First on CNBC: Excerpt: Nvidia Founder & CEO Jensen Huang Speaks with Jon Fortt on CNBC’s “Squawk Box” Today - CNBC
HUANG: Excellent. Excellent. Timing is everything. We've been thinking about this area for a long time, waiting for that moment. And and, as in many of the things that we do, whether it's digital biology and turning drug discovery from a, from a discovery p...
Key takeaways
China is leading an exponential surge in humanoid‑robot production, with Omdia projecting the global market for general‑purpose embodied‑intelligent robots to double annually and reach 2.6 million units by 2035, driven by Chinese volume manufacturing and U.S. AI advances. At CES 2026 in Las Vegas, the industry highlighted both promising breakthroughs and stark limitations: NVIDIA unveiled new vision‑language and reasoning models (Gr00t and Cosmos) aimed at giving robots a “ChatGPT moment,” while AMD backed Italy’s Generative Robotics with a humanoid called Gene.01 for industrial use. Chinese firms such as Unitree displayed high‑profile demos—including a $70,000 G1 robot performing boxing and dancing—yet observers noted frequent performance failures and limited real‑world capability. Boston Dynamics, in partnership with Hyundai, introduced a production‑ready Atlas humanoid capable of lifting about 110 pounds and operating in harsh factory conditions, with Hyundai planning deployments from 2028 and a U.S. plant that could output up to 30,000 units annually. Meanwhile, London‑based startup Humanoid compressed a typical 18‑month hardware cycle to seven months, delivering an alpha version of its HMND 01 platform that combines wheeled industrial bots and bipedal research units, leveraging NVIDIA’s Isaac simulation tools and a new Jetson‑based networking stack. Despite the rapid advances, analysts warn that true general‑purpose robots that handle diverse, unstructured tasks remain emerging, and some industry voices question whether current humanoids will ever meet the practical expectations of consumers and manufacturers.
HUANG: Excellent. Excellent. Timing is everything. We've been thinking about this area for a long time, waiting for that moment. And and, as in many of the things that we do, whether it's digital biology and turning drug discovery from a, from a discovery process to an engineering process, from a scientific process to a science and engineering process to self-driving cars to even the work that we do in computer graphics, ray tracing is now completely done in real time. It took us 30 years to do it in real time, and so you have to pursue something for a long period of time looking for that moment where that enabling technology is discovered. In the case of humanoid robotics, let me let me first say that a computer doesn't know and doesn't care what kind of tokens it's generating. It could JON FORTT: Robotics. It's been a dream, part of CES for a long time. But it's also been elusive. And we had iRobot kind of not go in a great direction. Granted we do have autonomous vehicles now, and those are really robots—
HUANG: Robots.
FORTT: I guess, right? We're talking about physical AI. What makes this moment different for robotics in particular? And maybe give me humanoid because we tend to get very excited about it. But I wonder, too excited? FORTT: Yeah, right. With Runway yeah.
HUANG: I could give him that prompt and he will generate an amazing video. Isn't that right?
FORTT: Yeah.
HUANG: And that video has a person reaching out and picking up a cup. Why is that model different than a generative model for a humanoid robot picking up a cup? The moment I saw that working that well, then the rest of it is still a whole bunch of research, a whole bunch of, a whole bunch of technology. But you could tell that the enabling technology is just right around the corner.
FORTT: Tell me how much more performant Vera Rubin is because I get questions I got one on "Fast Money," how much does it cost? And I guess the flip side of that is how much value does it deliver?
HUANG: That's it. That's exactly right.
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