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90 件
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4:25:13EN
Lex Fridman· 2026年1月31日ポッドキャストThe Architecture Barely Changed. Data, Cost, and Open Weights Did.ホスト Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.モデルと学習Scaling LawsOpen-weight models+3
5:15:00EN
Lex Fridman· 2024年11月11日ポッドキャスト · 2 人Dario Amodei Has Seen This Scaling Movie Enough Timesゲスト Dario Amodei · ホスト Lex FridmanAnthropic’s CEO puts numbers on frontier training costs and AGI, then hands the mic to the people who shape Claude’s character and look inside its weights.モデルと学習安全性とガバナンスScaling Laws+3
2:47:17EN
Lex Fridman· 2024年3月7日ポッドキャスト · 2 人If You Want Human-Level AI, Abandon Generative Modelsゲスト Yann Lecun · ホスト Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.モデルと学習World modelsAGI(汎用人工知能)+3
4:14:33EN
Lex Fridman· 2023年5月9日ポッドキャスト · 2 人The Next Token Is Not a Proof: Stephen Wolfram on ChatGPT and Computational Truthゲスト Stephen Wolfram · ホスト Lex FridmanIn his fourth conversation with Lex Fridman, Stephen Wolfram contrasts large language models with Wolfram|Alpha, then follows computational irreducibility from ChatGPT through observers, thermodynamics, and the three great theories of twentieth-century physics.モデルと学習PhilosophyAI research+3
3:28:47EN
Lex Fridman· 2022年10月29日ポッドキャスト · 2 人Karpathy Calls Trained Neural Nets Complicated Alien Artifactsゲスト Andrej Karpathy · ホスト Lex FridmanOn Lex Fridman's podcast, Andrej Karpathy refuses the brain analogy, walks the Fermi paradox through Nick Lane's chemistry, and treats the Transformer as a general-purpose differentiable computer.モデルと学習AGI(汎用人工知能)Autonomous Driving+3
2:10:08EN
Lex Fridman· 2022年7月26日ポッドキャスト · 2 人Gato Is Only the Beginningゲスト Oriol Vinyals · ホスト Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.モデルと学習AGI(汎用人工知能)AI research+3
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
2:45:10EN
Lex Fridman· 2022年1月22日ポッドキャスト · 2 人A Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.ゲスト Yann Lecun · ホスト Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.モデルと学習World modelsComputer Vision+3
2:31:57EN
Lex Fridman· 2021年9月20日ポッドキャスト · 2 人Jay McClelland on How Thought Emerges From Neural Networksゲスト Jay McClelland · ホスト Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.モデルと学習機械学習の基礎Deep Learning+3
2:51:33EN
Lex Fridman· 2021年8月29日ポッドキャスト · 2 人The Self Is a GPT Prompt: Wojciech Zaremba on Consciousness, Codex, and Fermi's Silenceゲスト Wojciech Zaremba · ホスト Lex FridmanOpenAI co-founder Wojciech Zaremba tells Lex Fridman he thinks we might be alone in the universe — and that GPT-3, Codex, and a one-handed robot already hint at how intelligence is built.モデルと学習コーディングエージェント機械学習の基礎+3
2:18:29EN
Lex Fridman· 2021年8月8日ポッドキャスト · 2 人Your Cortex Is 150,000 Brains Voting on a Coffee Cupゲスト Jeff Hawkins · ホスト Lex FridmanJeff Hawkins tells Lex Fridman that intelligence is learning a model of the world, the neocortex is tens of thousands of independent maps that vote, and the fastest path to machine intelligence is reverse-engineering that sheet.モデルと学習Neuroscience & AI機械学習の基礎+3
2:30:30EN
Lex Fridman· 2021年7月31日ポッドキャスト · 2 人The Fallacy of the Successful First Stepゲスト Ishan Misra · ホスト Lex FridmanBerkeley's Jitendra Malik explains why computer vision still looks easy, why fully autonomous driving is not near, and what children know that today's networks do not.モデルと学習Computer VisionMultimodal AI+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
2:10:06EN
Lex Fridman· 2020年8月14日ポッドキャスト · 2 人You Might Have to Understand the World to Understand the Letter Aゲスト Dileep George · ホスト Lex FridmanDileep George on recursive cortical networks, why a five-year-old can read any new CAPTCHA, and what the Wright brothers actually learned from birds.モデルと学習Neuroscience & AIWorld models+3
1:41:37EN
Lex Fridman· 2020年7月21日ポッドキャスト · 2 人The Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't Solvedゲスト Jitendra Malik · ホスト Lex FridmanBerkeley's Jitendra Malik tells Lex Fridman why computer vision keeps underestimating itself, why full self-driving still needs cognition, and why vision is the parent of language.モデルと学習画像と動画Autonomous Driving+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
3:00:18EN
Lex Fridman· 2020年6月13日ポッドキャスト · 2 人Only a Simulation Can Be Consciousゲスト Joscha Bach · ホスト Lex FridmanJoscha Bach tells Lex Fridman why a neuron cannot feel anything, why existence is the default, and why this dying world is still the best level of the game.モデルと学習Consciousness & IntelligencePhilosophy of Mind+3
1:37:28EN
Lex Fridman· 2020年5月8日ポッドキャスト · 2 人We Are Still Massively Underestimating Deep Learningゲスト Ilya Sutskever · ホスト Lex FridmanIlya Sutskever tells Lex Fridman why 2012 was about conviction, why bigger models can get worse before they get better, and what he would do with an AGI.モデルと学習Deep Learning機械学習の基礎+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
1:12:48EN
Lex Fridman· 2020年2月29日ポッドキャスト · 2 人John Hopfield's Physics of Mind: Glitches Become Featuresゲスト John Hopfield · ホスト Lex FridmanThe Princeton physicist walks Lex Fridman from a wobbly London bridge to Hopfield networks, consciousness-as-story, and why his famous model still does not explain learning.モデルと学習Neuroscience & AI機械学習の基礎+3
1:44:55EN
Lex Fridman· 2020年2月14日ポッドキャスト · 2 人If You Need 60,000 Digits, You Have Not Found Intelligenceゲスト Vladimir Vapnik · ホスト Lex FridmanVladimir Vapnik tells Lex Fridman that intelligence is the art of shrinking a sea of functions with a few good predicates — and that MNIST, solved with sixty examples per class, is the test.モデルと学習機械学習の基礎AI research+3
49:53EN
Lex Fridman· 2019年11月25日ポッドキャスト · 2 人Gilbert Strang still teaches with thick chalk and four subspacesゲスト Gilbert Strang · ホスト Lex FridmanThe MIT linear-algebra legend talks with Lex Fridman about OpenCourseWare, singular values, neural nets as a million folds, and why calculus hogged the undergraduate timetable.モデルと学習機械学習の基礎Deep Learning+3
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