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59 件
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38:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年9月18日ポッドキャスト · 2 人Diffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Siliconホスト Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.モデルと学習InferenceAI cost & performance+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
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
35:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年3月20日ポッドキャスト · 2 人Robots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.ホスト Sarah Guo, Elad GilPhysical Intelligence’s cofounder tells No Priors why a generalist robot model has to be trained across embodiments, why open-sourcing hardware is a bet against the problem going unsolved, and why humanoids are a little overrated.モデルと学習RoboticsData quality & curation+3
57:41EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025年2月25日ポッドキャスト · 2 人A Hundred Million Cells, Four People, Three Days: Biology's ImageNet Momentホスト Sarah Guo, Elad GilVevo Therapeutics and the Arc Institute open-sourced Tahoe-100M and a 230-million-cell atlas in the same week — and argued that virtual cells, not just protein folders, are the next language model of biology.モデルと学習AI for scienceData quality & curation+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
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
34:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年6月27日ポッドキャスト · 2 人Five Independent Teams Found the Same 10-to-1 Mix That Beats Transformersホスト Sarah Guo, Elad GilThe authors of S4 and Mamba argue that mostly state-space layers plus a dash of attention is the architecture that actually works—and they are shipping it first as real-time speech.モデルと学習Transformers & attention音声 AI+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
40:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年1月25日ポッドキャスト · 2 人99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses Firstホスト Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.モデルと学習RoboticsFoundation Models+3
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年11月2日ポッドキャスト · 2 人Reliability is the bottleneck. Autonomy is what would make AI feel alive.ホスト Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.モデルと学習AGI(汎用人工知能)Scaling Laws+3
37:01EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年9月28日ポッドキャスト · 2 人DNA Is Code, but You Compile It with a Pipetteホスト Sarah Guo, Elad GilGinkgo Bioworks CEO Jason Kelly tells No Priors why cells are worth the magic, why biology has no AWS, and why a pandemic should look like cybersecurity.モデルと学習AI for scienceBiosecurity+3
35:24EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年8月24日ポッドキャスト · 2 人The Author of Attention Is All You Need Now Compiles mRNA Like Bytecodeホスト Sarah Guo, Elad GilJakob Uszkoreit on why Transformers won, why models spend compute on the wrong things, and why drug discovery has to become generation rather than screening.モデルと学習AI for scienceTransformers & attention+2
42:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年5月18日ポッドキャスト · 2 人Ten Percent of Search Is Health — and the Doctor Is Googling Tooホスト Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.モデルと学習AI in healthcare安全性とガバナンス+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
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年4月6日ポッドキャスト · 2 人A 6-Billion-Parameter Clone of ChatGPT’s Core Trickホスト Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.モデルと学習Open-weight modelsファインチューニング+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
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