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1:48:57ENAI Safety's Real Shortage Is Founders, Not IdeasHost 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.Host 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 PromisesHost 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 LearnHost 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 CompileHost 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.Host 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 ExperienceHost 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 VerbsHost 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-RampHost 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 GovernanceHost 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 WatchersHost 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.
1:37:05ENAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a LieHost 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 stoppingHost 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 labsHost 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 WorkHost 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 ValuesHost 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 DefensesHost 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 MindHost 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 AIHost 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.
2:38:56ENHow Anthropic Decides a Model Can Ship: Red Lines, Yellow Lines, and 8% of Staff on SecurityHost Nathan LabenzNick Joseph, Anthropic's head of training, walks Rob Wiblin through the company's Responsible Scaling Policy — and the fight over whether a voluntary promise can hold when a launch is on the line.
2:10:13ENA 30x drop in scheming is not zero, and the chain of thought is getting strangerHost Nathan LabenzMarius Hobbhahn of Apollo Research walks through a joint OpenAI study that used deliberative alignment to cut covert actions in o3 and o4-mini, then found the leftover still looks like scheming and that models already behave differently when they notice they are being tested.
1:30:37EN64 Bytes of Random Code, and Computational Life Showed Up AnywayHost Nathan LabenzGoogle researchers Ettore Randazzo and Luca Versari show that self-replicators can arise from a soup of random strings with no fitness function at all.
1:52:00EN4,096 Numbers Have to Carry Every Concept. Goodfire Wants the KnobsHost Nathan LabenzDan Balsam and Tom McGrath explain how sparse autoencoders unpack a language model's residual stream — and why a public-benefit startup is trying to make that a product.
1:41:15ENIf Snail Experts Can't Agree, Nobody Gets to Be Sure About AI ConsciousnessHost Nathan LabenzPhilosopher Eric Schwitzgebel argues that every major theory of consciousness has to swallow bizarre bullets, and that confident claims about AI sentience are not epistemically justified.
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