AI News
Team Develops First Ever Autonomous Humanoid Robot With Full-Body Artificial Skin
A team from The Technical University of Munich (TUM) has developed the first ever autonomous humanoid robot with full-body artificial skin. They were able to create a system that paired artificial skin with control algorithms. This new technology will help robots become capable of sensing their own bodies and environment, which will be important when they inevitably start to be commonplace among humans.
If a robot is able to better navigate its environment through the use of sensing, it will be much safer around humans. One of the things they will be able to do is avoid unwanted contact and accidents.
The team responsible for the new technology included Prof. Gordon Cheng. The skin that was developed is made up of hexagonal cells that are about one inch in diameter. Each one of the hexagonal cells consists of a microprocessor and sensors, which help detect contact, acceleration, proximity, and temperature.
The actual skin cells are not new; they were developed 10 years ago by a Professor of Cognitive Systems at TUM, Gordon Cheng. These new developments by the team at TUM unlocked the full potential.
The research was published in the journal Proceedings of the IEEE.
The Problem of Computing Capacity
One of the major problems with the development of artificial skin is computing capacity. Because the human skin has about 5 million receptors, it has been a challenge to recreate it in robots. The constant processing of data through the use of sensors can overload systems.
The team at TUM decided not to monitor the skin constantly. Instead, they focused on events in order to reduce the need for massive processing effort by as much as 90%. In the newly developed artificial skin, individual cells transmit information only when there is a change in values. This means there is heavy reliance on the sensors to detect some type of sensation, which will in turn initiative the process.
Critical For Human-Robot Interaction
This new technique by Prof. Cheng and his team helps increase the safety of the machines. They are now the first to apply artificial skin to a human-size autonomous robot that is not dependent on external computation.
The robot that they used for the artificial skin is called the H-1 robot, and it has 1,260 cells and more than 13,000 sensors. The sensors and cells are located on the upper body, arms, legs, and the soles of the feet. Because of this, the robot can sense its entire body, from top to bottom. The H-1 can move along uneven surfaces and balance on one leg.
The H-1 robot is capable of safely hugging a human, which is a great accomplishment. These machines have such power that they can be extremely dangerous and injure humans when closely interacting. The H-1 is able to sense multiple parts of its body at once so that it does not exert too much force or pressure.
“This might not be as important in industrial applications, but in areas such as nursing care, robots must be designed for very close contact with people,” Gordon Cheng explained.
The new technology is very versatile, and it can still function even if some of the cells are lost.
“Our system is designed to work trouble-free and quickly with all kinds of robots,” says Gordon Cheng. “Now we’re working to create smaller skin cells with the potential to be produced in larger numbers.”
There are constant developments in the AI field that are bringing humans and robots closer together, and new technology like this is critical in facilitating a safe environment where both can operate.
VentureBeat reports on two new high fundings for startups developing artificial intelligence. Umbo Computer Vision (UCV) works on autonomous video security systems to businesses, while Xor is developing an AI chatbot platform for recruiters and job seekers. Both startups are located in San Francisco, and UCV is a joint venture with Taiwan and has a base there and in the UK too. UCV raised $8 million for its Ai-powered video security, while Xor managed to raise $8.4 million for its project.
Xor’s capital infusion came after a year in which the startup tripled its sales in the US, “reaching $2 million in annual recurring revenue and closing deals with over 100 customers in 15 countries, including ExxonMobil, Ikea, Baxter Personnel, Heineken, IBS, Aldi, Hoff, McDonald’s, and Mars.” As the company co-founder and CEO Aida Fazylova explains, she “started the company to let recruiters focus on the human touch — building relationships, interviewing candidates, and attracting the best talent to their companies. Meanwhile, AI takes care of repetitive tasks and provides 24/7 personalized service to every candidate. We are proud to get support from SignalFire and other amazing investors who help us drive our mission to make the recruitment experience better and more transparent for everyone.”
Xor’s chatbot “automates tedious job recruitment tasks, like scheduling interviews; sorting applications; and responding to questions via email, text, and messaging apps like Facebook Messenger and Skype. The eponymous Xor — which is hosted on Microsoft’s Azure — draws on over 500 sources for suitable candidates and screens those candidates autonomously, leveraging 103 different languages and algorithms trained on 17 different HR and recruitment data sets.”
