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1:29:10EN
Lex Fridman· 20 févr. 2020Podcast · 2 voixAndrew Ng: The Hardest Part of AI Is Rarely the AlgorithmInvité : Andrew Ng · Anime : Lex FridmanIn a conversation with Lex Fridman, Ng traces a path from late-night Coursera recordings to factory floors, arguing that messy data, habits, and starting small matter more than hype.Entreprise et stratégieDeep LearningScaling Laws+3
14:55EN
Lex Fridman· 29 oct. 2019Podcast · 2 voixKasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the QuestionsInvité : Garry Kasparov · Anime : Lex FridmanGarry Kasparov revisits the 1997 loss to Deep Blue, explains why machines beat humans in closed systems, and argues that the human role is to pick the right questions and not interfere with superior machine knowledge.AI HistoryPhilosophyHuman-AI Collaboration+3
1:03:13EN
Lex Fridman· 30 sept. 2019Podcast · 2 voixYou Can't Have Both Kinds of Fairness, Says Peter NorvigInvité : Peter Norvig · Anime : Lex FridmanThe co-author of Artificial Intelligence: A Modern Approach walks Lex Fridman through recidivism scores, utility functions, Lisp, MOOCs, and why human-level intelligence should not be the goal.Modèles et entraînementFondamentaux du MLSécurité et gouvernance+3
56:47EN
Lex Fridman· 8 sept. 2019Podcast · 2 voixWhy Vijay Kumar Refuses to Call Them DronesInvité : Vijay Kumar · Anime : Lex FridmanThe Penn roboticist on swarm design, true autonomy, and why batteries — not algorithms — still limit the sky.RoboticsAutonomous SystemsMulti-agent systems+3
1:46:01EN
Lex Fridman· 29 avr. 2019Podcast · 2 voixThe Night AlphaStar Beat TLO, the Team Went to a BarInvité : Oriol Vinyals · Anime : Lex FridmanOriol Vinyals on how DeepMind turned StarCraft II into a sequence problem, built a league of agents, and still refuses to call the game solved.AgentsReinforcement LearningMulti-agent systems+3
1:01:24EN
Lex Fridman· 12 mars 2019Podcast · 2 voixLeslie Kaelbling: You Buy the Ticket Before You Can Plan the AirportInvité : Leslie Kaelbling · Anime : Lex FridmanThe MIT roboticist tells Lex Fridman why abstractions, belief-space control, and built-in bias matter more than picking a tribe of symbols or neural nets.AgentsReinforcement LearningRobotics+3
1:19:59EN
Lex Fridman· 23 déc. 2018Podcast · 2 voixSchmidhuber’s bet: true meta-learning rewrites the learner, not the last layerInvité : Juergen Schmidhuber · Anime : Lex FridmanJürgen Schmidhuber tells Lex Fridman how Gödel machines, compression-as-science, Power Play, LSTMs, and world models all descend from a teenage plan to multiply one person’s curiosity into a better physicist than he could ever be.Modèles et entraînementFondamentaux du MLAGI Timelines+3
42:45EN
Lex Fridman· 16 déc. 2018Podcast · 2 voixA one-legged robot learned a backflip from "this is better"Invité : Pieter Abbeel · Anime : Lex FridmanPieter Abbeel tells Lex Fridman why preference comparisons, self-play, ten-minute demos, and messy ensembles of simulators are the practical path through deep reinforcement learning.Modèles et entraînementReinforcement LearningRobotics+2
1:07:29EN
Lex FridmanPodcastDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroAnime : 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.Modèles et entraînementReinforcement LearningDeep Learning+3
9:59EN
Lex FridmanPodcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningAnime : 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.Modèles et entraînementFondamentaux du MLDeep Learning+3
18:46EN
Lex FridmanPodcastDeep Learning Plus One Idea: Ilya Sutskever on Building AGIAnime : 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.Modèles et entraînementAGIReinforcement Learning+3
17:40EN
Lex FridmanPodcastFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIAnime : 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.Modèles et entraînementReinforcement LearningAI research+3
1:27:30EN
Lex FridmanPodcastFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One LectureAnime : Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.Modèles et entraînementReinforcement LearningDeep Learning+2
1:27:15EN
Lex FridmanPodcastPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement LearningAnime : 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.Modèles et entraînementReinforcement LearningFondamentaux du ML+3
13:58EN
Lex FridmanPodcastDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoAnime : 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.Modèles et entraînementReinforcement LearningFondamentaux du ML+3
57:55EN
Lex FridmanPodcastFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement LearningAnime : 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.Modèles et entraînementReinforcement LearningDeep Learning+3
1:00:15EN
Lex FridmanPodcast · 2 voixCircuit Search, Hindsight and Self-Play: Ilya Sutskever's Case for Where Learning Is GoingInvité : Ilya Sutskever · Anime : Lex FridmanIn an MIT AGI lecture, OpenAI's co-founder explains why deep learning works, then walks through meta-learning, hindsight experience replay, sim-to-real transfer, self-play and learning goals from human feedback.Modèles et entraînementFondamentaux du MLDeep Learning+3
26:45EN
Lex FridmanPodcast · 2 voixStart Small, Build Habits, Pick Your Team: Andrew Ng's Practical Advice for Learning Deep LearningInvité : Andrew Ng · Anime : Lex FridmanIn a clip from the Lex Fridman Podcast, Andrew Ng explains how to begin in deep learning, how to study effectively, and how to choose a career path.Modèles et entraînementDeep LearningFondamentaux du ML+3
1:31:29EN
Lex FridmanPodcastIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsAnime : 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.Modèles et entraînementDeep LearningAutonomous Driving+3
1:12:00EN
Lex FridmanPodcastWhy Deep Learning Works at All: Yoshua Bengio on Composition, Saddle Points and the Case for Unsupervised LearningAnime : 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.Modèles et entraînementFondamentaux du MLDeep Learning+2
1:02:06EN
Lex FridmanPodcastDeep Learning for Self-Driving Cars: Why Edge Cases and Human Nature Are the Real ProblemAnime : 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.Modèles et entraînementAutonomous DrivingDeep Learning+3