Skild AI says S1 can pick up robot tasks from one video

NVIDIA’s blog describes Skild AI’s new S1 model as a way to teach robots a task by showing one video example rather than preparing a separate training run for each new job. According to the post, the model takes the recording as a prompt, interprets the sequence and objects involved, and then maps that to actions on the robot in front of it without updating model weights.

The examples given are not limited to one production line. NVIDIA says Skild has used S1 on tasks including plant potting, pancake making, pour-over coffee brewing and kit assembly, with jobs lasting up to 10 minutes. The post also says the system can react when items shift position and can recover from some errors during execution.

The more concrete operational claim is deployment. NVIDIA says Skild, NVIDIA and Foxconn are deploying the Skild Brain on dual-arm manipulators for assembly of NVIDIA Blackwell systems. In the workflow described, the robot installs a busbar and limit block, fastens 16 screws and continues when the scene differs from plan.

The important limits sit in the same post. Reported performance numbers come from Skild’s own testing as relayed by NVIDIA: about 66% success at each step on new multi-step tasks, versus 9% for a comparable AI system, plus an estimate that one short video can match the value of roughly 380 hands-on training examples. The article does not provide independent verification, full-task completion figures or detailed comparison conditions, which is where robotics claims tend to meet the furniture.