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Nvidia today announced that it has released a family of foundational AI models called Cosmos that can be used to train humanoids, industrial robots and self-driving cars. While language models learn how to generate text by training on a copious amount of books, articles and social publications, Cosmos is designed to generate images and 3D models of the physical world.
During a keynote presentation at the annual CES conference in Las Vegas, Nvidia CEO Jensen Huang showed examples of Cosmos being used to simulate activities in stores. Cosmos was built on 20 million hours of real footage of “humans walking, hands moving, manipulating things,” Jensen said. “It’s not about generating creative content, it’s about teaching AI to understand the physical world.”
Researchers and startups hope that these kinds of foundational models can give robots used in factories and homes more sophisticated capabilities. Cosmos can, for example, generate realistic video boxes falling from shelves in a warehouse, which can be used to train a robot to recognize accidents. Users can also tune the models with their own data.
A number of companies are already using Cosmos, Nvidia says, including humanoid robot startups Agility and Figure AI, and self-driving car companies like Uber, Waabi and Wayve.
Nvidia also announced software designed to help different types of robots learn to perform new tasks more efficiently. The new feature is part of Nvidia’s existing Isaac robot simulation platform that will allow robot builders to take a small number of examples of a desired task, such as grasping a particular object, and generate a large amount of data of synthetic training.
Nvidia hopes Cosmos and Isaac will appeal to companies looking to build and use humanoid robots. Jensen was joined on stage at CES by life-sized images of 14 different humanoid robots developed by companies including Tesla, Boston Dynamics, Agility, and Figura.
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