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449 件
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スライド 3 枚1:24:44EN
Matthew Berman· 2026年2月7日Forward Future Live: Portable AI Infrastructure, Software and Formal ProofMatthew Berman, Nick Wentz, Tim Davis, Joseph Floyd, Carina Hong · Forward FutureTim Davis, Joseph Floyd and Carina Hong join Matthew Berman and Nick Wentz for a February 2026 discussion.インフラとデプロイエンタープライズ AIAI research+1
1:04:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月1日ポッドキャスト125 million cells took a decade. The next billion takes monthsホスト Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.モデルと学習AI for scienceData quality & curation+3
1:03:00EN
Unsupervised Learning: With Jacob Effron· 2026年1月29日ポッドキャストA Model That Solves New Math Problems Every Week Still Isn't AGIホスト Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.モデルと学習Reinforcement LearningAGI Timelines+3
2:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月22日ポッドキャストFine-Tuning Isn't Dead — But It Turned a Helpful Model Evilホスト Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.モデルと学習ファインチューニング安全性とガバナンス+3
スライド 5 枚17:44EN
Matthew Berman· 2026年1月17日Recursive Language Models: Extending Long-Input Work Beyond a Context WindowMatthew Berman · Forward FutureMatthew Berman examines an MIT research approach that lets language models inspect external text and make sub-calls, along with its benchmark and cost tradeoffs.コンテキストエンジニアリングInference評価(Evals)+2
37:00EN
Sequoia Capital· 2026年1月14日ポッドキャストThe AlphaChip Team That Laid Out Four TPUs Now Wants Every Company to Be DesignlessAnna Goldie and Azalia Mirhoseini tell Sequoia how an RL floorplanner survived TPU-team anger, learned to draw donut-shaped macros, and became a bet that AI will design chips that then feed AI.インフラとデプロイReinforcement LearningAI startups & small teams+3
スライド1:30EN
Matthew Berman· 2026年1月12日An AI-Generated Proof for Erdős Problem 397Matthew Berman · Forward FutureMatthew Berman discusses Neel Somani's GPT-5.2 Pro-assisted proof and speculates about self-improving AI. Later research found that the problem already had a published human solution.MathematicsAI researchAGI(汎用人工知能)
スライド 3 枚8:16EN
Matthew Berman· 2026年1月12日AI and Erdős Problem 397: A Verified Proof, Prior Work and the Prospect of Self-ImprovementMatthew Berman · Forward FutureMatthew Berman discusses AI-assisted mathematics and argues that algorithmic discoveries could accelerate AI development, while the history of problem 397 adds important context.MathematicsAI for scienceAI research+2
1:55:02EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月4日ポッドキャストAn Index Fund on AGI: How MATS Filters the Next 120 AI Safety Researchersホスト Nathan LabenzRyan Kidd, co-executive director of MATS, tells Nathan Labenz why he will not shout a timeline, why every safety technique is also a capabilities technique, and who actually gets hired.セキュリティと安全性安全性とガバナンスAI research+3
1:18:15EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月27日ポッドキャストIf AI Becomes a Being, Steering It Is Slaveryホスト Nathan LabenzEmmett Shear and DeepMind's Séb Krier clash over whether alignment means controlling a tool or raising a creature that cares.セキュリティと安全性安全性とガバナンスMulti-agent systems+3
1:18:03ZH
Zhang Xiaojun Podcast· 2025年12月24日ポッドキャスト · 2 人李广密:2025 年末的模型竞争、在线学习与 AI 创业ゲスト 李广密 · ホスト 张小珺从模型公司和算力竞争,到持续学习、机器人与全球创业,回看一位投资人在 2025 年末的判断。AI researchモデルと学習AI Strategy+2
33:27EN
AI Explained· 2025年12月23日A 2025 AI Retrospective: Reasoning, Benchmarks and Uneven ProgressAI Explained reviews generated media, METR time horizons and competing views of general intelligence, then offers forecasts for 2026.AI researchBenchmarksGenerative media+2
スライド1:55:39EN
