Skild trains S1 robot physical AI model on NVIDIA infrastructure
Skild AI has launched its S1 robot foundation model on NVIDIA infrastructure, training robotics systems using single video demonstrations.
The system uses video inputs to execute long-horizon, previously unseen tasks through in-context learning, operating without parameter weight updates or task-specific post-training.
Deepak Pathak, cofounder and CEO of Skild AI, said: “Learning by experience, and not preprogramming, is the step change that has happened in robotics. NVIDIA Isaac Lab and NVIDIA Cosmos technologies help Skild create the scalable, diverse experience its robots need to learn across many scenarios and embodiments.”
Pathak’s company reached a $100 million annual revenue run rate 10 months following its initial commercial rollout. Skild currently maintains over 60 deployment partnerships spanning manufacturing, logistics, inspection, security, and food preparation.
In-context learning from video prompts
Standard industrial deployments require fresh datasets, retraining, and validation whenever product specifications or factory layouts change.
S1 replaces this cycle by taking an operator’s...
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