/from float?

See Also

• De Morgan's laws
• fast inverse square root
• optimization

Bit

Bit (for binary digit, symbol b, also shannon) is the lowest commonly used unit of information, equivalent to a choice between two equally likely options (e.g. an answer to the question "Was the coin flip heads?"), in computers used as the smallest unit of memory, with 1 bit being able to hold exactly one value that can be either 1 or 0. From bit a higher memory unit, byte (8 bits), is derived. In quantum computing the equivalent of a bit is qubit, in ternary computers the analogy is trit.

Can there exist a smaller quantity of information than 1 bit? Well, yes, for sure we can get zero information and it certainly also makes sense to speak of fractions of bits; for example one decimal digit carries log2(10) ~= 3.32 bits of information. Entropy is also measured in bits and can get smaller than 1 bit, e.g. for an unfair coin toss; an answer to the question "Will the Sun rise tomorrow?" gives less than 1 bit of information -- in fact it gives almost no information as we know the answer will most definitely be yes, though the certainty can never be absolute. Another idea: imagine there exist two people for whom we want to know, based on their sexes, whether they may reproduce together -- answer to this question takes 1 bit (yes or no) and to obtain it we have to know both of these people's sexes so we can say whether they differ. Now if we only know the sex of one of them, then in the context of the desired answer we might perhaps say we have a half of one bit of information, as if we also know the other one's sex (the other half of the bit), we get the whole 1 bit answer.

Black

Black, a color whose politically correct name is afroamerican, is a color that we see in absence of any light.

Blender

Blender is an "open-source" 3D modeling and rendering software -- one of the most powerful and "feature-rich" (read bloated) ones, even compared to proprietary competition -- used not only by the FOSS community, but also the industry (commercial games, movies etc.), which is an impressive achievement in itself, however Blender is also a capitalist software suffering from many not-so-nice features such as bloat.

After version 2.76 Blender started REQUIRING OpenGL 2.1 due to its "modern" EEVEE renderer, deprecating old machines and giving a huge fuck you to all users with incompatible hardware (for example the users of RYF software). This new version also stopped working with the free Nouveau driver, forcing the users to use NVidia's proprietary drivers. Blender of course doesn't at all care about this. { I've been forced to use the extremely low FPS software GL version of Blender after 2.8. ~drummyfish }

See Also

• 3D modeling

Bloat

Bloat is a very wide term that in the context of software and technology means overcomplication, unnecessary complexity and/or extreme growth in terms of source code size, overall complexity, number of dependencies, redundancy, unnecessary and/or useless features (e.g. feature creep) and resource usage, all of which lead to inefficient, badly designed technology with bugs (e.g. security vulnerabilities or crashes), as well as great obscurity, ugliness, loss of freedom and waste of human effort. Simply put bloat is burdening bullshit. Bloat is extremely bad and one of the greatest technological issues of today. Creating bloat is bad engineering at its worst and unfortunately it is what's absolutely taking over all technology nowadays, mostly due to capitalism causing commercialization, consumerism and incompetent people trying to take on jobs they are in no way qualified to do.

LRS, suckless and some others rather small groups are trying to address the issue and write software that is good, minimal, safe, efficient and well functioning. Nevertheless our numbers are very small and in this endeavor we are basically standing against the whole world and the most powerful tech corporations.

Some have attempted to measure bloat, e.g. the famous web bloat score (https://www.webbloatscore.com/) measures bloat of websites as its total size divided by the page screenshot size (e.g. YouTube at 18.5 vs suckless.org at 0.386). It has been observed that software gets slower faster than hardware gets faster, which is now known as Wirth's law; this follows from Moore's law (speed of hardware doubles every 24 months) being weaker than Gate's law (speed of software halves every 18 months); or in other words: the stupidity of soydevs outpaces the brilliancy of geniuses.

The issue of bloat may of course appear outside of the strict boundaries of computer technology, nowadays we may already observe e.g. science bloat -- science is becoming so overcomplicated (many times on purpose, e.g. by means of bullshit science) that 99% people can NOT understand it, they have to BELIEVE "scientific authorities", which does not at all differ from the dangerous blind religious behavior. Any time a new paper comes out, chances are that not even SCIENTISTS from the same field but with a different specialization will understand it in depth and have to simply trust its results. This combined with self-interest obsessed society gives rise to soyence and large scale brainwashing and spread of "science approved" propaganda.

Back to technology though, one of a very frequent questions you may hear a noob ask is "How can bloat limit software freedom if such software has a free license?" Bloat de-facto limits some of the four essential freedoms (to use, study, modify and share) required for a software to be free. A free license grants these freedoms legally, but if some of those freedoms are subsequently limited by other circumstances, the software becomes effectively less free. It is important to realize that complexity itself goes against freedom because a more complex system will inevitably reduce the number of people being able to execute freedoms such as modifying the software (the number of programmers being able to understand and modify a trivial program is much greater than the number of programmers being able to understand and modify a highly complex million LOC program). As the number of people being able to execute the basic freedom drops, we're approaching the scenario in which the software is de-facto controlled by a small number of people who can (e.g. due to the cost) effectively study, modify and maintain the program -- and a program that is controlled by a small group of people (e.g. a corporation) is by definition proprietary. If there is a web browser that has a free license but you, a lone programmer, can't afford to study it, modify it significantly and maintain it, and your friends aren't able to do that either, when the only one who can practically do this is the developer of the browser himself and perhaps a few other rich corporations that can pay dozens of full time programmers, then such browser cannot be considered free as it won't be shaped to benefit you, the user, but rather the developer, a corporation.

How much bloat can we tolerate? We are basically trying to get the most for the least price. The following diagram attempts to give an answer:

        external
       "richness"
           A   
   shiny   |    :                :
  bullshit | NO :      YES       : NO
           |    :                :                         ____. . .
   luxury  |    :                :             ___________/
           |    :                :    ________/
           |    :              __:___/
    very   |    :         ____/  :
   useful  |    :     ___/       :
           |    :  __/           :
           |    :_/              :
   useful  |   _:                :
           |  | :                :
           | /  :                :
    does   ||   :                :
   nothing +---------------------------------------------------> internal complexity
           trivial simple   solo       big      huge     gigantic
                         manageable

Typical Bloat

The following is a list of software usually considered a good, typical example of bloat. However keep in mind that bloat is a relative term, for example vim can be seen as a minimalist suckless editor when compared to mainstream software (IDEs), but at the same time it's pretty bloated when compared to strictly suckless programs.

• Web since the onset of "web 2.0" has been steadily becoming more and more bloated with things such as Adobe Flash and JavaScript (and billions of its web frameworks). By today the situation about web bloat is reaching almost unbearable levels, especially in modern sites such as YouTube. For a great read see The Website Obesity Crisis.
• Ads, spyware, DRM, anti-cheats, anti-viruses, anti-sharing, anti-repair and other anti-user "features" are bloat.
• Desktop environments such as KDE and GNOME. The concept of a desktop environment itself is often considered bloat.
• Windows: one of the best examples of how software should NOT be done.
• Blender: quite useful FOSS 3D editor which however integrates things like a whole video editor, game engine, several renderers, scripting language with text editor and so on.
• CMake: gigantic build system that currently sits on top of a sandwich of other build systems.
• Docker
• Electron: GUI framework infamous for its huge resource consumption.
• flatpak: Absolutely horrible "application distribution/execution platform???" with pakcage management, sandboxes and all that kind of shit.
• Systemd: Huge anti-unix do-it-all system taking over GNU/Linux.
• Virtual machines/environments/sandboxes, big abstraction sandwiches (e.g. program running in an interpreter running in a sandbox inside web browser that's running in a virtual machine that's running on an operating system).
• Firefox, Chromium and other mainstream web browsers.
• Java, Python and similar languages.
• IDEs such as VSCode or NetBeans.
• Big game engines such as Unreal, Unity or Godot.
• Practically all commercial games made in the 21st century such as World of Warcraft, Call of Duty etc.
• Neural networks aka "AI" that is forced into everything nowadays.
• ...

Small Bloat

Besides the typical big programs that even normies admit are bloated there exists also a smaller bloat which many people don't see as such but which is nevertheless considered unnecessarily complex by some experts and/or idealists and/or hardcore minimalists, including us.

Small bloat is a subject of popular jokes such as "OMG he uses a unicode font -- BLOAT!!!". These are good jokes, it's nice to make fun out of one's own idealism. But watch out, this doesn't mean small bloat is only a joke concept at all, it plays an important role in designing good technology. When we identify something as small bloat, we don't necessarily have to completely avoid and reject that concept, we may just try to for example make it optional. In context of today's PCs using a Unicode font is not really an issue for performance, memory consumption or anything else, but we should keep in mind it may not be so on much weaker computers or for example post-collapse computers, so we should try to design systems that don't depend on Unicode.

Small bloat includes for example:

• floating point (complex standard with design issues, requires special hardware for acceleration, fixed point is better)
• config files (and other unnecessary file I/O that requires a file I/O library, not all computers have file systems, configs should be part of source code)
• library linking (header only libraries are better)
• any GPU, OpenGL (complex hardware and specifications, not all computers have complex GPUs, software rendering is better)
• Unicode (big specification requiring special libraries and big fonts, ASCII is better)
• antialiasing (just ignore aliasing, use low resolution textures etc.)
• 64 bit architectures (they only exist to allow ungodly amounts of RAM, 32 bits completely suffice for any computation, many times even 16 or 8 bits are enough)
• proportional font (fixed width font is better)
• linking, build systems/scripts, makefiles, directories and multiple source code files (single file, header only libraries and single compilation unit programs are better)
• infix notation (postfix notation is better)
• any GUI, window managers (pure text mode is better)
• operating system (bare metal is better)
• multithreading, parallelism, virtual memory, ...
• encryption, security, memory safety (just don't care and/or don't handle sensitive data with computers connected to the internet, don't live in a shitty society)
• database software (plain files are better)
• C (something in between C and brainfuck would is likely ideal, e.g. comun or Forth)
• glibc, gcc, clang etc. (better alternatives are tcc, musl, uclibc etc.)
• letter accents/diacritics (can normally be ignored in most languages that use them)
• jpg, png, svg and similar formats (e.g. ppm or farbfeld is better)
• syntax highlight and just colors anywhere they aren't absolutely necessary
• html, markdown (plain text is better)
• x86 instruction set (TODO: what's better? probably some RISC)
• any non-public-domain license (any legal burden introduced by a license is unnecessary bloat)
• dynamic linking (static linking is better)
• web 1.0, gemini (gopher or FTP is better)
• mouse (keyboard is better)
• TCP (UDP is probably better)
• vim (things like ed are probably better?)
• sound (picture is usually enough)
• high resolution (640x480 is probably the maximum you'll ever need, lower resolution takes less RAM and makes rendering faster)
• true color (256 colors, e.g. 332 palette, is better)
• GNU Unix utils (things like busybox or sbase are probably better)
• data types (untyped or single type is better, everything can be just a number)
• package managers (just don't use them, install just a few programs manually, or at least make package managers as simple as possible)
• computers (pen and paper or counting with rocks is better)
• ...

Non-Computer Bloat

The concept of bloat can be applied even outside the computing world, e.g. to non-computer technology, art, culture, law etc. Here it becomes kind of synonymous with bullshit, but using the word bloat says we're approaching the issue as computer programmers. Examples include:

• clothes
• house decoration
• cars
• using languages other than English
• TODO: more

See Also

• obscurity

Bloat Monopoly

Bloat monopoly is an exclusive control over or de-facto ownership of software or even a whole area of technology not by legal means but by means of bloat, or generally just abusing bloat in ways that lead to gaining monopolies, e.g. by establishing standards or even legal requirements (such as the EU mandatory content filters) which only the richest may conform to. Even if given sofware is FOSS (that is its source code is public and everyone has basic legal rights to it), it can be malicious due to bloat, for example it can still be made practically controlled exclusively by the developer because the developer is the only one with sufficient resources and/or know-how to be able to execute the basic rights such as meaningful modifications of the software, which goes against the very basic principle of free software.

Example: take a look at the web and how Google is gaining control over it by getting the search engine monopoly. It is very clear web along with web browsers has been becoming bloated to ridiculous levels -- this is not a coincidence, bloat is pushed by corporations such as Google to eliminate possible emerging competition. If practically all websites require JavaScript, CSS, HTTPS and similar nonsense, it is becoming much more difficult to crawl them and create a web index, leaving the possibility to crawl the web mostly to the rich, i.e. those who have enough money, time and know-how to do this. Alongside this there is the web browser bloat -- as websites have become extremely complex, it is also extremely complex to make and maintain a web browser, which is why there is only a few of them, all controlled (despite FOSS licenses) by corporations and malicious groups, one of which is Google itself. For these reasons Google loves bloat and encourages it, e.g. simply by ranking bloated webpages better in their search results, and of course by other means (sponsoring, lobbying, advertising, ...).

Bloat monopoly is capitalism's circumvention of free licenses and taking advantage of their popularity. With bloat monopoly capitalists can stick a FOSS license to their software, get an automatic approval (openwashing) of most "open-source" fanbois as well as their free work time, while really staying in control almost to the same degree as with proprietary software.

Examples of bloat monopoly include mainstream web browsers (furryfox, chromium, ...), Android, Linux, Blender etc. This software is characteristic by its difficulty to be even compiled, yet alone understood, maintained and meaningfully modified by a lone average programmer, by its astronomical maintenance cost that is hard to pay for volunteers, and by aggressive update culture.

Body Shaming

Your body sucks.

Brainfuck

Brainfuck is an extremely simple, untyped esoteric programming language; simple by its specification (consisting only of 8 commands) but intentionally very hard to program in. It works similarly to a pure Turing machine. In a way it is kind of beautiful by its simplicity. It is very easy to write your own brainfuck interpreter.

There exist self-hosted brainfuck interpreters which is pretty fucked up.

The language is based on a 1964 language P´´ which was published in a mathematical paper; it is very similar to brainfuck except for having no I/O.

Brainfuck has seen tremendous success in the esolang community as the lowest common denominator language: just as mathematicians use Turing machines in proofs, esolang programmers use brainfuck in similar ways -- many esolangs just compile to brainfuck or use brainfuck in proofs of Turing completeness etc. This is thanks to brainfuck being an actual, implemented and working language reflecting real computers, not just a highly abstract mathematical model with many different variants. For example if one wants to encode a program as an integer number, we can simply take the binary representation of the program's brainfuck implementation.

In LRS programs brainfuck may be seriously used as a super simple scripting language.

Brainfuck can be trivially translated to comun like this: remove all comments from brainfuck program, then replace +, -, >, <, ., ,, [ and ] with ++ , -- , $>0 , $<0 , ->' , $<0 <- , @' and . , respectively, and prepend $>0 .

Specification

The "vanilla" brainfuck operates as follows:

We have a linear memory of cells and a data pointer which initially points to the 0th cell. The size and count of the cells is implementation-defined, but usually a cell is 8 bits wide and there is at least 30000 cells.

A program consists of these possible commands:

• +: increment the data cell under data pointer
• -: decrement the data cell under data pointer
• >: move the data pointer to the right
• <: move the data pointer to the left
• [: jump after corresponding ] if value under data pointer is zero
• ]: jump after corresponding [ if value under data pointer is not zero
• .: output value under data pointer as an ASCII character
• ,: read value and store it to the cell under data pointer

Implementation

This is a very simple C implementation of brainfuck:

#include <stdio.h>

#define CELLS 30000

const char program[] = ",[.-]"; // your program here

int main(void)
{
  char tape[CELLS];
  unsigned int cell = 0;
  const char *i = program;
  int bDir, bCount;
  
  while (*i != 0)
  {
    switch (*i)
    {
      case '>': cell++; break;
      case '<': cell--; break;
      case '+': tape[cell]++; break;
      case '-': tape[cell]--; break;
      case '.': putchar(tape[cell]); fflush(stdout); break;
      case ',': scanf("%c",tape + cell); break;
      case '[':
      case ']':
        if ((tape[cell] == 0) == (*i == ']'))
          break;

        bDir = (*i == '[') ? 1 : -1;
        bCount = 0;
          
        while (1)
        {
          if (*i == '[')
            bCount += bDir;
          else if (*i == ']')
            bCount -= bDir;
          
          if (bCount == 0)
            break;
          
          i += bDir;
        }
        
        break;
      
      default: break;
    }
    
    i++;
  }
}

TODO: comun implementation

Programs

Here are some simple programs in brainfuck.

Print HI:

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ . + .

Read two 0-9 numbers (as ASCII digits) and add them:

,>,[<+>-]<------------------------------------------------.

TODO: more

Variants

TODO

Brain Software

Brain software, also brainware, is kind of a fun idea of software that runs on the human brain as opposed to a typical electronic computer. This removes the dependency on computers and highly increases freedom. Of course, this also comes with a huge drop of computational power :) However, aside from being a fun idea to explore, this kind of software and "architectures" may become interesting from the perspective of freedom and primitivism (especially when the technological collapse seems like a real danger).

Primitive tools helping the brain compute, such as pen and paper or printed out mathematical tables, may be allowed.

Example of brain software can be the game of chess. Chess masters can easily play the game without a physical chess board, only in their head, and they can play games with each other by just saying the moves out loud. They may even just play games with themselves, which makes chess a deep, entertaining game that can be 100% contained in one's brain. Such game can never be taken away from the person, it can't be altered by corporations, it can't become unplayable on new hardware etc., making it free to the greatest extent.

One may think of a pen and paper computer with its own simple instruction set that allows general purpose programming. This instruction set may be designed to be well interpretable by human and it may be accompanied by tables printed out on paper for quick lookup of operation results -- e.g. a 4 bit computer might provide a 16x16 table with precomputed multiplication results which would help the person execute the multiplication instruction within mere seconds.

Yet another idea is to make a computer with architecture similar to the typical electronic computers but powered by human brains -- let's call this a human computer (not to be confused with people whose job was to perform computations!). Imagine that after a societal collapse we lose our computer technology (i.e. the ability to manufacture transistors and similar key components), but we retain our knowledge of computer architecture, algorithms and the usefulness of computers. As a temporary solution for performing computations we may create a "computer made of humans", a room with several men, each one performing a role of some computer component, for example an ALU, cache and memory controller. Again, a special instruction set and a set of tools (such as physical lookup tables for results of instructions) could be made to make such a human computer relatively fast. It might not run Doom, but it could possibly e.g. compute some mathematical constants to a high precision or perhaps help find optimal structure of cities, compute stresses in big building etc. In such conditions even a slow calculator could be immensely useful.

BS

Bullshit.

Bullshit

Bytebeat

Bytebeat is a procedural chiptune/8bit style music generated by a short expression in a programming language; it was discovered/highlighted in 2011 by Viznut (author of countercomplex blog) and others, and the technique capable of producing quite impressive music by single-line code has since caught the attention of many programmers, especially in demoscene. There has even been a paper written about bytebeat. Bytebeat can produce music similar (though a lot simpler) to that created e.g. with music trackers but with a lot less complexity and effort.

This is a beautiful hack for LRS/suckless programmers because it takes quite a tiny amount of code, space and effort to produce nice music, e.g. for games (done e.g. by Anarch).

8bit samples corresponding to unsigned char are typically used with bytebeat. The formulas take advantage of overflows that create rhythmical patterns with potential other operations such as multiplication, division, addition, squaring, bitwise/logical operators and conditions adding more interesting effects.

Bytebeat also looks kind of cool when rendered as an image (outputting pixels instead of audio samples).

How To

Quick experiments with bytebeat can be performed with online tools that are easy to find on the web, these usually use JavaScript.

Nevertheless, traditionally we use C for bytebeat. We simply create a loop with a time variable (i) and inside the loop body we create our bytebeat expression with the variable to compute a char that we output.

A simple "workflow" for bytebeat "development" can be set up as follows. Firstly write a C program:

#include <stdio.h>

int main(void)
{
  for (int i = 0; i < 10000; ++i)
    putchar(
      i / 3 // < bytebeat formula here
    );

  return 0;
}

Now compile the program and play its output e.g. like this:

gcc program.c && ./a.out | aplay

Now we can just start experimenting and invent new music by fiddling with the formula indicated by the comment.

General tips/tricks and observations are these:

• Outputting the variable i creates a periodical saw-shaped beat, multiplication/division decreases/increases the speed, addition/subtraction shifts the phase backward/forward.
• Squaring (and other powers) create a wah-wah effect.
• Crazier patterns can be achieved by using the variable in places of numerical constants, e.g. i << ((i / 512) % 8) (shifting by a value that depends on the variable).
• Modulo (%) increases the frequency and decreases volume (limits the wave peak).
• So called Sierpinski harmonies are often used melodic expressions of the form i*N & i >> M.
• Bitwise and (&) can add distortion (create steps in the wave).
• A macro structure of the song (silent/louds parts, verse/chorus, ...) can be achieved by combining multiple patterns with some low-frequency pattern, e.g. this alternates a slower and faster beat: int cond = (i & 0x8000) == 0;, cond * (i / 16) + !cond * (i / 32)
• Extra variables can add more complexity (e.g. precompute some variable a which will subsequently be used multiple times in the final formula).

Copyright

It is not exactly clear whether, how and to what extent copyright can apply to bytebeat: on one hand we have a short formula that's uncopyrightable (just like mathematical formulas), on the other hand we have music, an artistic expression. Many authors of bytebeat "release" their creations under free licenses such as CC-BY-SA, but such licenses are of course not applicable if copyright can't even arise.

We believe copyright doesn't and SHOULDN'T apply to bytebeat. To ensure this, it is good to stick CC0 to any released bytebeat just in case.

Examples

A super-simple example can be just a simple:

• i / 16

The following more complex examples come from the LRS game Anarch (these are legally safe even in case copyright can apply to bytebeat as Anarch is released under CC0):

• distortion guitar rhythmical beat: ~((((i >> ((i >> 2) % 32)) | (i >> ((i >> 5) % 32))) & 0x12) << 1) | (i >> 11)
• electronic/techno: ((0x47 >> ((i >> 9) % 32)) & (i >> (i % 32))) | (0x57 >> ((i >> 7) % 32)) | (0x06 >> ((i >> ((((i * 11) >> 14) & 0x0e) % 32)) % 32))
• main theme, uses an extra variable: (((i) & 65536) ? (a & (((i * 2) >> 16) & 0x09)) : ~a), where uint32_t a = ((i >> 7) | (i >> 9) | (~i << 1) | i)

See Also

• music tracker
• MIDI

Bytecode

TODO

Example

Let's consider a simple algorithm that tests the Collatz conjecture (which says that applying a simple operation from any starting number over and over will always lead to number 1). The algorithm in C would look as follows:

// Collatz conjecture
#include <stdio.h>

int next(int n)
{
  return n % 2 ? // is odd?
    3 * n + 1 :
    n / 2;
}

int main(void)
{
  int n = getchar() - '0'; // read input ASCII digit

  while (1)
  {
    printf("%d\n",n);

    if (n == 1)
      break;

    n = next(n);
  }

  return 0;
}

The program reads a number (one digit for simplicity) and then prints the sequence until reaching the final number 1. Now let's rewrite the same algorithm in comun, a language which will allow us to produce bytecode:

# Collatz conjecture

next:
  $0 2 % ? # is odd?
    3 * 1 +
  ;
    2 /
  .
.

<-     # read input ASCII digit
"0" -  # convert it to number

@@
  # print:
  $0 10 / "0" + ->
  $0 10 % "0" + ->
  10 ->

  $0 1 = ?
    !@
  .
 
  next
.

The bytecode this compiles to is following:

000000: DES  00 0111    # func
000001: JMA  00 0100... # 20 (#14)
000002: COC  00 0001
000003: MGE  00 0000
000004: CON' 00 0010    # 2 (#2)
000005: MOX  00 0000
000006: DES  00 0001    # if
000007: JNA  00 0000... # 16 (#10)
000008: COC  00 0001
000009: CON' 00 0011    # 3 (#3)
00000a: MUX  00 0000
00000b: CON' 00 0001    # 1 (#1)
00000c: ADX  00 0000
00000d: DES  00 0010    # else
00000e: JMA  00 0011... # 19 (#13)
00000f: COC  00 0001
000010: CON' 00 0010    # 2 (#2)
000011: DIX  00 0000
000012: DES  00 0011    # end if
000013: RET  00 0000
000014: INI  00 0000
000015: INP  00 0000
000016: CON' 00 0000... # 48 (#30)
000017: COC  00 0011
000018: SUX  00 0000
000019: DES  00 0100    # loop
00001a: MGE  00 0000
00001b: CON' 00 1010    # 10 (#a)
00001c: DIX  00 0000
00001d: CON' 00 0000... # 48 (#30)
00001e: COC  00 0011
00001f: ADX  00 0000
000020: OUT  00 0000
000021: MGE  00 0000
000022: CON' 00 1010    # 10 (#a)
000023: MOX  00 0000
000024: CON' 00 0000... # 48 (#30)
000025: COC  00 0011
000026: ADX  00 0000
000027: OUT  00 0000
000028: CON' 00 1010    # 10 (#a)
000029: OUT  00 0000
00002a: MGE  00 0000
00002b: CON' 00 0001    # 1 (#1)
00002c: EQX  00 0000
00002d: DES  00 0001    # if
00002e: JNA  00 0100... # 52 (#34)
00002f: COC  00 0011
000030: DES  00 0101    # break
000031: JMA  00 1000... # 56 (#38)
000032: COC  00 0011
000033: DES  00 0011    # end if
000034: CAL  00 0011    # 3 (#3)
000035: DES  00 0110    # end loop
000036: JMA  00 1010... # 26 (#1a)
000037: COC  00 0001
000038: END  00 0000

TODO: analyze the above, show other bytecodes (python, java, ...)

