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NVIDIA, the $3.3 trillion semiconductor powerhouse, plans to roll out a new line of compact computers for humanoid robots in early 2025, marking a strategic shift amid growing competition in its core artificial intelligence (AI) chip business. The company’s latest offering, dubbed Jetson Thor, aims to power the next generation of AI-driven robots.
“The ChatGPT moment for physical AI and robotics is around the corner,” Deepu Talla, NVIDIA’s vice president of robotics, said in an interview with the Financial Times. Talla calls this shift a response to a “tipping point” in robotics development.
Two key technological breakthroughs drive this transition: generative AI and robot training in virtual environments. These developments help bridge what roboticists call the “Sim-to-Real gap,” ensuring robots trained in simulated settings can operate effectively in the real world.
NVIDIA reportedly won’t be competing directly with robot manufacturers like Tesla or Apptronik. Instead, the company wants to position itself as the underlying provider. It plans to offer software for training AI models and simulation environments through its Omniverse platform, as well as hardware like compact computers for humanoid robots called Jetson Thor.
“We provide the platform for enabling all of these companies to do any of those tasks,” Talla said.
This pivot comes as NVIDIA faces mounting competition in its AI chip business. Major customers like Amazon, Microsoft, and Google are developing their own chips to reduce dependence on NVIDIA’s products. Meanwhile, rival AMD is increasing pressure in the AI semiconductor market.
The global robotics market presents a significant opportunity, projected to grow from $78 billion in 2024 to $165 billion by 2029. NVIDIA has already secured key partnerships, with Amazon deploying its robotics simulation technology in three U.S. warehouses. Additionally, companies like Toyota and Boston Dynamics are already utilizing its training software.
However, challenges remain in the robotics sector. David Rosen, who leads the Robust Autonomy Lab at Northeastern University, points out: “As of right now, we don’t have very effective tools for verifying the safety and reliability properties of machine learning systems, especially in robotics. This is a major open scientific question in the field.”
The technology giant recently demonstrated its commitment to robotics by investing in Figure AI. In February, NVIDIA joined Microsoft and OpenAI in an investment round that valued the humanoid robotics company at $2.6 billion.
Right now, robotics makes up only a small part of NVIDIA’s revenue. Most of its earnings come from its data center business, which made up 88% of its $35.1 billion in sales during the third quarter. However, NVIDIA sees robotics as a crucial growth driver for the future.
