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Lex Fridman Podcast

#108 – Sergey Levine: Robotics and Machine Learning

2020-07-14 · 98 min · 15 entities

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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 supporting these sponsors: – ExpressVPN: 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 If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter , LinkedIn , Facebook , Medium , or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts , follow on Spotify , or support it on Patreon . Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. OUTLINE: 00:00 – Introduction 03:05 – 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