LeRobot Closes More of the Learning Loop

Hugging Face's LeRobot 0.6 release expands the open robotics toolkit beyond training individual policies. It adds policies that learn to anticipate future states, a common reward-model interface, six simulation benchmark families under one evaluation command, depth and language annotations for datasets, and a rollout tool that can record human corrections when a policy fails. The project also reports faster video-data loading and a leaner base installation. Together, the changes make repeated deployment, evaluation, correction, and retraining a more coherent open workflow.