Robots can learn a year's worth of data in under an hour with NVIDIA's new AI model for accelerating the mass deployment of humanoid robots.

NVIDIA says HOVER neural network, accessed through the tech giant's Isaac platform, has 1.5 million parameters to power rapid, complex learning for robots.

With Isaac's simulator tool, robots learn skills quickly by practicing thousands of movements in a virtual world. The model instantly adapts to different robots, cutting down on time and costs by skipping extra training. HOVER links with vision-language models to turn instructions into quick, precise movements.

Companies like Agility Robotics, Figure AI, Boston Dynamics, 1X Technologies, Fourier, Sanctuary, Neura Robotics, and Robot Era use the Isaac platform for their humanoid robots.

NVIDIA has a suite of tools specifically aimed at expediting the production of humanoids.

NVIDIA says its NIM microservices can reduce robot deployment times from weeks to minutes. The MimicGen NIM microservice creates synthetic motion data, while the RoboCasa NIM microservice makes simulation-ready environments. Osmo, NVIDIA’s cloud-based service, simplifies robot training and simulation. The company says it cuts development times from months to under a week.

Teleoperation, which captures human actions to train robots, can be done faster and cheaper with NVIDIA’s AI and Omniverse digital twin tools. The software is compatible with the Apple Vision Pro, which captures human demonstrations that are simulated and expanded into large datasets for training robots.

NVIDIA has been vocal about humanoid robots, investing heavily in their development and capabilities. Program members get early access to foundational models in NVIDIA’s Project GR00T. The project, announced earlier in 2024, uses NVIDIA’s tech to teach robots how to move and interpret human language.

A robotic startup could use a foundational model with their hardware as a starting point. Since the model already knows a lot, the startup can focus on teaching the robot to perform tasks that can’t yet be automated.

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