Nvidia
@nvidia·2.2M subscribers·2.7K videos
Closing the Physical AI Data Gap With Simulation and Foundation Models
Posted
March 18, 2026
Views
3,137
Likes
108
Engagement
3.44%
March 18, 2026
3,137
108
3.44%
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4:03Now PlayingPhysical AI is the next frontier, but real-world data alone isn’t enough to train robots for the complexity of the physical world.
Developers are closing the physical AI data gap using simulation, synthetic data, and large-scale compute.
With NVIDIA Cosmos™ world foundation models, NVIDIA Isaac™ Lab for robot training and evaluation, Newton for GPU-accelerated differentiable physics, and Isaac GR00T foundation models for robot reasoning and action, teams can train and scale robot policies faster than ever.
Read the press release
#PhysicalAI #NVIDIAGTC
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