NVIDIA CEO Tells NTU Grads to Run, Not Walk — But Be Prepared to Stumble

by Melody Tu

“You are running for food, or you are running from becoming food. And often times, you can’t tell which. Either way, run.”

NVIDIA founder and CEO Jensen Huang today urged graduates of National Taiwan University to run hard to seize the unprecedented opportunities that AI will present, but embrace the inevitable failures along the way.

Whatever you pursue, he told the 10,000 graduates of the island’s premier university, do it with passion and conviction — and stay humble enough to learn the hard lessons that await.

“Whatever it is, run after it like we did. Run. Don’t walk,” Huang said, having swapped his signature black leather jacket for a black graduation robe, with the school’s plum-blossom emblem highlighting a royal blue, white and aqua collar.

“Remember, either you are running for food; or you are running from becoming food. And often times, you can’t tell which. Either way, run.”

Huang, who moved from Taiwan when he was young, recognized his parents in the audience, and shared three stories of initial failures and retreat. He called them instrumental in helping forge NVIDIA’s character during its three-decade journey from a three-person gaming-graphics startup to a global AI leader worth nearly a trillion dollars.

“I was … successful — until I started NVIDIA,” he said. “At NVIDIA, I experienced failures — great big ones. All humiliating and embarrassing. Many nearly doomed us.”

The first involved a key early contract the company won to help Sega build a gaming console. Rapid changes in the industry forced NVIDIA to give up the contract in a near-death brush with bankruptcy, which Sega’s leadership helped avert.

“Confronting our mistake and, with humility, asking for help saved NVIDIA,” he said.

The second was the decision in 2007 to put CUDA into all the company’s GPUs, enabling them to crunch data in addition to handling 3D graphics. It was an expensive, long-term investment that drew much criticism didn’t pay off for years until the chips started being used for machine learning.

“Our market cap hovered just above a billion dollars,” he recalled. “We suffered many years of poor performance. Our shareholders were skeptical of CUDA and preferred we improve profitability.”

The third was the decision in 2010 to charge into the promising mobile-phone market as graphics-rich capabilities were coming into reach. The market quickly commoditized, though, and NVIDIA retreated just as quickly, taking initial heat but opening the door to investing in promising new markets — robotics and self-driving cars.

“Our strategic retreat paid off,” he said. “By leaving the phone market, we opened our minds to invent a new one.”

Huang told grads that of the parallels in terms of boundless promise between the world he entered upon graduating four decades ago, on the cusp of the PC revolution, and the brave new age of AI they are entering today.

“For your journey, take along some of my learnings,” he said. Admit mistakes and ask for help; endure pain and suffering to realize your dreams; and make sacrifices to dedicate yourself to a life of purpose.

Life in the Fast Lane: Sarah Tariq Drives Autonomous Vehicle Software at NVIDIA

by Isha Salian

Sarah Tariq joined NVIDIA 18 years ago as an intern — and is now the company’s vice president of autonomous driving software, leading a team of several hundred engineers.

Originally from Islamabad, Pakistan, Tariq is based in Silicon Valley with a team spread across the U.S., Europe, India and China. They’re focused on developing next-generation, in-vehicle computing systems that will power a wide range of vehicles, including the future models of Mercedes-Benz and Jaguar Land Rover.

“NVIDIA is developing a unified platform that does it all: We’re specifying the sensors plus creating the hardware and software needed to drive passengers safely from point A to B,” Tariq said. “Our system, referred to as NDAS, is integrating standard features including emergency braking, lane keeping and parking assistance together with higher-level software for autonomously navigating urban traffic, including safely navigating complex intersections and interactions with other road users including pedestrians and bicyclists.”

Team of NVIDIANs pose in the autonomous vehicle garage
Tariq (right) and members of her team in NVIDIA’s autonomous vehicle garage in Silicon Valley.

Ramping Up: From Intern to VP

After finishing her undergrad studies back home, Tariq moved to the U.S. for her master’s in computer science. Soon after starting a Ph.D. program in 2005 at Georgia Tech, focused on computer vision and computer graphics, she came to NVIDIA as an engineering intern working on graphics for gaming.

“I came for a couple months, and ended up staying for nearly a decade,” she said. “At the time, I felt that whatever I could do in grad school, I could do it better at NVIDIA, where I had access to much more information and resources.”

Over nine years, Tariq worked as a software engineer on NVIDIA’s developer technology team — collaborating with external developers to optimize video game performance, implementing real-time rendering of fluid and hair in games, and accelerating molecular dynamics and quantum chemistry algorithms on supercomputers.

