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Sergey Levine is a professor at Berkeley and a world-class researcher in deep learning, reinforcement learning, robotics, and computer vision, including the development of algorithms for end-to-end training of neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep RL algorithms. Support this podcast by signing up with these sponsors: - ExpressVPN at https://www.expressvpn.com/lexpod - Cash App - use code "LexPodcast" and download: - Cash App (App Store): https://apple.co/2sPrUHe - Cash App (Google Play): https://bit.ly/2MlvP5w EPISODE LINKS: Sergey's Twitter: / svlevine Sergey's Website: http://rail.eecs.berkeley.edu/ Sergey's Papers: https://scholar.google.com/citations?... PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: • Lex Fridman Podcast Clips playlist: • Lex Fridman Podcast Clips OUTLINE: 0:00 - Introduction 3:05 - State-of-the-art robots vs humans 16:13 - Robotics may help us understand intelligence 22:49 - End-to-end learning in robotics 27:01 - Canonical problem in robotics 31:44 - Commonsense reasoning in robotics 34:41 - Can we solve robotics through learning? 44:55 - What is reinforcement learning? 1:06:36 - Tesla Autopilot 1:08:15 - Simulation in reinforcement learning 1:13:46 - Can we learn gravity from data? 1:16:03 - Self-play 1:17:39 - Reward functions 1:27:01 - Bitter lesson by Rich Sutton 1:32:13 - Advice for students interesting in AI 1:33:55 - Meaning of life CONNECT: - Subscribe to this YouTube channel - Twitter: / lexfridman - LinkedIn: / lexfridman - Facebook: / lexfridmanpage - Instagram: / lexfridman - Medium: / lexfridman - Support on Patreon: / lexfridman