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38:14EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026년 9월 18일팟캐스트 · 2명Diffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Silicon진행자 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.모델과 학습InferenceAI cost & performance+3
3:36:13EN
Zhang Xiaojun Podcast· 2026년 8월 13일팟캐스트 · 2명NVIDIA’s Ming-Yu Liu on Cosmos, Physical AI, and Creating New Markets게스트 Ming-Yu Liu · 진행자 张小珺NVIDIA research VP Ming-Yu Liu explains how a decade of generative-model research led to Cosmos 3, a world foundation model for Physical AI. He also shares what he learned from Jensen Huang about long-term bets, teamwork, and building markets instead of fighting over existing ones.World modelsRoboticsAI research+2
2:59:03EN
Zhang Xiaojun Podcast· 2026년 7월 28일팟캐스트 · 2명You Kaichao on How vLLM Grew from Open-Source Project to AI Infrastructure Company게스트 You Kaichao · 진행자 张小珺Inferact co-founder You Kaichao traces vLLM’s path from Berkeley research to a company, then explains why model, inference, hardware and agent design increasingly have to move together.Company BuildingAI startups & small teamsAI research+2
3:46:12EN
Zhang Xiaojun Podcast· 2026년 7월 16일팟캐스트 · 2명Kay Ke on Physical Intelligence, Robot Learning, and the Future of Robotics게스트 Kay Ke · 진행자 张小珺Physical Intelligence researcher Kay Ke traces the field's research lineages and explains Pi's progression from π₀ to π*₀.₆. She also reflects on education, fiction, ambition, and what it means to build robots that work beyond a demo.RoboticsReinforcement LearningAI research+2
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.평가와 관측 가능성평가(Evals)Benchmarks+3
32:22EN
20VC with Harry Stebbings· 2026년 4월 7일팟캐스트 · 2명Demis Hassabis on AGI, Scientific Discovery and the Challenges Ahead게스트 Demis Hassabis · 진행자 Harry StebbingsThe Google DeepMind CEO discusses compute, continual learning, safety standards and his hopes for AI in science, medicine and energy.AGI(범용 인공지능)AI researchAI Safety+2
슬라이드 4장13:30EN
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.MathematicsReasoning & test-time computeAI research+2
42:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025년 6월 26일팟캐스트 · 2명AlphaEvolve found algorithms humans missed for 50 years — then sped up Gemini 23%진행자 Sarah Guo, Elad GilGoogle DeepMind’s Pushmeet Kohli and Matej Balog tell No Priors how an evolutionary coding agent searches algorithm space the way AlphaGo searched Go.코딩 에이전트에이전트 엔지니어링평가(Evals)+3
3:14:34EN
Lex Fridman· 2025년 6월 14일팟캐스트 · 2명If ten things make a problem hard, Terence Tao turns nine of them off게스트 Terence Tao · 진행자 Lex FridmanThe Fields Medalist walks Lex Fridman from the Kakeya needle and Navier-Stokes through Lean, Perelman, and why today's AI still cannot smell a dead-end proof.MathematicsAI for scienceAI research+3
38:10EN
No 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.모델과 학습Reasoning & test-time computeReinforcement Learning+3
2:36:13ZH
Zhang Xiaojun Podcast· 2025년 2월 24일팟캐스트 · 2명松琳解读 DeepSeek、Kimi 与 MiniMax 的注意力新论文게스트 Songlin Yang(松琳) · 진행자 张小珺从动态稀疏注意力到线性注意力混合架构:三条长上下文路线如何兼顾训练、推理与硬件效率Transformers & attentionGPU programming & kernels모델과 학습+2
53:07ZH
Zhang Xiaojun Podcast· 2025년 2월 17일팟캐스트 · 2명张亚勤:信息智能、物理智能与生物智能的 AGI 路线图게스트 张亚勤 · 진행자 张小珺张亚勤把 AGI 的发展分为信息、物理和生物三类智能:信息智能可能在五年内接近人类,通用机器人约需十年,生物智能则可能在二十年后扩展人的记忆与健康。他也讨论大模型如何为自动驾驶和机器人补上数据、常识与行动能力。AGI(범용 인공지능)RoboticsAI research+2
45:31EN