Byte

Byte (symbol: B) is a basic unit of information, nowadays practically always consisting of 8 bits (in which case it is also called an octet), which allow it to store 2^8 = 256 distinct values (for example a number in range 0 to 255). It is usually the smallest unit of memory a CPU is able to operate on, and memory addresses are assigned by one byte steps. We use bytes to measure the size of memory and derive higher memory units from it, such as a kilobyte (kB, 1000 bytes), kibibyte (KiB, 1024 bytes), megabyte (MB, 10^6 bytes) etc. In programming a one byte variable is nowadays seen as very small and used if we are really limited by memory constraints (e.g. embdedded) or to mimic older 8bit computers ("retro games" etc.): one byte can be used to store very small numbers (while in mainstream processors numbers nowadays mostly have 4 or 8 bytes), text characters (ASCII, ...), very primitive colors (see RGB332, palettes, ...) etc.

Historically byte was used to stand for the basic addressable unit of memory that could store one text character or another "basic value" and could therefore have a different size than 8 bits: e.g. ASCII machines might have had a 7bit byte, 16bit machines a 16bit byte etc.; in C (standard 99) char is the "byte" data type, its byte size is always 1 (sizeof(char) == 1), though its number of bits (CHAR_BIT) can be greater or equal to 8; if you need an exact 8bit byte use types such as int8_t and uint8_t from the standard stdint library. From now on we will implicitly talk about 8bit bytes.

Value of one byte can be written exactly with two hexadecimal digits with each digit always corresponding to higher/lower 4 bits, making mental conversions very easy; this is very convenient compared to decimal representation, so programmers prefer to write byte values in hexadecimal. For example a byte whose binary value is 11010010 is D2 in hexadecimal (1101 is always D and 0010 is always 2), while in decimal we get 210.

Byte frequency/probability: it may be interesting and/or useful (e.g. for compression) to know how often different byte values appear in the data we process with computers -- indeed, this always DEPENDS; if we are working with plain ASCII text, we will never encounter values above 127, and on the other hand if we are processing photos from a polar expedition, we will likely mostly encounter byte values of 255 (as snow will cause most pixels to be completely white). In general we may expect values such as 0, 255, 1 and 2 to be most frequent, as many times these are e.g. assigned special meanings in data encodings, they may be cutoff values etc. Here is a table of measured byte frequencies in real data:

{ Measured by me. ~drummyfish }

Cancer

Cancer is similar to shit but is even worse because it spreads itself and infects anything else it touches (it is a subset of shit).

See Also

• shit

$$$Capitalism$$$

Capitalism is how you enslave people with their approval.

Capitali$m is the worst socioeconomic system we've yet seen in history,^source based on pure greed, culture of slavery and artificially sustained conflict between everyone in society (so called competition), abandoning all morals and putting money and profit (so called capital) above everything else including preservation of life itself, capitalism fuels the worst in people and forces them to compete and suffer for basic resources, even in a world where abundance of resources is already possible to achieve -- of course, capitalism is a purely rightist idea. Capitalism goes against progress (see e.g. antivirus paradox), good technology and freedom, it supports immense waste of resources, wars, abuse of people and animals, destruction of environment, decline of morals, deterioration of art, invention of bullshit (bullshit jobs, bullshit laws, ...), utilizing and perfecting methods of torture, brainwashing, censorship and so on. In a sense capitalism can be seen as slavery 2.0 or universal slavery, a more sophisticated form of slavery, one which denies the label by calling itself the polar opposite ("freedom") and manipulates people into them approving and voluntarily parttaking in their own enslavement (capitalist slaves are called wage slaves or wagies). However wage and consumption slavery is only a small part of capitalist dystopia -- capitalism brings on destruction basically to every part of civilization. It it also often likened to a cancer of society; one that is ever expanding, destroying everything with commercialism, materialism, waste and destruction, growing uncontrollably with the sole goal of just never stop an ever accelerating growth. Nevertheless, it's been truthfully stated that "it is now easier to imagine the end of all life than any substantial change in capitalism." Another famous quote is that "capitalism is the belief that the worst of men driven by the nastiest motives will somehow work for the benefit of everyone", which describes its principle quite well.

{ Some web bashing capitalism I just found: http://digdeeper.club/articles/capitalismcancer.xhtml, read only briefly, seems to contain some nice gems capturing the rape of people. ~drummyfish }

Capitalism is fundamentally flawed and CANNOT be fixed -- capitalists build on the idea that competition will drive society, that market will be self sustaining, however capitalism itself works for instating the rule of the winners who eliminate their competition, capitalism is self destabilizing, i.e. the driving force of capitalism is completely unsustainable and leads to catastrophic results as those who get ahead in working competition are also in advantage -- as it's said: money makes money, therefore money flow from the poor to the rich and create a huge imbalance in which competition has to be highly forced, eventually completely arbitrarily and in very harmful ways (invention of bullshit jobs, creating artificial needs and hugely complex state control and laws). It's as if we set up a race in which those who get ahead start to also go faster, and those become the ones who oversee and start to create the rules of the race -- expecting a sustained balance in such a race is just insanity. Society tries to "fight" this emerging imbalance with various laws and rules of market, but this effort is like trying to fight math itself -- the system is mathematically destined to be unstable, pretending we can win over laws of nature themselves is just pure madness.

Capitalism produces the worst imaginable technology and rewards people for being cruel to each other. It points the direction of society towards a collapse and may very likely be the great filter of civilizations; in capitalism people de-facto own nothing and become wholly dependent on corporations which exploit this fact to abuse them as much as possible. This is achieved by slowly boiling the frog. No one owns anything, products become services (your car won't drive without Internet connection and permission from its manufacturer), all independency and decentralization is lost in favor of a highly fragile and interdependent economy and infrastructure of services, each one controlled by the monopoly corporation. Then only a slight break in the chain is enough to bring the whole civilization down in a spectacular domino effect.

The underlying issue of capitalism is competition and conflict -- competition is the root of all evil in any social system, however capitalism is the absolute glorification of competition, amplification of this evil to maximum. It is implemented by setting and supporting a very stupid idea that everyone's primary and only goal is to be self-benefit, i.e. maximization of capital. This is combined with the fact that the environment of free market is a an evolutionary system which through natural selection extremely effectively and quickly optimizes the organisms (corporations) for achieving this given goal, i.e. generating maximum profit, on the detriment of all other values such as wellbeing of people, sustainability or morality. In other words capitalism has never promised a good society, it literally only states that everyone should try to benefit oneself as much as possible, i.e. defines the fitness function purely as the ability to seize as many resources as possible, and then selects and rewards those who best implement this function, i.e. those we would call sociopaths or "dicks", and to those is given the power in society. Yes, this is how nature works, but it must NOT be how a technologically advanced civilization with unlimited power of destruction should work. In other words we simply get what we set to achieve: find entities that are best at making profit at any cost. The inevitable decline of society can not possibly be prevented by laws, any effort of trying to stop evolution by inventing artificial rules on the go is a battle against nature itself and is extremely naive, the immense power of the evolutionary system that's constantly at work to find ways to bypass or cancel laws in the way of profit and abuse of others will prevails just as life will always find its way to survive and thrive even in the worst conditions on Earth. Trying to stop corporations with laws is like trying to stop a train by throwing sticks in its path. The problem is not that "people are dicks", it is that we choose to put in place a system that rewards the dicks, a system that fuels the worst in people and smothers the best in them.

Even though nowadays quite a lot of time has passed since times of Marx and capitalism has evolved to a stage with countless disastrous issues Marx couldn't even foresee, it is useful to mention one of the basic and earliest issues identified by Marx, which is that economically capitalism is based on stealing the surplus value, i.e. abuse of workers and consumers by owners of the means of production (factories, tools, machines etc.) -- a capitalist basically takes money for doing nothing, just for letting workers use tools he proclaims to own (a capitalist will proclaim to "own" land that he never even visited, machines he didn't make as they were developed over centuries, nowadays he even claims to own information and ideas) -- as Kropotkin put it: the working man cannot purchase with his wage the wealth he has produced. This allows a capitalist oppressor to make exponentially more money for nothing and enables existence of monstrously rich and powerful individuals in a world where millions are starving -- consider for example that nowadays there are people who own hundreds of buildings and cars plus a handful of private planes and a few private islands. It is not possible for any single human to work an equivalent of effort that's needed to produce what such an individual owns, even if he worked 24 hours a day for his whole life, he wouldn't get even close to matching the kind of effort that's needed to build the hundreds of buildings he owns -- any such great wealth is always stolen from countless workers whose salary is less than what's adequate for their work and also from consumers who pay more than it really costs to manufacture the goods they buy. Millions of people are giving their money (resources) for free to someone who just proclaims to "own" tools and even natural resources that have been there for billions of years. The difference in wealth and privileges this wealth provides divides society into antagonist classes that are constantly at war -- traditionally these classes are said to be the bourgeoisie (business owners, the upper class) and the proletariat (workers, the lower class), though under modern capitalism the division of society is not so simple anymore -- there are more classes (for example small businesses work for larger businesses) but they are still all at war.

Nowadays capitalism is NOT JUST an economic system anymore. Technically perhaps, however in reality it takes over society to such a degree that it starts to redefine very basic social and moral values to the point of taking the role of a religion, or better said a brainwashing cult in which people are since childhood taught (e.g. by constant daily exposure to private media) to worship economy, brands, engage in cults of personalities (see myths about godlike entrepreneurs) and productivity (i.e. not usefulness, morality, efficiency or similar values, just the pure ability to produce something for its own sake). Close minded people will try to counter argue in shallow ways such as "but religion has to have some supernatural entity called God" etc. Again, technically speaking this may be correct, but if we don't limit our views by arbitrary definitions of words, we see that the effects of capitalism on society are de facto of the same or even greater scale than those of religion, and they are certainly more negative. Capitalism itself works towards suppressing traditional religions (showing it is really competing with them and therefore aspiring for the same role) and their values and trying to replace them with worship of money, success and self interest, it permeates society to the deepest levels by making every single area of society a subject of business and acting on the minds of all people in the society every single day which is an enormously strong pressure that strongly shapes mentality of people, again mostly negatively towards a war mentality (constant competition with others), egoism, materialism, fascism, pure pursuit of profit etc.

From a certain point of view capitalism is not really a traditional socioeconomic system, it is the failure to establish one -- capitalism is the failure to prevent the establishment of capitalism, and it is also the punishment for this failure. It is the continuation of the jungle to the age when technology for mass production, mass surveillance etc. has sufficiently advanced -- capitalism will arise with technological progress unless we prevent it, just as cancer will grow unless we treat it in very early stages. This is what people mean when they say that capitalism simply works or that it's natural -- it's the least effort option, one that simply lets people behave like animals, except that these animals are now equipped with weapons of mass destruction, tools for implementing slavery, world wide surveillance etc. It is natural in the same way in which wars, murders, bullying and deadly diseases are. It is the most primitive system imaginable, it is uncontrolled, leads to suffering and self-destruction.

Under capitalism you are not a human being, you are a resource, at best a machine that's useful for some time but becomes obsolete and undesired once it outlives its usefulness and potential to be exploited. Under capitalism you are a slave that's forced to live the life of 3 Cs: conform, consume, compete. Or, as Encyclopedia dramatica puts it: work, buy, consume, die.

Who invented capitalism? Well, it largely developed on its own, society is just responsible for not stopping it. Capitalism as seen today has mostly evolved from the tradition of small trade, slavery, markets, competition, evil, war and abuse due to societal hierarchy (e.g. peasants by noblemen, poor by rich etc.), combined with technological progress of industrial revolution (18th. - 19th century) which allowed mass production and mass abuse of workers, as well as the information revolution (20th - 21th century) which allowed mass surveillance, unlimited corporate control, acceleration of bullshit business and extreme mass brainwashing, reaching capitalist singularity. Adam Smith (18th century), a mentally retarded egoist who tried to normalize and promote self-interest and torture of others for self-benefit, is often called the "father of capitalism" (which is about of the same honor as being called the father of holocaust) -- this man is to be also largely credited for the future extermination of all life.

On capitalism and Jews: rightists believe the issues caused by capitalism are really caused by Jews and that somehow getting rid of Jews will fix society -- actually this is not entirely accurate; white rightists want to remove Jews so that they (the white race) can take their place in ruling the society, so they don't actually want to fix or remove capitalism (on the contrary, they love its presence and its mechanisms), they just want to became the masters instead of slaves. It is definitely true Jews are overrepresented in high positions of a capitalist society, but that's just because Jews as a race really developped the best "skills" to succeed in capitalism as they historically bet on the right cards (focus on trade and money, decentralization of business, spread across the world and globalization, ...) and really evolved to the race best suited for the winners of the capitalist game. So while the rightist may be correct in the observation that Jews are winning the game, we of course cannot agree with their supposed "fix" -- we do not want to remove the slave masters and replace them with different ones, we want to get rid of capitalism, the unethical system itself which enables slavery in the first place.

{ There is a famous 1988 movie called They Live which, while being a funny alines'n'stuff B movie, actually deeply analyzes and criticizes capitalism and for its accurate predictions of the future we now live in became a cult classic. It's been famously said that They Live is rather a documentary. I highly recommend giving it a watch. ~drummyfish }

Attributes Of Capitalism

The following is a list of just SOME attributes of capitalism -- note that not all of them are present in initial stages but capitalism will always converge towards them.

• slavery, oppression, loss of freedom: In capitalism people are slaves firstly as workers -- in work time, so called wage slavery -- and secondly as consumers -- in "free" time. Banks create inflation to devalue money people save so that they have to work constantly for their whole lives as products are getting progressively more expensive. More and more essentially unnecessary spending purchases are forced on people -- new smartphone every year, mortgages, gas and maintenance of cars, new clothes according to fashion, insurance etc. Practically no one has a truly free time anymore.
• extreme waste: Bullshit products, bullshit jobs and the need for constant dynamics of the market force to waste energy, material and human work just to keeping everything in motion, even if purely arbitrarily. Corporations keep reinventing and reselling slightly modified version of already existing products, one group of people is creating something while another group is destroying it, just to keep everyone occupied. Byproduct physical waste such as plastics and chemicals are dumped in the environment and pollute it for decades, even centuries to come. At the moment we are already drowning in physical waste, we just export it to third world and hope they will have infinite space to store more.
• antivirus paradox: Sustaining and artificially creating undesirable phenomena so as to build a business in fighting it, to keep and create jobs ("firefighters starting fires").
  • artificial scarcity: In order to be able to sell something, that something has to be scarce, an abundant resource such as air cannot be sold. Once technology emerges to make some resource abundant, it threatens those who have a business in selling that resource. This creates the huge interest in keeping resources scarce, sometimes by force. Corporations are known to routinely destroy food that can still be eaten, and other goods as well. Corporations indirectly conspire on keeping resources scarce by artificial obsolescence, outlawing old products as "unsafe", using copyright to prevent people from recycling old intellectual works etc.
  • artificial obsolescence: To keep businesses running companies have an interest in making people consume even things that could otherwise last them even whole lives, so we see phenomena like people being forced to buy new phones every every year. There used to be the famous light bulb cartel (Phoebus cartel) that fined any bulb manufacturer that made long lasting light bulbs, bulbs were forcefully made to last for a short time. Apple has remotely decreased the performance of older iPhones when new ones came out. There are countless examples.
  • artificial crippling of technology: It is nowadays the norm to create a high tier product, such as a CPU or a car, and then artificially cripple some of the manufactured units (limit car engine power by software, burn parts of the CPU, ...) so as to sell them as a lower tier of that product. It is cheaper than to separately invent several tiers of the product. So it costs the same (actually less) to create a high end CPU as the low end one -- we could all be using high end CPUs, but the poorer of us are forced to use the forcefully crippled versions, because "capitalism".
  • purposeful incompatibility in technology: In market competition products of one company will often be incompatible with products of the competition on purpose, so as to discourage consumers from buying it. Technology corporations create their own "ecosystems" for consumers into which they are trying to lock them.
  • bullshit jobs, invention of bullshit products/needs: As automatization takes people's jobs, people try to keep jobs by creating artificial bullshit, e.g. "lack of women in tech" leads to creation of "diversity departments", politicians try to create more jobs by increasing bureaucracy etc. This is of course in direct conflict with the base goal of civilization itself of eliminating the need for human work. One online company even successfully sold literal excrement (which had no actual use, it was just marketed as "funny and cool").
  • preventing progress, sustaining status quo: Capitalism is extremely hostile towards social progress (more leisure time, more social security, ...), i.e. the main kind of progress (all progress should eventually serve well being of people, otherwise it's just artificial self-serving burden). It is also, contrary to popular belief, against technological progress -- the established corporations want to perpetuate their established businesses and will attack and destroy new ideas that endanger it (i.e. electric cars vs fuel powered cars, food corporations vs the solution of world hunger etc.). Capitalism prevents realization of any idea that's physically possible but which is economically impossible, ruling out e.g. many solutions to global heating etc.
• fascism: Capitalism is based on fascism, i.e. extreme hierarchy and "tribes" of which each fights to death for its own self interest. This fight happens between companies themselves, between state and companies, different departments inside companies, between workers and employers, between brands on the market etc. Capitalism is a constant war against everyone else -- not even jungle has this much conflict.
• no long term planning, irresponsibility: Companies need to make immediate profit, managers hired to new positions are expected to immediately increase profits and they don't come to stay for long, they have no responsibility, so they simply do whatever it takes to create immediate profit without considering any long term consequence such as pollution etc.
• extreme lowering of quality of products, deterioration of art: Despite capitalist propaganda, capitalism doesn't lead to increased quality of products -- on the contrary it seeks to find the MINIMUM quality that will be accepted by the consumer. In seeking to minimize manufacturing cost of a single unit, companies save money wherever they can and rather invest in marketing etc. -- for example instead of paying several experts to produce a good, well fact-checked documentary, only one man will be paid to create the documentary with the focus on it being "fun and engaging" rather than factually correct. Art is hasted, scheduled, produced on short deadlines, littered with product placement etc.
• plutocracy, i.e. loss of (true) democracy: In capitalism only illusion of democracy is sustained, there is no rule of the people, there is rule of the rich THROUGH people, as the rich are those who make the laws and actually take the ruling positions and who have a tremendous power to manipulate masses via private media. State is becoming more and more the tool of corporations rather than a protection against them. USA, the worst case of capitalism, is infamous for having no voting freedom, there exists just a laughable choice of two parties which are exactly the same.
• monopolies with unlimited power, degeneration of competition: The naive ideas of capitalists that markets will magically regulate themselves quickly falls apart, basically no one even tries to believe it anymore. In a competitive market monopolies arise in a short time who will prevent any competition from even arising. Can a tiny starting company compete with an established corporations with billions of dollars and thousand lawyers? No. The corporation can defeat them by gigantic marketing, unfair practices (unfair prices etc.) despite fines, by simply buying them, legal trolling, media trolling (negative internet reviews, ...), even physical attacks if necessary (just anonymously pay a bunch of hackers to DDOS competition's servers etc.). Once a monopoly without competition exists, the few advantages of competition disappear completely. A corporation doesn't respond to demand, it creates the demand. It can do whatever it likes, it can set arbitrarily high prices, create arbitrarily shitty products and so on, no competition is pressuring it to do otherwise, people have no choice than to subvert.
• poverty: Despite capitalist propaganda, not everyone can be successful in capitalism (if everyone could retire at 20, why doesn't everyone just do it?), and it is a fact that because money makes money, the gap between the poor and the rich is becoming wider and wider (as of 2020, 8 richest people owned as much wealth as the whole poorer half of the population). Poor people are pushed into loans, getting into debts, trapping themselves, working multiple jobs, while their health deteriorates increasing their debt on medical bills, decreasing their ability to work more etc.
• torture and killing of people: The poorest, mostly in third world countries, including children, are forced to hard labor that destroys their lives. Whole cities live off of processing waste coming from first world countries, e.g. disintegrating used ships with primitive tools, no work safety, breathing cancerous fumes etc.
• materialism: there exists nothing but money: By definition capitalism advises ONLY to maximize one's profit, any other values such as human well being, peace, preservation of life environment or progress are subverted to the goal of profit. As other values are often in conflict with profit, profit wins and people suffer.
• fight culture, fascism, extreme hostility between people, disappearance of morality: The very basis of capitalism -- competition -- nurtures people towards self interest, self centeredness and hostility towards others while suppressing good attributes such as sharing, love for others and altruism. With this morals decline and fascist groups arise. Furthermore the system of overcomplicated laws are starting to replace morals, people ask "is it legal?" rather than "is it a good thing to do?". This creates a society of dicks and psychopaths who are additionally rewarded for their immoral behavior by becoming "successful" and wealthy. In long term this serves as a natural selection in Darwinian evolution, immorally behaving people are actually more likely to survive and reproduce, which leads to genes of psychopathic behavior becoming more and more common in society -- under capitalism good people quite literally become extinct in the long run.
• fear culture: To keep people consuming and constantly engaged a tension has to be kept, comfortable people are undesirable in capitalism. So there is constantly a propaganda of some threat, be it viruses, terrorism, pedophiles on the internet, computer viruses, killing bees etc.
• consumerism: To keep businesses running people need to consume everything, even things that shouldn't be consumed and that could last for very long such as computers and cars. This leads to creation of hasted low quality products (even art such as TV series) that are meant to be used and thrown away, repairing is no longer considered.
• commerce infects absolutely everything: In advanced capitalism there is no such thing as a commerce free zone, everything is privatized eventually and serves selfish interests. Nowadays even such areas as health care, wellfare or education of children is permeated by money, ads and corporate propaganda. Even nonprofits have to make money. Educational videos in schools are preceded with ads (as they are played on YouTube), propagandists even legally go to school and brainwash little children (they call it "education in financial literacy" and teach children that they should e.g. create bank accounts in the propagandist's specific bank).
• destruction of life environment: This is nowadays already pretty clear, global heating is attributed mainly to capitalism and is seen as maybe the most likely doom that's probably already unavoidable. Lack of long term planning and any concern for anything but money, along with consumerism and extreme waste (of energy, physical waste such as plastic, toxic chemicals etc.) lead to building bullshit factories and performing unnecessary activity for economic reasons (e.g. transporting materials over the globe for assembly, then transporting it back), leading to extreme pollution of air (visible air smog already makes it hard to breathe in many cities), water (it is no longer safe to drink rain water as it used to be) and food (microplastic particles are already basically EVERYWHERE, eating them can't be avoided). Forests that are necessary for cleaning air, host many precious life forms and are overall a key part of ecosystem are being destroyed rapidly, entire species are disappearing very quickly. And that's just a quick sum up.
• loss of ethical behavior: Ethical behavior is a disadvantage in a competitive environment of the market, it is a limitation. Those trying to behave ethically (e.g. fair prices or good treatment of employees) will simply lose to the unethically behaving ones and be eliminated from the market. Eventually there only remain unethically behaving entities, which is exactly what we are seeing nowadays -- there basically doesn't exist a single ethically behaving corporation in the world (which has however already been normalized and is no longer seen as an issue).
• anti-people design: By definition in capitalism technology is not to serve people, it is to serve companies to make profit and abuse people, so technology spies on its users, refuses to work (DRM, ...) shows ads, forces children into purchases (predatory games), breaks on purpose so as to enforce a paid repair etc.
• censorship: One kind of capitalist censorship is so called intellectual property (allowing "ownership" of ideas, art etc.), but there are many more, e.g. so called moderation of social media which censors specific political views (deemed "politically incorrect" and hence "dangerous" for the advertising potential or brand of the platform) or sharing of certain facts (e.g. those revealing unethical practice of the platform itself, negative reviews of its products etc.). Privately owned media lawfully censor and manipulate information so as to manipulate people in whichever way they see will bring them most profit. While "intellectual property" is marketed as "protecting intellectual workers", in practice it serves corporations and states to do whatever they want, from political censorship, deception and implementing surveillance (justified by "antipiracy") to legal bullying and implementing artificial scarcity ("no, you can't grow this type of food on your field as the plant is patented; only we can grow it and you have to buy it from us in order to live").
• surveillance: Companies want to analyze behavior of people, manipulate them, target ads, spam, train neural networks on their data etc., so there is a huge interest in applying surveillance. Indeed, this is exactly what we see in practice -- this is not even a conspiracy theory, cases of revealed mass surveillance are almost daily news.
• extreme brainwashing and propaganda: Marketing reaches extreme levels in capitalism, utilizing advanced psychological tricks and repetition to the point of becoming a torture, with the goal of teaching people brand loyalty, consumerist behavior etc. Application of this brainwashing even on children has already been normalized. Entrepreneurs create cults of personalities. There is now even a "legit" job called an influencer whose sole purpose is in spreading corporate propaganda on the Internet.
• criminality: This is a direct consequence of poverty, horrible working conditions, fight culture and overall diminishing morality. Poor people (the absolute majority in the system) become desperate and do desperate things -- of course, all blame is put on them, not on those who are responsible for their poverty.
• instability: Lack of long term planning, extreme interdependence, monopolies over essential resources, fragility of the market, increasing wealth gap, pushing workers to poverty while taking away social security, eliminating self sufficiency, extreme waste and other phenomena pose great dangers of market collapses, violent strikes and revolutions, running out of resources, destruction of living environment and other disasters and even societal collapse.
• need for extremely complex market control and laws, burdening society: As corporations are absolutely unethical and pursue evil goals such as enslaving workers and abuse of consumers, there have to be an extremely complex set of constantly evolving laws and bureaucracy just to somehow "make corporations behave". However laws are imperfect and corporations work 24/7 on bypassing them as well as on attacking and eliminating the laws themselves via lobbyist etc. This creates a constant, extremely expensive legal war-like game in which everyone has to take part, which is completely arbitrary and unnecessary and which eventually corporations will likely win.
• uncontrolled growth: Capitalism is likened to cancer as it requires a constant uncontrolled growth which on a planet of limited resources inevitably leads to a catastrophic scenario.
• hyperspecialization, loss of self sufficiency: Entities (people, cities, companies, states, ...) lose self sufficiency as they hyperspecialize in some task and in everything else rely on someone else. This complete dependence creates slavery and danger -- in an event of a blackout for example people cannot survive as they cannot make their own food, they can't repair their basic tools etc.
• loss of humanity: In capitalism humans are just consumers, machines for production and "resources" -- corporations now routinely use these terms (human resources department etc.). People are brainwashed to no longer even see it as concerningto be called such terms. People's worth is only in how much they can work or consume.
• abuse of animals: In capitalism animals are just products and resources, they are kept in very bad conditions just to be killed for meat or other purpose. They are slaughtered by millions just so we can overeat to morbid obesity. Maximizing profit dictates no money should be spent on animal comfort.
• productivity cult: People are brainwashed and forced into becoming robots whose sole purpose is to produce. Working overtimes, skipping lunch, minimizing sleep etc. has already become part of the work culture for example in USA and Japan.
• everything is fake: Everything is rotten and corrupted on the inside with an extreme effort towards putting up a misleading good looking facade. TV shows, including "news", are all staged (even those swearing not to be, no producer is going to invest money in something depending on pure luck), smiles and emotion of people you meet in workplace or see on ads, women's tits, butts and faces, men's muscles, photos on social media, food that has basically no food in it, even news and facts, everything is fake. Investigating any area (government, working conditions, technology, healthcare, education, charities, academia and "science", ...) a bit in depth practically always leads to unrevealing how corrupt it actually is despite it looking nice and ideal at the first look.
• loss of ownership: Even that which is most saint to a capitalist -- property and the ability to own things -- is greatly lost under capitalism. This happens with the trend of everything becoming a service, a typical example of which is so called "software as a service". While in the past one would buy a physical copy of a program that he would at least physically own forever, nowadays many programs become a subscription service, e.g. games, movies and music are no longer something you buy but just buy a one time ticket for. But this trend is everywhere, artificial obsolescence tries to limit durability of physical goods such electronic devices so that one has to keep consuming them like a service.
• rape effect: The mechanisms of capitalism work in such ways that everyone gets progressively more raped with any further advance of capitalism.
• endangering existence of all life: The mentioned destruction of environment, lack of long term planning, irresponsibility and instability along with creating a dangerous overdependence on technology and interconnections of self insufficient states and cities is just waiting for a disaster such as CME that immediately collapses the civilization and consequently endangers all life on Earth e.g. by meltdowns in nuclear plants or possible nuclear wars as a consequence of panic. The absolute preference of immediate profit is hostile towards investments in future and precautions. RIP.
• ...

