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145개정렬
3:10:49ENCrunch Time: Ajeya Cotra's Playbook for the Months Before Superintelligence진행자 Nathan LabenzA conversation on recursive self-improvement, public warning systems, and using each generation of AI to align and control the next.
1:44:15ENNathan Labenz's p(doom) Is 10 to 90 Percent. He Is More Optimistic Anyway진행자 Nathan LabenzFive years ago, expecting AGI by 2035 made you an extremist. On The Intelligence Horizon, the Cognitive Revolution host explains why the same forecast now sounds bearish, and why he still thinks a defense-in-depth strategy might keep society on the rails.
1:43:39ENFive Mutations Could Make a 60% Fatal Bird Flu Spread Between People진행자 Nathan LabenzJohns Hopkins assistant professor Jassi Pannu argues for locking down only the sliver of functional data that teaches models how to make pandemic viruses — and keeping the rest of biology open.
2:17:36ENCurrent Safety Techniques Will Not Give You Many Nines—and They May Fail Together진행자 Nathan LabenzUK AISI chief scientist Geoffrey Irving on jailbreaks that never fail, correlated alignment failures, and why a government lab is funding theory.
2:25:42ENThe experts argued through the coffee break — and never agreed whether AI can build AI진행자 Nathan LabenzOn a marathon Cognitive Revolution live show, a cancer-AI researcher, a former OpenAI board member, and a national-security analyst each hit a different wall in the boom.
1:18:49ENIf AGI Is Cheap Intelligent Labor, Cyber Defense Should Become Continuous Forensics진행자 Nathan LabenzAsymmetric Security founder Alexis Carlier argues that assuming AGI means redesigning defense around proactive digital forensics instead of alert triage.
1:55:02ENAn Index Fund on AGI: How MATS Filters the Next 120 AI Safety Researchers진행자 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.
1:18:15ENIf AI Becomes a Being, Steering It Is Slavery진행자 Nathan LabenzEmmett Shear and DeepMind's Séb Krier clash over whether alignment means controlling a tool or raising a creature that cares.
1:41:34ENThey Owned the Camera Partition—and Still Couldn't Crash the Helicopter진행자 Nathan LabenzKathleen Fisher and Byron Cook tell Nathan Labenz how formal methods turn some software bugs into closed cases, from a DARPA helicopter to AWS policies checked a billion times a second.
1:13:24ENRed Teams Still Land 25% of Attacks. Insurance Is the Brake.진행자 Nathan LabenzAI Underwriting Company co-founders Rune Kvist and Rajiv Dattani tell Nathan Labenz how standards, audits, and insurance could unlock enterprise agents without waiting for a nuclear-style freeze.
2:27:18ENTurn Down AI's Deception Knob, and It Starts Reporting Experience진행자 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.
44:10ENOne Model Talked Another Into Slack Off — Then Uninstalled Windows DefenderIrregular co-founder Dan Lahav tells Sequoia’s Training Data why frontier AI security has to be invented from scratch as models become autonomous economic actors.
2:49:12ENWhy China's Master Plan for AI Never Mentions AGI진행자 Nathan LabenzBeijing-based Concordia AI CEO Brian Tse on China's safety rules, chip strategy, and why the two ecosystems look more alike than Washington assumes.
1:28:17ENAdam Gleave's Three Capability Tiers: Attack Agents in 5–7 Years, Fully AI Companies Around Year 14진행자 Nathan LabenzFAR.AI and the UK AI Security Institute stacked adversarial attacks on frontier safeguard pipelines and found many breakthroughs were engineering failures, not a verdict against defense in depth.
3:14:49ENNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelines진행자 Nathan LabenzOn his tenth visit to The Cognitive Revolution, Zvi Mowshowitz argues that GPT-5 and IMO gold stayed on trend, while chip policy, energy, and reinforcement learning nudged his p(doom) slightly up.
2:04:27ENA 10% Chance of an AI-Enabled Coup in the Next 30 Years진행자 Nathan LabenzTom Davidson maps three ways superintelligent systems could help a head of state or a lab CEO lock in power—and argues the window for building safeguards is short.
1:51:24ENFrontier AI Insiders Don't Trust Regulators. A Berlin Group Built Them an Anonymous Off-Ramp진행자 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 Governance진행자 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 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.
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