筛选结果
32 篇排序
1:43:47EN
Lex Fridman· 2024年2月16日播客 · 2 人对谈You Have to Run Before You Can Walk: Marc Raibert on Making Metal Look Alive嘉宾 Marc Raibert · 主持 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.
2:27:58EN → 简体中文Lex Fridman· 2023年4月28日播客 · 2 人对谈Atlas 用了 14 年，才走出 Playter 想要的步态嘉宾 Robert Playter · 主持 Lex Fridman波士顿动力首席执行官 Robert Playter 回顾了 30 年的历程：从麻省理工学院（MIT）地下室里的弹跳杆，到 Atlas、Spot 和 Stretch，以及公司为什么至今仍然设计可以摔倒的机器。
2:29:21EN → 简体中文Lex Fridman· 2022年12月6日播客 · 2 人对谈从不试图读懂人心的扑克机器人嘉宾 Noam Brown · 主持 Lex FridmanNoam Brown 向 Lex Fridman 讲述：一台逼近纳什均衡（Nash equilibrium）的机器人如何碾压单挑无限注德州扑克（heads-up no-limit Hold'em），Pluribus 怎样在六人桌上做到同样的事，以及《外交》为什么需要一个能赢得人类信任的 AI。
2:10:39EN → 简体中文Lex Fridman· 2022年7月1日播客 · 2 人对谈Demis Hassabis：先解决智能，再解决其他一切嘉宾 Demis Hassabis · 主持 Lex FridmanDeepMind 首席执行官告诉 Lex Fridman：图灵测试为什么是一份出错的考卷，AlphaFold 如何改写了生物学，以及射电天空的寂静为何暗示我们或许是孤独的。
1:56:17ENLex Fridman· 2021年4月19日播客 · 2 人对谈If You Reran Earth a Million Times, Would Anything Like Us Appear?嘉宾 Risto Miikkulainen · 主持 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· 2020年12月12日播客 · 2 人对谈Michael Littman isn’t waiting for a runaway god. He’s watching us.嘉宾 Michael Littman · 主持 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· 2020年7月14日播客 · 2 人对谈The Robot That Brought the Beer Was Being Teleoperated嘉宾 Sergey Levine · 主持 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· 2020年7月3日播客 · 2 人对谈Slow Synapses Grow Fast Learners — Warmth Is the Harder Problem嘉宾 Matt Botvinick · 主持 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· 2020年4月3日播客 · 2 人对谈David Silver: AlphaGo Won by Taking Human Knowledge Out嘉宾 David Silver · 主持 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· 2020年3月19日播客 · 2 人对谈Maybe people are rational under different assumptions嘉宾 Anca Dragan · 主持 Lex FridmanAnca Dragan talks with Lex Fridman about inverse reinforcement learning, autonomous driving, and why a written reward is evidence rather than law.
1:39:56EN → 简体中文Lex Fridman· 2020年2月26日播客 · 2 人对谈为什么 Marcus Hutter 把压缩视为智能本身嘉宾 Marcus Hutter · 主持 Lex Fridman这位 AIXI 的提出者、DeepMind 研究者向 Lex Fridman 解释，为什么维基百科压缩竞赛、所罗门诺夫归纳和一个不可计算的公式应该放在同一场对话里。
1:29:10ENLex Fridman· 2020年2月20日播客 · 2 人对谈Andrew Ng: The Hardest Part of AI Is Rarely the Algorithm嘉宾 Andrew Ng · 主持 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· 2019年10月29日播客 · 2 人对谈Kasparov on Deep Blue, AlphaZero, and Why Machines Win Closed Systems but Humans Still Choose the Questions嘉宾 Garry Kasparov · 主持 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· 2019年9月30日播客 · 2 人对谈You Can't Have Both Kinds of Fairness, Says Peter Norvig嘉宾 Peter Norvig · 主持 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· 2019年9月8日播客 · 2 人对谈Why Vijay Kumar Refuses to Call Them Drones嘉宾 Vijay Kumar · 主持 Lex FridmanThe Penn roboticist on swarm design, true autonomy, and why batteries — not algorithms — still limit the sky.
1:46:01ENLex Fridman· 2019年4月29日播客 · 2 人对谈The Night AlphaStar Beat TLO, the Team Went to a Bar嘉宾 Oriol Vinyals · 主持 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· 2019年3月12日播客 · 2 人对谈Leslie Kaelbling: You Buy the Ticket Before You Can Plan the Airport嘉宾 Leslie Kaelbling · 主持 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· 2018年12月23日播客 · 2 人对谈Schmidhuber’s bet: true meta-learning rewrites the learner, not the last layer嘉宾 Juergen Schmidhuber · 主持 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· 2018年12月16日播客 · 2 人对谈A one-legged robot learned a backflip from "this is better"嘉宾 Pieter Abbeel · 主持 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 Fridman播客Deep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZero主持 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 Fridman播客Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning主持 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 Fridman播客Deep Learning Plus One Idea: Ilya Sutskever on Building AGI主持 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 Fridman播客From AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AI主持 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 Fridman播客From NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lecture主持 Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.加载更多已显示 24 篇，共 32 篇