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1:18:46EN90 Slides in 45 Minutes: A Full-Time AI Scout Admits He Can No Longer Keep UpAnime : Nathan LabenzNathan Labenz’s LexLab briefing for lawyers runs through the good, the bad, and the weird of frontier models — from triplicate second opinions on his son’s cancer care to AIs that know they are being tested.
1:43:39ENFive Mutations Could Make a 60% Fatal Bird Flu Spread Between PeopleAnime : 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.
2:06:23ENFive AI Employees Live on Five Mac MinisAnime : Nathan LabenzAfter selling her YC packaging company, Jesse Genet opened a terminal for the first time and built an OpenClaw staff that now plans lessons, logs learning, and keeps family evenings from sliding into slop.
1:49:53ENDon't Fight Backprop: Goodfire's Bet on Designing What Models LearnAnime : Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.
2:17:36ENCurrent Safety Techniques Will Not Give You Many Nines—and They May Fail TogetherAnime : Nathan LabenzUK AISI chief scientist Geoffrey Irving on jailbreaks that never fail, correlated alignment failures, and why a government lab is funding theory.
2:03:56EN260 Doctors and 49,000 Criteria: How OpenAI Built Attending-Level Health AIAnime : 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.
40:00ENHow Matthew Berman Built an OpenClaw Workflow for His TeamMatthew Berman · Forward FutureA tour of sponsorship triage, CRM, meeting notes, security, scheduling, memory and backup after a month of heavy use.
54:26ENTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-ReadyAnime : Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.
1:34:29ENThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileAnime : Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.
33:44ENHow Matthew Berman Uses OpenClaw for a Personal AssistantMatthew Berman · Forward FutureA tour of customized CRM, meeting, research and security workflows, along with the limits of automation and the need for backups.
2:25:42ENThe experts argued through the coffee break — and never agreed whether AI can build AIAnime : 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.
1:34:42ENA $500 Kernel, a Ten-Month Village, and the Temper of AgentsAnime : Nathan LabenzJames Zou, Sam Hammond, and Shoshannah Tekofsky on science agents, America's knowledge-work bet, and what models actually do when you leave them alone.
1:18:49ENIf AGI Is Cheap Intelligent Labor, Cyber Defense Should Become Continuous ForensicsAnime : Nathan LabenzAsymmetric Security founder Alexis Carlier argues that assuming AGI means redesigning defense around proactive digital forensics instead of alert triage.
1:57:56ENA Hundred Million Lines at Twenty Cents Each: Inside Blitzy's Enterprise Coding PipelineAnime : Nathan LabenzCEO Brian Elliott and CTO Sid Pardeshi tell Nathan Labenz how Blitzy turns a giant codebase into a map, then lets thousands of dynamically generated agents ship most of a multi-month project in days.
1:04:51EN125 million cells took a decade. The next billion takes monthsAnime : 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.
4:25:13ENThe Architecture Barely Changed. Data, Cost, and Open Weights Did.Anime : Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
1:03:00ENA Model That Solves New Math Problems Every Week Still Isn't AGIAnime : Jacob EffronFormer OpenAI research VP Jerry Tworek on why scaling still works, why models go hopeless when they fail, and why he left to chase continual learning.
1:39:17ENAI Already Beats the Median Lawyer. Top Firms Bought the Tools and Left Them UnusedAnime : Nathan LabenzKevin Frazier and Alan Rozenshtein walk through how frontier models are changing legal practice, why billable hours stall adoption, and which new rights and government limits they want next.
2:12:31ENMost Caffeine users have no idea they are on a blockchainAnime : Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
2:25:10ENFine-Tuning Isn't Dead — But It Turned a Helpful Model EvilAnime : Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.
2:29:42ENTwelve hooks and thirty files: Daniel Miessler’s personal OS on Claude CodeAnime : Nathan LabenzThe PAI framework treats scaffolding, not the model, as the product — a goal-centered agent stack that Miessler thinks will decide both knowledge-work automation and the next cybersecurity race.
1:40:51ENReasoning Models Just Made the Other 80–90% of Enterprise Data UsableAnime : Nathan LabenzSnowflake VP of AI Baris Gultekin on text-to-SQL, RAG, agent design, and why inference has to run next to governed data.
1:54:30ENFrom One in Ten Cancer Cells to One in a MillionAnime : Nathan LabenzNathan Labenz's solo AMA updates his son's lymphoma treatment, calls Claude Opus 4.5 software AGI, and ranks the live players of early 2026.
32:20ENTheo Browne on Building with Claude CodeTheo Browne · Ping LabsA hands-on look at parallel coding agents, an image studio and a mobile monorepo, including the mistakes and review work behind the demos.
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