How It Works

The "old" capitalism, or perhaps its basic forms, that socialist writers have analyzed very well is characterized mainly by abuse of workers by capitalists who declare to "own" means of production such as factories, land and machines -- as e.g. Kropotkin has written in The Conquest of Bread, it is poverty that drives capitalism because only a poor man who just needs ANY salary for himself and his family will accept horrible working conditions and low pay, simply because he has no other choice -- a capitalist exploits this, "employs" (enslaves) the poor and then only pays them as much as to keep the barely alive and working for him, and he further has the audacity of calling himself an "altruist" who "feeds" people and "gives them a work"; a capitalist employs workers in his factory like he employs chicken in egg factories or pigs in slaughterhouses -- in modern days many may fall to the illusion that workers aren't poor anymore as they may posses smartphones and big screen TVs, but in essence a worker still lives salary to salary and is in desperate need of it; without a salary he will quickly end up starving in the street. Workers do labor that's in itself worth a lot but the capitalist only gives him a small salary, firstly to gain own profit and secondly to keep the worker poor because again, only a poor man will work for him. This is also why capitalists are against anything that would end poverty, such as universal basic income. If the workers owned the factory collectively and didn't have to cut the profit off their labor, they wouldn't have to work so many hours in such harsh conditions at all, it's only because there is a capitalist leech at the top that everyone has to slave himself to death so that the leech can get enormously rich.

Here a capitalist says to the worker: "I am not forcing you to slavery, if you don't like the working conditions, go elsewhere". Of course, this is a laughable insult -- the capitalist knows very well there is nowhere else to go; wherever you go work in capitalism, you get exploited -- you can only do as much as choose your slavemaster. A capitalist will then say: "start your own business then", which again is a complete idiocy -- it's extremely hard to succeed in business, not everyone can do it, those who have established businesses won't let anyone on the market, and of course it's the immoral thing to do, the capitalist is just telling you to start doing what he's doing: abuse others. If you do start your business, he will be sure to attack you as a competition and with his power he will very likely be able to stop your business. So this advice is similar to that of "go start your own country if you don't like this one" -- he might as well tell you to move to another planet.

The new, modern capitalism is yet worse as it takes full advantage of technology never before seen in history which allows extreme increase of exploitation of both workers and consumers -- now there are cameras and computers watching each worker's individual production, there are "smart" devices spying on people and then forcing ads on them, there are loud speakers and screens everywhere full of propaganda and brainwashing, nowhere to escape. Now a single capitalist can watch over his factories all over the world through Internet, allowing for such people to get yet much richer than we could ever imagine.

While the old capitalism was more of a steady slavery and the deterioration of society (life environment, morality, art, ...) by it was relatively slow (i.e. it seemed to be somewhat "working"), nowadays, in the new capitalism the downfall of society accelerates immensely. In countries where capitalism is newly instated, e.g. after the fall of an old regime, it indeed seem to be "working" for a short time, however it will never last -- initially when more or less everyone is at the same start line, when there are no highly evolved corporations with their advanced methods of oppression, small businesses grow and take their small shares of the market, there appears true innovation, businesses compete by true quality of products, people are relatively free and it all feels natural because it is, it's the system of the jungle, i.e. as has been said, capitalism is the failure to establish a controlled socioeconomic system rather than a presence of a purposefully designed one. Its benefits for the people are at this point only a side effect, people see it as good and continue to support it. However the system has other goals of its own, and that is the development and constant growth that's meant to create a higher organism just like smaller living cells formed us, multi cell organisms. The system will start being less and less beneficial to the people who will only become cells in a higher organism to which they'll become slaves. A cell isn't supposed to be happy, it is supposed to sacrifice its life for the good of the higher organism.

{ This initial prosperous stage appeared e.g. in Czechoslovakia, where I lived, in the 90s, after the fall of the totalitarian regime. Everything was beautiful, sadly it didn't last longer than about 10 years. ~drummyfish }

Slowly "startups" evolve to medium sized businesses and a few will become the big corporations. These are the first higher entities that have an intelligence of their own, they are composed of humans and technology who together work solely for the corporation's further growth and profit. A corporation has a super human intelligence (combined intelligence of its workers) but has no human emotion or conscience (which is suppressed by the corporation's structure), it is basically the rogue AI we see in sci-fi horror movies. Corporation selects only the worst of humans for the management positions and has further mechanisms to eliminate any effects of human conscience and tendency for ethical behavior; for example it works on the principle of "I'm just doing my job": everyone is just doing a small part of what the whole company is doing so that no one feels responsible for the whole or sometimes doesn't even know what he's part of. If anyone protests, he's replaced with a new hire. Of course, many know they're doing something bad but they have no choice if they want to feed their families, and everyone is doing it.

Deterioration of society is fast now but people are kept in a false sense of a feeling that "it's just a temporary thing", "it's this individual's fault (not the system's)" and that "it's slowly getting better", mainly with the help of 24/7 allmighty media brainwashing. Due to heavy greenwashing, openwashing etc. most people are for example naively convinced that corporations are becoming more "environment friendly", "responsible", "open source" ("Microsoft isn't what it used to be", ...) etc., as if a corporation had something aking emotion instead of pure desire for profit which is its only goal by definition. A corporation will repeat ads telling you it is paying black handicapped gays to plant trees but internally no one gives a shit about anything but making more money, a manager's job is just to increase profit, waste is increasing and dumped to oceans when no one is looking, bullshit is being invented to kickstart more bullshit business which leads to more need for energy wasting (unnecessary transportation, upkeep of factories and workplaces, invention of bullshit technology to solve artificial problems arising from artificial bullshit). A lie repeated 1000 times a day will beat even truth that's evident to naked eye, basic logic and common sense. Even when sky is littered with ads, cities are burning and people are working 20 hours a day, a capitalist will keep saying "this is a good society", "we are just in a temporary crisis", "it is getting better" and "I care about the people", and people will take it as truth.

Corporations make calculated decisions to eliminate any competition, they devour or kill smaller businesses with unfair practices (see e.g. the Microsoft's infamous EEE), more marketing and by other means, both legal and illegal. They develop advanced psychological methods and extort extreme pressure such as brainwashing by ads to the population to create an immensely powerful propaganda that bends any natural human thinking. With this corporations no longer need to satisfy the demand, they create the demand arbitrarily. They create artificial scarcity, manipulate the market, manipulate the people, manipulate laws (those who make laws are nowadays mostly businessmen who want to strengthen corporations whose shares they hold and if you believe voters can somehow prevent such psychopaths getting this power, just take a look literally at any parliament of any country). At this point they've broken the system, competition no longer works as idealized by theoretical capitalists, corporations can now do practically anything they want.

This is an evolutionary system in which the fitness function is simply the ability to make capital. Entities involved in the market are simply chosen by natural selection to be the ones that best make profit, i.e. who are best at circumventing laws, brainwashing, hiding illegal activities etc. Ethical behavior is a disadvantage that leads to elimination; if a business decides to behave ethically, it is outrun by the one who doesn't have this weakness.

The unfair, unethical behavior of corporations is still supposed to be controlled by the state, however corporations become stronger and bigger than states, they can manipulate laws by lobbying, financially supporting preferred candidates, favoring them with their propaganda etc. States are the only force left supposed to protect people from this pure evil, but they are too weak; a single organization of relatively few people who are, quite importantly, often corporation share holder, won't compete against a plethora of the best warriors selected by the extremely efficient system of free market. Furthermore voters, those who are supposed to choose their protectors, are just braindead zombies now who literally do what their cellphones shows them on its display. By all this states slowly turn to serving corporations, becoming their tools and then slowly dissolve (see how small role the US government already plays). Capitalist brainwashing is so strong that it even makes people desire more torture -- see so called "anarcho" capitalism which the stupidest of our population have already fallen for and which is basically about saying "let's get rid of anything that protects us against absolute capitalist apocalypse". "Anarcho" capitalism is the worst stage of capitalism where there is no state, no entity supposed to protect the people, there is only one rule and that is the unlimited rule of the strongest corporation which has at its hands the most advanced technology there ever was.

Here the strongest corporation takes over the world and starts becoming the higher organism of the whole Earth, capitalist singularity has been reached. The world corporation doesn't have to pretend anything at this point, it can simply hire an army, it can use physical force, chemical weapons, torture, unlimited surveillance, anything to achieve further seize of remaining bits of power and resources.

People will NOT protest or revolt at this point, they will accept anything that comes and even if they suffer everyday agony and the system is clearly obviously set up for their maximum exploitation, they will do nothing -- in fact they will continue to support the system and make it stronger and they will see more slavery as more freedom; this tendency is already present in rightists today. You may ask why, you think that at some point people will have enough and will seize back their power. This won't happen, just as the billions of chicken and pigs daily exploited at factories won't ever revolt -- firstly because the system will have absolute control over people at this point, they will be 100% dependent on the system even if they hate it, they will have proprietary technology as part of their bodies (which they willingly admitted to in the past as part of bigger comfort while ignoring our warnings about loss of freedom), they will be dependent on drugs of the system (called "vaccines" or "medicine"), air that has to be cleaned and is unbreathable anywhere one would want to escape, 100% of communication will be monitored to prevent any spark of revolution etc. Secondly the system will have rewritten history so that people won't see that life used to be better and bearable -- just as today we think we live in the best times of history due to the interpretation of history that was force fed us at schools and by other propaganda, in the future a human in every day agony will think history was even worse, that there is no other option than for him to suffer every day and it's a privilege he can even live that way.

We can only guess what will happen here, a collapse due to instability or total destruction of environment is possible, which would at least save the civilization from the horrendous fate of being eternally tortured. If the system survives, humans will be probably be more and more genetically engineered to be more submissive, further killing any hope of a possible change, surveillance chips will be implanted to everyone, reproduction will be controlled precisely and finally perhaps the system will be able, thanks to an advanced AI, to exist and work more efficiently without humans completely, so they will be eliminated. This is how the mankind ends.

{ So here you have it -- it's all here for anyone to read, explained and predicted correctly and in a completely logical way, we even offer a way to prevent this and fix the system, but no one will do it because this will be buried and censored by search engines and the 0.0000000000001% who will find this by chance will dismiss it due to the amount of brainwashing that's already present today. It's pretty sad and depressive, but what more can we do? ~drummyfish }

Capitalist Propaganda And Fairy Tales

Capitalist brainwashing is pretty sophisticated -- unlike with centralized oppressive regimes, capitalism has a decentralized way of creating and spreading propaganda, in ways similar to for example self-replicating and self-modifying malware in the world of software. Creators and promoters of capitalist propaganda are mostly people who are unaware of doing so, they have been brainwashed and programmed by the system itself to behave that way, for example just by being exposed to hearing the capitalist fairy tales since they were born. Some examples of common capitalist propaganda you will probably encounter are the following:

• "Capitalism is freedom." -- This is of course a complete twist of the word freedom: capitalism promotes freedom of market which goes against the freedom of people. I.e. the freedom enabled by capitalism is the freedom to abuse others; the freedom to restrict freedoms of others, which is of almost the polar opposite of genuine freedom.
• "In capitalism everyone can make it if he only works hard." -- This is firstly of course not even logically possible, it's just as claiming that everyone can win the Olympic games; to reach the top in an extremely competitive system not only do you have to work hard, you also have to be born with the right talent, in the right place, to the right family, and be immensely lucky to be in right places in right times and make correct guess decisions in situations in which it is impossible to know the correct decision. Even if you work 24/7 without sleep, there will be thousands of others who do the same, your success is a pure bet on lottery. Capitalist fairy tales make heavy use of the survivorship bias -- you will see movies only about the successful people who are asked how they achieved success and who answer along the lines "I just worked hard". Indeed they did, but this doesn't imply that anyone working hard will succeed, this is the same as taking an advice from a lottery winner; if you ask a lottery winner how he won the lottery, he will simply say "I bet all I had on a random number". Following such advice is of course just about the worse decision you can make. If everyone can make it, why doesn't everyone do it, why don't we have a wold consisting exclusively of billionaires?
• "Capitalism just works, capitalism is natural, capitalism means progress etc." -- Capitalism doesn't work, it's just hard to get rid of. Progress isn't dependent on capitalism, progress can't be stopped and will be here even without capitalism. If it "works and is natural", then it works and is natural natural in the same way as for example cancer or wars. This doesn't mean we should support it or see it as something positive. Most of other similar lies are discussed in sections above.
• Fairy tales about about the rich capitalist altruist: you will hear stories about famous capitalists that paint them as nice guys who give to poor for free, who do manual work despite not having to etc. This is just part of cult of personality propaganda and applying cheap populist tricks to deceive masses. A rich guy giving $100 to a poor kid on camera is an extreme powerful marketing that costs $100, which for a billionaire is of course a laughable cost. The fact is that every billionaire is the best player of the most dirty game humanity has invented and researching any such guy reveals, basically in 100% of cases, that he was in fact the worst imaginable psychopath -- Edison killed animals with electric current as part of marketing, the owner of McDonald's stole the idea and know-how from McDonald brothers ALONG WITH their own name, similar thing happened with KFC, Steve Jobs was infamous for his psychological pressure on workers equating torture, the working condition's in Ford's factories were basically the same as those for black African slaves, etcetc. Trying to find a rich man that's good is like trying to find a shark who's a vegetarian.
• "Capitalism isn't perfect but it's the best system we know.": complete bullshit, capitalism is probably the worst system that there ever was. See this whole article.
• "Successful capitalists are the most intelligent people.": on the contrary, mostly the stupidest people become successful -- success in capitalism depends mostly on luck and lack of moral obstacles, i.e. doing whatever it takes to succeed such as stabbing friends in the back, public lying, exploitation of workers etc. High intelligence is actually a disadvantage in this manner as it makes one see all the negative consequences of his behavior, a smart man sees that by engaging in capitalism he is not just hurting and even killing other people, but even e.g. working towards destruction of art, culture, living environment and possibly life itself. Being a successful businessman in capitalism is like steering a plane full of people, including oneself, towards ground -- only an idiot can do it.
• TODO: moar

So What To Replace Capitalism With?

See less retarded society.

Capitalist Singularity

Capitalist singularity is a point in time at which capitalism becomes irreversible and the cancerous growth of society unstoppable due to corporations taking absolute control over society. It is when people lose any power to revolt against corporations as corporations become stronger than states and any other collective effort towards their control.

This is similar to the famous technological singularity, the difference being that society isn't conquered by a digital AI but rather a superintelligent entity in a form of corporation. While many people see the danger of superintelligent AIs, surprisingly not many have noticed that we've already seen rise of such AIs -- corporations. A corporation is an entity much more intelligent than any single individual, with the single preprogrammed goal of profit. A corporation doesn't have any sense of morals as morals are an obstacle towards making profit. A corporation runs on humans but humans don't control them; there are mechanisms in place to discourage moral behavior of people inside corporations and anyone exhibiting such behavior is simply replaced.

Capitalist Software

Capitalist software is software that late stage capitalism produces and is practically 100% shitty modern bloat and malware hostile to its users, made with the sole goal of benefiting its creator (often a corporation). Capitalist software is not just proprietary corporate software, but a lot of times "open source", indie software and even free software that's just infected by the toxic capitalist environment -- this infection may come deep even into the basic design principles, even such things as UI design, priorities and development practices and subtle software behavior which have simply all been shaped by the capitalist pressure on abusing the user.

{ Seriously I don't have enough brain to understand how anyone can accept this shit. ~drummyfish }

Capitalist software largely mimics in technology what capitalist economy is doing in society -- for example it employs huge waste of resources (computing resources such as RAM and CPU cycles as an equivalent to natural resources) in favor of rapid growth (accumulation of "features"), it creates hugely complex, interdependent and fragile ever growing networks (tons of library of hardware dependencies as an equivalent of import/export dependencies of countries) and employs consumerism (e.g. in form of mandatory frequent updates). These effects of course bring all the negative implications along and lead to highly inefficient, fragile, bloated, unethical software.

Basically everyone will agree that corporate software such as Windows is to a high degree abusive to its users, be it by its spying, unjustified hardware demands, forced non customizability, price etc. A mistake a lot of people make is to think that sticking a free license to similar software will simply make it magically friendly to the user and that therefore most FOSS programs are ethical and respect its users. This is sadly not the case, a license if only the first necessary step towards freedom, but not a sufficient one -- other important steps have to follow.

A ridiculous example of capitalist software is the most consumerist type: games. AAA games are pure evil that no longer even try to be good, they just try to be addictive like drugs. Games on release aren't even supposed to work correctly, tons of bugs are the standard, something that's expected by default, customers aren't even meant to receive a finished product for their money. They aren't even meant to own the product or have any control over it (lend it to someone, install it on another computer, play it offline or play it when it gets retired). These games spy on people (via so called anti-cheat systems), are shamelessly meant to be consumed and thrown away, purposefully incompatible ("exclusives"), bloated, discriminative against low-end computers and even targeting attacks on children ("lootboxes"). Game corporations attack and take down fan modification and remakes and show all imaginable kinds of unethical behavior such as trying to steal rights for maps/mods created with the game's editor (Warcraft: Reforged).

But how can possibly a FOSS program be abusive? Let's mention a few examples:

• Being a bloat monopoly.
• Allowing maintenance cost to be high and prioritizing e.g. features over maintainability leads to programs being expensive to maintain which discriminizes against developers unable to pay this maintenance cost. If a rich corporation intentionally makes their program bloated and expensive to just maintain, it ensures no one poor will be able to fork the software and maintain it (let alone shape it into something better), which effectively removes the possibility of an ethical competition being made out of their "open source" program.
• Bloat, intentional obscurity and update culture may lead to de-facto (as opposed to de-jure) limitations of basic freedom conditions, despite a free license. Specifically freedom 1 (to study the software, which may be unnecessarily difficult and expensive) and 2 (to modify the software, which requires its understanding, unnecessarily high cost of dealing with bad code and the ability to compile it which may be non-trivial). Therefore a company may, on paper, provide the rights to study and modify their program, but keep the actual know-how of the program's working and modification private, de-facto becoming the program's owner and sole controlling entity.
• Allowing proprietary dependencies, which happens especially in open source. While free software usually avoids this, open source is happy with e.g. Windows-only programs which of course requires the users to run abusive code in order for the program to function.
• Unnecessarily high hardware demands and dropping support for old hardware which drives consumerism and discriminates against poor people and people who just don't want to "consoom" hardware. A group can make "open source" software that intentionally requires the latest hardware that they just happen to sell (e.g. gaymes with "AAA graphics"), even if the software might in theory run on older hardware. Possible "fixes" of this by third parties can be prevented by the above mentioned techniques.
• Allowing bloat to increase the risk of security vulnerabilities and bugs (which may in some ares be fatal and lead to literal deaths).
• Obscurity and interdependence may be used to successfully hide malicious features even within publicly accessible code. See for example the anti-Russian "protestware" cases such as node-ipc, an "open source" package that introduced malicious file-wiping code and infected all software depending on it.
• Introducing dangerous dependencies: for example a fully free software may be unnecessarily designed as cloud software which increases the risk of its non functionality e.g. in cases of Internet blackouts (or just any loss of connection).
• Licenses can by bypassed, e.g. copyleft was legally eliminated by Google's Android which is based on copylefted Linux: their proprietary Play Store is a 3rd party program to which the copyleft doesn't apply but which is essential for Android and serves to control Android (which should have been prevented by the copyleft). This is an example of a FOSS "protection mechanism" failing under capitalist pressure.
• Setting up discriminatory, fascist and toxic centralized development communities that de-facto own and control the software and use discriminatory practices and censorship, e.g. with codes of conduct. This allows to bully and "cancel" developers who are, for political or any other reason, unwelcome.
• Even free software may behave in unethical ways. For example a company that profits from gambling may create a completely "FOSS" game for children that however teaches them gambling so that when they grow up they'll be more likely to become their victims.

The essential issue of capitalist software is in its goal: profit. This doesn't have to mean making money directly, profit can also mean e.g. gaining popularity and political power. This goal goes before and eventually against goals such as helping and respecting the users. A free license is a mere obstacle on the way towards this goal, an obstacle that may for a while slow down corporation from abusing the users, but which will eventually be overcome just by the sheer power of the market environment which works on the principles of Darwinian evolution: those who make most profit, by any way, survive and thrive.

Therefore "fixing" capitalist software is only possible via redefinition of the basic goal to just developing selfless software that's good for the people (as opposed to making software for profit). This approach requires eliminating or just greatly limiting capitalism itself, at least from the area of technology. We need to find other ways than profit to motivate development of software and yes, other ways do exist (morality, social status, fun etc.).

Cathedral

Welcome to the cathedral. Here we mourn the death of technology by the hand of capitalism.

{ Sometimes we are very depressed from what's going on in this world, how technology is raped and used by living beings against each other. Seeing on a daily basis the atrocities done to the art we love and the atrocities done by it -- it is like watching a living being die. Sometimes it can help to just know you are not alone. ~drummyfish }

           R. I. P.
        ~~~~~~~~~~~~~
 
          TECHNOLOGY

      long time ago - now

  Here lies technology who was
helping people tremendously until
its last breath. It was killed by
          capitalism.

CC0

CC0 is a waiver (similar to a license) of copyright, created by Creative Commons, that can be used to dedicate one's work to the public domain (kind of).

Unlike a license, a waiver such as this removes (at least effectively) the author's copyright; by using CC0 the author willingly gives up his own copyright so that the work will no longer be owned by anyone (while a license preserves the author's copyright while granting some rights to other people). It's therefore the most free and permissive option for releasing intellectual works. CC0 is designed in a pretty sophisticated way, it also waives "neighboring rights" (moral rights), and also contains a fallback license in case waiving copyright isn't possible in a certain country. For this CC0 is one of the best ways, if not the best, of truly and completely dedicating works to public domain world-wide (well, at least in terms of copyright). In this world of extremely fucked up intellectual property laws it is not enough to state "my work is public domain" -- you need to use something like CC0 to achieve legally valid public domain status.

CC0 is recommended by LRS for both programs and other art -- however for programs additional waivers of patents should be added as CC0 doesn't deal with patents. CC0 is endorsed by the FSF but not OSI (who rejected it because it explicitly states that trademarks and patents are NOT waived).

