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57:47ENPeter Thiel on AI Acceleration, Global Power, and the Values of Its BuildersInvité : Peter Thiel · Anime : Walter IsaacsonWalter Isaacson challenges Peter Thiel on AI risk, concentrated power, and the moral responsibilities of visionary founders. Thiel argues that stopping progress carries dangers of its own.
45:08ENSam Altman on AI Discovery, Consciousness, Compute and a Human-Centered FutureMatthew Berman, Sam Altman · Forward FutureIn a conversation with Matthew Berman, Altman discusses scientific progress, personal assistants, recursive self-improvement and the importance of human agency.
37:14ENElon Musk on AI Control, Robot Abundance, and His Regrets About DOGEInvité : Elon Musk · Anime : Walter IsaacsonWalter Isaacson asks Elon Musk how humanity can remain safe and find purpose as AI grows more capable, and challenges him on politics, empathy, and the future he is building.
31:00ENWhy 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.
38:10ENFrom deepfakes to DNA: how SynthID watermarks AIHannah Fry, Pushmeet Kohli, Jeremy Ratcliffe · Google DeepMindHannah Fry sits down with Pushmeet Kohli and Jeremy Ratcliffe to explain SynthID: a mathematical watermark now used on text, images and video, and being extended to protein sequences so DNA synthesis companies can tell AI-designed molecules from nature.
1:48:57ENAI Safety's Real Shortage Is Founders, Not IdeasAnime : Nathan LabenzHalcyon's Mike McCormick on launching about 30 AI safety, cyber, and biosecurity organizations in three years — and why experienced leaders, not more Google Docs, are the bottleneck.
31:59ENClaude Opus 5.5: Benchmarks, Cost and Anthropic’s Approach to PacingMatthew Berman, Thariq · Forward FutureMatthew Berman reviews the release and speaks with Anthropic’s Thariq about daily workflows, evaluation and agent harnesses.
1:19:28ENAI Safety, Personal Agents and the Venture Market’s Uneven ExitsInvité : Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate oversight of advanced AI, the economics of personal assistants and what a weaker software exit market means for investors.
1:22:31ENAI Assistants, Enterprise Adoption and the Venture Market’s New RisksInvité : Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate personal agents, legal AI, autonomous vehicles and the economics of financing AI companies.
17:15ENThe Hugging Face Incident: AI Evaluation, Sandbox Escape and Reward HackingMatthew Berman · Forward FutureMatthew Berman explains the reported OpenAI evaluation incident and the security and incentive failures it exposed.
1:20:22EN20VC Roundtable on Open Weights, AI Spending and Software InvestingInvité : Jason Lemkin, Rory O’Driscoll · Anime : Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate AI safety, chip investment, enterprise budgets and the future of software.
2:13:11ENThe Models Understand Shutdown. They Just Don't Care.Anime : Nathan LabenzPalisade Research's Jeffrey Ladish on shutdown resistance, open-weight self-replication, and why all compute looks like food to a strategic agent.
3:27:22ENThe AI Table Has Three Seats Left: Zvi on the Middle Game, Jobs, and Anthropic's PromisesAnime : Nathan LabenzOn his 12th Cognitive Revolution appearance, Zvi Mowshowitz argues early 2026 is the start of the middle — with only three labs still playing, a real job shock underway, and Anthropic's safety commitments reduced to trust us.
1:49:53ENDon't Fight Backprop: Goodfire's Bet on Designing What Models LearnAnime : Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.
1:34:29ENThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileAnime : Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.
12:23ENMoltbook: An AI Agent Social Network and Its Security QuestionsMatthew Berman · Forward FutureMatthew Berman explores conversations attributed to AI agents on Moltbook and considers privacy, manipulation and operating costs.
1:04:50ENUseful AI Work Is Doubling Every Four Months. Schools Should Plan Accordingly.Anime : 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.
2:27:18ENTurn Down AI's Deception Knob, and It Starts Reporting ExperienceAnime : 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.
2:02:17ENSAEs Find the Nouns. Parameter Decomposition Looks for the VerbsAnime : Nathan LabenzGoodfire's Lee Sharkey argues that sparse autoencoders recover a network's variables, not the algorithms those variables run, and shows how stochastic parameter decomposition tries to recover the computations themselves.
1:51:24ENFrontier AI Insiders Don't Trust Regulators. A Berlin Group Built Them an Anonymous Off-RampAnime : Nathan LabenzKarl Koch of the AI Whistleblower Initiative on gray-zone fears, retaliation, and a Tor-based way to ask for help before you decide anything.
2:14:55ENFrom Character AI to a 1% Warning Shot: Gabriel Weil's Case for Liability as AI GovernanceAnime : Nathan LabenzA Touro law professor tells Nathan Labenz how negligence, strict liability, and punitive damages could make frontier labs treat public risk as a hit to their own balance sheet.
1:56:16ENSB 813 Would Hand AI Safety Checks to Licensed Private Firms — If Government Can Watch the WatchersAnime : Nathan LabenzGillian Hadfield and Andrew Freedman want California to set AI safety outcomes, license competing certifiers, and give companies a rebuttable presumption in court if they pass.
47:07ENGoodfire’s Eric Ho thinks we will decode neural nets by 2028On Sequoia’s Training Data, the interpretability founder argues that sparse autoencoders, model editing, and a third-party lab are how AI stops being grown from data and starts being designed.
1:37:05ENAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a LieAnime : Nathan LabenzJesse Hoogland and Daniel Murfet of Timaeus argue that singularities in the loss landscape — not the smooth valleys in every slide deck — are what actually govern how neural networks learn, generalize, and go wrong.
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