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53 件並び順
1:28:08ENThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missedホスト Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
31:39ENThe Skull Is Already the Vat: Max Hodak on Restoring Sightホスト Sarah Guo, Elad GilPatients blinded by macular degeneration put on laser-projector glasses, read books, and fill in Sudoku — because a chip under the retina is sending vision back into the brain.
47:22ENFrom One in a Thousand to 15 Percent: Chai Discovery Treats Drug Design as a Scaling ProblemJoshua Meier and Matthew McPartlon tell Sequoia’s Training Data why antibody design is an engineering problem, not a bespoke science, and why they sell a molecular CAD suite instead of their own drugs.
1:29:35ENFred Turner on Curative’s Pandemic Pivot, Health Insurance and AI Automationゲスト Fred Turner · ホスト Harry StebbingsCurative’s CEO recounts building a COVID testing operation, moving into health insurance and using AI agents across the company’s workflows.
55:19ENThe drone is 15% of Zipline: 140 million miles, zero incidentsKeller Rinaudo Cliffton and Eric Watson explain why the aircraft is the small part of an automated logistics system now cheaper than a car.
1:08:23ENShiv Rao on Building Abridge, Clinical Workflows and AIゲスト Shiv Rao · ホスト Harry StebbingsThe Abridge co-founder discusses years of market development, model choices, data trust and the limits of automating clinical work.
1:03:40ENAndrew Dudum on Hims & Hers, Preventive Care and Building a Public Companyゲスト Andrew Dudum · ホスト Harry StebbingsThe Hims & Hers CEO discusses management, healthcare distribution, marketing and expansion. His medical and commercial claims are presented as his views, not independently verified evidence.
1:44:15ENNathan Labenz's p(doom) Is 10 to 90 Percent. He Is More Optimistic Anywayホスト 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.
1:56:33ENThe Future Live: Agents at Work, Persistent Memory and AI for HealthMatthew Berman, Nick Wentz, Rob Seaman, Varun Vummadi, Charles Packer, Dominic King · Forward FutureMatthew Berman and Nick Wentz speak with leaders from Slack, Giga, Letta and Microsoft AI about practical uses and unresolved risks.
2:03:56EN260 Doctors and 49,000 Criteria: How OpenAI Built Attending-Level Health AIホスト Nathan LabenzKaran Singhal tells Nathan Labenz how ChatGPT Health was evaluated with physicians, walled off from model training, and aimed at raising both the floor and the ceiling of human health.
2:25:42ENThe experts argued through the coffee break — and never agreed whether AI can build AIホスト 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.
1:04:51EN125 million cells took a decade. The next billion takes monthsホスト Nathan LabenzMark Zuckerberg and Priscilla Chan on pairing a frontier biology lab with a frontier AI lab so models train on data that was designed for them.
48:14ENA New Drug Burns $2 Billion and 10 Years. Benchling's CEO Wants AI to Cut That to Threeホスト Sarah Guo, Elad GilMost medicines fail in years seven to ten, after hundreds of millions have already gone into the clinic—and Sajith Wickramasekara thinks sending things to space may already be easier.
1:29:30EN2,500 Compounds and a 51 Percent Hit Rate: How a Small Graph Net Found New Antibioticsホスト Nathan LabenzMIT's Jim Collins tells Nathan Labenz how a bootlegged 2018 project, a binary growth-inhibition label, and Chemprop graph networks pulled novel antibiotics out of chemical space that labs could never screen by hand.
1:38:05ENHemant Taneja on Scaling General Catalyst, AI and the Future of Ventureゲスト Hemant Taneja · ホスト Harry StebbingsThe General Catalyst CEO discusses early-stage returns, AI’s effect on work and the difficulty of investing through rapid technological change.
44:49ENHow OpenEvidence Became the Clinical OS for 40% of U.S. Doctorsホスト Sarah Guo, Elad GilFounder Daniel Nadler tells No Priors how a free search tool for physicians, not an answer engine for patients, took high-stakes clinical knowledge in 18 months.
1:28:48ENDoctors code at 45%. The model beat them by 12 points — then 4,000 physicians had to try it once.ホスト Nathan LabenzAmbience Healthcare and Cleveland Clinic walk through the AI scribe that cut pajama time, climbed ICD-10 with reinforcement fine-tuning, and won 75% voluntary use.
49:27ENFrom 0.1% to 20%: Chai-2 Turns Antibody Design Into Prompt Engineeringホスト Sarah Guo, Elad GilChai Discovery co-founders Joshua Meier and Jack Dent tell Sarah Guo how a generative model now designs antibodies that bind on the first 24-well plate.
1:05ENSatya Nadella on AI, Productivity, and Cancer CareMatthew Berman, Satya Nadella · Forward FutureIn a short interview excerpt, the Microsoft CEO discusses the potential of cheaper AI to help coordinate healthcare work.
1:26:21ENFor under $10, Google's AI independently recovered a lab result nobody had publishedホスト Nathan LabenzVivek Natarajan and Anil Palepu tell Nathan Labenz how AMIE beats primary-care doctors on treatment plans, and how Co-Scientist matched Imperial College's unpublished bacterial-resistance mechanism.
38:43ENTwo in Five Doctors Want Out. An On-Call Cardiologist Built the Note That Lets Them Stayホスト Sarah Guo, Elad GilAbridge CEO Shiv Rao on treating the doctor-patient conversation as healthcare's source of truth, and why the company ran straight at the hardest health systems.
1:31:35ENThirty Years of Research, Collapsed into One Sentenceホスト Nathan LabenzImmunologist Derya Unutmaz on writing a medical patent in half an hour, treating o1 Pro as a professor-level collaborator, and why he no longer trusts his own expertise until he asks the model.
1:04:52ENThe Consumer Playbook That Put Medical AI in 100,000 Exam RoomsOpenEvidence CEO Daniel Nadler explains how a free App Store product, trained only on peer-reviewed literature, reached as much as a quarter of U.S. physicians in a year.
1:33:01ENRare Diseases Are Common: How a Harvard Gene Hunter Uses o1-pro on the Cases Sequencing Already Missedホスト Nathan LabenzDr. Catherine Brownstein of Boston Children's Hospital explains why cheap genomes made her job harder, why data sharing still beats any model, and where ChatGPT Pro actually gives her hours back.
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