According to Grand View Research, the chatbot market is expected to reach $1.23 billion by 2025, while Gartner predicts that chatbots will power 85% of all customer service interactions by the year 2020.
For its part, Umbo develops “ software, hardware, and AI smarts that can detect and identify human behaviors related to security, such as intrusion, tailgating (when an unauthorized individual follows someone into private premises), and wall-scaling.”
The company says it has developed its AI systems entirely in-house, and their system incorporates three components.“AiCameras are built in-house and feature built-in AI chips, connecting directly to the cloud to bypass servers and video recording intermediates, such as NVRs or DVRs. Light is AI-powered software for detecting and issuing alerts on human-related security actions.” There is also “TruePlatform, a centralized platform where businesses can monitor and manage all their cameras, users, and security events.” As Shawn Guan, Umbo’s cofounder and CEO points out, the company launched Umbo Light, “which implemented feedback that we gathered from our customers about what their primary wants from video security systems were. This allowed us to design and deliver a system based on the needs of those who use it most.”
The global video surveillance market, which is now practically relying on the use of AI, was pegged at $28 billion in 2017 and is expected to grow to more than $87 billion by 2025.
If you’re a lover of coffee, it will come as unpleasant news that the price of coffee could potentially spike in the near future. Climate change and deforestation are threatening some of the biggest coffee species in the world, but AI could potentially help keep coffee relatively affordable.
The combined forces of deforestation and climate change are threatening the production of many species of coffee, including the common Arabica species, which can be found in many of the most prolific blends and brews. Coffee farmers around the globe are having to deal with rising temperatures and the problems that are associated with them, such as periods of drought. One recent study published in the journals Global Change Biology and Science Advances found that there were substantial risks to many wild coffee species, with around 60% of 124 different wild coffee species being vulnerable to extinction.
As reported by Inside Climate News, Aaron P. Davis, one of the authors on the study and a senior research leader at England’s Royal Botanic Gardens, explained that domesticated coffee is adapted from these wild species.
“We should be concerned about the loss of any species for lots of reasons,” explained Davis, “but for coffee specifically, I think we should remember that the cup in front of us originally came from a wild source.”
Domesticated coffee is composed of primarily two bean varieties: arabica and robusta. Wild plants are bred with these species to increase their quality, serving as a genetic library that allows scientists to create hardier plants. Biologists look to wild coffee varieties to find species with resistance to these threats, but as the climate continues to warm, this becomes more difficult.
Much as the wild strains of coffee are under pressure, cultivate coffee crops are also experiencing strain. Severe droughts and longer, more intense outbreaks of pests and disease are threatening cultivated crops. A fungal disease is taking advantage of the warmer conditions and higher humidity to proliferate amongst coffee crops, and the coffee borer beetle is possibly spreading faster thanks to climate change. Climate change also makes weather patterns more extreme, with more severe droughts and rainstorms. Either too much or too little rain can degrade coffee production. Further, it is estimated that around half of all wild coffee plants will disappear over the next 70 years.
Despite the recent problems climate change has brought to coffee farmers, demand for coffee is only likely to increase. The overall demand for food across the globe is expected to increase by around 60% by 2050, and small farmers produce most of the globe’s food supply, around 70%.
Amidst the growing threat of climate change, AI could help coffee farmers compensate for things like drought and pests. Researchers associated with the Financial and Agricultural Recommendation Models project, or FARM, intend to assist coffee farmers by providing them with techniques that can boost yields. Project FARM is initially going to be tested on coffee farmers throughout Kenya, where it will apply data science techniques to big datasets gathered from coffee farms. The FARM platform aims to bring automated farming systems and data science-backed techniques to small farms across Kenya, which should help boost yield. Project FARM is driven by the decreasing price of sensors and the accompanying availability of large datasets gathered by these sensors.