She then shifted gears to the automotive team and NVIDIA DRIVE, where she was the technical lead on a self-parking project.

Tariq then spent six years at Zoox — an AV startup later acquired by Amazon — developing perception for robotaxis and leading the overall improvement of driving quality. She returned to NVIDIA in 2021 to lead autonomous driving software development.

“There are so many groundbreaking and meaningful initiatives we’re working on at NVIDIA — it’s an amazing aspect of the company,” she said. “Engineers can apply the knowledge of accelerated computing to any field they want to make an impact in.”

Building a Fleet of Top Talent

One of Tariq’s goals is to build an inclusive team where members feel supported and empowered to do their life’s work. On a trip to Germany last year to support our collaboration with an auto partner, Tariq was heartened to discover that the team of NVIDIANs taking a test drive were all women.

“We didn’t try to stage that at all — it just ended up that all these great, capable women were the right people to send on that mission,” Tariq said. “It was such a contrast to back when I was studying and would be the only woman in a group of 50.”

NVIDIA team in one of our test autonomous vehicles.
NVIDIA team in one of our test autonomous vehicles.

Racing Toward Autonomy 

Tariq looks forward to the NVIDIA-powered vehicles that will hit the road in the coming years — and the significant positive impact the technology could have on people’s lives.

“Autonomous driving is rapidly evolving and full of interesting technical challenges,” she said. “After having worked in and seen the industry from many angles, I believe the best way to make the promise of autonomous driving a reality is the way NVIDIA’s approaching it — by creating groundbreaking hardware and software for autonomy that can efficiently be deployed on large-scale consumer cars, and software that continues to learn and improve using the data it sees worldwide.”

Learn more about NVIDIA’s work in autonomous driving through the DRIVE Labs YouTube video series.

Award-Winning NVIDIA Robotics Research Takes Center Stage at ICRA

At the International Conference on Robotics and Automation, NVIDIA demonstrates the power of robotics simulation for real-world use cases.
by Jason Black

More than a dozen NVIDIA robotics research papers will take center stage at this year’s IEEE International Conference on Robotics and Automation (ICRA), taking place May 29-June 2, in London.

One, titled “Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behavior,” will be recognized with an IEEE Best Paper award.

Many of this year’s submissions demonstrate robotics capabilities trained in simulation that were then shown to work in the real world.

Additional papers from members of the NVIDIA Robotics Research Lab to be presented at ICRA include:

  • “DeXtreme: Transferring Agile In-Hand Manipulation From Simulation to Reality” (Read paper, watch video)
  • “MVTrans: Multi-View Perception of Transparent Objects” (Read paper, watch video)
  • “Self-Supervised Learning of Action Affordances as Interaction Modes” (Read paper, watch video)
  • “nerf2nerf: Pairwise Registration of Neural Radiance Fields” (Read paper, watch video)
  • “DexGrasp-1M: Dexterous Multi-Finger Grasp Generation Through Differentiable Simulation” (Read paper, watch video)

  • “ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models” (Read paper, watch video)
  • “DefGraspNets: Grasp Planning on 3D Fields With Graph Neural Nets” (Read paper, watch video)
  • “CuRobo: Parellelized Collision-Free Robot Motion Generation” (Read paper)
  • “RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control” (Read paper, watch video)
  • “FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments” (Read paper, watch video)

  • “Planning for Multi-Object Manipulation With Graph Neural Network Relational Classifiers” (Read paper)
  • “CabiNet: Scaling Neural Collision Detection for Object Rearrangement With Procedural Scene Generation” (Read paper, watch video)
  • “Global and Reactive Motion Generation With Geometric Fabric Command Sequences” (Read paper, watch video)

Many of the papers above include GitHub code links for those who want to explore.

Visit NVIDIA partners at ICRA — including Ahead.io, Cogniteam, Connect Tech, Mathworks and Silicon Highway. They’ll be showcasing real-world robotics research demos, powered by the NVIDIA Jetson Orin platform for edge AI and robotics as well as the NVIDIA Isaac robotics simulation platform.

In addition, check out this technical blog on how robotics software company Cogniteam set up a multi-robot simulation scenario using its Nimbus platform and NVIDIA Isaac Sim. The setup offered capabilities such as local simulation tasks, remote access to simulation machines, global monitoring of simulation data and more — all accessible through a web browser.

Learn more about the NVIDIA Robotics Research Lab, a Seattle-based center of excellence focused on robot manipulation, perception and physics-based simulation. It’s part of NVIDIA Research, which comprises more than 300 leading researchers around the globe, focused on topics spanning AI, computer graphics, computer vision and self-driving cars.