Matthew Berman· 2025年12月20日AI Infrastructure, Gemini and Prediction Markets: Forward Future LiveMatthew Berman, Nick Wentz, Doug O’Laughlin, Koray Kavukcuoglu, Logan Kilpatrick, Abhishek Fatehpuria · Forward FutureSemiAnalysis, Google DeepMind and Robinhood guests join Matthew Berman and Nick Wentz to discuss model speed, chip supply, research, safety and financial products.インフラとデプロイAI cost & performanceAI research+2
1:58:48EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月18日ポッドキャストARC Went from $1,000 a Task to Pocket Change. That Is Not a Normal Year of AIホスト Nathan LabenzCognitive Revolution’s first live show compresses nine conversations into a year-end scan of denial, sample efficiency, companions, memory, Gemini 3 Flash, and scientific judgment.企業と戦略BenchmarksAGI(汎用人工知能)+3
1:18:05EN
Unsupervised Learning: With Jacob Effron· 2025年12月18日ポッドキャストThe Real Bottleneck in AI Research Is Compute, Not Ideasホスト Jacob EffronAfter NeurIPS, Ari Morcos and Rob Toews sit down with Jacob Effron to argue about plateauing models, SSI’s secrecy, OpenAI’s cash burn, and a set of spicy 2026 bets.企業と戦略AI StrategyScaling Laws+3
56:07EN
Google DeepMind· 2025年12月16日Demis Hassabis on World Models, Scientific Discovery and the Path to AGIHannah Fry, Demis Hassabis · Google DeepMindIn a 2025 conversation, the Google DeepMind CEO discusses simulation, uneven model capabilities, safety and social change.AI researchAI for scienceAGI(汎用人工知能)+1
17:44EN
Google DeepMind· 2025年12月10日Inside Google DeepMind’s Robotics Lab: From Lunch Packing to LaundryHannah Fry, Kanishka Rao, Colin, Houston · Google DeepMindHannah Fry visits demonstrations of robot dexterity, unfamiliar objects and longer tasks.RoboticsAI researchMultimodal AI
48:24EN
Google DeepMind· 2025年11月28日John Jumper on AlphaFold, Protein Design and Experimental ScienceHannah Fry, John Jumper · Google DeepMindThe Nobel laureate explains how structure predictions help researchers while retaining important limitations.AI for scienceDrug DiscoveryAI research
1:04:50EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月25日ポッドキャストUseful AI Work Is Doubling Every Four Months. Schools Should Plan Accordingly.ホスト Nathan LabenzIn a keynote to K-12 educators, Cognitive Revolution host Nathan Labenz argued that task length, not chat quality, is the number that should reshape how schools think.AI in Education安全性とガバナンスReward hacking+3
1:11:18EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月12日ポッドキャストHe Got Bored Five Minutes Into a Waymo. Nathan Labenz Says That's the Pointホスト Nathan LabenzOn a crossover with the Existential Hope podcast, the Cognitive Revolution host argues that the scarcest resource in AI is a positive picture of daily life, not another doom scenario.企業と戦略安全性とガバナンスAI Strategy+3
スライド1:56EN
Matthew Berman· 2025年11月10日Can a Language Model Detect an Injected Concept?Matthew Berman · Forward FutureMatthew Berman discusses an Anthropic experiment in which models sometimes report an artificial change to their internal activations.Model InterpretabilityConsciousnessAI research
12:53EN
AI Explained· 2025年11月10日Nested Learning and Model Introspection: Two Early AI Research ResultsAI Explained separates research progress from the 2025 bubble debate.Continual learningModel InterpretabilityAI research
スライド 4 枚2:07:36EN
Matthew Berman· 2025年11月8日AI Agents, Video Creation and Chipmaking: Forward Future LiveMatthew Berman, Nick Wentz, Alex Mashrabov, Ben Goodger, João Moura, Jeff Koch · Forward FutureA November 2025 livestream brings together leaders from Higgsfield, OpenAI and CrewAI, plus a semiconductor analyst, to discuss AI products and infrastructure.エージェントGenerative mediaインフラとデプロイ+2
2:27:18EN
Cognitive Revolution "How AI Changes Everything"· 2025年11月5日ポッドキャストTurn Down AI's Deception Knob, and It Starts Reporting Experienceホスト Nathan LabenzCameron Berg of AE Studio tells Nathan Labenz how suppressing deception features in Llama 3.3 70B pushed self-reports of subjective experience toward 100 percent.セキュリティと安全性Model Interpretability安全性とガバナンス+3
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