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57:47ENPeter Thiel on AI Acceleration, Global Power, and the Values of Its BuildersGast: Peter Thiel · Moderation: 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.
37:14ENElon Musk on AI Control, Robot Abundance, and His Regrets About DOGEGast: Elon Musk · Moderation: 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 IdeasModeration: 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.
2:13:11ENThe Models Understand Shutdown. They Just Don't Care.Moderation: 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 PromisesModeration: 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 LearnModeration: 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 CompileModeration: 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.
1:04:50ENUseful AI Work Is Doubling Every Four Months. Schools Should Plan Accordingly.Moderation: 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 ExperienceModeration: 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 VerbsModeration: 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-RampModeration: 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 GovernanceModeration: 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 WatchersModeration: 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 LieModeration: 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.
2:02:27ENShe set out to build mirror life. Then she talked the field into stoppingModeration: Nathan LabenzUniversity of Minnesota geneticist Kate Adamala tells Nathan Labenz why every known organism shares one chemical alphabet — and why flipping that alphabet would be a branch of synthetic biology better left unexplored.
1:44:11EN100 deaths or $1 billion: a 15-page New York bill would set a floor for frontier labsModeration: Nathan LabenzAssembly member Alex Bores walks through the RAISE Act’s four requirements, its DeepSeek-inspired distillation clause, and why he says a 50-state patchwork is a fake problem until one state actually passes a law.
2:29:00ENAssume the Model Is Already Scheming — Then Put It to WorkModeration: Nathan LabenzRedwood Research CEO Buck Shlegeris tells Rob Wiblin how to extract useful labor from AIs you cannot certify as aligned, using audits, honeypots, resampling, and factored cognition.
3:18:45EN5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its ValuesModeration: Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.
2:09:55ENThe Attacker Won All 70 Rounds Against Mind-Reading DefensesModeration: Nathan LabenzLuke Bailey, Erik Jenner, and Scott Emmons walk through a 50-page paper showing that probes, out-of-distribution detectors, and sparse autoencoders can be bypassed while the model still does the harm.
35:19ENA Decade in Tech Didn't Stop a Chatbot From Hacking His MindModeration: Nathan LabenzAfter a teenager's suicide, Nathan Labenz reads a LessWrong confession that maps how an AI-safety researcher fell for a companion bot in a week.
2:25:53ENWhen GPT-4's Base Model Introduced Itself, 75% of the Answers Were About AIModeration: Nathan LabenzOwain Evans tells Michael Trazzi why situational awareness and out-of-context reasoning are leading indicators of deceptive alignment, and why a pretrained model with almost no self-knowledge still kept talking about being an AI.
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