필터 결과
32개정렬
1:43:47EN
Lex Fridman· 2024년 2월 16일팟캐스트 · 2명You Have to Run Before You Can Walk: Marc Raibert on Making Metal Look Alive게스트 Marc Raibert · 진행자 Lex FridmanThe Boston Dynamics founder tells Lex Fridman why aggressive hopping beat cautious walking, how 109 Atlas falls became a method, and why robots still need a second kind of intelligence.
2:27:58ENLex Fridman· 2023년 4월 28일팟캐스트 · 2명It took Atlas fourteen years to walk the way Playter wanted게스트 Robert Playter · 진행자 Lex FridmanBoston Dynamics CEO Robert Playter traces thirty years from a MIT basement pogo stick to Atlas, Spot, and Stretch — and why the company still designs machines that are allowed to fall.
2:29:21ENLex Fridman· 2022년 12월 6일팟캐스트 · 2명The Poker Bot That Never Tried to Read a Soul게스트 Noam Brown · 진행자 Lex FridmanNoam Brown tells Lex Fridman how a Nash-equilibrium bot crushed heads-up no-limit Hold'em, how Pluribus did it six-handed, and why Diplomacy required an AI that could earn human trust.
2:10:39ENLex Fridman· 2022년 7월 1일팟캐스트 · 2명Demis Hassabis: Solve Intelligence, Then Solve Everything Else게스트 Demis Hassabis · 진행자 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.
1:56:17ENLex Fridman· 2021년 4월 19일팟캐스트 · 2명If You Reran Earth a Million Times, Would Anything Like Us Appear?게스트 Risto Miikkulainen · 진행자 Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.
2:01:07ENLex Fridman· 2020년 12월 12일팟캐스트 · 2명Michael Littman isn’t waiting for a runaway god. He’s watching us.게스트 Michael Littman · 진행자 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.
1:37:31ENLex Fridman· 2020년 7월 14일팟캐스트 · 2명The Robot That Brought the Beer Was Being Teleoperated게스트 Sergey Levine · 진행자 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.
2:00:32ENLex Fridman· 2020년 7월 3일팟캐스트 · 2명Slow Synapses Grow Fast Learners — Warmth Is the Harder Problem게스트 Matt Botvinick · 진행자 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.
1:48:01ENLex Fridman· 2020년 4월 3일팟캐스트 · 2명David Silver: AlphaGo Won by Taking Human Knowledge Out게스트 David Silver · 진행자 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.
1:38:33ENLex Fridman· 2020년 3월 19일팟캐스트 · 2명Maybe people are rational under different assumptions게스트 Anca Dragan · 진행자 Lex FridmanAnca Dragan talks with Lex Fridman about inverse reinforcement learning, autonomous driving, and why a written reward is evidence rather than law.
1:39:56ENLex Fridman· 2020년 2월 26일팟캐스트 · 2명Why Marcus Hutter Treats Compression as Intelligence Itself게스트 Marcus Hutter · 진행자 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.
1:29:10ENLex Fridman· 2020년 2월 20일팟캐스트 · 2명Andrew Ng: The Hardest Part of AI Is Rarely the Algorithm게스트 Andrew Ng · 진행자 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.
14:55ENLex Fridman· 2019년 10월 29일팟캐스트 · 2명Kasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the Questions게스트 Garry Kasparov · 진행자 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.
1:03:13ENLex Fridman· 2019년 9월 30일팟캐스트 · 2명You Can't Have Both Kinds of Fairness, Says Peter Norvig게스트 Peter Norvig · 진행자 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.
56:47ENLex Fridman· 2019년 9월 8일팟캐스트 · 2명Why Vijay Kumar Refuses to Call Them Drones게스트 Vijay Kumar · 진행자 Lex FridmanThe Penn roboticist on swarm design, true autonomy, and why batteries — not algorithms — still limit the sky.
1:46:01ENLex Fridman· 2019년 4월 29일팟캐스트 · 2명The Night AlphaStar Beat TLO, the Team Went to a Bar게스트 Oriol Vinyals · 진행자 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.
1:01:24ENLex Fridman· 2019년 3월 12일팟캐스트 · 2명Leslie Kaelbling: You Buy the Ticket Before You Can Plan the Airport게스트 Leslie Kaelbling · 진행자 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.
1:19:59ENLex Fridman· 2018년 12월 23일팟캐스트 · 2명Schmidhuber’s bet: true meta-learning rewrites the learner, not the last layer게스트 Juergen Schmidhuber · 진행자 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.
42:45ENLex Fridman· 2018년 12월 16일팟캐스트 · 2명A one-legged robot learned a backflip from "this is better"게스트 Pieter Abbeel · 진행자 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.
1:07:29ENLex Fridman팟캐스트Deep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZero진행자 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 Fridman팟캐스트Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning진행자 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 Fridman팟캐스트Deep Learning Plus One Idea: Ilya Sutskever on Building AGI진행자 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 Fridman팟캐스트From AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AI진행자 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 Fridman팟캐스트From NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lecture진행자 Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.더 보기32개 중 24개 표시