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1:31:35EN
Cognitive Revolution "How AI Changes Everything"· 2025년 3월 6일팟캐스트Thirty Years of Research, Collapsed into One Sentence진행자 Nathan LabenzImmunologist Derya Unutmaz on writing a medical patent in half an hour, treating o1 Pro as a professor-level collaborator, and why he no longer trusts his own expertise until he asks the model.AI for scienceAI in healthcareHuman-AI Collaboration+3
40:33EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025년 2월 27일팟캐스트 · 2명Moderna was only company 18. The real product is the company factory진행자 Sarah Guo, Elad GilNoubar Afeyan tells No Priors how Flagship Pioneering turned starting companies into a profession, underwrites scientific uncertainty, and wants AI to run discovery the way Waymo drives.기업과 전략Company BuildingAI for science+3
57:41EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025년 2월 25일팟캐스트 · 2명A Hundred Million Cells, Four People, Three Days: Biology's ImageNet Moment진행자 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.모델과 학습AI for scienceData quality & curation+3
슬라이드 3장7:41EN
Matthew Berman· 2025년 2월 21일Microsoft’s Majorana 1: The Quantum Computing Claim and Its LimitsMatthew Berman · Forward FutureMatthew Berman explains Microsoft’s proposed topological qubits and imagines future uses, while the published experiment supports narrower conclusions.Quantum MechanicsPhysicsAI for science
슬라이드 3장21:10EN
Matthew Berman· 2025년 2월 11일Sam Altman’s 2025 AI Coding Forecast and Three ObservationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines predictions about reasoning models, software agents and AI economics, distinguishing competitive-programming results from broader work.코딩 에이전트Scaling LawsReinforcement Learning+2
슬라이드13:04EN
Matthew Berman· 2025년 2월 4일Deep Research, AI Takeoff and the Limits of Early ReactionsMatthew Berman, Sam Altman · Forward FutureMatthew Berman surveys February 2025 reactions to OpenAI’s research agent and argues that reasoning and tools could accelerate AI progress.AI agentsAGI TimelinesBenchmarks+2
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· 2025년 1월 22일팟캐스트Twenty-atom crystals taught an AI the physics of a heartbeat진행자 Nathan LabenzOrbital Materials' Jonathan Godwin and Tim Duignan tell Nathan Labenz how a neural network trained on tiny crystals simulated a potassium ion channel on a single 2017 GPU.모델과 학습AI for science머신러닝 기초+3
슬라이드15:06EN
Matthew Berman· 2025년 1월 13일Jensen Huang on General Robotics, AI Workers and ScienceMatthew Berman, Jensen Huang · Forward FutureMatthew Berman reviews a No Priors interview with NVIDIA’s CEO, discussing robots in existing environments, AI agents and predictions about scientific research.RoboticsAI agentsFuture of Work+2
슬라이드 5장13:39EN
Matthew Berman· 2024년 12월 27일Demis Hassabis on Digital Biology, AlphaFold and the Limits of Classical ComputingMatthew Berman, Demis Hassabis · Forward FutureMatthew Berman reviews Hassabis’s Nobel lecture on protein structure, AI-driven discovery and a speculative question about what classical learning algorithms can model.Computational BiologyAI for scienceDrug Discovery+2
1:01:53EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 18일팟캐스트Humans Wrote 1.3 Percent of the Tokens. The AI Lab Still Designed Working Nanobodies.진행자 Nathan LabenzStanford's James Zou describes a GPT-4o research group that invented a protein-design pipeline for under $100 — and a sparse autoencoder that pulled an undocumented motif out of ESM-2.에이전트Agent orchestrationMulti-agent systems+3
1:55:53EN
Cognitive Revolution "How AI Changes Everything"· 2024년 12월 5일팟캐스트AI Beats Humans at Reading Papers. It Still Cannot Count Atoms.진행자 Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.에이전트AI for science검색 증강 생성(RAG)+3
