Sergey discusses innovative approaches to connecting language models with robotic tasks, highlighting the importance of grounding in physical interactions. He explains how using reinforcement learning value functions can enhance task feasibility by identifying which actions are possible in a given state. This intersection of semantics and physical affordances opens new avenues for research in robotics and AI.
