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70 件並び順
24:25ENBuilding a Sleep Tracker With Pythagora 2.0Matthew Berman · Forward FutureMatthew Berman demonstrates an AI-assisted development workflow, from an editable specification to testing and debugging a sleep-tracking prototype.
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Nathan Labenz how AMIE beats primary-care doctors on treatment plans, and how Co-Scientist matched Imperial College's unpublished bacterial-resistance mechanism.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.
14:50ENAI News in November 2024: Mistral, Gemini, Nuclear Safety and Medical AIMatthew Berman · Forward FutureMatthew Berman surveys Le Chat updates, model rankings, nuclear safeguards and a diagnostic reasoning study.
39:05ZH王小川:o1、强化学习与从快思考走向慢思考ゲスト 王小川 · ホスト 张小珺百川智能创始人解读 o1 的可能技术路径,讨论强化学习、医疗场景和创业公司的选择。
1:32:45ENHe doubled a company with AI — then asked the labs to pause hyperscalingホスト Nathan LabenzOn the Nick Halaris Show, Cognitive Revolution host Nathan Labenz argues for adopting today's models fast and slowing the race to systems more powerful than we are.
1:37:07ENA Text-Only AI Outdiagnosed GPs. Google Still Won't Ship It.ホスト Nathan LabenzGoogle researchers Vivek Natarajan and Khaled Saab walk Nathan Labenz through five medical-AI papers, from radiology reports to an AI doctor that still has to earn trust.
1:01:55ENA $9 AI nurse, an 86 on the medical boards, and a 10% extinction lineホスト Nathan LabenzNathan Labenz’s solo scouting report walks from medical state of the art through how models actually learn, then to live players, scaling trends, and a control plan that still does not exist.
1:59:15ENA Protein Backbone in a Minute: The Real Progress, Bottlenecks, and Risks of AI Biologyホスト Nathan LabenzThe White House set a thousand-fold lower reporting bar for biological models than for language models—and this conversation shows why that gap already looks prescient.
3:04:52ENDoctors Chose AI on Eight of Nine Dimensions: A GPT-4 Red-Teamer's Scouting Reportホスト Nathan LabenzNathan Labenz tells 80,000 Hours what late-2023 systems can already do, which thresholds still matter, and why a polarized policy fight is a gift to heavy-handed regulation.
21:48ENVinod Khosla’s 12 Predictions for Technology and AbundanceMatthew Berman · Forward FutureMatthew Berman responds to a venture capitalist’s vision for 2035–2049, from AI expertise and robots to transportation, energy and climate technology.
18:17ENAI News in September 2023: Apple, Model Releases and InfrastructureMatthew Berman · Forward FutureMatthew Berman surveys a week of consumer products, autonomous-driving claims, safety policies and research, alongside an unverified extraterrestrial claim.
39:02ENAI’s product advantage is consistency. Its real weakness is getting conned.ホスト Nathan LabenzNathan Labenz updates the Cognitive Revolution scouting report: jailbreaks, resume automation, Med-PaLM’s 40% radiology win, and what might follow Transformers.
1:18:18ENFifteen Thousand Brain Numbers Were Enough to Reconstruct What Someone Sawホスト Nathan LabenzTanishq Mathew Abraham walks through MindEye, the fMRI-to-image system that maps a handful of voxel values onto CLIP and diffusion models.
1:16:44ENAlex Lebrun on AI Assistants for Doctors, Model Limits and Building Nablaゲスト Alex Lebrun · ホスト Harry StebbingsThe Nabla co-founder explains his approach to healthcare AI, lessons from Facebook and his 2023 views on competition and regulation.
1:25:35ENTwo and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical Schoolホスト Nathan LabenzVivek Natarajan walks Nathan Labenz through Med-PaLM and Med-PaLM 2: the data-light techniques, the nine-axis clinician evals, and why a high USMLE-style score is the wrong trophy.
42:18ENTen Percent of Search Is Health — and the Doctor Is Googling Tooホスト Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.
1:11:11ENEmad Mostaque on Open AI Models, National Data and the Race to Deployゲスト Emad Mostaque · ホスト Harry StebbingsThe Stability AI co-founder describes his 2023 vision for open models, healthcare applications and AI businesses, alongside concerns about a speculative boom.
1:28:43ENClinical Guidelines Are 11% Evidence. Curai’s Founder Still Wants GPT-4 in the Exam Roomホスト Nathan LabenzNeal Khosla of Curai Health argues that large language models already match median U.S. physicians on today’s tests — and that the real work is scaffolding, supervision, and a doctor’s signature.
58:24ENAmong 100 Random Doctors, Zak Kohane Would Be Surprised If One Beat GPT-4ホスト Nathan LabenzHarvard's biomedical informatics chair on a rare newborn case, why drug-style trials will not certify a general medical model, and why the AI should still work for the patient.
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