絞り込み結果
277 件並び順
1:53:50ENA curriculum rewrite takes five years. AI does not wait.ホスト Nathan LabenzJohan Falk, a Swedish teacher-turned-analyst, argues that AI literacy and AI friends are more urgent than putting a tutor in every classroom.
58:21ENAttacks Take 23 Minutes. Response Still Takes Days.ホスト Sarah Guo, Elad GilPalo Alto Networks CEO Nikesh Arora on how AI is remaking search, enterprise software, and the timeline of a cyberattack.
1:28:17ENAdam Gleave's Three Capability Tiers: Attack Agents in 5–7 Years, Fully AI Companies Around Year 14ホスト 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.
1:44:35ENJoe Hudson: $500 Billion Went Into AI, and Nobody Defined 'Good for Humanity'ホスト Nathan LabenzSam Altman says the OpenAI coach's superpower is emotional clarity — and that it will be one of the most critical skills in a post-AGI world.
3:14:49ENNothing This Summer Jumped the Curve: Why Zvi Lengthened His AGI Timelinesホスト 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 Yearsホスト 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-Rampホスト 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.
1:48:49EN$500, 2,000 Steps, and a Vending Machine: Grok 4 Profited, Claude Called the FBIホスト Nathan LabenzAndon Labs put frontier models in charge of simulated and real vending machines to see what breaks when nobody is in the loop.
3:17:35ENTen Thousand Comments and 76 Spare Gigawatts: Four Months Writing America's AI Action Planホスト Nathan LabenzDean W. Ball spent four months as the White House's senior AI adviser, then left as the Action Plan landed — and explains how a to-do list got written inside a building that cannot run ChatGPT.
1:14:05ENSullivan boils US-China AI competition down to four buckets, four examples, and a path he calls boringホスト Nathan LabenzThe former national security advisor treats transformative AI as a planning assumption, not a prophecy, and wants Washington to compete hard with Beijing without pretending a grand bargain will cure the rivalry.
2:14:55ENFrom Character AI to a 1% Warning Shot: Gabriel Weil's Case for Liability as AI Governanceホスト 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.
37:37ENA dozen people, 28 minutes, and one shared desktopThe OpenAI trio behind ChatGPT Agent explain how Deep Research and Operator became a virtual computer that can reason for half an hour and still ask you before it spends money.
1:56:16ENSB 813 Would Hand AI Safety Checks to Licensed Private Firms — If Government Can Watch the Watchersホスト 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.
1:19:46ENSuspended from Columbia, He Raised $15 Million to Cheat on Everythingホスト Nathan LabenzRoy Lee, founder of Cluely, argues that an undetectable desktop overlay, AI maximalism, and a post-AGI life of 800-year spans are the same bet.
1:37:05ENAn Algebraic Geometer Quit Tenure Because the Bowl-Shaped Loss Plot Is a Lieホスト 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.
38:48ENTask Length Doubles Every Few Months. Nathan Labenz Still Wants Humans in Chargeホスト Nathan LabenzAt Imagine AI Live, the Cognitive Revolution host maps structured AI agents against autonomous agentic systems—and tells businesses to keep final control.
41:25ENBen Mann thinks superintelligence by 2028 is quite possibleホスト Sarah Guo, Elad GilAnthropic's co-founder tells No Priors how Claude 4 unlocked hours of unattended agent work, why the lab built Claude Code, and what an economic Turing test would actually measure.
1:00:48ENThe Phrase That Alarms a16z’s AI Policy Chief: “It Only Covers a Handful of Companies”ホスト Nathan LabenzMatt Perault argues that AI rules should target harmful use, not the science of building models, and that “modest” thresholds can lock in an oligopoly.
2:02:27ENShe set out to build mirror life. Then she talked the field into stoppingホスト 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.
1:54:08ENWhy Anthropic's first check went to a company building microscopes for neural netsホスト Nathan LabenzGoodfire's Dan Balsam and Tom McGrath argue that mechanistic interpretability now has a proto-paradigm, two stubborn gaps, and three products worth shipping today.
1:44:11EN100 deaths or $1 billion: a 15-page New York bill would set a floor for frontier labsホスト 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 OpenAIホスト 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 Workホスト 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.
もっと見る277 件中 24 件を表示









