Nvidia CEO: ‘The ChatGPT moment for general robotics is just around the
Nvidia CEO Jensen Huang said the artificial intelligence (AI) revolution is on the verge of delivering breakthroughs in robotics, while delivering remarks Monday at the annual Consumer Electronics Show conference in Las Vegas.
“The ChatGPT moment for general robotics is just around the corner,” Huang said in reference to the impact of OpenAI’s ChatGPT spurring broader interest in generative AI technology with the release of a conversational AI chatbot in late 2022.
“In fact, all of the enabling technologies that I’ve been talking about is going to make it possible for us in the next several years to see very rapid breakthroughs, surprising breakthroughs in general robotics.”
Huang said AI tools will help facilitate the growth of general robotics technologies in areas like information technology, self-driving cars and humanoid robots that can help automate more of the work performed in manufacturing facilities and warehouses.
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“Now the reason why general robotics is so important is whereas robots with tracks and wheels require special environments to accommodate them, there are three robots, three robots in the world that we can make that require no greenfields. Brownfield adaptation is perfect,” Huang explained. “If we could possibly build these amazing robots, we could deploy them in exactly the world that we’ve built for ourselves.”
“These three robots are one, agentic robots and agentic AI, because they’re information workers. So long as they could accommodate the computers in our offices, it’s going to be great. Number two, self-driving cars. And the reason for that is we spent 100-plus years building roads and cities. And then, number three, humanoid robots,” Huang said.
The Nvidia CEO added that advances in robotics to enable these three uses will lead to “the largest technology the world’s ever seen” and he added that the company thinks the “robotics era is just around the corner.”
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“The critical capability is how to train these robots. In the case of humanoid robots, the imitation information is really hard to collect, and the reason for that is, in the case of car, you just drive it, we’re driving cars all the time,” Huang noted.
“In the case of these humanoid robots, the imitation information, the human demonstration is rather laborious to do. So we need to come up with a…
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