Closing the Physical AI Data Gap With Simulation and Foundation Models

Estimated read time 1 min read

Post Content

 

​ Physical 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: https://nvidianews.nvidia.com/news/nvidia-and-global-robotics-leaders-take-physical-ai-to-the-real-world

#PhysicalAI #NVIDIAGTC   Read More NVIDIA 

#Techno #nvidia

You May Also Like

More From Author