Рет қаралды 96,748
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 www.expressvpn.com/lexpod
- Cash App - use code "LexPodcast" and download:
- Cash App (App Store): apple.co/2sPrUHe
- Cash App (Google Play): bit.ly/2MlvP5w
EPISODE LINKS:
Sergey's Twitter: / svlevine
Sergey's Website: rail.eecs.berkeley.edu/
Sergey's Papers: scholar.google.com/citations?...
PODCAST INFO:
Podcast website:
lexfridman.com/podcast
Apple Podcasts:
apple.co/2lwqZIr
Spotify:
spoti.fi/2nEwCF8
RSS:
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 KZbin channel
- Twitter: / lexfridman
- LinkedIn: / lexfridman
- Facebook: / lexfridmanpage
- Instagram: / lexfridman
- Medium: / lexfridman
- Support on Patreon: / lexfridman