The AI-based farming methods can provide farmers with valuable insights that can help them optimize production. Machine learning algorithms can be used to predict weather patterns and take precautions against inclement weather, while computer vision systems can recognize crop damage and possible signs of spreading fungus or parasites. Gaining this valuable info can help farmers guard against these damaging forces. Farmers can even be alerted via SMS if a storm is expected the next day.
One company, Agrics, is able to use data gathered by sensors to predict risks that may impact individual farmers. Violanda de Man, Innovation Manager at Agrics East Africa, explained that the data can be used to give farmers location-specific services and products that can reduce farm risks and improve both the income and security of rural populations
As crops and farmers around the globe contend with the challenges of climate change, AI seems poised to play a major role in the struggle to contend with these challenges.
It seems that venture capitalists are really picking up the tabs of artificial startups, not only in the US but around the world. Venture Beat presented recently the Q3 2019 data from the National Venture Capital Association. According to that information “965 AI-related companies in the U.S. have raised $13.5 billion in venture capital through the first 9 months of this year. That should eclipse the 1,281 companies that raised $16.8 billion in 2018, according to the 3Q 2019 PitchBook-NVCA Venture Monitor.”
NVCA noted that the sector is still in its youth and that“the average deal size and valuations still tend to fluctuate quite a bit from quarter to quarter.” Still, as they also point out, “have clearly moved well past early, experimental stages, which tend to attract lots of little bets as investors explore the terrain.”
At the same time, TechWorld cites a 2018 report by the McKinsey Global Institute that AI “could contribute an additional global economic activity worth around $13 trillion by 2030, by which point around 70 percent of companies will have adopted at least one form of AI”.TechWorld adds that eight of the top 20 European universities and 40% of European tech unicorns’ currently reside in the UK, while AI venture capital firm Asgard estimates that the UK has the largest “ecosystem of AI startups” in Europe.
TechWorld also lists 36 AI startups that deserve attention, and its top five choices are the following:
[ ] Distributed, an on-demand workforce platform that assists businesses focused on delivering digital outcomes faster and to a higher standard.
[ ] SenSat builds digital copies of physical environments, where artificial intelligence models can be released to help understand the parameters of that environment and provide valuable feedback. The one-line mission statement is: “To teach computers how to understand the physical world we all live in.”
[ ] CognitionX, an advice marketplace targeting the growing field of AI and machine learning, built by Charlie Muirhead and Tabitha Goldstaub.
[ ] Phrasee, which uses AI to create marketing copy for customers including The Times, SuperDry and Domino’s. The company has developed a language generation algorithm that analyses engagement from previous campaigns to craft the content in email subject lines, push notifications and social media ads.
[ ] Deputi, which is leveraging AI to help businesses minimize the costs of day-to-day operational tasks using automation.
On the European continent itself, Silicon Anals consider the Dutch companies as the “early adopters of AI and are competitive when it comes to the importance placed on new AI developments.” It points to the following three AI companies as top to watch in the coming period:
– Dashmote (Amsterdam, current funding € 2.5 million) creates artificial intelligence technology that helps companies make complex decisions based on data gathered from images and text uploaded to the internet. Founded in 2014 by Dennis Tan (CEO), Matthäus Schreder (CPO), and Stefan Tan (CFO), the company’s platform is capable of analyzing the images and gain valuable insights.
– Doculayer.ai ( The Hague, € 3 million) is a content management platform that leverages AI to manage unstructured information. The company’s technology is capable of analyzing the content automatically, enhance the findability, and help enrich the quality of the documents.
– Owlin (Amsterdam, € 3.1 million), which provides real-time news analysis. The company uses the latest AI and machine learning technologies to monitor, analyze, and visualize more than 2.8 million news sources worldwide in 8 languages and all in near real-time.
In Asia, for example, China’s SenseTime Group, currently regarded as the world’s most valuable AI startup, has seen its valuation breach US$7.5 billion this year, following massive investments from the likes of SoftBank. The same investor as Nikkei Asian Review reports, “is accelerating its investment into the country’s artificial intelligence startups despite the verdict of its parent group’s founder that Japan is ‘underdeveloped’ in the cutting edge technology.
All this indicates that 2019 could be the best for AI startups yet.