Skild AI releases robot foundation model S1
Robot foundation model S1 released — the company says it learns new tasks in context from a single demonstration video and performs them without weight updates or per-task retraining, handling multi-step tasks of dozens of steps lasting up to 10 minutes. The company claims a per-step success rate of about 66% on multi-step tasks, about 7 times the 9% of a comparison system, and explains that one video is worth about 380 direct demonstrations of training data. It used NVIDIA Cosmos, Isaac Lab/Sim, Omniverse, TensorRT and Newton for training, simulation and inference, and says it reached $100 million in annualized revenue and some 60 deployment partnerships within 10 months of launch.
Why it matters
A case of the in-context learning paradigm of LLMs being transplanted to robot manipulation, showing robot foundation models heading toward generalization without per-task fine-tuning.
Source — Primary sources first; secondary reports are labelled “Press”
Officialblogs.nvidia.comhttps://blogs.nvidia.com/blog/skild-ai-s1-physical-ai/Added in Week 38, 2026 · See that week