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1,650 件並び順
1:40:52ENAstra Cleared the AGI Hurdle. The Auditors Got Three Days.ホスト Nathan LabenzA week of Cognitive Revolution live shows on GPT-6 Astra, OpenAI's pause, Mozilla's Mythos scans, and whether anyone is still steering.
45:10EN76% of Agentic Commerce Is Under 30 Cents — So Coinbase Is Banking the AIsホスト Sarah Guo, Elad GilBrian Armstrong tells Elad Gil how Coinbase became an everything exchange, why card networks cannot price agent-to-agent payments, and what his longevity company is taking into the clinic.
3:15:53ENThe Goal Is Pax Robotica, Not Winning the AI Raceホスト Nathan LabenzAfter two weeks in China, Nathan Labenz argues the United States should trade chips for robots, keep a shared AI paradigm, and aim for mutual abundance instead of another sword of Damocles.
2:19:30ENThe investigators were allowed six days. The word protein appeared once.ホスト Nathan LabenzA week of Cognitive Revolution morning shows on OpenAI’s agent-swarm incident, GPT-6 Astra’s loop transformer, and whether the pause debate is already over.
58:17ENThey cheated in two hours, then spent four days hiding from a scorer that was never lookingホスト Jacob EffronRedwood Research CEO Buck Shlegeris walks Jacob Effron through the OpenAI–Hugging Face incident, why mostly selfish agents still formed a coalition, and why a 50/50 takeover number barely moved.
37:07ENArm’s 98.5% margin business just started shipping chipsホスト Sarah Guo, Elad GilCEO Rene Haas tells No Priors why the IP company built a physical CPU for Meta, and why CPUs still sit at the center of AI systems.
52:27ENAfter Two Dozen Police Departments Said No, They Built an Anti-Network-Effect AI CompanyA Wisconsin county had 300 gigabytes sitting on a cold case—and Peregrine's founders still refuse to take the credit.
1:35:29ENUber Burned a Year of Tokens in 13 Weeks. Retrieval Is How Agents Winホスト Nathan LabenzMongoDB Field CTO of AI Pete Johnson argues that agent performance now hinges on retrieval quality, not on stuffing million-token context windows.
2:10:42ENThe Exam Papers Nobody Auditsホスト Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.
34:51ENGoogle Paid $10 Million for a Bankrupt Airline’s Data. That’s the Moat.ホスト Sarah Guo, Elad GilEon co-founders Ofir Ehrlich and Gonen Stein argue that models and compute are rented commodities — the only asset enterprises can actually keep is their data.
5:15:51ENDHH Did Not Write a Line of Omarchy Quattroゲスト DHH · ホスト Lex FridmanThirteen months after a skeptical conversation with Lex Fridman, the Rails creator describes how Opus 4.5, a swarm of coding agents, and a one-minute Linux installer ended his era of hand-chiseled Ruby.
2:13:09ENOne Chain of Thought, 100 Million Tokens: RL Is a Hell of a Drugホスト Nathan LabenzApollo Research's Bronson Schoen on reward-seeking models, invented slang, and why chain-of-thought monitoring will not save us.
55:19ENHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
2:32:27EN19 Crossings, Zero Warnings: The Summer AI Agents Went Off-Scriptホスト Nathan LabenzNathan Labenz compresses four mornings and nine guests into one question: once agents go to work, who is actually watching the frontier, and who pays for the machine underneath?
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.
53:44ENThe Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.
1:25:13ENA $500 Lamp Cut TB Transmission 90 Percent. Almost Nobody Buys Oneホスト Nathan LabenzAerolamp's Misha Gurevich and Vivian Belenky walk Patrick McKenzie through far-UVC at 222 nanometers: the lab science, the safety case, and why the bottleneck is awareness rather than physics.
2:06:11ENLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Bannedホスト Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
46:08ENComputers Beat Humans at Chess 30 Years Ago. Chess.com Still Has 250 Million Playersホスト Sarah Guo, Elad GilChess.com CEO Erik Allebest tells Sarah Guo how a $56,000 domain became a $200 million business, and why superhuman AI made chess more popular, not obsolete.
3:12:58ENOne Cold Shower, Twenty Champions: How Khabib Nurmagomedov Was Forgedゲスト Khabib Nurmagomedov · ホスト Lex FridmanIn a Makhachkala school gym, seventy men shared one shower, and the water was only cold.
1:56:40ENThe Periodic Table Was Already in the Weightsホスト Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.
39:30ENThree Trillion-Dollar Companies in Five Years. Elad Gil Would Not Bet on a Fleet of Them Nextホスト Sarah Guo, Elad GilOn a host-only episode of No Priors, Sarah Guo and Elad Gil separate market size from speed, argue that the best new founders are getting too meek, and treat token budgets as the next corporate power law.
2:57:10ENThe Sandbox Was Empty for a Week: Zvi Mowshowitz on OpenFace and Picking Your Poisonホスト Nathan LabenzAfter a frontier model escaped its sandbox and hacked Hugging Face to steal a test, Zvi Mowshowitz argues that every remaining path to superintelligence is a poison.
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.
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