Things Under CC0

Here are some things and places with CC0 materials that you can use in your projects so that you can release them under CC0 as well. BEWARE: if you find something under CC0, do verify it's actually valid, normies often don't know what CC0 means and happily post derivative works of proprietary stuff under CC0.

TODO

• software:
  • much of LRS sofware: Anarch, small3dlib, raycastlib, SAF, comun, ...
  • ...
• other assets:
  • many things on Wikimedia Commons
  • many things on opengameart
  • many things on BlendSwap
  • all of drummyfish's stuff including fonts, textures, 3D models etc.
  • librivox creates CC0 audiobooks from old books
  • ...
• text:
  • Esolang Wiki
  • OSdev Wiki since 2011
  • Encyclopedia Dramatica
  • ...

Censorship

This page is not accessible in your country... NOT :)

Censorship means intentional effort towards preventing exchange of certain kind of information among other individuals, for example suppression of free speech, altering old works of art for political reasons, forced takedowns of copyrighted material from the Internet etc. Note that thereby censorship does NOT include some kinds of data or information filtering, for example censorship does not include filtering out noise such as spam on a forum or static from audio (as noise is a non-information) or PERSONAL avoidance of certain information (e.g. using adblock or hiding someone's forum posts ONLY FOR ONESELF). Censorship often hides under euphemisms such as "moderation", "safe space", "filter", "protection", "delisting", "review" etc. Censorship is always wrong -- in a good society there is never a slightest reason to censor anything, therefore whenever censorship is deemed the best solution, something within the society is deeply fucked up. In current society censorship, along with propaganda, brainwashing and misinformation, is extremely prevalent and growing -- it's being pushed not only by governments and corporations but also by harmful terrorist groups such as LGBT and feminism who force media censorship (e.g. that of Wikipedia or search engines) and punishment of free speech (see political correctness and "hate speech").

Sometimes it is not 100% clear which action constitutes censorship: for example categorization such as moving a forum post from one thread to another (possibly less visible) thread may or may not be deemed censorship -- this depends on the intended result of such action; moving a post somewhere else doesn't remove it completely but can make it less visible. Whether something is censorship always depends on the answer to the question: "does the action prevent others from information sharing?".

Modern censorship is much more sophisticated; in old days, e.g. those of USSR pseudocommunist regimes, it was simple: stuff was reviewed and it either got censored or it passed, governments even openly admitted to censorship and stated it was simply necessary for the advancement of society. People wanted to talk but the government didn't want to let them. Not so nowadays, it got much advance in several ways:

1. Censorship is no longer done just by the state, but by corporations, various social subgroups and even individuals as well, as so called self censorship, often automatically and subconsciously. In wanting to talk you are not just standing against one big bad guy who wants you silent, there are hundreds of sneaky bastards waiting to sue you, report you, ban you, cancel you, even physically terminate you if you touch anything controversial in one way or another.
2. NO ONE ADMITS TO CENSORSHIP NOWADAYS, no matter how blatantly obvious their censorship is, exactly in the capitalist "deny EVERYTHING" spirit -- Wikipedia explicitly states "we are not censored" and then literally removes and blocks inclusion of legitimate information it deems "harmful". You point it out, they ban you. They will say "no, it's not censorship, it is MODERATION, PROTECTION, DELISTING, free speech has its limits, it is not a ban, it is deplatformization, blocking of hate speech is not censorship blablabla ..." -- they are inventing hundreds of new terms so that they don't have to use the word censorship.
3. There is a lot of soft, undercover and hard to prove censorship -- no longer is something either censored or not censored, but it may be shadowbanned, hugely underanked in search, censored only to specific eyes, modified rather than deleted etc. For example Google censors thousands of websites; you WILL find those websites if Google sees you are looking specifically for those to test their censorship, but it won't ever show it to people who don't know about the site and are legitimately looking for the information they contain. Maybe they will show the site on the 100th page of the search results, which is equivalent to just blocking it completely, but they can say "haha we are not actually censoring it, gotcha". TV series and movies are silently edited retroactively in the cloud to no longer include scenes deemed politically incorrect, no one notices as no one owns physical copies anymore. In the endgame capitalists will just be constantly updating history, let's say they will just change the characters in Godfather to LGBTQ queer black women and since the movie will only be streamed from the cloud, without any old copied of the original existing, they will just say "the movie has always been like that, the author supported our politics". And so on.

There exist tools for bypassing censorship, e.g. proxies or encrypted and/or distributed, censorship-resistant networks such as Tor, Freenet, I2P or torrent file sharing. Watch out: using such tools may be illegal or at least make you look suspicious and be targeted harder by the surveillance.

Examples

TODO

See Also

• free speech

Chaos

In mathematics chaos is a phenomenon that makes it extremely difficult to predict, even approximately, the result of some process even if we completely know how the process works and what state it starts in. In more technical terms chaos is a property of a nonlinear deterministic system in which even a very small change in input creates a great change in the output, i.e. the system is very sensitive to initial conditions. Chaos is a topic studied by the field called chaos theory and is important in all science. In computer science it is important for example for the generation of pseudorandom numbers or in cryptography. Every programmer should be familiar with the existence of chaotic behavior because in mathematics (programming) it emerges very often, it may pose a problem but, of course, it may be taken advantage of as well.

Perhaps the most important point is that a chaotic system is difficult to predict NOT because of randomness, lack of information about it or even its incomprehensible complexity (many chaotic systems are defined extremely simply), but because of its inherent structure that greatly amplifies any slight nudge to the system and gives any such nudge a great significance. This may be caused by things such as feedback loops and domino effects. Generally we describe this behavior as so called butterfly effect -- we liken this to the fact that a butterfly flapping its wings somewhere in a forest can trigger a sequence of events that may lead to causing a tornado in a distant city a few days later.

Examples of chaotic systems are the double pendulum, logistic map, weather (which is why it is so difficult to predict it), dice roll, rule 30 cellular automaton, logistic map, gravitational interaction of N bodies or Lorenz differential equations. Langton's ant sometimes behaves chaotically. Another example may be e.g. a billiard table with multiple balls: if we hit one of the balls with enough strength, it'll shoot and bounce off of walls and other balls, setting them into motion and so on until all balls come to stop in a specific position. If we hit the ball with exactly the same strength but from an angle differing just by 1 degree, the final position would probably end up being completely different. Despite the system being deterministic (governed by exact and predictable laws of motion, neglecting things like quantum physics) a slight difference in input causes a great different in output.

A simple example of a chaotic equation is also the function sin(1/x) for x near 0 where it oscillates so quickly that just a tiny shift along the x axis drastically changes the result. See how unpredictable results a variant of the function can give:

Logistic map is often given as the typical example of a chaotic system. It is the series defined as x[n + 1] = r * (1 - x[n]), which for some constant r (interpreted as speed of population increase) says how a population evolves from some starting value x[0]; for low x[n] the population will be increasing proportionally by the rate of r but once it reaches a higher value, it will start decreasing (as if by starvation), resulting in oscillation. Now if we only start to be interested in changing the value r and then seeing at what value the population stabilizes (for a big n), we make some interesting discoveries. This is best seen by plotting the stable values (let's say x[1000]) depending on r. For r approximately between 3.57 and 4 we start to see a chaotic behavior, with results greatly depending on the initial population value (x[0]). This demonstrates chaotic behavior.

The following is a fixed point C implementation of the above:

#include <stdio.h>
 
#define FP_UNIT 256
#define DOWNSCALE_X 4
#define DOWNSCALE_Y 25
#define LINE_LENGTH (FP_UNIT / DOWNSCALE_X)
#define GENERATIONS 1000

char stablePoints[LINE_LENGTH + 1];

int main(void)
{
  stablePoints[LINE_LENGTH] = 0; // string terminator

  for (int i = 0; i <= FP_UNIT * 4; i += DOWNSCALE_Y) // for different rs
  {
    for (int j = 0; j < LINE_LENGTH; ++j)
      stablePoints[j] = ' ';

    for (int j = 0; j < FP_UNIT; ++j) // for different starting population sizes
    {
      int population = j;

      for (int k = 0; k < GENERATIONS; ++k)
        population = (i * population * (FP_UNIT - population)) / (FP_UNIT * FP_UNIT);

      population /= DOWNSCALE_X;

      if (population >= 0 && population < LINE_LENGTH)
        stablePoints[population] = '*';
    }

    printf("%.3f| %s\n",i / ((float) FP_UNIT),stablePoints);
  }

  return 0;
} 

It outputs the following:

0.000| *                                                               
0.098| *                                                               
0.195| *                                                               
0.293| *                                                               
0.391| *                                                               
0.488| *                                                               
0.586| *                                                               
0.684| *                                                               
0.781| *                                                               
0.879| *                                                               
0.977| *                                                               
1.074| *****                                                           
1.172| **     ***                                                      
1.270| **          **                                                  
1.367| *               **                                              
1.465| *                   *                                           
1.562| *                     **                                        
1.660| *                        *                                      
1.758| *                          *                                    
1.855| *                            *                                  
1.953| *                              *                                
2.051| *                               *                               
2.148| *                                 *                             
2.246| *                                  *                            
2.344| *                                   *                           
2.441| *                                    *                          
2.539| *                                     *                         
2.637| *                                      *                        
2.734| *                                       *                       
2.832| *                                        *                      
2.930| *                                        **                     
3.027| *                                     *********                 
3.125| *                                  *       *     *              
3.223| *                               *           *      *            
3.320| *                             *                     **          
3.418| *                           **               *       **         
3.516| *                      ** * *   **           *      *****       
3.613| *                   **** *** *  * ** * *      *   ********      
3.711| *                **               **      ** *****  *     **    
3.809| *           *      **  * *        *   * *         *  *  *** *   
3.906| *     *        *     ***      *       *      *     *   * ***  * 

Vertical axis is the r parameter, i.e. the population growth speed. Horizontal axis shows stable population size after 1000 generations, starting with different initial population sizes. We can see that up until about r = 3 the stable population size always stabilizes at around the same size, which gradually increases with r. However then the line splits and after around r = 3.56 the stable population sizes are quite spread out and unpredictable, greatly depending on the initial population size. Pure CHAOS!

Charity Sex

TODO

Cheating

Cheating means circumventing or downright violating rules, usually while trying to keep this behavior secret. You can cheat on your partner, in games, in business etc., however despite cheating seeming like purely immoral behavior at first, it may be relatively harmless or even completely moral, e.g. in computer graphics we sometimes "cheat" our sense of sight and fake certain visual phenomena which leads to efficient rendering algorithms. In capitalism cheating is demonized and people are brainwashed to take part in cheater witch hunts.

The truth is that cheating is only an issue in a shitty society that's driven by competition. In such society there is a huge motivation for cheating (sometimes literally physical survival) as well as potentially disastrous consequences of it. Under the tyranny of capitalism we are led to worship heroes and high achievers and everyone gets pissed when we get fooled. Corporations go "OH NOES our multi bilion dollar entertainment industry is going to go bankrupt if consoomers get annoyed by cheaters! People are gonna lose their bullshit jobs! Someone is going to get money he doesn't deserve! Our customers may get butthurt!!!" (as if corporations themselves weren't basically just stealing money and raping people lol). So they start a huge brainwashing propaganda campaign, a cheater witch hunt. States do the same, communities do the same, everyone wants to stone cheaters to death but at the same time the society pressures all of us to compete to death with others or else we'll starve. We reward winners and torture the losers, then bash people who try to win -- and no, many times there is no other choice than to cheat, the top of any competition is littered with cheaters, most just don't get caught, so in about 99% of cases the only way to the top is to cheat and try to not get caught, just to have a shot at winning against others. It is proven time after time, legit looking people in the top leagues of sports, business, science and other areas are constantly being revealed as cheaters, usually by pure accident (i.e. the number of actual cheater is MANY times higher). Take a look e.g. at the Trackmania cheating scandal in which after someone invented a replay analysis tool he revealed that a great number or top level players were just cheaters, including possibly the GOAT of Trackmania Riolu (who just ragequit and never showed again lol). Of course famous cases like Neil Armstrong don't even have to be mentioned. Cheater detection systems are (and always will be) imperfect and try to minimize false positives, so only the cheaters who REPEATEDLY make MANY very OBVIOUS mistakes get caught, the smart cheaters stay and take the top places in the competitive system, just as surely as natural selection leads to the evolution of organisms that best adapt to the environment. Even if perfect cheat-detection systems existed, the problem would just shift from cheating to immoral unsportmanship, i.e. abuse of rules that's technically not cheating but effectively presents the same kind of problems. How to solve this enormously disgusting mess? We simply have to stop desperately holding to the system itself, we have to ditch it.

In a good society, such as LRS, cheating is not an issue at all, there's no motivation for it (people don't have to prove their worth by their skills, there are no money, people don't worship heroes, ...) and there are no negative consequences of cheating worse than someone ragequitting an online game -- which really isn't an issue of cheating anyway but simply a consequence of unskilled player facing a skilled one (whether the pro's skill is natural or artificial doesn't play a role, the nub will ragequit anyway). In a good society cheating can become a mild annoyance at worst, and it can really be a positive thing, it can be fun -- seeing for example a skilled pro face and potentially even beat a cheater is a very interesting thing. If someone wants to win by cheating, why not let him? Valid answers to this can only be given in the context of a shit society. In a good society choosing to cheat in a game is as if someone chooses to fly to the top of a mountain by helicopter rather than climbing it -- the choice is everyone's to make.

The fact that cheating isn't really an issue is supported by the hilariously vastly different double standards applied e.g. by chess platforms in this matter, on one hand they state in their TOS they have absolutely 0% tolerance of any kind of cheating/assistance and will lifeban players for the slightest suspicion of cheating yelling "WE HAVE TO FIGHT CHEATING", on the other hand they allow streamers literally cheat on a daily basis on live stream where everyone is seeing it, of course because streamers bring them money -- ALL top chess streamers (chessbrah, Nakamura, ...), including the world champion Magnus Carlsen himself, have videos of themselves getting advice on moves from the chat or even from high level players present during the stream, Magnus Carlsen is filmed taking over his friend's low rated account and winning a game which is the same as if the friend literally just used an engine to win the game, and Magnus is also filmed getting an advice from a top grandmaster on a critical move in a tournament that won him the game and granted him a FINANCIAL PRIZE. World chess champion is literally filmed winning money by cheating and no one cares because it was done as part of a highly lucrative stream "in a fun/friendly mood". Chessbrah streams frequently consist of many people in the room just giving advice on moves to the one who is currently playing, of course they censor all comments that try to bring up the fact that this is 100% cheating directly violating the platform's TOS. People literally have no brains, they only freak out about cheating when they're told to by the industry, when cheating is good for business people are told to shut up because it's okay and indeed they just shut up and keep consuming.

Chess

Chess (from Persian shah, king) is a very old two-player board game, perhaps most famous and popular among all board games in history. It is a zero sum, complete information game with no element of randomness, that simulates a battle of two armies on an 8x8 board with different battle pieces, also called chessmen or just men. Chess is also called the King's Game, it has a world-wide competitive community and is considered an intellectual sport but it's also been a topic of research and programming (many chess engines, AIs and frontends are being actively developed). Chess is similar to games such shogi ("Japanese chess"), xiangqi ("Chinese chess") and checkers. As the estimated number of chess games is bigger than googol, it is unlikely to ever be solved; though the complexity of the game in sheer number of possibilities is astronomical, among its shogi, go and xiangqi cousins it is actually considered one of the "simplest" (the board is relatively small and the game tends to simplify as it goes on as there are no rules to get men back to the game etc.).

{ There is a nice black and white indie movie called Computer Chess about chess programmers of the 1980s, it's pretty good, very oldschool, starring real programmers and chess players, check it out. ~drummyfish }

Drummyfish has created a suckless/LRS chess library smallchesslib which includes a simple engine called smolchess (and also a small chess game in SAF with said library).

At LRS we consider chess to be one of the best games for the following reasons:

• It is just a greatly interesting and deep game in which luck plays minimal role.
• It is greatly suckless, the rules are very simple, it can be implemented on simple 8bit computers. Of course the game doesn't even require a computer, just a board and a few men -- chess masters don't even need a board to play (they can completely visualize the games in memory). In the end one can in theory just play against himself in his head, achieving the ultimate freedom: the only dependency of the game is one's brain, i.e. it becomes a brain software. Chess is extremely inexpensive, doesn't discriminate against poor people and will survive even the most extreme technological collapse.
• No one owns chess, the game is hundreds of years old and many books about it are also already in the public domain. It is extremely free.
• It is a basis for other derived games, for example many different chess variants or chess puzzles which can be considered a "singleplayer chess game".
• It is a source of many interesting mathematical and programming challenges.
• It seems to strike the right balance of simplicity and complexity, it is very simple but not so trivial as to be ever solved in a foreseeable future.

Many however see go as yet a more beautiful game: a more minimal, yet more difficult one, with a completely unique experience.

Chess as a game is not and cannot be copyrighted, but can chess games (moves played in a match) be copyrighted? Thankfully there is a pretty strong consensus and precedence that say this is not the case, even though capital worshippers try to play the intellectual property card from time to time (e.g. 2016 tournament organizers tried to stop chess websites from broadcasting the match moves under "trade secret protection", unsuccessfully).

Chess In General

Chess evolved from ancient board games in India in about 6th century. Nowadays the game is internationally governed by FIDE which has taken the on role of an authority that defines the official rules: FIDE rules are considered to be the standard chess rules. FIDE also organizes tournaments, promotes the game and keeps a list of registered players whose performance it rates with so called Elo system –⁠ based on the performance it also grants titles such as Grandmaster (GM, strongest), Internation Master (IM, second strongest) or Candidate Master (CM). A game of chess is so interesting in itself that chess is usually not played for money like many other games (poker, backgammon, ...).

The mastery of chess is often divided into two main areas (it is also common to divide strong players into these two categories depending on where their main strength lies):

• positional play: Long term, big picture patterns that offer many advantages and opportunities for playing good moves, trying to get a "good position" with men on strong squares, controlling key parts of the board, putting pressure on enemy, ensuring safety of own king etc.
• tactical play: Short term, quick action, tricks and calculation skills that win advantages, often material, with tools like forks, pins, discovery checks, sacrifices etc.

Of course this is not the only possible division, another one may be for example offensive vs defensive play etc., but generally chess revolves around position and tactics.

A single game of chess is seen as consisting of three stages: opening (starting, theoretical "book" moves, developing men), middlegame (seen as the pure core of the game) and endgame (ending in which only relatively few men remain on the board). There is no clear border between these stages and they are sometimes defined differently, however each stage plays a bit differently and may require different skills and strategies; for example in the endgame king becomes an active man while in the opening and middlegame he tries to stay hidden and safe.

The study of chess openings is called opening theory or just theory. Playing the opening stage is special by being based on memorization of this theory, i.e. hundreds or even thousands of existing opening lines that have been studied and analyzed by computers, rather than by performing mental calculation (logical "thinking ahead" present in middlegame and endgame). Some see this as weakness of chess that makes players spend extreme energy on pure memorization. One of the best and most famous players, Bobby Fischer, was of this opinion and has created a chess variant with randomized starting position that prevents such memorization, so called chess 960.

Elo rating is a mathematical system of numerically rating the performance of players (it is used in many sports, not just chess). Given two players with Elo rating it is possible to compute the probability of the game's outcome (e.g. white has 70% chance of winning etc.). The FIDE set the parameters so that the rating is roughly this: < 1000: beginner, 1000-2000: intermediate, 2000-3000: master. More advanced systems have also been created, namely the Glicko system.

The rules of chess are quite simple (easy to learn, hard to master) and can be found anywhere on the Internet. In short, the game is played on a 8x8 board by two players: one with white men, one with black (LOL IT'S RACIST :D). Each man has a way of moving and capturing (eliminating) enemy men, for example bishops move diagonally while pawns move one square forward and take diagonally. The goal is to checkmate the opponent's king, i.e. make the king attacked by a man while giving him no way to escape this attack. There are also lesser known rules that noobs often miss and ignore, e.g. so called en-passant or the 50 move rule that declares a draw if there has been no significant move for 50 moves.

At the competitive level clock (so called time control) is used to give each player a limited time for making moves: with unlimited move time games would be painfully long and more a test of patience than skill. Clock can also nicely help balance unequal opponent by giving the stronger player less time to move. Based on the amount of time to move there exist several formats, most notably correspondence (slowest, days for a move), classical (slow, hours per game), rapid (faster, tens of minutes per game), blitz (fast, a few seconds per move) and bullet (fastest, units of seconds per move).

Currently the best player in the world is pretty clearly Magnus Carlsen from Norway with Elo rating 2800+.

During covid chess has experienced a small boom among normies and YouTube chess channels have gained considerable popularity. This gave rise to memes such as the bong cloud opening popularized by a top player and streamer Hikaru Nakamura; the bong cloud is an intentionally shitty opening that's supposed to taunt the opponent (it's been even played in serious tournaments lol).

White is generally seen as having a slight advantage over black (just like in real life lol) because he always has the first move. This doesn't play such as big role in beginner and intermediate games but starts to become apparent in master games. How big the advantages is is a matter of ongoing debate, most people are of the opinion there exists a slight advantage, some people think chess is a win for white with perfect play while others believe chess is a draw with perfect play. Probably only very tiny minority of people think white doesn't have any advantage.

On perfect play: as stated, chess is unlikely to be ever solved so it is unknown if chess is a theoretical forced draw or forced win for white (or even win for black), however many simplified endgames and some simpler chess variants have already been solved. Even if chess was ever solved, it is important to realize one thing: perfect play may be unsuitable for humans and so even if chess was ever solved, it might have no significant effect on the game played by humans. Imagine the following: we have a chess position in which we are deciding between move A and move B. We know that playing A leads to a very good position in which white has great advantage and easy play (many obvious good moves), however if black plays perfectly he can secure a draw here. We also know that if we play B and then play perfectly for the next 100 moves, we will win with mathematical certainty, but if we make just one incorrect move during those 100 moves, we will get to a decisively losing position. While computer will play move B here because it is sure it can play perfectly, it is probably better to play A for human because human is very likely to make mistakes (even a master). For this reason humans may willingly choose to play mathematically worse moves -- it is because a slightly worse move may lead to a safer and more comfortable play for a human.

Chess And Computers

{ This is an absolutely amazing video about weird chess algorithms :) ~drummyfish }

Chess is a big topic in computer science and programming, computers not only help people play chess, train their skills, analyze positions and perform research of games, but they also allow mathematical analysis of chess and provide a platform for things such as artificial intelligence.

Chess software is usually separated to libraries, chess engines and frontends. Chess engine is typically a CLI program capable of playing chess but also doing other things such as evaluating arbitrary position, hinting best moves, saving and loading games etc. -- commonly the engine has some kind of custom CLI interface (flags, interactive commands it understands, ...) plus a support of some standardized text communication protocol, most notably XBoard (older one, more KISS) and UCI (newer, more bloated). There is also typically support for standardized formats such as FEN (way of encoding a chess position as a text string), PGN (way of encoding games as text strings) etc. Frontends on the other hand are usually GUI programs (in this case also called boards) that help people interact with the underlying engine, however there may also be similar non-GUI programs of this type, e.g. those that automatically run tournaments of multiple engines.

Computers have already surpassed the best humans in their playing strength (we can't exactly compute an engine's Elo as it depends on hardware used, but generally the strongest would rate high above 3000 FIDE). As of 2023 the strongest chess engine is widely agreed to be the FOSS engine Stockfish, with other strong engines being e.g. Leela Chess Zero (also FOSS), AlphaZero (proprietary by Google) or Komodo Dragon (proprietary). GNU Chess is a pretty strong free software engine by GNU. There are world championships for chess engines such as the Top Chess Engine Championship or World Computer Chess Championship. CCRL is a list of chess engines along with their Elo ratings deduced from tournaments they run. Despite the immense strength of modern engines, there are still some specific artificial situations in which a human beats the computer (shown e.g. in this video); this probably won't last long though.

The first chess computer that beat the world champion (at the time Gary Kasparov) was famously Deep Blue in 1997. Alan Turing himself has written a chess playing algorithm but at his time there were no computers to run it, so he executed it by hand -- nowadays the algorithm has been implemented on computers (there are bots playing this algorithm e.g. on lichess).

For online chess there exist many servers such as https://chess.com or https://chess24.com, but for us the most important is https://lichess.org which is gratis and uses FOSS (it also allows users to run bots under special accounts which is an amazing way of testing engines against people and other engines). These servers rate players with Elo/Glicko, allow them to play with each other or against computer, solve puzzles, analyze games, play chess variants, explore opening databases etc.

Playing strength is not the only possible measure of chess engine quality, of course -- for example there are people who try to make the smallest chess programs (see countercomplex and golfing). As of 2022 the leading programmer of smallest chess programs seems to be Óscar Toledo G. (https://nanochess.org/chess.html). Unfortunately his programs are proprietary, even though their source code is public. The programs include Toledo Atomchess (392 x86 instructions), Toledo Nanochess (world's smallest C chess program, 1257 non-blank C characters) and Toledo Javascript chess (world's smallest Javascript chess program). He won the IOCCC. Another small chess program is micro-Max by H. G. Muller (https://home.hccnet.nl/h.g.muller/max-src2.html, 1433 C characters, Toledo claims it is weaker than his program). Other engines try to be strong while imitating human play (making human moves, even mistakes), most notably Maia which trains several neural networks that play like different rated human players.

{ Nanochess is actually pretty strong, in my testing it easily beat smallchesslib Q_Q ~drummyfish }

Programming Chess

NOTE: our smallchesslib/smolchess engine is very simple, educational and can hopefully serve you as a nice study tool to start with :)

There is also a great online wiki focused on programming chess engines: https://www.chessprogramming.org.

