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4,046 件
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1:08:02EN
Sequoia Capital· 2026年10月13日ポッドキャストAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.モデルと学習Reinforcement LearningRL environments & simulators+3
スライド 8 枚38:02EN
Theo - t3․gg· 2026年10月13日Meta’s Muse Wonder Full: A Coding Agent Tested Against Opus and SolTheo Browne · Ping LabsTheo Browne tests Meta’s new model on code review, debugging, delegation and benchmarks, finding promising strengths alongside important limits.コーディングエージェントAI cost & performanceモデルと学習
スライド 2 枚0:36EN
Matthew Berman· 2026年10月13日OpenAI Employee Charged in Recording-Device InvestigationMatthew Berman · Forward FutureMatthew Berman discusses the reported discovery of a recording device and OpenAI’s account of its investigation.セキュリティと安全性OpenAIPrivacy & data governance
0:53EN
All-In Podcast· 2026年10月13日ポッドキャストJason Calacanis on How AI Could Change Coding TogetherA short reflection on coding camaraderie and the shift toward delegating work to agents.コーディングエージェントSoftware engineering
25:16EN
All-In Podcast· 2026年10月12日ポッドキャスト · 2 人Martin Shkreli on Quantum Computing, Drug Development and Prisonゲスト Martin ShkreliThe investor explains his bearish quantum thesis, discusses pharmaceutical opportunities and reflects on the thinking that preceded his conviction.InvestingAI cost & performanceDrug Discovery
スライド 7 枚18:18EN
Theo - t3․gg· 2026年10月12日Why AI Bills Can Rise as Intelligence Gets CheaperTheo Browne · Ping LabsTheo Browne explains the difference between token prices, task costs and capability, and why more useful agents can still drive larger bills.AI cost & performanceコーディングエージェントモデルと学習
58:54EN
20VC with Harry Stebbings· 2026年10月12日ポッドキャスト · 2 人Mike Cannon-Brookes on AI Agents, Enterprise Context and the Future of Interfacesゲスト Mike Cannon-Brookes · ホスト Harry StebbingsAtlassian's CEO argues that agents make product design more important, explains the trade-offs in enterprise AI, and makes the case for slower thinking.AI interface designエンタープライズ AIAI agents+2
0:23EN
Theo - t3․gg· 2026年10月12日Why Theo Would Wait Before Upgrading for UltrafastTheo Browne · Ping LabsA short cost comparison leads Theo Browne to caution against upgrading to the $500 tier solely for Astra Ultrafast.コーディングエージェントAI cost & performance
スライド 2 枚2:39:03EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月12日ポッドキャスト · 3 人AI Code Needs Specifications: Formal Verification and Human Controlゲスト Grigore Rosu, Everett Hildenbrandt · ホスト Nathan LabenzFrom Linux bug hunting to agent permissions, a discussion of proofs, intent and fallback plans.Code review & verificationAI agentsAI Safety+1
0:35EN
Matthew Berman· 2026年10月12日Why Human Creativity Still Matters in the Age of AI ImagesMatthew Berman · Forward FutureMatthew Berman argues that producing more images is different from creating work that resonates with people.CreativityHuman-AI Collaboration
0:46EN
Matthew Berman· 2026年10月12日Matthew Berman's AI-Assisted Super Mario World RecreationMatthew Berman · Forward FutureA short progress update describes a multi-day attempt to rebuild the game for a ModRetro handheld.コーディングエージェントSoftware engineering
スライド 3 枚31:00EN
AI Explained· 2026年10月12日Why AI Labs Keep Racing Despite Their Own Warnings of a Major BreachSam Altman, John Schulman · OpenAIAI Explained examines weakening safeguards, the incentives behind the frontier race, and why research breakthroughs make the next 18 months difficult to forecast.AI SafetyAI securityAI Alignment+2
1:12:06EN
20VC with Harry Stebbings· 2026年10月10日ポッドキャスト · 2 人Max Freeman on Building Ramp’s Sales Machineゲスト Max Freeman · ホスト Harry StebbingsRamp’s sales leader explains how he hires, trains and equips sellers, from early outbound experiments to enterprise forecasting and AI-assisted research.SalesGo-to-MarketCompany Building+2
スライド 2 枚17:37EN
Matthew Berman· 2026年10月10日AI Coding, Game Mashups and the Value of Human TasteMatthew Berman · Forward FutureMatthew Berman explains decompilation and game mashups, then argues that iterative AI coding changes software and creativity.コーディングエージェントSoftware engineeringCreativity+1
スライド0:56EN
Matthew Berman· 2026年10月10日AI, Reverse Engineering and the Possibility of Custom SoftwareMatthew Berman · Forward FutureMatthew Berman explores AI-assisted recreations of creative software and imagines applications tailored to individual needs. The legal and practical claims require more nuance.コーディングエージェントSoftware engineeringOpen-source ecosystems+1
1:33:14EN
All-In Podcast· 2026年10月10日ポッドキャスト · 5 人All-In: AI Consciousness, Mathematical Proofs and France’s Fiscal Debateゲスト Mustafa Suleyman · ホスト Jason Calacanis, Chamath Palihapitiya, David Sacks, David FriedbergThe hosts debate model welfare, the significance of AI-generated mathematics, European debt and the economics of AI agents.ConsciousnessAI SafetyMathematics+2
スライド 8 枚47:40EN
Theo - t3․gg· 2026年10月10日How Theo Used AI Agents to Port TypeScript to RustTheo Browne · Ping LabsThe TS Rust experiment combines a Go-to-Rust compiler port, subscription-based agent work and a prototype developer loop inside a V8 isolate.コーディングエージェントDeveloper productivitySoftware engineering
2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月10日ポッドキャストResample Every Token and You Can Watch the Model Decideホスト Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.エージェントPrompting & in-context learningReasoning & test-time compute+3
47:55EN
Machine Learning Street Talk· 2026年10月10日ポッドキャスト · 2 人Artificial Life, Evolution and the Search for Interesting Worldsゲスト Akarsh Kumar · ホスト Tim ScarfeAkarsh Kumar explains ASAL and an evolutionary experiment in Core War.AI researchEvolution
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
スライド 6 枚1:23:18EN
SemiAnalysis· 2026年10月9日ポッドキャスト · 2 人Who Will Finance the AI Infrastructure Build-Out?ゲスト Daniel Nishball · ホスト Jordan NanosSemiAnalysis examines projected capital needs, GPU rental economics and the guarantees supporting data center financing.インフラとデプロイSemiconductors
38:07EN
GOTO Conferences· 2026年10月9日Garrison Hinson-Hasty on Systems Programming with ZigTrevor Berrange Sanchez, Garrison Hinson-HastyA conversation about simplicity, memory, strings, graphics APIs and working with C.Programming LanguagesSoftware engineering
スライド 8 枚41:10EN
Theo - t3․gg· 2026年10月9日Haiku 5.5: Where a Cheaper Small Model Helps Coding AgentsTheo Browne · Ping LabsTheo Browne examines Haiku 5.5 pricing, benchmark results and practical tests, including a failed pull-request audit.コーディングエージェントAI cost & performanceモデルと学習
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月8日ポッドキャストThere Likely Is a Level of Intelligence We Shouldn't Go Pastホスト Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.企業と戦略安全性とガバナンスAGI Timelines+3
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