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36:19EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026년 6월 26일팟캐스트 · 2명The Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score Models진행자 Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
1:16:21ENNo Priors: AI, Machine Learning, Tech, & Startups· 2026년 1월 8일팟캐스트 · 2명Jensen Huang’s Year-End Case That Token Costs Can Fall a Billion-Fold Without Killing Jobs진행자 Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO uses radiology, open source, and a $2 trillion R&D budget to argue that 2025’s extremes missed the stack.
18:59ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 10월 31일팟캐스트 · 2명86 Out of 100: The Clips No Priors Could Not Leave on the Cutting-Room Floor진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil stitch nine 2025 conversations into one short tour of legal AI, spatial intelligence, jobs, deterrence, and a doctor who made it home for dinner.
36:58ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 10월 9일팟캐스트 · 2명STaR's Author Wants Models With EQ, Not Just More IQ진행자 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.
13:30EN
3Blue1Brown· 2025년 8월 17일How AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.
38:10ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 5월 1일팟캐스트 · 2명o3 should wait exactly as long as the answer takes진행자 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.
39:22ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024년 11월 14일팟캐스트 · 2명A Fields Medalist Stuck for Two Hours. AlphaProof Climbed for Three Days.진행자 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.
29:29ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024년 10월 17일팟캐스트 · 2명The Week AI Won Its First Nobels, Two Investors Listed Who Is Most at Risk진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil talk NotebookLM, intelligent NPCs, artificial wombs, OpenAI’s o1, and which businesses look AI-durable.
1:00:36ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023년 2월 2일팟캐스트 · 2명Forty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lesson진행자 Sarah Guo, Elad GilMeta’s Noam Brown tells Sarah Guo and Elad Gil how Cicero negotiated in English for 40 games on a tiny web community — and why thinking at decision time beat three years of scaling.
1:26:21EN
Lex Fridman· 2018년 12월 9일팟캐스트 · 2명The Machine Should Never Treat Its Objective as Gospel게스트 Stuart Russell · 진행자 Lex FridmanStuart Russell talks with Lex Fridman about metareasoning, self-driving reliability, and why uncertainty about human goals is the core of the control problem.
15:01ENLex Fridman팟캐스트 · 2명Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks게스트 Daniel Kahneman · 진행자 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.
10:16ENLex Fridman팟캐스트 · 2명Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
10:34ENLex Fridman팟캐스트 · 2명Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AI게스트 François Chollet · 진행자 Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.