Today we’re open-sourcing Steel, our internal physics solver built with @NVIDIA.
It runs simulations up to 13× faster than PhysX while using ~3× less GPU memory.
Steel unlocks scaleable simulation for manipulation, for everyone.
We just hit 100M ARR within 10 months of starting deployments.
We are in factory lines. On construction sites. In kitchens. In data centers.
Cleaning. Welding. Building. Cooking.
Deploying.
Truly incredible.
The fact that the robot is able to learn from examples, which is also how humans learn: we watch people do things and then learn from their actions.
Now, the robot can do the same.
This could be the future of robotics.
Introducing S1, our new foundation model that learns from one example.
It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning.
Watch S1 operate in real-time via in-context learning:
