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#108 – Sergey Levine: Robotics and Machine Learning

Lex Fridman Podcast

Conversations that explore technology, history, philosophy, physics, mathematics, biology, chemistry, engineering, AI, robotics, programming, music, film, art, sports, psychology, neuroscience, geopolitics, business, economics, religion, astronomy, and the human condition with people from all walks of life.

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.

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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

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: <a href="https://www.expressvpn.com/lexpod">https://www.expressvpn.com/lexpod</a> 
– Cash App – use code “LexPodcast” and download: 
– Cash App (App Store): <a href="https://apple.co/2sPrUHe">https://apple.co/2sPrUHe</a> 
– Cash App (Google Play): <a href="https://bit.ly/2MlvP5w">https://bit.ly/2MlvP5w</a>
If you would like to get more information about this podcast go to <a href="https://lexfridman.com/ai">https://lexfridman.com/ai</a> or connect with @lexfridman on <a href="https://twitter.com/lexfridman">Twitter</a>, <a href="https://www.linkedin.com/in/lexfridman/">LinkedIn</a>, <a href="https://www.facebook.com/lexfridman">Facebook</a>, <a href="https://medium.com/@lexfridman">Medium</a>, or <a href="https://www.youtube.com/lexfridman">YouTube</a> where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on <a href="https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584">Apple Podcasts</a>, follow on <a href="https://open.spotify.com/show/2MAi0BvDc6GTFvKFPXnkCL">Spotify</a>, or support it on <a href="https://www.patreon.com/lexfridman">Patreon</a>.
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

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#108 – Sergey Levine: Robotics and Machine Learning

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