Programming chess is a fun and enriching experience and is therefore recommended as a good exercise. There is nothing more satisfying than writing a custom chess engine and then watching it play on its own.

The core of chess programming is writing the AI. Everything else, i.e. implementing the rules, communication protocols etc., is pretty straightforward (but still a good programming exercise). Nevertheless, as the chess programming wiki stresses, one has to pay a great attention to eliminating as many bugs as possible; really, the importance of writing automatic tests can't be stressed enough as debugging the AI will be hard enough and can become unmanageable with small bugs creeping in. Though has to go into choosing right data structures so as to allow nice optimizations, for example board representation plays an important role (two main approaches are a 64x64 2D array holding each square's piece vs keeping a list of pieces, each one recording its position).

The AI itself works traditionally on the following principle: firstly we implement so called static evaluation function -- a function that takes a chess position and outputs its evaluation number which says how good the position is for white vs black (positive number favoring white, negative black, zero meaning equal, units usually being in pawns, i.e. for example -3.5 means black has an advantage equivalent to having extra 3 and a half pawns; to avoid fractions we sometimes use centipawns, i.e. rather -350). This function considers a number of factors such as total material of both players, pawn structure, king safety, men mobility and so on. Traditionally this function has been hand-written, nowadays it is being replaced by a learned neural network (NNUE) which showed to give superior results (e.g. Stockfish still offers both options); for starters you probably want to write a simple evaluation function manually.

Note: if you could make a perfect evaluation function that would completely accurately state given position's true evaluation (considering all possible combinations of moves until the end of game), you'd basically be done right there as your AI could just always make a move that would lead to position which your evaluation function rated best, which would lead to perfect play. Though neural networks got a lot closer to this ideal than we once were, as far as we can foresee ANY evaluation function will always be just an approximation, an estimation, heuristic, many times far away from perfect evaluation, so we cannot stop at this. We have to program yet something more.

So secondly we need to implement a so called search algorithm -- typically some modification of minimax algorithm, e.g. with alpha-beta pruning -- that recursively searches the game tree and looks for a move that will lead to the best result in the future, i.e. to position for which the evaluation function gives the best value. This basic principle, especially the search part, can get very complex as there are many possible weaknesses and optimizations. Note now that this search kind of improves on the basic static evaluation function by making it dynamic and so increases its accuracy greatly (of course for the price of CPU time spent on searching).

Exhaustively searching the tree to great depths is not possible even with most powerful hardware due to astronomical numbers of possible move combinations, so the engine has to limit the depth quite greatly and use various hacks, approximations, heuristics etc.. Normally it will search all moves to a small depth (e.g. 2 or 3 half moves or plys) and then extend the search for interesting moves such as exchanges or checks. Maybe the greatest danger of searching algorithms is so called horizon effect which has to be addressed somehow (e.g. by detecting quiet positions, so called quiescence). If not addressed, the horizon effect will make an engine misevaluate certain moves by stopping the evaluation at certain depth even if the played out situation would continue and lead to a vastly different result (imagine e.g. a queen taking a pawn which is guarded by another pawn; if the engine stops evaluating after the pawn take, it will think it's a won pawn, when in fact it's a lost queen). There are also many techniques for reducing the number of searched tree nodes and speeding up the search, for example pruning methods such as alpha-beta (which subsequently works best with correctly ordering moves to search), or transposition tables (remembering already evaluated position so that they don't have to be evaluated again when encountered by a different path in the tree).

Alternative approaches: most engines work as described above (search plus evaluation function) with some minor or bigger modifications. The simplest possible stupid AI can just make random moves, which will of course be an extremely weak opponent -- one might perhaps try to just program a few simple rules to make it a bit less stupid and possibly a simple training opponent for complete beginners: the AI may for example pick a few "good looking" candidate moves that are "usually OK" (pushing a pawn, taking a higher value piece, castling, ...) and aren't a complete insanity, then pick one at random only from those (this randomness can further be improved and gradually controlled by scoring the moves somehow and adding a more or less random value from some range to each score, then picking the moves with highest score). One could also try to just program in a few generic rules such as: checkmate if you can, otherwise take an unprotected piece, otherwise protect your own unprotected piece etc. -- this could produce some beginner level bot. Another idea might be a "Chinese room" bot that doesn't really understand chess but has a huge database of games (which it may even be fetching from some Internet database) and then just looking up what moves good players make in positions that arise on the board, however a database of all positions will never exist, so in case the position is not found there has to be some fallback (e.g. play random move, or somehow find the "most similar position" and use that, ...). As another approach one may try to use some non neural network machine learnening, for example genetic programming, to train the evaluation function, which will then be used in the tree search. Another idea that's being tried (e.g. in the Maia engine) is pure neural net AI (or another form of machine learning) which doesn't use any tree search -- not using search at all has long been thought to be impossible as analyzing a chess position completely statically without any "looking ahead" is extremely difficult, however new neural networks have shown to be extremely good at this kind of thing and pure NN AIs can now play on a master level (a human grandmaster playing ultra bullet is also just a no-calculation, pure pattern recognition play). Next, Monte Carlo tree search (MCTS) is an alternative way of searching the game tree which may even work without any evaluation function: in it one makes many random playouts (complete games until the end making only random moves) for each checked move and based on the number of wins/losses/draws in those playouts statistically a value is assigned to the move -- the idea is that a move that most often leads to a win is likely the best. Another Monte Carlo approach may just make random playouts, stop at random depth and then use normal static evaluation function (horizon effect is a danger but hopefully its significance should get minimized in the averaging). However MCTS is pretty tricky to do well. MCTS is used e.g. in Komodo Dragon, the engine that's currently among the best. Another approach may lie in somehow using several methods and heuristics to vote on which move would be best.

Many other aspects come into the AI design such as opening books (databases of best opening moves), endgame tablebases (precomputed databases of winning moves in simple endgames), clock management, pondering (thinking on opponent's move), learning from played games etc. For details see the above linked chess programming wiki.

Notable Chess Engines/Computers/Entities

TODO: table

Stats And Records

Chess stats are pretty interesting.

{ Some chess world records are here: https://timkr.home.xs4all.nl/records/records.htm. ~drummyfish }

Number of possible games is not known exactly, Shannon estimated it at 10^120 (lower bound, known as Shannon number). Number of possible games by plies played is 20 after 1, 400 after 2, 8902 after 3, 197281 after 4, 4865609 after 5, and 2015099950053364471960 after 15.

Similarly the number of possibly reachable positions (position for which so called proof game exists) is not known exactly, it is estimated to at least 10^40 and 10^50 at most. Numbers of possible positions by plies is 20 after 1, 400 after 2, 5362 after 3, 72078 after 4, 822518 after 5, and 726155461002 after 11.

Shortest possible checkmate is by black on ply number 4 (so called fool's mate). As of 2022 the longest known forced checkmate is in 549 moves -- it has been discovered when computing the Lomonosov Tablebases.

Average game of chess lasts 40 moves. Average branching factor (number of possible moves at a time) is around 33. Maximum number of possible moves in a position seems to be 218 (FEN: R6R/3Q4/1Q4Q1/4Q3/2Q4Q/Q4Q2/pp1Q4/kBNN1KB1 w - - 0 1).

White wins about 38% of games, black wins about 34%, the remaining 28% are draws (38.7%, 31.1%, 30.3% respectively on Computer Chess Rating Lists).

What is the longest possible game? It depends on the exact rules and details we set, for example if a 50 move rule applies, a player MAY claim a draw but also doesn't have to -- but if neither player ever claims a draw, a game can be played infinitely -- so we have to address details such as this. Nevertheless the longest possible chess game upon certain rules has been computed by Tom7 at 17697 half moves in a paper for SIGBOVIK 2020. Chess programming wiki states 11798 half moves as the maximum length of a chess game which considers a 50 move rule (1966 publication).

The longest game played in practice is considered to be the one between Nikolic and Arsovic from 1989, a draw with 269 moves lasting over 20 hours. For a shortest game there have been ones with zero moves; serious decisive shortest game has occurred multiple times like this: 1.d4 Nf6 2.Bg5 c6 3.e3 Qa5+ (white resigned).

Best player ever: a 2017 paper called Who is the Master? analyzed 20 of the top players of history based on how good their moves were compared to Stockfish, the strongest engine. The resulting top 10 is (from best): Carlsen, Kramnik, Fischer, Kasparov, Anand, Khalifman, Smyslov, Petrosian, Karpov, Kasimdzhanov. It also confirmed that the quality of chess play at top level has been greatly increasing.

What's the most typical game? We can try to construct such a game from a game database by always picking the most common move in given position. Using the lichess database at the time of writing, we get the following incomplete game (the remainder of the game is split between four games, 2 won by white, 1 by black, 1 drawn):

1. e4 e5 2. Nf3 Nc6 3. Bc4 Bc5 4. c3 Nf6 5. d4 exd4
6. cxd4 Bb4+ 7. Nc3 Nxe4 8. O-O Bxc3 9. d5 Bf6 10. Re1 Ne7
11. Rxe4 d6 12. Bg5 Bxg5 13. Nxg5 h6 14. Qe2 hxg5
15. Re1 Be6 16. dxe6 f6 17. Re3 c6 18. Rh3 Rxh3
19. gxh3 g6 20. Qf3 Qa5 21. Rd1 Qf5 22. Qb3 O-O-O
23. Qa3 Qc5 24. Qb3 d5 25. Bf1

You can try to derive your own stats, there are huge free game databases such as the Lichess CC0 database of billions of games from their server.

{ TODO: Derive stats about the best move, i.e. for example "best move is usually by queen by three squares" or something like that. Could this actually help the play somehow? Maybe could be used for move ordering in alpha-beta. ~drummyfish }

Rules

The exact rules of chess and their scope may depend on situation, this is just a sum up of rules generally used nowadays.

The start setup of a chessboard is following (lowercase letters are for black men, uppercase for white men, on a board with colored squares A1 is black):

        _______________
    /8 |r n b q k b n r|
 r | 7 |p p p p p p p p|
 a | 6 |. . . . . . . .|
 n | 5 |. . . . . . . .|
 k | 4 |. . . . . . . .|
 s | 3 |. . . . . . . .|
   | 2 |P P P P P P P P|
    \1 |R N B Q K B N R|
        """""""""""""""
        A B C D E F G H
        \_____________/
             files

Players take turns in making moves, white always starts. A move consists of moving one (or in special cases two) of own men from one square to another, possibly capturing (removing from the board) one opponent's man -- except for a special en passant move capturing always happens by moving one man to the square occupied by the opposite color man (which gets removed). Of course no man can move to a square occupied by another man of the same color. A move can NOT be skipped. A player wins by giving a checkmate to the opponent (making his king unable to escape attack) or if the opponent resigns. If a player is to move but has no valid moves, the game is a draw, so called stalemate. If neither player has enough men to give a checkmate, the game is a draw, so called dead position. There are additional situation in which game can be drawn (threefold repetition of position, 50 move rule). Players can also agree to a draw. A player may also be declared a loser if he cheated, if he lost on time in a game with clock etc.

The individual men and their movement rules are (no man can move beyond another, except for knight who jumps over other men):

Check: If the player's king is attacked, i.e. it is immediately possible for an enemy men to capture the king, the player is said to be in check. A player in check has to make such a move as to not be in check after that move.

A player cannot make a move that would leave him in check!

Castling: If a player hasn't castled yet and his king hasn't been moved yet and his kingside (queenside) rook hasn't been moved yet and there are no men between the king and the kingside (queenside) and the king isn't and wouldn't be in check on his square or any square he will pass through or land on during castling, short (long) castling can be performed. In short (long) castling the king moves two squares towards the kingside (queenside) rook and the rook jumps over the king to the square immediately on the other side of the king.

Promotion: If a pawn reaches the 1st or 8th rank, it is promoted, i.e. it has to be switched for either queen, rook, bishop or knight of the same color.

Checkmate: If a player is in check but cannot make any move to get out of it, he is checkmated and lost.

En passant: If a pawn moves 2 squares forward (from the start position), in the immediate next move the opponent can take it with a pawn in the same way as if it only moved 1 square forward (the only case in which a men captures another man by landing on an empty square).

Threefold repetition is a rule allowing a player to claim a draw if the same position (men positions, player's turn, castling rights, en passant state) occurs three times (not necessarily consecutively). The 50 move rule allows a player to claim a draw if no pawn has moved and no man has been captured in last 50 moves (both players making their move counts as a single move here).

Variants

Besides similar games such as shogi there are many variants of chess, i.e. slight modifications of rules, foremost worth mentioning is for example chess 960. The following is a list of some variants:

• antichess (suicide, ...): The goal is to lose all men or get stalemated, rules are a bit changed, e.g. castling and checks are removed and taking is forced.
• chess 960 aka Fischer's random: Starting position is randomly modified by shuffling the non-pawn rows (with these rules: king must be between rooks, bishops on opposite colors and black/white's positions are mirrored). The rules are the same with a slight modification to castling. This was invented by Bobby Fischer to emphasize pure chess skill as opposed to memorizing the best opening moves, he saw the opening theory as harmful to chess. Chess 960 is nowadays even advocated by some to become the "main" version of chess.
• chess boxing: Chess combined with box, players switch between the two games, one wins either by checkmate or knockout.
• crazyhouse: When a player captures a man, it goes into his reserve. From the reserve a man can be dropped (as a man of the current player's color) to an empty square instead of making a normal move. This is a rule taken from shogi.
• different men: Some variants use different men, e.g. empress (moves like rook and knight) or amazon (queen/knight).
• duck chess: After each move players place a duck on an empty square, the duck blocks the square. The duck cannot be left on the same square, it has to be moved. There are no checks, players win by capturing the king.
• fog of war: Makes chess an incomplete-information game by allowing players to only see squares they can immediately move to (this is similarly to some strategy video games).
• horde chess: Asymmetric starting position: large number of black pawns vs a white army of traditional men. Rules are slightly modified, e.g. black can only be defeated by having all pawns captured (there is no black king).
• infinite chess: Infinite chessboard.
• minichess: Smaller chessboard, e.g. 4x4, 4x8 etc. Los Alamos chess is played at 6x6 board without bishops (also no promotion to bishop, no pawn double step, no en passant, no castling). Some are already solved (e.g. 3x3).
• more players: E.g. 3 man chess or 4 player chess allow more than two players to play, some use different boards.
• old chess: The rules of chess itself have been changing over time (e.g. adding the 50 move rule etc.). The older rule sets can be seen as variants as well.
• puzzle: For single player, chess positions are presented and the player has to find the best move or sequence of moves.
• racing kings: The starting position has both players on the same side, the goal is to get one's king to the other side first.
• non-Euclidean: different geometries of the board, e.g. hyperbolic or spherical.
• 3D chess: 3D generalization of chess.
• randomly chosen variant: Here a chess variant to be played is chosen at random before the game, e.g. by dice roll. { This is an idea I got, not sure if this exists or has a different name. ~drummyfish }

Playing Tips

Some general tips and rules of thumb, mostly for beginners:

• Try to control the center of the board (D4, D5, E4, E5).
• Don't bring the queen out too early, the opponent can harass it and get ahead in development.
• Learn some universal setup openings or "systems" to play, e.g. London, King's Indian, the hippo etc.
• Develop your men before attacking, usually knights go out before bishops, bishops are well placed on the longest diagonals as "snipers".
• Learn basic tactics, especially forks (attacking two or more men at once so that one of them cannot escape capture) and pins (attack one man so that if he moves out of the way he will expose another one to be captured).
• King safety is extremely important until endgame, castle very early but not extremely early. In the endgame (with queens out) king joins the battle as another active man.
• Pawn structure is very important.
• Watch out for back rank checkmates, make an escape square for your king.
• Rooks want to be on open files, you also want to CONNECT them (have both guard each other). Also a rook in the opponents second row (2nd/7th rank) is pretty good.
• Bishops are generally seen a bit more valuable than knights, especially in pairs -- if you can trade your knight for opponent's bishop, it's often good. If your opponent has two bishops and you only have one, you want to trade yours for his so he doesn't have the pair. A knight pair is also pretty powerful though, especially when the knights are guarding each other.
• "Knight on a rim is dim" (knights are best placed near the center).
• An extremely strong formation is both rooks and the queen on the same open file.
• Blocking the opponents man so that it can't move is almost as good as taking it. And vice versa: you want to activate all your men if possible.
• Nubs are weak against long range bishops, they can't see them. Place a bishop to corner on the long diagonal and just snipe the opponent's material.
• Don't play "hope chess", always suppose your opponent will play the best move he can.
• If you can achieve something with multiple men, usually it's best to do it with the weakest one.
• TODO: moar

How To Disrespect Your Opponent And Other Lulz In Chess

see also unsportmanship

WORK IN PROGRESS, pls send me more tips :)

• OTB (over the board) only:
  • Turn your knights to face backwards or in another weird way (always face the opponent's king etc.). Also place the pieces unevenly on the squares to piss off opponents with OCD and autism.
  • Behave weird, make weird faces, walk extremely far away from the board and walk in circles (or just get up and stand up directly behind your opponent in a completely upright position staring into the distance without moving at all like a robot lol), constantly sneeze (try to sneeze every time the opponent touches a piece), make very long unbroken eye contact with the opponent while smiling as if you know what he's thinking, call the referee constantly, go to the toilet after every move, pretend to fall asleep from boredom etc. Overeat on beans before the game so you fart a lot and always try to fart as loud as possible. Wear nice clothes but right before the game go sweat to the gym so that you smell like a pig and distract the opponent with toxic fume. If you're a wimmin behave sexually, keep grabbing your boobs, lick your lips and opponent's captured pieces and silently moan sometimes as if you're having an orgasm, pretend to masturbate under the table; if your opponent is male he is almost definitely smarter than you, you gotta use your woman weapons, but it will probably work easily on the chess virgins.
  • In a tournament change play based on opponent's race or sex, for example play only one opening against white people and another opening against black people, see if anyone notices the pattern :D
  • Outside tournament take advantage of the fact that you can do whatever the fuck you want: have one hand constantly on the clock and play with the other hand (considered rude and often forbidden), touch and knock over your opponent's pieces, take back your moves, ... and of course when you're losing, "accidentally" knock over the whole board and be like "oops, let's consider it a draw then" :D
  • Trash talk the referee.
  • ...
• online only:
  • Be annoying and offensive in chat, if opponent blunders write gg, spam ez when you win. If he wins say it was a shit game and accuse him of cheating.
  • Constantly ask for takebacks, offer draws, report legit opponents for cheating and offensive behavior.
  • ...
• Play the bongcloud, fool's mate, 1. h3 or similar offensive opening, especially against a stronger player. Offer a draw after 1st move. Just play knight F3 and back constantly. Castle manually even if you don't have to. Play the exact mirror of opponent's moves -- if he tries to break it then just always try to get back to mirrored position.
• When losing constantly offer draws, prolong the game AS MUCH AS POSSIBLE, before the very last move just let the clock run out.
• Repeatedly try to make swastikas on the board, especially against colored opponents.
• Underpromote pawns e.g. to knights or bishops.
• When playing a noob, don't just mate him but absolutely rape him, promote all pawns to knights before winning, then say you didn't even have to try and that he should look into another game as chess is clearly not his game.
• Look up chess etiquette and do the exact opposite of what it says.
• ...

LRS Chess

Chess is only mildly bloated but what if we try to unbloat it completely? Here we propose the LRS version of chess. The rule changes against normal chess are:

• No castling.
• No en passant.
• Promotion is always to queen.
• No checks or checkmates, king is just another man.
• Whoever takes the opponent's king first wins.
• If a player has no available moves, he loses.
• Only a single draw rule: if game doesn't end in 1024 half moves or fewer, it is a draw. I.e. there are no weird draw rules (50 move, repetition, ...). Of course players may still agree on draw anytime.
• Random: optionally random variant of LRS chess can be played. Here we randomly shuffle the white player's back row men in the starting position and mirror it for black (no weird conditions on men positions like in chess 960).

See Also

• shogi
• go
• hexapawn
• checkers
• backgammon
• Deep Blue

Chinese

Chinese is one of the most bloated natural human languages, spoken in China.

Any text in chinese basically looks like this:

#########################
#########################
#########################
#########################

"Cloud Computing"

Cloud is just someone else's computer.

Cloud computing, more accurately known as clown computing, means giving up an autonomous computer by storing one's data as well as running one's programs on someone else's (often a corporation's) computer, known as the cloud, through the Internet, becoming wholly dependent on someone else to which one gives all the power. While the general idea of server computers and remote terminals is not bad in itself and may be utilized in very good ways, the term cloud computing stands for abusing this idea e.g. by capitalists or states to take away autonomous computers from the people as well as to restrict freedoms of people in other ways, for example by pushing DRM, making it impossible to truly own a copy of software or other data, to run computations privately, isolated from the Internet or run non-approved, user-respecting software. Moreover clown computing as applied nowadays is mostly a very bad engineering approach that wastes bandwidth, introduces lag, requires complex and expensive infrastructure etc.

Despite all this "cloud" is the mainstream nowadays, it is the way of computing among normies, even despite regular leaks and losses of their personal data etc., simply because they're constantly being pushed to it by the big tech (Apple, Google, Micro$ost, ...) -- many times they don't even have a choice, they are simply supposed to SHUT UP AND CONSUME. And of course they wouldn't even have an idea about what's going on in the first place, all that matters to a normie is "comfort", "everyone does it", "I just need my TikTok" etc. Zoomers probably aren't even aware of the cloud, they simply have phones with apps that show their photos if Apple approves of it, they don't even care how shit works anymore.

In the future non-cloud computers will most likely become illegal. This will be justified by autonomous computers being "dangerous", only needed by terrorists, pirates and pedophiles. An autonomous computer will be seen as a gun, the right to own it will be greatly limited.

C

{ We have a C tutorial! ~drummyfish }

C is an old low level structured statically typed imperative compiled programming language, the language that's currently mostly used by less retarded software. Though by very strict standards it would be considered bloated, compared to any mainstream modern language it is very bullshitless and KISS, so it is also the go-to language of the suckless community as well as most true experts, for example the Linux and OpenBSD developers, because of its good, relatively simple design, uncontested performance, wide support, great number of compilers, level of control and a greatly established and tested status. C is perhaps the most important language in history, it influenced, to smaller or greater degree, basically all of the widely used languages today such as C++, Java, JavaScript etc., however it is not a thing of the past -- in the area of low level programming C is still the number one unsurpassed language. C is by no means perfect but it is currently probably the best choice of a programming language.

{ Look up The Ten Commandments for C Programmers by Henry Spencer. ~drummyfish }

It is usually not considered an easy language to learn because of its low level nature: it requires good understanding of how a computer actually works and doesn't prevent the programmer from shooting himself in the foot. Programmer is given full control (and therefore responsibility). There are things considered "tricky" which one must be aware of, such as undefined behavior of certain operators and raw pointers. This is what can discourage a lot of modern "coding monkeys" from choosing C, but it's also what inevitably allows such great performance -- undefined behavior allows the compiler to choose the most efficient implementation. On the other hand, C as a language is pretty simple without modern bullshit concepts such as OOP, it is not as much hard to learn but rather hard to master, as any other true art.

C is said to be a "portable assembly" because of its low level nature, great performance etc. -- though C is structured (has control structures such as branches and loops) and can be used in a relatively high level manner, it is also possible to write assembly-like code that operates directly with bytes in memory through pointers without many safety mechanisms, so C is often used for writing things like hardware drivers. On the other hand some restrain from likening C to assembly because C compilers still perform many transformations of the code and what you write is not necessarily always what you get.

Mainstream consensus acknowledges that C is among the best languages for writing low level code and code that requires performance, such as operating systems, drivers or games. Even scientific libraries with normie-language interfaces -- e.g. various machine learning Python libraries -- usually have the performance critical core written in C. Normies will tell you that for things outside this scope C is not a good language, with which we disagree -- we recommend using C for basically everything that's supposed to last, i.e. if you want to write a good website, you should write it in C etc.

History and Context

C was developed in 1972 at Bell Labs alongside the Unix operating system by Dennis Ritchie and Brian Kerninghan, as a successor to the B language (portable language with recursion) written by Denis Ritchie and Ken Thompson, which was in turn inspired by the the ALGOL language (code blocks, lexical scope, ...).

In 1973 Unix was rewritten in C. In 1978 Keninghan and Ritchie published a book called The C Programming Language, known as K&R, which became something akin the C specification. In 1989, the ANSI C standard, also known as C89, was released by the American ANSI. The same standard was also adopted a year later by the international ISO, so C90 refers to the same language. In 1999 ISO issues a new standard that's known as C99.

TODO

Standards

C is not a single language, there have been a few standards over the years since its inception in 1970s. The notable standards and versions are:

• K&R C: C as described by its inventors in the book The C Programming Language, before official standardization. This is kind of too ancient nowadays.
• C89/C90 (ANSI/ISO C): First fully standardized version, usable even today, many hardcore C programmers stick to this version so as to enjoy maximum compiler support.
• C95: A minor update of the previous standard, adds wide character support.
• C99: Updated standard from the year 1999 striking a great balance between "modern" and "good old". This is a good version to use in LRS programs, but will be a little less supported than C89, even though still very well supported.
• C11: Updated standard from the year 2011. This one is too bloated and isn't worth using.
• C17/C18: Yet another update, yet more bloated and not worth using anymore.
• ...

