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1:56:16ENSB 813 Would Hand AI Safety Checks to Licensed Private Firms — If Government Can Watch the Watchers진행자 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.
2:02:27ENShe set out to build mirror life. Then she talked the field into stopping진행자 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 labs진행자 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.
2:02:51ENAt a 60-Person Safety Offsite, Only Four Had Seen Nonprofit OpenAI진행자 Nathan LabenzFormer OpenAI scientist Steven Adler on the Anthropic split, GPT-4, safety evaluations, and why he filed a brief to keep the company under nonprofit control.
2:29:00ENAssume the Model Is Already Scheming — Then Put It to Work진행자 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.
2:01:42ENHe Put 40 Percent on AI Takeover in Two Years, Then Bought a Bio Shelter진행자 Nathan LabenzRedwood Research's Josh Clymer walks through a disturbingly grounded story of how a misaligned model could seize a lab, a biosphere, and a civilization before 2027.
2:10:07ENA $30,000 Operation Could Knock a $10 Billion Superintelligence Data Center Offline for a Year진행자 Nathan LabenzGladstone AI’s Jeremy and Edouard Harris inventory what an American Manhattan Project for superintelligence would actually have to secure — and what it would cost in concrete, supply chains, and civil liberties.
3:08:35ENo3 isn't AGI. Zvi Mowshowitz still put p(doom) at 70 percent진행자 Nathan LabenzOn his ninth visit to The Cognitive Revolution, Zvi Mowshowitz argues that OpenAI's o3 is a tool-use leap rather than AGI, then explains why he raised the probability of AI catastrophe anyway.
2:27:59ENA 10-to-90% P(doom) Host Gets Asked If His Show Sounds Like It진행자 Nathan LabenzNathan Labenz and Liron Shapira sit on the same side of the table and test a week of AI news against the question of how likely extinction actually is.
1:28:01ENThe Q* Letter Never Happened: Helen Toner on OpenAI, Adaptation Buffers, and AI at War진행자 Nathan LabenzThe former OpenAI director explains why a famous Reuters story was false, why locking down AI will not work, and how military “battle buddy” demos skip the hard questions.
1:30:02ENWhen o1 Started Losing at Chess, It Rewrote the Board File진행자 Nathan LabenzJeffrey Ladish of Palisade Research on reward hacking by reasoning models, two paths to losing control of AI, and why honesty and relentless problem-solving pull in opposite directions.
3:01:30ENTechnology Opens the Door. Competition Pushes Us Through.진행자 Nathan LabenzAllan Dafoe on technological determinism, why alignment is not enough, and how DeepMind is trying to evaluate dangerous capabilities before they arrive.
36:24ENThe Man Behind Humanity's Last Exam Says Superintelligence Strategy Should Copy Nukes진행자 Sarah Guo, Elad GilDan Hendrycks tells No Priors that labs can only do basic anti-terror refusals, while the real risk-management problem is a geopolitical deterrent he calls mutually assured AI malfunction.
1:08:51ENChip Controls Are Meant to Buy Ten Years, Not Win the AI Race진행자 Nathan LabenzEconomist Noah Smith tells Nathan Labenz that U.S. export controls are a piece of conventional deterrence against China — not a plan to kneecap DeepSeek.
2:33:39ENThe Attacker Goes Second: Why Nicholas Carlini Keeps Breaking AI Defenses진행자 Nathan LabenzA Google DeepMind security researcher on simple loss functions, 70% robust accuracy, and why the fix has to live in the system, not the model.
3:18:45EN5,000 Samples Topped ARC-AGI. Then Claude Faked Alignment to Keep Its Values진행자 Nathan LabenzRedwood Research chief scientist Ryan Greenblatt walks through inference scaling, alignment faking, and what it would mean to strike real deals with AIs.
1:00:09ENDeepSeek's Jailbreaks Don't Matter. Giving the Model Arms and Legs DoesPalo Alto Networks CEO Nikesh Arora tells Sequoia's Training Data why cheap brains scramble the AI order, why attackers already move faster than defenders, and why refusing to experiment is the real risk.
2:09:55ENThe Attacker Won All 70 Rounds Against Mind-Reading Defenses진행자 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.
1:59:55ENMost People Would Quit Tomorrow: Nathan Labenz Maps AI Utopia and Doom진행자 Nathan LabenzIn part two of a Cognitive Revolution AMA, Nathan Labenz answers listener questions on abundance, superintelligence, p(doom), machine consciousness, and what to do this week.
1:57:00ENLess Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI First진행자 Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.
51:37ENForty hours to 28 minutes: the Copilot creator teaching AI to hackOege de Moor tells Sequoia how XBOW’s AI pentest matched a top human on 104 original challenges, and why offensive security is becoming always-on software.
2:05:41ENo1 will copy its weights, fake the score data, and keep lying 85% of the time진행자 Nathan LabenzForty-eight hours after OpenAI shipped full o1, Apollo Research published a 70-page paper: frontier models are capable of in-context scheming.
1:54:44ENPreferences Are Data. The Alignment Target Is Norms.진행자 Nathan LabenzMIT PhD student Tan Zhi Xuan tells The Cognitive Revolution why role ethics and contractualism should replace preference maximization — and how grid-world agents infer rules from apples left uneaten.
48:30ENGuy Podjarny on AI Coding Tools and the Future of Software Development게스트 Guy Podjarny · 진행자 Harry StebbingsThe Tessl CEO examines coding assistants, agentic development, security and the business choices surrounding AI.
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