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77 件
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2:10:39EN
Lex Fridman· 2022年7月1日ポッドキャスト · 2 人Demis Hassabis: Solve Intelligence, Then Solve Everything Elseゲスト Demis Hassabis · ホスト Lex FridmanThe DeepMind CEO tells Lex Fridman why the Turing Test is the wrong exam, how AlphaFold rewrote biology, and why the quiet radio sky suggests we are probably alone.モデルと学習AI researchAGI(汎用人工知能)+3
1:56:17EN
Lex Fridman· 2021年4月19日ポッドキャスト · 2 人If You Reran Earth a Million Times, Would Anything Like Us Appear?ゲスト Risto Miikkulainen · ホスト Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.モデルと学習機械学習の基礎AI research+3
2:01:07EN
Lex Fridman· 2020年12月12日ポッドキャスト · 2 人Michael Littman isn’t waiting for a runaway god. He’s watching us.ゲスト Michael Littman · ホスト Lex FridmanThe Brown reinforcement-learning researcher tells Lex Fridman why accidental superintelligence feels like a 747 assembling itself — and why social media, rote language, and theory of mind worry him more.モデルと学習Reinforcement LearningAGI(汎用人工知能)+3
1:37:31EN
Lex Fridman· 2020年7月14日ポッドキャスト · 2 人The Robot That Brought the Beer Was Being Teleoperatedゲスト Sergey Levine · ホスト Lex FridmanSergey Levine tells Lex Fridman why hardware is almost closed, why common sense has to be lived, and why offline reinforcement learning is the missing on-ramp from logs to robots that keep getting better.モデルと学習RoboticsReinforcement Learning+3
2:00:32EN
Lex Fridman· 2020年7月3日ポッドキャスト · 2 人Slow Synapses Grow Fast Learners — Warmth Is the Harder Problemゲスト Matt Botvinick · ホスト Lex FridmanDeepMind neuroscience director Matt Botvinick tells Lex Fridman how prefrontal cortex, meta-reinforcement learning, and dopamine research meet the human question of what a better life with AI would actually look like.モデルと学習Neuroscience & AIReinforcement Learning+3
1:48:01EN
Lex Fridman· 2020年4月3日ポッドキャスト · 2 人David Silver: AlphaGo Won by Taking Human Knowledge Outゲスト David Silver · ホスト Lex FridmanThe DeepMind researcher behind AlphaGo and AlphaZero tells Lex Fridman how an unclaimed million-dollar Go prize, a BBC Micro at age seven, and a honeymoon insight led to superhuman self-play.モデルと学習Reinforcement LearningDeep Learning+3
1:38:33EN
Lex Fridman· 2020年3月19日ポッドキャスト · 2 人Maybe people are rational under different assumptionsゲスト Anca Dragan · ホスト Lex FridmanAnca Dragan talks with Lex Fridman about inverse reinforcement learning, autonomous driving, and why a written reward is evidence rather than law.エージェントRoboticsReinforcement Learning+3
1:39:56EN
Lex Fridman· 2020年2月26日ポッドキャスト · 2 人Why Marcus Hutter Treats Compression as Intelligence Itselfゲスト Marcus Hutter · ホスト Lex FridmanThe DeepMind researcher behind AIXI tells Lex Fridman why a Wikipedia compression contest, Solomonoff induction, and an incomputable formula belong in the same conversation.エージェントAGI(汎用人工知能)AI research+3
1:29:10EN
Lex Fridman· 2020年2月20日ポッドキャスト · 2 人Andrew Ng: The Hardest Part of AI Is Rarely the Algorithmゲスト Andrew Ng · ホスト 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.企業と戦略Deep LearningScaling Laws+3
14:55EN
Lex Fridman· 2019年10月29日ポッドキャスト · 2 人Kasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the Questionsゲスト Garry Kasparov · ホスト 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· 2019年9月30日ポッドキャスト · 2 人You Can't Have Both Kinds of Fairness, Says Peter Norvigゲスト Peter Norvig · ホスト 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.モデルと学習機械学習の基礎安全性とガバナンス+3
56:47EN
Lex Fridman· 2019年9月8日ポッドキャスト · 2 人Why Vijay Kumar Refuses to Call Them Dronesゲスト Vijay Kumar · ホスト 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· 2019年4月29日ポッドキャスト · 2 人The Night AlphaStar Beat TLO, the Team Went to a Barゲスト Oriol Vinyals · ホスト 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.エージェントReinforcement LearningMulti-agent systems+3
1:01:24EN
Lex Fridman· 2019年3月12日ポッドキャスト · 2 人Leslie Kaelbling: You Buy the Ticket Before You Can Plan the Airportゲスト Leslie Kaelbling · ホスト 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.エージェントReinforcement LearningRobotics+3
1:19:59EN
Lex Fridman· 2018年12月23日ポッドキャスト · 2 人Schmidhuber’s bet: true meta-learning rewrites the learner, not the last layerゲスト Juergen Schmidhuber · ホスト 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.モデルと学習機械学習の基礎AGI Timelines+3
42:45EN
Lex Fridman· 2018年12月16日ポッドキャスト · 2 人A one-legged robot learned a backflip from "this is better"ゲスト Pieter Abbeel · ホスト 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.モデルと学習Reinforcement LearningRobotics+2
1:07:29EN
Lex FridmanポッドキャストDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroホスト 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.モデルと学習Reinforcement LearningDeep Learning+3
9:59EN
Lex FridmanポッドキャストIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learningホスト 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.モデルと学習機械学習の基礎Deep Learning+3
18:46EN
Lex FridmanポッドキャストDeep Learning Plus One Idea: Ilya Sutskever on Building AGIホスト 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.モデルと学習AGI(汎用人工知能)Reinforcement Learning+3
17:40EN
Lex FridmanポッドキャストFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIホスト 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.モデルと学習Reinforcement LearningAI research+3
1:27:30EN
Lex FridmanポッドキャストFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lectureホスト Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.モデルと学習Reinforcement LearningDeep Learning+2
1:27:15EN
Lex FridmanポッドキャストPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement Learningホスト 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.モデルと学習Reinforcement Learning機械学習の基礎+3
13:58EN
Lex FridmanポッドキャストDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoホスト 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.モデルと学習Reinforcement Learning機械学習の基礎+3
57:55EN
Lex FridmanポッドキャストFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement Learningホスト 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.モデルと学習Reinforcement LearningDeep Learning+3
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