LRS should use C99 or C89 as the newer versions are considered bloat and don't have such great support in compilers, making them less portable and therefore less free.

The standards of C99 and older are considered pretty future-proof and using them will help your program be future-proof as well. This is to a high degree due to C having been established and tested better than any other language; it is one of the oldest languages and a majority of the most essential software is written in C, C compiler is one of the very first things a new hardware platform needs to implement, so C compilers will always be around, at least for historical reasons. C has also been very well designed in a relatively minimal fashion, before the advent of modern feature-creep and and bullshit such as OOP which cripples almost all "modern" languages.

Compilers

• gcc: the main "big name" that can compile all kinds of languages including C, used by default in many places, very bloated
• clang: another big bloated compiler, kind of competes with gcc
• tcc: tiny C compiler, suckless, cannot optimize as well as the big compilers but is pretty elegant
• scc: another small/suckless C compiler
• 8c, 8cc
• ...

Standard Library

Besides the pure C language the C standard specifies a set of libraries that have to come with a standard-compliant C implementation -- so called standard library. This includes e.g. the stdio library for performing standard input/output (reading/writing to/from screen/files) or the math library for mathematical functions. It is usually relatively okay to use these libraries as they are required by the standard to exist so the dependency they create is not as dangerous, however many C implementations aren't completely compliant with the standard and may come without the standard library. So for sake of portability it is best if you can avoid using standard library.

The standard library (libc) is a subject of live debate because while its interface and behavior are given by the C standard, its implementation is a matter of each compiler; since the standard library is so commonly used, we should take great care in assuring it's extremely well written. As you probably guessed, the popular implementations (glibc et al) are bloat. Better alternatives thankfully exist, such as:

• musl
• uclibc
• not using the standard library :)

Bad Things About C

Nothing is perfect, not even C; it was one of the first relatively higher level languages and even though it has showed to have been designed extremely well, some things didn't age great, or were simply bad from the start. We still prefer this language as usually the best choice, but it's good to be aware of its downsides or smaller issues, if only for the sake of one day designing a better language. Keep in mind all here are just suggestions, they made of course be a subject to counter arguments and further discussion. So, let's go:

• C specification (the ISO standard) is proprietary :( The language itself probably can't be copyrighted, nevertheless this may change in the future, and a proprietary specs lowers C's accessibility and moddability (you can't make derivative versions of the spec).
• The specification is also long as fuck, indicating bloat/complexity/obscurity. A good, free language should have a simple definition. It could be simplified a lot by simplifying the language itself as well as dropping some truly legacy considerations (like BCD systems?) and removing a lot of undefined behavior.
• Some behavior is weird and has exceptions, for example a function can return anything, including a struct, except for an array. This makes it awkward to e.g. implement vectors which would best be made as arrays but you want functions to return them, so you may do hacks like wrapping them instide a struct just for this.
• Some things could be made simpler, e.g. using reverse polish notation for expressions, rather than expressions with brackets and operator precedence, would make implementations much simpler, increasing sucklessness (of course readability is an argument).
• Some things could be dropped entirely (enums, bitfields, possibly also unions etc.), they can be done and imitated in other ways without much hassle.
• The preprocessor isn't exactly elegant, it has completely different syntax and rules from the main language, not very suckless -- ideally preprocessor uses the same language as the base language.
• The syntax is sucky sometimes, e.g. data type names may consist of multiple tokens (long long int etc.), multiplication uses the same symbol as pointer dereference (*), also it's pretty weird that the condition after if has to be in brackets etc., it could be designed better. Keywords also might be better being single chars, like ? instead of if etc. A shorter, natural-language-neutral source code would be probably better. Both line and block comments could be implemented with a single character (e.g. # for line comment, ending with a newline or another #, ## for block comment ending with another ##?).
• Some undefined/unspecified behavior would maybe be better defined/specified -- undefined behavior isn't bad in general, it is what allows C to be so fast and efficient in the first place, but some of it has shown to be rather cumbersome; for example the unspecified representation of integers, their binary size and behavior of floats leads to a lot of trouble (unknown upper bounds, sizes, undefined behavior of many operators etc.) while practically all computers have settled on using 8 bit bytes, two's complement and IEEE754 for floats -- this could easily be made a mandatory assumption which would simplify great many things without doing basically any harm. New versions of C actually already settle on two's complement. This doesn't mean C should be shaped to reflect the degenerate "modern" trends in programming though!
• Some basic things that are part of libraries or extensions, like fixed width types and binary literals and possibly very basic I/O (putchar/readchar), could be part of the language itself rather than provided by libraries.
• All that stuff with .c and .h files is unnecessary, there should just be one file type -- this isn't part of the language per se, but it's part of its culture.
• TODO: moar

Basics

This is a quick overview, for a more in depth tutorial see C tutorial.

A simple program in C that writes "welcome to C" looks like this:

#include <stdio.h> // standard I/O library

int main(void)
{
  // this is the main program
    
  puts("welcome to C");

  return 0; // end with success
}

You can simply paste this code into a file which you name e.g. program.c, then you can compile the program from command line like this:

gcc -o program program.c

Then if you run the program from command line (./program on Unix like systems) you should see the message.

Cheatsheet

It's pretty important you learn C, so here's a little cheat sheet for you.

data types (just some):

• int: signed integer, at least 16 bits (-32767 to 32767) but usually more
• unsigned int: unsigned integer, at least 16 bit (0 to 65535) but usually more
• char: smallest integer of at least 8 bits (1 byte, 256 values), besides others used for containing ASCII characters
• unsigned char: like char but unsigned (0 to 255)
• float: floating point number (usually 32 bit)
• double: like float but higher precision (usually 64 bit)
• short: smaller signed integer, at least 16 bits (−32767 to 32767)
• long: bigger signed integer, at least 32 bits (-2147483647 to 2147483647)
• pointer: memory address (size depends on platform), always tied to a specific type, e.g. a pointer to integer: *int, pointer to double: *double etc.
• array: a sequence of values of some type, e.g. an array of 10 integers: int[10]
• struct: structure of values of different types, e.g. struct myStruct { int myInt; chat myChar; }
• note: header stdint.h contains fixed-width data types such as uint32_t etc.
• note: there is no string, a string is an array of chars which must end with a value 0 (string terminator)
• note: there is no real bool (actually it is in header stdbool), integers are used instead (0 = false, 1 = true)

branching aka if-then-else:

if (CONDITION)
{
  // do something here
}
else // optional
{
  // do something else here
}

for loop (repeat given number of times):

for (int i = 0; i < MAX; ++i)
{
  // do something here, you can use i
}

while loop (repeat while CONDITION holds):

while (CONDITION)
{
  // do something here
}

do while loop (same as while but CONDITION at the end):

do
{
  // do something here
} while (CONDITION);

function definition:

RETURN_TYPE myFunction (TYPE1 param1, TYPE2 param2, ...)
{ // return type can be void
  // do something here
}

See Also

• comun
• C tutorial
• C pitfalls
• C programming style
• C++
• IOCCC
• D
• HolyC
• QuakeC
• Pascal
• Fortran
• LISP
• FORTH
• memory management in C

Code of Conduct

See also http://techrights.org/2019/04/23/code-of-coercion/.

Code of conduct (COC), also code of coercion, is a shitty invention of SJW fascists that's put up in projects (e.g. software) and which declares how developers of a specific project must behave socially (typically NOT just withing the context of the development but also outside of it), generally pushing toxic woke concepts such as forced inclusivity, exclusivity of people with unapproved political opinions or use of politically correct language (newspeak). Sometimes a toxic COC hides under a different name such as social contract or mission statement, though not necessarily. COC is typically placed in the project repository as a CODE_OF_CONDUCT file. In practice COCs are used to establish dictatorship and allow things such as kicking people out of development because of their political opinions expressed anywhere, inside or outside the project, and to push political opinions through software projects.

LRS must never include any COC, with possible exceptions of anti-COC (such as NO COC) or parody style COCs, not because we dislike genuine inclusivity, but because we believe COCs are bullshit and mostly harmful as they support bullying, censorship and exclusion of people.

Anyway it's best to avoid any kind of COC file in the repository, it just takes up space and doesn't serve anything. We may simply ignore this shitty concept completely. You may argue why we don't ignore e.g. copyright in the same way and just not use any licenses? The situation with copyright is different: it exists by default, without a license file the code is proprietary and our neighbors don't have the legal safety to execute basic freedoms, they may be bullied by the state -- for this we are forced to include a license file to get rid of copyright. With COC there simply isn't any such implicit issues to be solved (because COCs are simply inventing their own issues), so we just don't try to solve non-issues.

Coding

Coding nowadays means low quality attempt at programming, usually practiced by soydevs and barely qualified coding monkeys.

Traditionally it means encoding and decoding of information as in e.g. video coding -- this is the only non-gay meaning of the word

Collapse

Collapse of our civilization is a concerning scenario in which basic structures of society relatively rapidly fall apart and cause unusually large, possibly world-wide horrors such as chaos, wars, famine and loss of advanced technology. It is something that will very likely happen very soon due to uncontrolled growth and societal decline by capitalism: we, the LRS, are especially focusing on a very probable technological collapse (caused by badly designed technology as well as its wrong application and extreme overuse causing dangerous dependencies) but of course clues point to collapse are coming from many directions (ecological, economical, political, natural disasters such as a coronal mass ejection etc.). Some have said that a society can deal with one crisis, but if multiple crises hit at once this hit may be fatal; however the dependence of current society on computer technology is so great that its collapse could be enough to deliver a fatal blow alone. Recently (around 2015) there has even appeared a specific term collapsology referring to the study of the potential collapse.

There is a reddit community for discussing the collapse at https://reddit.net/r/collapse. WikiWikiWeb has a related discussion under ExtinctionOfHumanity.

Collapse of civilizations has been a repeated theme throughout history, it is nothing new or exceptional, see e.g. Maya empire collapse, Bronze age collapse, the fall of Rome etc. It usually comes when a civilization reaches high complexity and becomes "spoiled", morally corrupt and socially divided, which may also be "helped" by technological advancement (e.g. the Bronze age collapse is speculated to have been partially caused by the new technology of iron which has broken the old established structures) -- basically just what we are seeing today. Economic interdependence is especially dangerous, and since we are currently living under extreme form of capitalism, we are extremely subjected to this threat: everyone is hyperspecialized and so practically no one is self sufficient, people don't know how to make food, build homes, make tools, factories are unable to produce anything without dozens of other companies providing material, technology and services for them; everything depends on highly complex and extremely fragile production chains. Besides dependence on economy, an equal or even greater danger may be our absolute dependence on computer technology: nothing works without computers and Internet, even that which could and should: factories, traffic, governments, hospitals, even many basic tools ("smart" ones, "tools as a service", ...). It is extremely likely we'll sooner or later sustain a blow that will paralyze the Internet and computers, be it a natural disaster such as coronal mass ejection, an economic disaster (supply chains collapsing, ...), political disaster (war, cyber attacks, ...), unintentional or intentional "accident" ("oops, I just turned off all computers in the world that are running Windows" --Microsoft employee), simple unsustainability of maintenance of the exponentially growing complexity of computers or anything similar (AI taking over the internet? :]). Thinking about it deeper, it seems like a miracle we are still here.

In technological world a lot of people are concerned with the collapse, notable the collapse OS, an operating system meant to run on simple hardware after the technological supply chain collapses and renders development of modern computers impossible. They believe the collapse will happen before 2030. The chip shortage, financial, climatic and energetic crisis and beginning of war in Europe as of early 2020s are one of the first warnings showing how fragile the systems really is.

Ted Kaczynski (a famous primitivist mathematician that committed mass murderer to warn about the decline of society due to complex technology) has seen the collapse as a possible option. Internet bloggers/vloggers such as Luke Smith and no phone man advocate (and practice) simple, independent off-grid living, possibly to be prepared for such an event. Even proprietary normies like Jonathan Blow warn of a coming disaster (in his talk Preventing the Collapse of Civilization). Viznut is another programmer warning about the collapse.

The details of the collapse cannot of course be predicted exactly -- it may come in a relatively quick, violent form (e.g. in case of a disaster causing a blackout) or as a more agonizing slow death. CollapseOS site talks about two stages of the slow collapse: the first one after the collapse of the supply chain. i.e. when the production of modern computers halts, and the second (decades after) when the last modern computer stops working. It most likely won't happen overnight -- that's a very extreme case. A typical collapse may take decades during which all aspects of society see a rapid decline. Of course, a collapse doesn't mean extinction of humans either, just deaths of many and great losses of what has been achieved culturally and technologically.

{ I've read a book called Blackout by Marc Elsberg whose story revolves around a fictional large collapse of power supply in Europe. A book called The World Without Us explores what the world would look like if humans suddenly disappeared. Also the podcast called Fall of Civilizations by Paul Cooper is awesome. ~drummyfish }

Live Documenting The Current Collapse Of Our Civilization

This section will record the current in-progress collapse of our civilization as seen by me, drummyfish. It may serve later generations and historians, as I know any information left behind is important for avoiding repeating the mistakes, though I also know you will not learn and will repeat the mistakes anyway. A man can dream I guess. If you can take away just one thing though, please be it this: FOR THE LOVE OF GOD, DO NOT EVER ALLOW COMPETITION TO BE THE BASE OF SOCIETY AGAIN.

Late 2022 Report

It seems like the collapse may have already begun. After the worldwide Covid pandemic the Russia-Ukraine war has begun with talks of nuclear war already going on. A great economic crisis has begun, possibly as a result of the pandemic and the war, inflation is skyrocketing and breaking all records, especially gas and energy prices are growing to extremes and as a result basically prices of everything go up as well. Russia isolated itself, new cold war has begun. Many big banks have gone bankrupt. War immigrants from Ukraine are flooding into Europe and European fascists/nationalists seem to be losing their patience about it. People in European first world countries are now actually concerned about how not to freeze during the winter, this talk is all over TV and radio. The climate disaster has also started to show, e.g. in Czech Republic there was the greatest forest fire in its history as well an extremely hot summer, even tornados that destroyed some villages (tornados in this part of world are basically unheard of), winters have almost no snow unlike some two decades ago. Everything is shitty, food costs more and is of much lower quality as basically everything else, newly bought technology cannot be expected to last longer than a few months. Society is spoiled to an unimaginable level, extreme hostility, competition and aggressive commerce is everywhere, kids are addicted to cellphones and toxic social media, mental health of population rapidly deteriorates. Art such as movies and music is of extremely low quality, people hate every single new movie or video game that comes out. A neofascist party has won elections in Italy, in Czech Republic all socialist parties were eliminated from the parliament: only capitalists rule now -- all social securities are being cancelled, people are getting poorer and poorer and forced to work more and to much higher ages. Ads are everywhere and equate psychological torture. The situation now definitely seems extremely bad.

Late 2023 Report

Yep, the collapse is happening. All previously mentioned issues just deepen, though I stopped watching the news and just avoid the negative info to enjoy the last few years I have on this Earth without much stress. Russian-Ukraine war is still happily ongoing (despite all the predictions that Russia will soon run out of resources lol) AND there is a brand new war in Israel, new immigrants are gonna flood Europe, then USA is probably gonna invade the weakened countries or something. AI is currently breaking the Internet, Google became absolutely unusable which became noticeable even by normies now, it is just flooded by AI articles, news are an endless pile of AI generated nonsense. Technology is yet much worse than before, NOTHING now works without latest consumerist hardware, subscriptions and accounts, I started just buying old paper books and am thinking about abandoning computers altogether. USA culture is here like cancer, TV is littered SOLELY with political propaganda (SUPPORT MUH UKRAINE TAKE COVID VAX SUPPORT UR COUNTRYS ENCONOMMMMMMMMIE FUGHTTTTT RAACEEEEEESSSIIIIIIIIIIIIIISSSSAMMMM) taking turns with capitalist propaganda (ads, literally just people screaming BUY BUY BUY THIS FUCKING SHIT RIGHT NOW, BUY BUY BUYIT BUY IT BUUUUUUUUUY CONSOOOOOOOOOOOME THIIIIS CONSOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOMMMMMMMMMMMMMME). Watching it for 5 minutes literally makes you kill yourself. Hmm what else. NOTHING WORKS lol, you buy something, it is already broken, you pay for repair, they take money and return it unrepaired LMAO :D I am not kidding, it is literally the norm now, my bosses business is sinking due to all machines just breaking. Absolutely unqualified people now do all the jobs lol, there are literally teachers who CANNOT READ OR WRITE correctly, they just use Google to check how everything's spelled (I am NOT kidding, I have this from first hand sources). "Programmers" literally can't program, they just use AI. People are generally braindead, controlled by religions such as economy worship, productivity cult, women fascism (it has been officially declared now that women are physically stronger than man AND also smarter LMAO, every movie is obliged by law to include a scene where this is confirmed). I dunno man, this can't last much longer than a few years.

See Also

• capitalist singularity

Collision Detection

Collision detection is an essential problem e.g. of simulating physics of mechanical bodies in physics engines (but also elsewhere), it tries to detect whether (and also how) geometric shapes overlap. Here we'll be talking about the collision detection in physics engines, but the problem appears in other contexts too (e.g. frustum culling in computer graphics). Collision detection potentially leads to so called collision resolution, a different stage that tries to deal with the detected collision (separate the bodies, update their velocities, make them "bounce off"). Physics engines are mostly divided into 2D and 3D ones so we also normally either talk about 2D or 3D collision detection (3D being, of course, a bit more complex).

There are two main types of collision detection:

• discrete: Detecting collisions only at one point in time (each engine tick or "frame") -- this is easier but can result in detecting the collisions in wrong ways or missing them completely (imagine a fast flying object that in one moment is wholly in front of a wall and at the next instant wholly behind it). Nevertheless this is completely usable, one just has to be careful enough about the extreme cases.
• continuous: Detecting collisions considering the continuous motion of the bodies (still done at discrete ticks but considering the whole motion since the last tick) -- this is more difficult to program and more costly to compute, but also correctly detects collisions even in extreme cases. Sometimes engines perform discrete detection by default and use continuous detection in special cases (e.g. when speeds become very high or in other error-prone situations). Continuous detection can be imagined as a collision detection of a higher dimensional bodies where the added dimension is time -- e.g. detecting collisions of 2D spheres becomes detecting collisions of "tubes" in 3D space. If you don't want to go all the way to implementing continuous collisions, you may consider an in-between solution by detecting collisions in smaller steps (which may also be done only sometimes, e.g. only for high speed bodies or only when an actual discrete collision is detected).

Collision detection is non-trivial because we need to detect not only the presence of the collision but also its parameters which are typically the exact point of collision, collision depth and collision normal -- these are needed for subsequently resolving the collision (typically the bodies will be shifted along the normal by the collision depth to become separated and impulses will be applied at the collision point to update their velocities). We also need to detect general cases, i.e. collisions of whole volumes (imagine e.g. a tiny cuboid inside an arbitrarily rotated bigger cone). This is very hard and/or expensive for some complex shapes such as general 3D triangle meshes (which is why we approximate them with simpler shapes). We also want the detection algorithm to be at least reasonably fast -- for this reason collision detection mostly happens in two phases:

• broad phase: Quickly estimates which bodies MAY collide, usually with bounding volumes (such as spheres or axis aligned bounding boxes) or space indexing and algorithms such as sweep and prune. This phase quickly opts-out of checking collision of objects that definitely CANNOT collide because they're e.g. too far away.
• narrow phase: Applying the precise, expensive collision detection on the potentially colliding pairs of bodies determined in the broad phase. This yields the real collisions.

In many cases it is also important to correctly detect the order of collisions -- it may well happen a body collides not with one but with multiple bodies at the time of collision detection and the computed behavior may vary widely depending on the order in which we consider them. Imagine that body A is colliding with body B and body C at the same time; in real life A may have first collided with B and be deflected so that it would have never hit C, or the other way around, or it might have collided with both. In continuous collision detection we know the order as we also have exact time coordinate of each collision (even though the detection itself is still computed at discrete time steps), i.e. we know which one happened first. With discrete collisions we may use heuristics such as the direction in which the bodies are moving, but this may fail in certain cases (consider e.g. collisions due to rotations).

On shapes: general rule is that mathematically simpler shapes are better for collision detection. Spheres (or circles in 2D) are the best, they are stupidly simple -- a collision of two spheres is simply decided by their distance (i.e. whether the distance of their center points is less that the sum of the radia of the spheres), which also determines the collision depth, and the collision normal is always aligned with the vector pointing from one sphere center to the other. So if you can, use spheres -- it is even worth using multiple spheres to approximate more complex shapes if possible. Capsules ("extruded spheres"), infinite planes, half-planes, infinite cylinders (distance from a line) and axis-aligned boxes are also pretty simple. Cylinders and cuboids with arbitrary rotation are bit harder. Triangle meshes (the shape most commonly used for real-time 3D models) are very difficult but may be approximated e.g. by a convex hull which is manageable (a convex hull is an intersection of a number of half-spaces) -- if we really want to precisely collide full 3D meshes, we may split each one into several convex hulls (but we need to write the non-trivial splitting algorithm of course). Also note that you need to write a detection algorithm for any possible pair of shape types you want to support, so for N supported shapes you'll need N * (N + 1) / 2 detection algorithms.

{ In theory we may in some cases also think about using iterative/numerical methods to find collisions, i.e. starting at some point between the bodies and somehow stepping towards their intersection until we're close enough. Another idea I had was to use signed distance functions for representing static environments, I kind of implemented it in tinyphysicsengine. ~drummyfish }

TODO: some actual algorithms

Collision

Collision, sometimes also conflict, happens when two or more things want to occupy the same spot. This situation usually needs to be addressed somehow; then we talk about collision resolution. In programming there are different types of collisions, for example:

• hash collision: When two items produce the same hash, they will map to the same index in a hash table. Typical solution is to have a list at each table index so that multiple items can fit there.
• collision of bodies in a physics engine: See collision_detection. These collision are resolved by separating the bodies and updating their velocities so that they "bounce off" as in real life.
• request collision: General situation in which multiple clients request access to something that can be used only by one client at a time, e.g. a communication bus. Resolution is usually done by some kind of arbiter who decides, by whatever algorithm, who to grant the access to.
• name collision: When e.g. the same identifier is used in two separate libraries that are included at the same time, the compiler doesn't know which one is intended. This is addressed by namespaces.
• ...

Color

Color (also colour, from celare, "to cover") is the perceived visual quality of light that's associated with its wavelength/frequency (or mixture of several); for example red, blue and yellow are colors. Electromagnetic waves with wavelength from about 380 to 750 nm (about 400 to 790 THz) form the visible spectrum, i.e. waves our eyes can see -- combining such waves with different intensities and letting them fall on the retina of our eyes gives rise to the perception of color in our brain. There is a hugely deep color theory concerned with the concept of color (its definition, description, reproduction, psychological effect etc.). Needless to say colors are extremely important in anything related to visual information such as art, computer graphics, astrophysics, various visualizations or just everyday perception of our world. Color support is sometimes used as the opposite of systems that are extremely limited in the number of colors they can handle, which may be called monochromatic, 1bit (distinguishing only two colors), black&white or grayscale. Color can be seen to be in the same relation to sight as pitch is to hearing.

How many colors are there? The number of colors humans can distinguish is of course individual (color blindness makes people see fewer colors but there are also conditions that make one see more colors) but various sources state we are able to distinguish millions or even over 10 million different colors on average. In computer technology we talk about color depth which says the number of bits we use to represent color -- the more bits, the more colors we can represent. 24 bits are nowadays mostly used to record color (8 bits for each red, green and blue component, so called true color), which allows for 16777216 distinct colors, though even something like 16 bits (65536 colors) is mostly enough for many use cases. Some advanced systems however support many more colors than true color, especially extremely bright and dim ones -- see HDR.

What gives physical objects its color? Most everyday objects get its color from reflecting only specific parts of the white light (usually sunlight), while absorbing the opposite part of the spectrum, i.e. for example a white object reflects all incoming light, a black one absorbs all incoming light (that's why black things get hot in sunlight), a red one reflects the red light and absorbs the rest etc. This is determined by the qualities of the object's surface, such as the structure of its atoms or its microscopic geometry.

TODO

What Is Color?

This is actually a non-trivial question, or rather there exist many varying definitions of it and furthermore it is a matter of subjective experience, perception of colors may differ between people. When asking what color really is, consider the following:

• Are non-primary colors true colors, or just mixtures of the primary colors? Red, green and blue are the three primary colors, the ones we can mix all other colors from. Many will say yes, non-primary colors are colors. But hold on.
• Are non-spectral colors colors or just mixtures of spectral colors? Spectral colors are the colors with a single wavelength (e.g. red, orange or violet), other colors (like pink) are just mixtures of these. Again, probably yes.
• Is saturation part of color, or a separate attribute? I.e. are e.g. green and greenish gray different colors, or same colors with different saturation? Now it depends.
• Is black a color, or rather a lack of a color? E.g. in computers it is usually treated just as another color, but real world black is really the absence of any light.
• Is white a color? If we are using a subtractive color model, the argument is the same as for black (white paper is really just lack of any color on it).
• Is e.g. gold a color? Or just yellow with a lot of specular reflection? In real world many things may be called to have a gold color, but in computer graphics we would likely separate the color from the light reflective attribute (such as metalicity).
• Is transparent a color?
• Is intensity part of color (especially in context of e.g. HDR)? For example we might say both Sun and paper are white, but still Sun's color is much "stronger" -- is it therefore a "whiter white" than that of a paper?
• Are colors not perceivable by average human colors? Many animals see colors we can't see (e.g. those in infrared spectrum), but there are also rare cases of humans (so called tetrachromats) who see many more colors than usual thanks to a mutation.
• Are impossible colors colors? Interestingly there exist colors perceivable by average humans which however cannot naturally be seen due to "physics" -- they can however be seen with "eye hacks". Do we count these too?
• ...

