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1:07:29EN
Lex FridmanPodcastDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroModeration: Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.
9:59ENLex FridmanPodcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningModeration: Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.
18:46ENLex FridmanPodcastDeep Learning Plus One Idea: Ilya Sutskever on Building AGIModeration: Lex FridmanIn a May 2020 conversation, Sutskever discusses self-play, simulation, bodies and consciousness, tests of intelligence, and how an AGI might be governed and aligned.
17:40ENLex FridmanPodcastFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIModeration: Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.
1:27:30ENLex FridmanPodcastFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One LectureModeration: Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.
1:27:15ENLex FridmanPodcastPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement LearningModeration: Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.
13:58ENLex FridmanPodcastDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoModeration: Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.
57:55ENLex FridmanPodcastFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement LearningModeration: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the AI pipeline and Q-learning to deep Q-networks, AlphaGo Zero and the DeepTraffic competition.
1:31:29ENLex FridmanPodcastIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsModeration: Lex FridmanThe first lecture of MIT 6.S094 introduces neural networks, reinforcement learning and computer vision through the question of how hard driving really is.
1:12:00ENLex FridmanPodcastWhy Deep Learning Works at All: Yoshua Bengio on Composition, Saddle Points and the Case for Unsupervised LearningModeration: Lex FridmanIn a 2016 Deep Learning School talk, Yoshua Bengio explains the assumptions that let neural nets beat the curse of dimensionality and lays out the open challenges ahead.
1:02:06ENLex FridmanPodcastDeep Learning for Self-Driving Cars: Why Edge Cases and Human Nature Are the Real ProblemModeration: Lex FridmanLex Fridman opens MIT's 6.S094 with a tour of what deep learning is, how it works, what it has achieved and where it still breaks, framed around autonomous vehicles.