Training Robotic Systems

Sergey and Daniel discuss the surprising findings that training a robotic system can overcome distributional shift issues at test time, even without complicated plans. They explore the effectiveness of surgical perturbations and the potential for large-scale reinforcement learning in designing robotic systems capable of generalizing to various tasks.