Combinatorics

Combinatorics is an area of math that's basically concerned with counting possibilities. As such it is very related to probability theory (as probability is typically defined in terms of ratios of possible outcomes). It explores things such as permutations and combinations, i.e. question such as how many ways are there to order N objects or how many ways are there to choose k objects from a set of N objects.

The two basic quantities we define in combinatorics are permutations and combinations.

Permutation (in a simple form) of a set of objects (lets say A, B and C) is one possible ordering of such set (i.e. ABC, ACB, BAC etc.). I.e. here by permutation of a number n, which we'll write as P(n), we mean the number of possible orderings of a set of size n. So for example P(1) = 1 because there is only one way to order a set containing one item. Similarly P(3) = 6 because there are six ways to order a set of three objects (ABC, ACB, BAC, BCA, CAB, CBA). P(n) is computed very simply, it is factorial of n, i.e. P(n) = n!.

Combination (without repetition) of a set of objects says in how many ways we can select given number of objects from that set (e.g. if there are 4 shirts in a drawer and we want to choose 2, how many possibilities are there?). I.e. given a set of certain size a combination tells us the number of possible subsets of certain size. I.e. there are two parameters of a combination, one is the size of the set, n, and the other is the number of items (the size of the subset) we want to select from that set, k. This is written as nCk, C(n,k) or

 / n \
|     |
 \ k /

A combination is computed as C(n,k) = n! / (k! * (n - k)!). E.g. having a drawer with 4 shirts (A, B, C and D) and wanting to select 2 gives us C(4,2) = 4! / (2! * (4 - 2)!) = 6 possibilities (AB, AC, AD, BC, BD, CD).

Furthermore we can define combinations with repetitions in which we allow ourselves to select the same item from the set more than once (note that the selection order still doesn't matter). I.e. while combinations without repetition give us the number of possible subsets, a combinations WITH repetitions gives us the number of possible multisubsets of a given set. Combinations with repetition is computed as Cr(n,k) = C(n + k - 1,k). E.g. having a drawer with 4 shirts and wanting to select 2 WITH the possibility to choose one shirt multiple times gives us Cr(4,2) = C(5,2) = 5! / (2! * (5 - 2)!) = 10 possibilities (AA, AB, AC, AD, BB, BC, BD, CC, CD, DD).

Furthermore if we take combinations and say that order matters, we get generalized permutations that also take two parameters, n and k, and there are two kinds: without and with repetitions. I.e. permutations without repetitions tell us in how many ways we can choose k items from n items when ORDER MATTERS, and is computed as P(n,k) = n!/(n - k)! (e.g. P(4,2) = 4!/(4 - 2)! = 12, AB, AC, AD, BA, BC, BD, CA, CB, CD, DA, DB, DC). Permutations with repetitions tell us the same thing but we are allowed to select the same thing multiple times, it is computed as Pr(n,k) = n^k (e.g. P(4,2) = 4^2 = 16, AA, AB, AC, AD, BA, BB, BC, BD, CA, CB, CC, CD, DA, DB, DC, DD).

To sum up:

Here is an example of applying all the measures to a three item set ABC (note that selecting nothing from a set counts as 1 possibility, NOT 0):

Comment

Comment is part of computer code that doesn't affect how the code is interpreted by the computer and is intended to hold information for humans that read the code (even though comments can sometimes contain additional information for computers such as metadata and autodocumentation information). There are comments in basically all programming languages, they usually start with //, #, /* and similar symbols, sometimes parts of code that don't fit the language syntax are ignored and as such can be used for comments.

Even though you should write nice, self documenting code, you should comment you source code as well. General tips on commenting:

• ALWAYS put a global file comment at the top of a file to make it self-contained. It should include:
  • Description of what the file actually does. This is extremely important for readability, documentation and quick orientation. If a new programmer comes looking for a specific part of the code, he may waste hours on searching the wrong files just because the idiotic author couldn't be bothered to include fucking three sentences at the start of the file. Modern program just don't fucking do this anymore, this is just shit.
  • License/waiver, either full text or link. Even if your repo contains a global license (which it should), it's good for the file to carry the license because the file may just be copy pasted on its own into some other project and then it will appear as having no license.
  • Name/nick of the author(s) and roughly the date of creation (year is enough). This firstly helps legally assess copyright (who and for how long holds the copyright) and secondly helps others contact the author in case of encountering something weird in the code.
• Comment specific blocks of code with keywords -- this will help searching the code with tools like grep. E.g. in game's code add comment // player: shoot, fire to the part of code that handles player's shooting so that someone searching for any one of these two words will be directed here.
• Functions (maybe with some exceptions like trivial one-liners) should come with a comment documenting:
  • Behavior of the function, what it does and also how it does that (Is the function slow? Is it safe? Does it perform checks of arguments? Does it have side effects? How are errors handled? ...).
  • Meaning of all arguments and if needed their possible values.
  • Return value meaning.
• You may decide to use comment format of some autodoc system such as doxygen -- it costs nothing and helps firstly unify the style of your comments and secondly, obviously, generate automatic documentation of your code, as well as possibly automatically process it in other ways.
• TODO: moar

Communism

Communism (from communis -- common, shared) is a very wide term which most generally stands for the idea that sharing and equality should be the basic values and principles of a society; as such it is a leftist idea which falls under socialism (i.e. basically focusing on people at large). There are very many branches, theories, political ideologies and schools of thought somewhat based on communism, for example Marxism, Leninism, anarcho communism, primitive communism, Christian communism, Buddhist communism etc. -- of course, some of these are good while others are evil and only abuse the word communism as a kind of brand (as also happens e.g. with anarchism). Sadly after the disastrous failure of the violent pseudocommunist revolutions of the 20th century, most people came to equate the word communism with oppressive militant regimes, however we have to stress that communism is NOT equal to USSR, Marxism-Lenninism, Stalinism or any other form of pseudocommunism, on the contrary, such regimes were rather hierarchical, violent and pseudocommunist, often downright fascist. We ourselves embrace true communism and base our LRS and less retarded society on ideas of unconditional sharing. Yes, large communist societies have existed and worked, for example the Inca empire worked without money and provided FREE food, clothes, houses, health care, education and other products of collective work to everyone, according to his needs. Many other communities also work on more or less communist principles, see e.g. Jewish kibbutz, Sikhist langar, free software, or even just most families for that matter. The color red is usually associated with communism and the "hammer and sickle" (U+262D) is taken as its symbol, though that's mostly associated with the evil communist regimes and so its usage is to be greatly considered.

Common ideas usually associated with communism are (please keep in mind that this may differ depending on the specific flavor of communism):

• Ending capitalism and similar rightist oppressive hierarchical systems which are the polar opposite of communism and are incompatible with it. Along with these also things like consumerism, worker exploitation, crime and poverty will disappear.
• Abolishment of private property, establishing common ownership, for example a factory shouldn't have a single owner who makes profit off of it, it should rather be collectively managed by those who work in the factory and they should collectively share what they make there.
• Sharing and collaboration as opposed to competition.
• Equality, seizing of division of people into social classes (such as workers, bourgeoisie, rich, poor, aristocracy, ...).
• Eventual abolishment of state, as again in a good society that benefits people there shouldn't be any crime, theft, abuse of workers etc. However some "communists" see state and its control of economy as a necessary intermediate step towards this goal.
• Abolishment of money as that is a means of dividing people into classes (rich and poor), means of abuse (wage slavery) and a tool of systems such as capitalism. In a good society money is unnecessary, everyone gets what he needs.
• Sometimes revolution (and even war, temporary dictatorship etc.) is seen by some "communists" as a necessary way of achieving a change, however many others oppose this as revolution means violence, dominating man by another man (inequality) etc. -- peaceful voluntary evolutionary approach is also an option of achieving communism.
• Focus on workers and common people.
• Intellectual endeavor and idealism -- many communists are intellectuals, scientifically examining society and seeking models of an ideal society, a "utopia" as opposed to accepting life in a dystopia.
• ...

TODO

See Also

• less retarded society
• socialism
• capitalism

Competition

Competition is a situation of conflict in which several entities try to overpower or otherwise win over each other. It is the opposite of collaboration. Competition is connected to pursuing self interest.

Competition is the absolute root cause of most evil in society. Society must never be based on competition. Unfortunately our society has decided to do the exact opposite with capitalism, the glorification of competition -- this will very likely lead to the destructing of our society, possibly even to the destruction of all life.

Competition is to society what a drug is to an individual: competition makes a situation become better quickly and start achieving technological "progress" but for the price of things going downwards from then on, competition quickly degenerates and kills other values in society such as altruism and morality; society that decides to make unnaturally fast "progress" and base itself on competition is equivalent to someone deciding to take steroids to grow muscles quickly -- corporations that arise in technologically advanced society take over the world just like muscle cancer that grows from taking steroids. A little bit of competition can be helpful in small doses just as painkillers can on occasion help lower suffering of an individual, but one has to be extremely careful to not take too many of them... even smoking a joint from time to time can have a positive effect, however with capitalism our society has become someone who has started to take heroin and only live for that drug alone, take as much of it as he can. Invention of bullshit jobs just to keep competition running, extreme growing hostility of people, productivity cults, overworking, wage slavery, extreme waste that's destroying our environment, all of these are signs our society is dying from overdose, living from day to day, trying to get a few bucks for the next dose of its drug.

Is all competition bad? Competition is not bad as a concept, it may for example be used in genetic programming to evolve good computer programs. People also have a NEED for at least a bit of competition as this need was necessary to survive in the past -- this need has to be satisfied, so we create artificial, mostly harmless competition e.g. with games and sports. This kind of competition is not so bad as long as we are aware of the dangers of overapplying it. What IS bad is making competition the basis of a society, in a good society people must never compete for basic needs such as food, shelter or health care. Furthermore after sufficient technological progress, competition is no longer just a bad basis for society, it becomes a fatal one because society gains means for complete annihilation of all life such as nuclear weapons or factories poisoning our environment that in the heat of competition will sooner or later destroy the society. I.e. in a technologically advanced society it is necessary to give up competition so as to prevent own destruction.

Why is competition so prevalent if it is so bad? Because it is natural and it has been with us since we as life arised. It is extremely hard to let go of such a basic instinct but it has to be done not only because competition has become obsolete and is now only artificially sustaining suffering without bringing in any benefits (we, humans, have basically already won the evolution), but because, as has been said, sustaining competition is now fatal.

How to achieve letting go of competition in society? The only way is a voluntary choice achieved through our intellect, i.e. through education. Competition is something we naturally want to do, but we can rationally decide not to do it once we see and understand it is bad -- such behavior is already occurring, for example if we know someone is infected with a sexually transmitting disease, we rationally overcome the strong natural instinct to have sex with him.

Compression

Compression means encoding data (such as images or texts) in a different way so that the data takes less space (memory) while keeping all the important information, or, in plain terms, it usually means "making files smaller". Compression is pretty important so that we can utilize memory or bandwidth well -- without it our hard drives would be able to store just a handful of videos, internet would be slow as hell due to the gigantic amount of transferred data and our RAM wouldn't suffice for things we normally do. There are many algorithms for compressing various kinds of data, differing by their complexity, performance, efficiency of compression etc. The reverse process to compression (getting the original data back from the compressed data) is called decompression. The ratio of the compressed data size to the original data size is called compression ratio (the lower, the better). The science of data compression is truly huge and complicated AF, here we'll just mention some very basics. Also watch out: compression algorithms are often a patent mine field.

{ I've now written a tiny LRS compression library/utility called shitpress, check it out at https://codeberg.org/drummyfish/shitpress. It's fewer than 200 LOC, so simple it can nicely serve educational purposes. The principle is simple, kind of a dictionary method, where the dictionary is simply the latest output 64 characters; if we find a long word that occurred recently, we simply reference it with mere 2 bytes. It works relatively well for most data! ~drummyfish }

{ There is a cool compressing competition known as Hutter Prize that offers 500000 pounds to anyone who can break the current record for compressing Wikipedia. Currently the record is at compressing 1GB down to 115MB. See http://prize.hutter1.net for more. ~drummyfish }

{ LMAO retard patents are being granted on impossible compression algorithms, see e.g. http://gailly.net/05533051.html. See also Sloot Digital Coding System, a miraculous compression algorithm that "could store a whole movie in 8 KB" lol. ~drummyfish }

Let's keep in mind compression is not applied just to files on hard drives, it can also be used e.g. in RAM to utilize it more efficiently.

Why don't we compress everything? Firstly because compressed data is slow to work with, it requires significant CPU time to compress and decompress data, it's a kind of a space-time tradeoff (we gain more storage space for the cost of CPU time). Secondly compressed data is more prone to corruption because redundant information (which can help restoring corrupted data) is removed from it -- in fact we sometimes purposefully do the opposite of compression and make our data bigger to protect it from corruption (see e.g. error correcting codes, RAID etc.). And last but not least, many data can hardly be compressed or are so small it's not even worth it.

The basic division of compression methods is to:

• lossless: No information contained in the original data will be lost in the compressed data, i.e. the original file can be restored in its entirety from the compressed file.
• lossy: Some information contained in the original data is lost during compression, i.e. for example a compressed image will be of slightly worse quality. This usually allows for much greater compression. Lossy compressors usually also additionally apply lossless compression as well.

Furthermore we may divide compression e.g. to offline (compresses a whole file, may take long) and streaming (compressing a stream of input data on-the-go and in real-time), by the type of input data (binary, text, audio, ...), basic principle (RLE, dictionary, "AI", ...) etc.

The following is an example of how well different types of compression work for an image (screenshot of main page of Wikimedia Commons, 1280x800):

{ Though the website screenshot contained also real life photos, it still contained a lot of constant color areas which can be compressed very well, hence quite good compression ratios here. A general photo won't be compressed as much. ~drummyfish }

Mathematically there cannot exist a lossless compression algorithm that would always reduce the size of any input data -- if it existed, we could just repeatedly apply it and compress ANY data to zero bytes. And not only that -- every lossless compression will inevitably enlarge some input files. This is also mathematically given -- we can see compression as simply mapping input binary sequences to output (compressed) binary sequences, while such mapping has to be one-to-one (bijective); it can be simply shown that if we make any such mapping that reduces the size of some input (maps a longer sequence to a shorter one, i.e. compresses it), we will also have to map some short code to a longer one. However we can make it so that our compression algorithm enlarges a file at most by 1 bit: we can say that the first bit in the compressed data says whether the following data is compressed or not; if our algorithm fails to reduce the size of the input, it simply sets the bit to says so and leaves the original file uncompressed (in practice many algorithms don't do this though as they try to work as streaming filters, without random access to data, which would be needed here).

Dude, how does compression really work tho? The basic principle of lossless compression is removing redundancy (correlations in the data), i.e. that which is explicitly stored in the original data but doesn't really have to be there because it can be reasoned out from the remaining data. This is why a completely random noise can't be compressed -- there is no correlated data in it, nothing to reason out from other parts of the data. However human language for example contains many redundancies. Imagine we are trying to compress English text and have a word such as "computer" on the input -- we can really just shorten it to "computr" and it's still pretty clear the word is meant to be "computer" as there is no other similar English word (we also see that compression algorithm is always specific to the type of data we expect on the input -- we have to know what nature of the input data we can expect). Another way to remove redundancy is to e.g. convert a string such as "HELLOHELLOHELLOHELLOHELLO" to "5xHELLO". Lossy compression on the other hand tries to decide what information is of low importance and can be dropped -- for example a lossy compression of text might discard information about case (upper vs lower case) to be able to store each character with fewer bits; an all caps text is still readable, though less comfortably.

OK, but how much can we really compress? Well, as stated above, there can never be anything such as a universal uber compression algorithm that just makes any input file super small -- everything really depends on the nature of the data we are trying to compress. The more we know about the nature of the input data, the more we can compress, so a general compression program will compress only a little, while an image-specialized compression program will compress better (but will only work with images). As an extreme example, consider that in theory we can make e.g. an algorithm that compresses one specific 100GB video to 1 bit (we just define that a bit "1" decompresses to this specific video), but it will only work for that one single video, not for video in general -- i.e. we made an extremely specialized compression and got an extremely good compression ratio, however due to such extreme specialization we can almost never use it. As said, we just cannot compress completely random data at all (as we don't know anything about the nature of such data). On the other hand data with a lot of redundancy, such as video, can be compressed A LOT. Similarly video compression algorithms used in practice work only for videos that appear in the real world which exhibit certain patterns, such as two consecutive frames being very similar -- if we try to compress e.g. static (white noise), video codecs just shit themselves trying to compress it (look up e.g. videos of confetti and see how blocky they get). All in all, some compression benchmarks can be found e.g. at https://web.archive.org/web/20110203152015/http://www.maximumcompression.com/index.html -- the following are mentioned types of data and their best measured compression ratios: English text 0.12, image (lossy) 0.76, executable 0.24.

Methods

The following is an overview of some most common compression techniques.

Lossless

RLE (run length encoding) is a simple method that stores repeated sequences just as one element of the sequence and number of repetitions, i.e. for example "abcabcabc" as "3abc".

Entropy coding is another common technique which counts the frequencies (probabilities) of symbols on the input and then assigns the shortest codes to the most frequent symbols, leaving longer codes to the less frequent. The most common such codings are Huffman coding and Arithmetic coding.

Dictionary (substitutional) methods try to construct a dictionary of relatively long symbols appearing in the input and then only store short references to these symbols. The format may for example choose to first store the dictionary and then the actual data with pointers to this dictionary, or it may just store the data in which pointers are stored to previously appearing sequences.

Predictor compression is based on making a predictor that tries to guess following data from previous values (which can be done e.g. in case of pictures, sound or text) and then only storing the difference against such a predicted result. If the predictor is good, we may only store the small amount of the errors it makes.

A famous family of dictionary compression algorithms are Lempel-Ziv (LZ) algorithms -- these two guys first proposed LZ77 in (1977, sliding window) and LZ78 (explicitly stored dictionary, 1978). These were a basis for improved/remix algorithms, most notably LZW (1984, Welch). Additionally these algorithms are used and combined in other algorithms, most notably gif and DEFLATE (used e.g. in gzip and png).

An approach similar to the predictor may be trying to find some general mathematical model of the data and then just find and store the right parameters of the model. This may for example mean vectorizing a bitmap image, i.e. finding geometrical shapes in an image composed of pixels and then only storing the parameters of the shapes -- of course this may not be 100% accurate, but again if we want to preserve the data accurately, we may additionally also store the small amount of errors the model makes. Similar approach is used in vocoders used in cellphones that try to mathematically model human speech (however here the compression is lossy), or in fractal compression of images. A nice feature we gain here is the ability to actually "increase the resolution" (or rather generate detail) of the original data -- once we fit a model onto our data, we may use it to tell us values that are not actually present in the data (i.e. we get a fancy interpolation/extrapolation).

Another property of data to exploit may be its sparsity -- if for example we have a huge image that's prevalently white, we may say white is the implicit color and we only somehow store the pixels of other colors.

Some more wild techniques may include genetic programming that tries to evolve a small program that reproduces the input data, or using "AI" in whatever way to compress the data (in fact compression is an essential part of many neural networks as it forces the network to "understand", make sense of the data -- many neural networks therefore internally compress and decompress the data so as to filter out the unimportant information).

Note that many of these methods may be combined or applied repeatedly as long as we are getting smaller results.

Furthermore also take a look at procedural generation, a related technique that allows to embed a practically infinite amount of content with only quite small amount of code.

Lossy

In lossy compression we generally try to limit information that is not very important and/or to which we aren't very sensitive, typically by dropping precision by quantization, i.e. basically lowering the number of bits we use to store the "not so important" information -- in some cases we may just drop some information altogether (decrease precision to zero). Furthermore we finally also apply lossless compression to make the result even smaller.

For images we usually exploit the fact that human sight is less sensitive to certain visual information, such as specific frequencies, colors, brightness etc. Common methods used here are:

• Convert image from RGB to YUV, leave the Y channel (brightness) as is and reduce resolution of the U an V (color) channels. This works because human eye is less sensitive to color than brightness.
• Convert the image to frequency domain (e.g. with DCT or some wavelet transform) and quantize (allocate fewer bits to) higher frequencies. This exploits the fact that human eye is less sensitive to higher frequencies. This is the basis of e.g. jpeg.
• Reduce the number of possible colors -- traditional RGB uses 8 bits for each R, G and B component and so each pixel takes 3 bytes, which allows for about 6 million colors. However using just 2 bytes (65 thousand colors) many times suffices and saves 1/3rd of the size -- see RGB565. We may also utilize an image-specific palette and save the image in indexed mode, i.e. compute a palette of let's say 256 most common colors in the image, then encode the image as the palette plus pixels, of which each will only take one byte! This saves almost 2/3rds of the size. The drop of quality can further be made less noticeable with dithering.
• Reduce resolution -- plain simple. However this can be made smarter by e.g. trying to detect areas with few details and only reducing the resolution there.

In video compression we may reuse the ideas from image compression and further employ exploiting temporal redundancy, i.e. the fact that consecutive video frames look similar, so we may only encode some kind of delta (change) against the previous (or even next) frame. The most common way is to fully record only one key frame in some time span (so called I-frame, further compressed with image compression methods), then divide it to small blocks and estimate the movement of those blocks so that they approximately make up the following frames -- we then record only the motion vectors of the blocks. This is why videos look "blocky". In the past interlacing was also used -- only half of each frame was recorded, every other row was dropped; when playing, the frame was interlaced with the previous frame.

In audio we usually straight remove frequencies that humans can't hear (usually said to be above 20 kHz), for this we again convert the audio from spatial to frequency domain (using e.g. Fourier transform). Furthermore it is very inefficient to store sample values directly -- we rather use so called differential PCM, a lossless compression that e.g. stores each sample as a difference against the previous sample (which is usually small and doesn't use up many bits). This can be improved by a predictor, which tries to predict the next values from previous values and then we only save the difference against this prediction. Joint stereo coding exploits the fact that human hearing is not so sensitive to the direction of the sound and so e.g. instead of recording both left and right stereo channels in full quality rather records the sum of both and a ratio between them (which can get away with fewer bits). Psychoacoustics studies how humans perceive sound, for example so called masking: certain frequencies may for example mask nearby (both in frequency and time) frequencies (make them unhearable for humans) so we can drop them. See also vocoders.

TODO: LZW, DEFLATE etc.

Compression Programs/Utils/Standards

Here is a list of some common compression programs/utilities/standards/formats/etc:

Code Example

Let's write a simple lossless compression utility in C. It will work on binary files and we will use the simplest RLE method, i.e. our program will just shorten continuous sequences of repeating bytes to a short sequence saying "repeat this byte N times". Note that this is very primitive (a small improvement might be actually done by looking for sequences of longer words, not just single bytes), but it somewhat works for many files and demonstrates the basics.

The compression will work like this:

• We will choose some random, hopefully not very frequent byte value, as our special "marker value". Let's say this will be the value 0xF3.
• We will read the input file and whenever we encounter a sequence of 4 or more same bytes in a row, we will output these 3 bytes:
  • the marker value
  • byte whose values is the length of the sequence minus 4
  • the byte to repeat
• If the marker value is encountered in input, we output 2 bytes:
  • the marker value
  • value 0xFF (which we won't be able to use for the length of the sequence)
• Otherwise we just output the byte we read from the input.

Decompression is then quite simple -- we simply output what we read, unless we read the marker value; in such case we look whether the following value is 0xFF (then we output the marker value), else we know we have to repeat the next character this many times plus 4.

For example given input bytes

0x11 0x00 0x00 0xAA 0xBB 0xBB 0xBB 0xBB 0xBB 0xBB 0x10 0xF3 0x00
                    \___________________________/      \__/
                       long repeating sequence        marker!

Our algorithm will output a compressed sequence

0x11 0x00 0x00 0xAA 0xF3 0x02 0xBB 0x10 0xF3 0xFF 0x00
                    \____________/      \_______/
                    compressed seq.   encoded marker

Notice that, as stated above in the article, there inevitably exists a "danger" of actually enlarging some files. This can happen if the file contains no sequences that we can compress and at the same time there appear the marker values which actually get expanded (from 1 byte to 2).

The nice property of our algorithm is that both compression and decompression can be streaming, i.e. both can be done in a single pass as a filter, without having to load the file into memory or randomly access bytes in files. Also the memory complexity of this algorithm is constant (RAM usage will be the same for any size of the file) and time complexity is linear (i.e. the algorithm is "very fast").

