Sergey Levine: Robotics and Machine Learning | Lex Fridman Podcast #108
Current state-of-the-art robots still lack the flexibility and common sense reasoning that humans possess, particularly in handling unexpected situations
Sergey Levine
1 episode on Lex Fridman Podcast
Sergey Levine is a professor of computer science at UC Berkeley and a leading researcher in deep learning, reinforcement learning, robotics, and computer vision. He has developed foundational algorithms for end-to-end training of neural network policies, scalable inverse reinforcement learning methods, and deep reinforcement learning techniques that are shaping the future of autonomous systems.