MBMatthew Berman· 2025년 2월 15일Jerry Chow on Quantum Computing, Encryption, AI and Error CorrectionMatthew Berman, Jerry Chow · Forward FutureIBM’s quantum systems director explains qubits, cryogenic hardware, software and the work needed to make quantum computers useful.Quantum MechanicsCybersecurityAI research
2:49:35ZH
Zhang Xiaojun Podcast· 2025년 2월 4일팟캐스트 · 2명潘嘉怡解读 R1、o1 与 Kimi K1.5:强化学习如何教模型学会推理게스트 潘嘉怡 · 진행자 张小珺伯克利博士生潘嘉怡带读 DeepSeek、OpenAI 与 Kimi 的推理模型报告,拆解长思维链、GRPO、奖励设计与蒸馏。R1-Zero 的“顿悟时刻”展示了推理策略如何在强化学习中涌现。Reinforcement Learning모델과 학습AI research+2
1:33:07ZH
Zhang Xiaojun Podcast· 2024년 8월 17일팟캐스트 · 2명广密复盘全球大模型这一年:Scaling Law、AGI 豪赌与中美格局게스트 李广密 · 진행자 张小珺拾象创始人李广密从硅谷一线观察出发,回顾 OpenAI、Anthropic、Google 与中国模型公司的竞争。他认为,模型能力与成本共同决定新一轮应用爆发,而巨额投入押注的是智能能否持续扩展以及 AI 对经济和产业的长期重构。모델과 학습Scaling LawsAI research+2
34:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 6월 27일팟캐스트 · 2명Five Independent Teams Found the Same 10-to-1 Mix That Beats Transformers진행자 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.모델과 학습Transformers & attention음성 AI+3
26:00EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024년 6월 11일팟캐스트 · 2명Why a Zapier founder thinks AGI research has been stalled for four years진행자 Sarah Guo, Elad GilMike Knoop and François Chollet put more than a million dollars on beating ARC-AGI, the eval they say actually measures general intelligence.평가와 관측 가능성AGI(범용 인공지능)Benchmarks+3
2:15:39EN
Lex Fridman· 2024년 6월 2일팟캐스트 · 2명Roman Yampolskiy Puts Superintelligent Ruin at 99.99 Percent게스트 Roman Yampolskiy · 진행자 Lex FridmanThe AI safety researcher tells Lex Fridman that controlling AGI is as impossible as a perpetual motion machine, and that tests, open source, and regulation cannot close the gap.보안과 안전안전과 거버넌스Existential Risk+3
2:50:44EN
Lex Fridman· 2024년 4월 17일팟캐스트 · 2명The Pirahã Have No Word for One게스트 Edward Gibson · 진행자 Lex FridmanMIT psycholinguist Ted Gibson tells Lex Fridman why related words sit together, why language is not thought, and why large language models ace form while missing meaning.Neuroscience & AIAI researchPhilosophy of Mind+1
2:47:17EN
Lex Fridman· 2024년 3월 7일팟캐스트 · 2명If You Want Human-Level AI, Abandon Generative Models게스트 Yann Lecun · 진행자 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.모델과 학습World modelsAGI(범용 인공지능)+3
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 11월 2일팟캐스트 · 2명Reliability is the bottleneck. Autonomy is what would make AI feel alive.진행자 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.모델과 학습AGI(범용 인공지능)Scaling Laws+3
39:50EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 7월 20일팟캐스트 · 2명Why AI Video Is Still a Four-Second Corgi진행자 Sarah Guo, Elad GilMeta research director Devi Parikh explains why text-to-video has stalled on short animated images, and what it will take to get past that plateau.멀티모달과 미디어Generative media비전과 영상+3
3:11:35EN
Lex Fridman· 2023년 6월 21일팟캐스트 · 2명Search was always a hack: Marc Andreessen on AI, truth, and the next internet게스트 Marc Andreessen · 진행자 Lex FridmanLex Fridman sits down with the Mosaic co-creator and Andreessen Horowitz founder to ask whether Google Search, the browser, and open-source AI survive the decade.기업과 전략Search & retrievalSynthetic data+3
2:07:04EN
Lex Fridman· 2023년 5월 28일팟캐스트 · 2명The Ribosome Already Solved Digital Manufacturing게스트 Neil Gershenfeld · 진행자 Lex FridmanNeil Gershenfeld tells Lex Fridman why Turing separated the head from the tape, how fab labs are the personal-computer moment for making things, and what it would take to grow a civilization from about twenty parts.오픈소스와 커뮤니티RoboticsAI research+3
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