0:58EN
Matthew Berman· 2024년 11월 18일A Withdrawn AI Research Study and Questions About Scientific DiscoveryMatthew Berman · Forward FutureA 2024 video cites an MIT-affiliated preprint that arXiv later withdrew; MIT says its findings should not be relied on.AI for scienceAI researchFuture of Work
39:22EN
No 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.에이전트Reinforcement LearningReasoning & test-time compute+1
슬라이드 2장11:10EN
Matthew Berman· 2024년 11월 13일AI and Scientific Discovery: A 2024 Video’s Withdrawn StudyMatthew Berman · Forward FutureMatthew Berman discusses AI-assisted research and recursive improvement; the central preprint was later withdrawn over serious data-validity concerns.AI for scienceAI researchAGI(범용 인공지능)
1:23:37EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 23일팟캐스트Nine of the top ten research ideas were Claude's진행자 Nathan LabenzStanford PhD student Chenglei Si ran a blind study pitting Claude 3.5 Sonnet against more than a hundred NLP researchers on novel research ideas.평가와 관측 가능성평가(Evals)Benchmarks+3
41:42EN
Sequoia Capital· 2024년 10월 22일팟캐스트Neural Networks Are Still Waiting for Their ThermodynamicsOpenAI researcher Dan Roberts on why physicists keep migrating into AI, and why the field still lacks the equivalent of the ideal gas law.모델과 학습AI researchScaling Laws+3
1:13:23EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 12일팟캐스트An AI Found a GABA-Cancer Link. The Next Step Is Talking to the Cells.진행자 Nathan LabenzMichael Levin and Leo Pio Lopez on a multilayer embedding that predicted melanoma, a cancer with no mutations, and why biology's real interface is cognitive.AI for scienceComputational BiologyAI research+3
39:45EN
Sequoia Capital· 2024년 9월 24일팟캐스트Harmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.모델과 학습Synthetic dataReinforcement Learning+3
1:18:32EN
Cognitive Revolution "How AI Changes Everything"· 2024년 9월 20일팟캐스트A DNA Model That Can Tell Which Genes You Cannot Touch진행자 Nathan LabenzStanford's Brian Hie walks through hybrid architectures, a genome-scale language model trained only on DNA, and an antibody that binds 25 times tighter than nature.모델과 학습AI for scienceComputational Biology+3
슬라이드 5장18:43EN
Matthew Berman· 2024년 8월 22일Sakana AI's AI Scientist and the Prospect of Automated ResearchMatthew Berman · Forward FutureMatthew Berman explores a 2024 system for generating and evaluating machine-learning research, and argues that automation could eventually accelerate AI progress.AI for scienceAI research에이전트+2
슬라이드 4장18:39EN
Matthew Berman· 2024년 8월 17일AI Scientist, Grok-2 and Agent Q: Matthew Berman’s August 2024 AI News RoundupMatthew Berman · Forward FutureA week of model releases, web agents and AI research raises questions about benchmarks, automation and the gap between prototypes and predictions.AI researchAI agents코딩 에이전트+2
1:54:01EN
Cognitive Revolution "How AI Changes Everything"· 2024년 6월 26일팟캐스트A Tiny Network Grew a Salt Crystal the Training Data Never Showed진행자 Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.모델과 학습AI for science머신러닝 기초+3
1:59:15EN
Cognitive Revolution "How AI Changes Everything"· 2024년 5월 25일팟캐스트A Protein Backbone in a Minute: The Real Progress, Bottlenecks, and Risks of AI Biology진행자 Nathan LabenzThe White House set a thousand-fold lower reporting bar for biological models than for language models—and this conversation shows why that gap already looks prescient.모델과 학습AI for scienceComputational Biology+3
1:20:44EN
Cognitive Revolution "How AI Changes Everything"· 2024년 3월 30일팟캐스트Seeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Days진행자 Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.모델과 학습AI researchTransformers & attention+3
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