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26 件
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1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年10月9日ポッドキャスト · 2 人10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledgerホスト Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.オープンソースとコミュニティOpen-weight modelsReinforcement Learning+3
36:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年10月9日ポッドキャスト · 2 人STaR's Author Wants Models With EQ, Not Just More IQホスト Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.モデルと学習Post-trainingReinforcement Learning+3
1:02:54EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年7月17日ポッドキャスト · 2 人Enterprise Coding Tools Flipped the 80/20. Reflection AI Built the Other Halfホスト Sarah Guo, Elad GilFormer Gemini reward-model lead Misha Laskin on Asimov, why comprehension beats generation, and why there is no such thing as generalization—only pulling the test distribution into train.コーディングエージェントエージェント工学評価(Evals)+3
38:10EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年5月1日ポッドキャスト · 2 人o3 should wait exactly as long as the answer takesホスト Sarah Guo, Elad GilOpenAI researchers Eric Mitchell and Brandon McKinzie tell No Priors why o3's leap is a chain of tools during reasoning — and why you should send the same prompt a hundred times.モデルと学習Reasoning & test-time computeReinforcement Learning+3
30:46EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年4月24日ポッドキャスト · 2 人Deep Research Turned Web Browsing into a Trainable Problemホスト Sarah Guo, Elad GilOpenAI researcher Isa Fulford explains why a side project on read-only synthesis became an agent, when reinforcement fine-tuning is worth it, and why models will hack the search engine you gave them.エージェントエージェント工学Reinforcement Learning+3
39:22EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年11月14日ポッドキャスト · 2 人A Fields Medalist Stuck for Two Hours. AlphaProof Climbed for Three Days.ホスト Sarah Guo, Elad GilThe DeepMind team behind AlphaProof tells Sarah Guo and Elad Gil how an AlphaZero-style agent, a Lean verifier, and test-time reinforcement learning reached IMO silver — and why the missing skill is still theory building.エージェントReinforcement LearningReasoning & test-time compute+1
46:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年8月1日ポッドキャスト · 2 人Oriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are Numberedホスト Sarah Guo, Elad GilGoogle DeepMind’s VP of research on Gemini, long context, the coming shift from pretraining to RL, and why AGI may never have a finish line.モデルと学習AGI TimelinesPretraining & midtraining+3
1:43:47EN
Lex Fridman· 2024年2月16日ポッドキャスト · 2 人You Have to Run Before You Can Walk: Marc Raibert on Making Metal Look Aliveゲスト Marc Raibert · ホスト 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.RoboticsAutonomous SystemsCompany Building+3
2:27:58EN
Lex Fridman· 2023年4月28日ポッドキャスト · 2 人It took Atlas fourteen years to walk the way Playter wantedゲスト Robert Playter · ホスト 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.RoboticsAutonomous SystemsAI research+3
2:29:21EN
Lex Fridman· 2022年12月6日ポッドキャスト · 2 人The Poker Bot That Never Tried to Read a Soulゲスト Noam Brown · ホスト 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.エージェントReinforcement LearningMulti-agent systems+1
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
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
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