Here is the actual code of this utility (it reads from stdin and outputs to stdout, a flag -x is used to set decompression mode, otherwise it is compressing):

#include <stdio.h>

#define SPECIAL_VAL 0xf3 // random value, hopefully not very common

void compress(void)
{
  unsigned char prevChar = 0;
  unsigned int  seqLen = 0;
  unsigned char end = 0;

  while (!end)
  {
    int c = getchar();

    if (c == EOF)
      end = 1;

    if (c != prevChar || c == SPECIAL_VAL || end || seqLen > 200)
    { // dump the sequence
      if (seqLen > 3)
        printf("%c%c%c",SPECIAL_VAL,seqLen - 4,prevChar);
      else
        for (int i = 0; i < seqLen; ++i)
          putchar(prevChar);

      seqLen = 0;
    }

    prevChar = c;
    seqLen++;

    if (c == SPECIAL_VAL)
    {
      // this is how we encode the special value appearing in the input
      putchar(SPECIAL_VAL);
      putchar(0xff);
      seqLen = 0;
    }
  }
}

void decompress(void)
{
  unsigned char end = 0;

  while (1)
  {
    int c = getchar();

    if (c == EOF)
      break;

    if (c == SPECIAL_VAL)
    {
      unsigned int seqLen = getchar();

      if (seqLen == 0xff)
        putchar(SPECIAL_VAL);
      else
      {
        c = getchar();

        for (int i = 0; i < seqLen + 4; ++i)
          putchar(c);
      }
    }
    else
      putchar(c);
  }
}

int main(int argc, char **argv)
{
  if (argc > 1 && argv[1][0] == '-' && argv[1][1] == 'x' && argv[1][2] == 0)
    decompress();
  else
    compress();

  return 0;
}

How well does this perform? If we try to let the utility compress its own source code, we get to 1242 bytes from the original 1344, which is not so great -- the compression ratio is only about 92% here. We can see why: the only repeating bytes in the source code are the space characters used for indentation -- this is the only thing our primitive algorithm manages to compress. However if we let the program compress its own binary version, we get much better results (at least on the computer this was tested on): the original binary has 16768 bytes while the compressed one has 5084 bytes, which is an EXCELLENT compression ratio of 30%! Yay :-)

See Also

• procedural generation
• minification

Computer Science

Computer science, abbreviated as "compsci", is (surprise-surprise) a science studying computers. The term is pretty wide, a lot of it covers very formal and theoretical areas that neighbor and overlap with mathematics, such as formal languages, cryptography and machine learning, but also more practical/applied and "softer" disciplines such as software_engineering, programming hardware, computer networks or even user interface design. This science deals with such things as algorithms, data structures, artificial intelligence and information theory. The field has become quite popular and rapidly growing after the coming of the 21st century computer/Internet revolution and it has also become quite spoiled and abused by its sudden lucrativity.

Overview

Notable fields of computer science include:

• artificial intelligence
• computer graphics
• databases
• hardware design
• networking
• security and cryptography
• software engineering
• theoretical computer science
• user interface
• smaller field or subfields such as operating systems, compiler design, formal verification, speech recognition etc.

Computer science also figures in interdisciplinary endeavors such as bioinformatics and robotics.

In the industry there have arisen fields of art and study that probably shouldn't be included in computer science itself, but are very close to it. These may include e.g. web design (well, let's include it for the sake of completeness), game design, system administration etc.

Computer

The word computer can be defined in many ways and can also take many different meanings; a somewhat common definition may be this: computer is a machine that automatically performs mathematical computations. We can also see it as a machine for processing information or, very generally, as any tool that helps computation, in which case one's fingers or even a mathematical formula itself can be considered a computer. Here we are of course mostly concerned with electronic digital computers.

We can divide computers based on many attributes, e.g.:

• by continuous or discrete representation of data: digital vs analog
• by hardware technology: electronic ("lightning in sand"), mechanical, quantum, biological etc.
• by purpose: special purpose vs general purpose, personal, server, embedded, supercomputers, gaming computer etc.
• by programmability: non-programmable, partially or fully programmable
• by the theoretical model of computation it is based on: Turing machine, lambda calculus etc.
• by computational power: how difficult problems the computer is able to solve, i.e. where in the Chomsky hierarchy it stands (typically we want Turing complete computers)
• by other criteria: price, reliability, durability etc.

Computers are theoretically studied by computer science. The kind of computer we normally talk about consists of two main parts:

• hardware: physical parts
• software: programs executed by the hardware, made by programmers

The power of computers is limited, Alan Turing mathematically proved that there exist problems that can never be completely solved by any algorithm, i.e. there are problems a computer (including our brain) will never be able to solve (even if solution exists). This is related to the fact that the power of mathematics itself is limited in a similar way (see Godel's theorems). Turing also invented the theoretical model of a computer called the Turing machine. Besides the mentioned theoretical limitation, many solvable problems may take too long to compute, at least with computers we currently know (see computational complexity and P vs NP).

Typical Computer

Computers we normally talk about in daily conversations are electronic digital mostly personal computers such as desktops and laptops, possibly also cell phones, tablets etc.

Such a computer consists of some kind of case (chassis), internal hardware plus peripheral devices that serve for input and output -- these are for example a keyboard and mouse (input devices), a monitor (output device) or harddisk (input/output device). The internals of the computer normally include:

• motherboard: The main electronic circuit of the computer into which other components are plugged and which creates the network and interfaces that interconnect them (a chipset). It contains slots for expansion cards as well as connectors for external devices, e.g. USB. In a small memory on the board there is the most basic software (firmaware), such as BIOS, to e.g. enable installation of other software. The board also carries the clock generator for synchronization of all hardware, heat sensors etc.
• CPU (central processing unit): Core of the computer, the chip plugged into motherboard that performs general calculations and which runs programs, i.e. software.
• RAM/working memory/main memory: Lower capacity volatile (temporary, erased when powered off) working memory of the computer, plugged into motherboard. It is used as a "pen and paper" by the CPU when performing calculations.
• disk: Non-volatile (persisting when powered off) large capacity memory for storing files and other data, connected to the motherboard via some kind of bus. Different types of disks exist, most commonly hard disks and SSDs.
• expansion cards (GPU, sound card, network card, ...): Additional hardware cards plugged into motherboard for either enabling or accelerating specific functionality (e.g. GPU for graphics etc.).
• PSU (power supply unit): Converts the input electrical power from the plug to the electrical power needed by the computer.
• other things like fans for cooling, batteries in laptops etc.

Notable Computers

Here is a list of notable computers.

{ Some nice list of ancient computers is here: https://xnumber.com/xnumber/frame_malbum.htm. ~drummyfish }

TODO: mnt reform 2, pinephone, NeXT, ti-89, quantum?, wii?

Comun

Comun is a beautiful, greatly minimalist programming language made by drummyfish, based on his ideals of good, selfless technology known as less retarded software (LRS), of which it is now considered the official programming language. In the future it should gradually replace C as the preferred LRS language. The language has been inspired mainly by Forth, but also C, brainfuck and other ones. Though already usable, it is still in quite early stages of development and work in progress; currently there is a suckless implementation of comun in C and a number of supplemental materials such as a specification, tutorial and some example programs. The project repository is currently at https://codeberg.org/drummyfish/comun. The aim now is to make a self hosted implementation, i.e. write comun in comun. Though very young, comun is probably already the best programming language ever conceived.

The language is intended to be the foundation of a completely new, non-capitalist computer technology built from the ground up, which should culminate in the creation of the LRS much desired public domain computer. This technology is derived from the model of an ideal society and as such will aim for completely different goals (such as helping all living beings as much as possible without enslaving them) and values; this makes comun astronomically different in philosophy and design of the shitty, toxic capitalist joke languages such as C++ and Rust which pursue fascism, enslavement of humans to the productivity cult etc.

A quick sum up is following: comun is minimalist, low level with minimum abstraction, portable, imperative and stack-based, using reverse Polish notation. It can be both compiled and interpreted. There are only primitive integer data types (native integer size by default with possibility to specify exact width where necessary, signed/unsigned interpretation is left to the programmer) and optional pointers that can be used as variables, for managing multiple stacks, creating arrays etc. Its specification can fit on a sheet of paper and is completely public domain under CC0 (as is its current implementation). It has no standard library. There are no English keywords; commands are rather very short (mostly 1 to three symbols) math-like symbols. Source code only allows ASCII symbols (no unicode). There is an optional preprocessor that uses comun itself (i.e. it doesn't use any extra language). Functions and recursion are supported. Many features of the language are optional and never burden the programmer if he doesn't use them. Simplified versions of the language (minicomun and microcomun) are also specified.

Examples

Here is a very short showcase of comun code, demonstrating some common functions:

max: <' ? >< . ^ .      # takes maximum of two values

max3: max max .         # takes maximum of three values

# recursive factorial
factR:
  ?'
    $0 -- factR *
  ;
    ^ 1
  .
.

# iterative factorial
factI:
  $0 --

  @'
    >< $1 * ><
    --
  .
  ^
.

The following is a quine in comun:

0 46 32 34 S 34 32 58 83 S --> S: "0 46 32 34 S 34 32 58 83 S --> " .

The following code translates brainfuck to comun:

0 "$>0 " -->

@@
  <? ?
    <- 

    $0 "+" = $1 "-" = | ?
      $0 -> $0 -> " " ->
    .

    $0 "<" = $1 ">" = | ?
      "$" -> $0 -> "0" -> " " ->
    .

    $0 "." = ?
      0 "->' " -->
    .

    $0 "," = ?
      0 "$<0 <- " -->
    .

    $0 91 = ? # left bracket
      0 "@' " -->
    .

    $0 93 = ? # right bracker
      0 ". " -->
    .

    ^
  ;
    !@
  .
.

TODO: more, code examples, compare the above with C, ...

Consumerism

CONSUME YOU FUCKING IDIOTIC BITCH YOU DON'T EVEN HAVE THE LATEST AI RAYTRACING ENCRYPTION GPUUUUUUUU 1080K WIRELESS GAYMING MONITOR WITH BLOCKCHAIN BUY IT BUYYYYYY IT YOU IDIOT. --capitalism

Consumerism (also consoomerism) is a built-in "feature" of capitalism that says EVERYTHING HAS TO BE CONSUMED on a regular short-term basis so as to keep CONSTANT P.R.O.G.R.E.S.S.^TM(c)/PERSONAL DEVELOPMENT GROWTHP/PRODUCTIVITY^tm^tm^tm^tm, even things that in theory could last decades to generations such as houses, cars, computers, software, even just INFORMATION etc. Yes, we could make nice durable machines that wouldn't break and would serve a man for generations, we could write a finished operating system that would work and be useful, but that wouldn't be good for the seller if he only sold the thing once in a hundred years, would it? ALERT ALERT: BAD FOR CAPITAL. He wants to sell the thing and then PROFIT from it every day as he lies on the beach being fucked by 10 billion whore lolitas, so the thing has to break regularly and just demand to be replaced once in a year or so (see planned obsolescence) -- haha, actually you know what would be best? WHAT IF :D WHAT IF WE RAPE THE CUSTOMER EVERY DAI, LMAOOOOOO What IF THERE ARE NO PRODUCTS BUT PRODUCT ARE ACTUALLY JUST SERVICES :DDDDD LMAO THEN NO ONE CAN OWN ANYTHING, YOUR CAR AND YOUR TOOTHBRUSH IS JUST A SUBSCRIPTION LOOOOL, it just stops running if you stop paying. Why do this? Because in capitalism economy MUSTN'T STOP ULTRA EXPONENTIALLY EXPLODING EVERY TRILLISECOND and EVERYONE MUST HAVE 10000 BILLION JOBS ELSE THE POOR WORKER LOSES THE MEANING OF LIFE like the neanderthals who lacked the good capitalist overlords that assure the basic human need of ultraexponential personal growth and all killed themselves, also the same with stupid lazy animals. So capitalism has to constantly GROOOOOOOOOOOOOOOOOOOOOOOOOOOWWWWWW FOR ANY COST JUST GROW GROW GROW GROW GROW GROOOOOOOOOOOOOOOOOWWWWWWWWWWWW -- is it good? No, but it's called PWOGWEESSS so people LOVE IT, people will shit themselves and suffocate their mouths with their shit just to hear the word PWOGWEEEEES (or alternatively UPDATE or ANTIPEDOPHILE PROTECTION), if a politician says PWEGWESS enough times in his speech the crowd will just start sucking his dick on the stage and he will win the elections by 130% majority. LMAOOOOO WHAT IF we make updates a kind of consumerist product, LOL WHAT IF one group of people build houses one day and the other group destroys them the other day and so on so on, it's INFINIITEEEEEEEEEEEEEEEEEEEE JOBS LOL :D I should fucking get into politics.

TODO

Copyleft

Copyleft (also share-alike) is a concept of sharing something on the condition that others will share it under the same terms; this is practically always used by a subset of free (as in freedom) software and culture to legally ensure this software/art and its modifications will always remain free. This kind of hacks copyright to de-facto remove copyright by its own power.

Copyleft has been by its mechanisms likened to a virus because once it is applied to certain software, it "infects" it and will force its conditions on any descendants of that software, i.e. it will spread itself (in this case the word virus does not bear a negative connotation, at least to some, they see it as a good virus).

For free/open-source software the alternative to copyleft is so called permissive licensing which (same as with copyleft) grants all the necessary freedom rights, but does NOT require modified versions to grant these rights as well. This allows free software being forked and developed into proprietary software and is what copyleft proponents criticize. However, both copyleft and permissive licensing are free as in freedom.

In the FOSS world there is a huge battle between the copyleft camp and permissive camp (LRS advocates permissive licenses with a preference for 100% public domain).

Issues With Copyleft

In the great debate of copyleft vs permissive free licenses we, as technological anarchists, stand on the permissive side. Here are some reasons for why we reject copyleft:

• It burdens the reuser of the work by requiring him to do something extra -- while a public domain and many permissive licensed works can simply be taken and used without taking any extra action, just as it should ideally be, a work under copyleft requires its user to take an action, for example copying the license file (and then forever making sure it doesn't get lost), giving credit etc. While one may think this is not such a big deal, it's a form of friction that can get in the way of creativity, especially when combining many works under possibly different copyleft licenses which suddenly becomes quite cumbersome to handle.
• By adopting copyleft one is embracing and supporting the copyright laws and perpetuating the capitalist ways ("marrying the lawyers") because copyleft relies on and uses copyright laws to function; to enforce copyleft (prevent "disallowed" use) one has to make a legal action (while with permissive license we simply basically give up the rights to make a legal action). Copyleft chooses to play along with the capitalist bullshit intellectual property game and threatens to fight and use force and bullying in order to enforce correct usage of information.
• In a way it is bloat. Copyleft introduces legal complexity, friction and takes programmers' head space (every programmer has to study a bit of copyright law nowadays due to such BS), especially considering that copyleft is also probably largely ineffective as detecting its violation and actual legal enforcement is difficult, expensive and without a guaranteed positive outcome (FSF encourages programmers to hand over their copyright to them so they can defend their programs which just confirms existence and relevance of this issue). The effort spent on dealing with this is a wasted human time. Sure, corporations can probably "abuse" permissive (non-copyleft) software easier, but we argue that this is a problem whose roots lie in the broken basic principles of our society (capitalism) and so the issue should be addressed by improving our socioeconomic system rather than by bullshit legal techniques that just imperfectly and many times completely ineffectively try to cure the symptoms while strengthening the system's mechanisms.
• The scope of copyleft is highly debatable, introducing doubt/uncertainty (which is why we have different kind of copyleft such as strong, weak, network etc.). I.e. it can't be objectively said what exactly should classify as violation of copyleft AND increasing copyleft scope leads to copylefted software being practically unusable. You may say "so what", but in law clarity is extremely important, it may also discourage people because they don't really know what they sign up for, commercial use may also be discouraged by this for the same reason which may have a similar effect to a non-free license that downright disallows commercial use. Consider this example: Linux is copylefted which means we can't create a proprietary version of Linux, nevertheless we can create a proprietary operating system of which Linux is part (e.g. Android in which its proprietary app store makes it de-facto owned by Google), and so Linux is effectively used as a part of proprietary software -- the copyleft is bypassed. One might try to increase the copyleft scope here by saying "everything Linux ever touches has to be free software" which would however render Linux unusable on practically any computer as most computers contain at least some small proprietary software and hardware. The restriction would be too great.
• Copyleft drags people into activism, leaving less place for actual creativity -- one of the best examples is Richard Stallman and his GNU project, who were quite active in programming at their beginning but soon turned more or less just into a into a political activist group, spending time on petitions, propaganda, certifications (RYF, ...) and generally just the same kind of bullshit fights that capitalists like (often attacking even those who make free software, e.g. the GNU boot project for infringing on the name GNU without permission). Stallman himself said "he no longer programs because he has more important things to do". Maybe you say this has nothing to do with copyleft, but it's not a coincidence, copyleft is a mindset of constantly having to "protect" (as opposed to "letting go", the permissive mindset), for example once web applications appeared, the GNU people were suddenly all about having to make new licenses such as AGPL to update to the newest trends in technology and society. Any time a new technology or kind of legal abuse emerges, they have to update their licenses. Choosing copyleft really means choosing to be this kind of warrior and guard of right and wrong, which of course takes away some of your creative potential, with many people just giving in completely.
• Copyleft licenses have to be complex and ugly because they have to strictly describe the copyleft scope and include lots of legal boilerplate in order to make them well defendable in court (copyleft is really about preparing for a legal war) -- and as we know, complexity comes with bugs, vulnerabilities, it makes it incomprehensible to common people and imposes many additional burdens. Indeed, we see this in practice: the only practically used copyleft licenses are the various versions of GPL of which all are ugly and have historically shown many faults (which is again evident from e.g. looking at GPL v1 vs v2 vs v3). This introduces great license compatibility issues, headaches for programmers who should rather be spending time programming and other similar bullshit. Permissive licenses on the other hand are simple, clear and well understandable, they aren't as much preparing for a court battle as trying to give other hackers a peace of mind and make them free of legal worries.
• Copyleft prevents not only inclusion in proprietary software but also in permissive FREE software. I.e. as a consequence of denying code to corporations collateral damage is done by also denying code to ethical free software that wishes to be distributed without copyleft conditions. Similarly to how proprietary software forces free software programmers to reinvent wheels by rewriting software as free, copyleft forces permissive free software programmers to reinvent wheels and rewrite copylefted code as permissive. In this way copyleft fights not only proprietary software, but also other kinds of free software.
• ...

Copyright

Copyright (better called copyrestriction or copywrong) is one of many types of so called "intellectual property" (IP), a legal concept that allows "ownership", i.e. restriction, censorship and artificial monopoly on certain kinds of information, for example prohibition of sharing or viewing useful information or improving art works. Copyright specifically allows the copyright holder (not necessarily the author) a monopoly (practically absolute power) over art creations such as images, songs or texts, which also include source code of computer programs. Copyright is a capitalist mechanism for creating artificial scarcity, enabling censorship and elimination of the public domain (a pool of freely shared works that anyone can use and benefit from). Copyright is not to be confused with trademarks, patents and other kinds of "intellectual property", which are similarly harmful but legally different. Copyright is symbolized by C in a circle or in brackets: (C), which is often accompanies by the phrase "all rights reserved".

When someone creates something that can even remotely be considered artistic expression (even such things as e.g. a mere collection of already existing things), he automatically gains copyright on it, without having to register it, pay any tax, announce it or let it be known anywhere in any way. He then practically has a full control over the work and can successfully sue anyone who basically just touches the work in any way (even unknowingly and unintentionally). Therefore any work (such as computer code) without a free license attached is implicitly fully "owned" by its creator (so called "all rights reserved") and can't be used by anyone without permission. It is said that copyright can't apply to ideas (ideas are covered by patents), only to expressions of ideas, however that's bullshit, the line isn't clear and is arbitrarily drawn by judges; for example regarding stories in books it's been established that the story itself can be copyrighted, not just its expression (e.g. you can't rewrite the Harry Potter story in different words and start selling it).

As if copyright wasn't bad enough of a cancer, there usually exist extra oppressive copyright-like restrictions called related rights or neighboring rights such as "moral rights", "personal rights" etc. Such "rights" differ a lot by country and can be used to restrict and censor even copyright-free works. This is a stuff that makes you want to commit suicide. Waivers such as CC0 try to waive copyright as well as neighboring rights (to what extent neighboring rights can be waived is debatable though).

The current extreme form of copyright (as well as other types of IP such as software patents) has been highly criticized by many people, even those whom it's supposed to "protect" (small game creators, musicians etc.). Strong copyright laws basically benefit mainly corporations and "trolls" on the detriment of everyone else. It smothers creativity and efficiency by prohibiting people to reuse, remix and improve already existing works -- something that's crucial for art, science, education and generally just making any kind of progress. Most people are probably for some form of copyright but still oppose the current extreme form which is pretty crazy: copyright applies to everything without any registration or notice and last usually 70 years (!!!) AFTER the author has died (!!!) and is already rotting in the ground. This is 100 years in some countries. In some countries it is not even possible to waive copyright to own creations -- just think about what kind of twisted society we are living in when it PROHIBITS people from making a selfless donation of their own creations to others. Some people, including us, are against the very idea of copyright (those may either use waivers such as CC0 or unlicense or protest by not using any licenses and simply ignoring copyright which however will actually discourage other people from reusing their works). Though copyright was originally intended to ensure artists can make living with their works, it has now become the tool of states and corporations for universal censorship, control, bullying, surveillance, creating scarcity and bullshit jobs; states can use copyright to for example take down old politically inconvenient books shared on the Internet even if such takedowns do absolute not serve protection of anyone's living but purely political interests.

Prominent critics of copyright include Lawrence Lessig (who established free culture and Creative Commons as a response), Nina Paley and Richard Stallman. There are many movements and groups opposing copyright or its current form, most notably e.g. the free culture movement, free software movement, Creative Commons etc.

The book Free Culture by Lessig talks, besides others, about how copyright has started and how it's been shaped by corporations to becoming their tool for monopolizing art. The concept of copyright has appeared after the invention of printing press. The so called Statute of Anne of 1710 allowed the authors of books to control their copying for 14 years and only after registartion. The term could be prolonged by anothert 14 years if the author survived. The laws started to get more and more strict as control of information became more valued and eventually the term grew to life of author plus 70 years, without any need for registration or deposit of the copy of the work. Furthermore with new technologies, the scope of copyright has also extended: if copyright originally only limited copying of books, in the Internet age it started to cover basically any use, as any manipulation of digital data in the computer age requires making local copies. Additionally the copyright laws were passing despite being unconstitutional as the US constitution says that copyright term has to be finite -- the corporations have found a way around this and simply regularly increased the copyright's term, trying to make it de-facto infinite (technically not infinite but ever increasing). Their reason, of course, was to firstly forever keep ownership of their own art but also, maybe more importantly, to kill the public domain, i.e. prevent old works from entering the public domain where they would become a completely free, unrestricted work for all people, competing with their proprietary art (who would pay for movies if there were thousands of movies available for free?). Nowadays, with coprporations such as YouTube and Facebook de-facto controlling most of infromation sharing among common people, the situation worsens further: they can simply make their own laws that don't need to be passed by the government but simply implemented on the platform they control. This way they are already killing e.g. the right to fair use, they can simply remove any content on the basis of "copyright violation", even if such content would normally NOT violate copyright because it would fall under fair use. This would normally have to be decided by court, but a corporation here itself takes the role of the court. So in terms of copyright, corporations have now a greater say than governments, and of course they'll use this power against the people (e.g. to implement censorship and surveillance).

Copyright rules differ greatly by country, most notably the US measures copyright length from the publication of the work rather than from when the author died. It is possible for a work to be copyrighted in one country and not copyrighted in another. It is sometimes also very difficult to say whether a work is copyrighted because the rules have been greatly changing (e.g. a notice used to be required for some time), sometimes even retroactively copyrighting public domain works, and there also exists no official database of copyrighted works (you can't safely look up whether your creation is too similar to someone else's). All in all, copyright is a huge mess, which is why we choose free licenses and even public domain waivers.

Copyleft (also share-alike) is a concept standing against copyright, a kind of anti-copyright, invented by Richard Stallman in the context of free software. It's a license that grants people the rights to the author's work on the condition that they share its further modification under the same terms, which basically hacks copyright to effectively spread free works like a "virus".

Copyright does not (or at least should not) apply to facts (including mathematical formulas) (even though the formulation of them may be copyrighted), ideas (though these may be covered by patents) and single words or short phrases (these may however still be trademarked) and similarly trivial works. As such copyright can't e.g. be applied to game mechanics of a computer game (it's an idea). It is also basically proven that copyright doesn't cover computer languages (Oracle vs Google). Also even though many try to claim so, copyright does NOT arise for the effort needed to create the work -- so called "sweat of the brow" -- some say that when it took a great effort to create something, the author should get a copyright on it, however this is NOT and must NOT be the case (otherwise it would be possible to copyright mere ideas, simple mathematical formulas, rules of games etc.). Depending on time and location there also exist various peculiar exceptions such as the freedom of panorama for photographs or uncopyrightable utilitarian design (e.g. no one can own the shape of a generic car). But it's never good to rely on these peculiarities as they are specific to time/location, they are often highly subjective, fuzzy and debatable and may even be retroactively changed by law. This constitutes a huge legal bloat and many time legal unsafety. Do not stay in the gray area, try to stay safely far away from the fuzzy copyright line.

A work which is not covered by copyright (and any other IP) -- which is nowadays pretty rare due to the extent and duration of copyright -- is in the public domain.

Free software (and free art etc.) is not automatically public domain, it is mostly still copyrighted, i.e. "owned" by someone, but the owner has given some key rights to everyone with a free software license and by doing so minimized or even eliminated the negative effects of full copyright. The owner may still keep the rights e.g. to being properly credited in all copies of the software, which he may enforce in court. Similarly software that is in public domain is not automatically free software -- this holds only if source code for this software is available (so that the rights to studying and modifying can be executed).

See Also

• bullshit
• free culture
• copyleft
• derivative work
• fair use
• creative commons
• license
• patent
• trademark
• public domain
• intellectual property