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729 件並び順
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.
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.
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.
2:16:29ENFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI Safetyホスト Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
1:04:14ENThe Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your Houseホスト Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.
1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can Winホスト Nathan LabenzAdam Gleave walks through FAR.AI’s first head-to-head AI security leaderboard, and explains why a decade of offense-dominant thinking is starting to crack.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His Inboxホスト Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
1:13:48ENCarriers Spend $200 Billion a Year. The Money Went Up the Stackホスト Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
2:23:38ENDavidad Cut His p(doom) From the Seventies to Under 5% — and Named a Bodhisattva as the Alignment Targetホスト Nathan LabenzThe former ARIA Safeguarded AI director tells Cognitive Revolution why boxing superintelligence is too late, why he thinks models are climbing a U-shaped wisdom curve, and why the remaining risk is a race you cannot monitor.
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token Oneホスト Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuberホスト Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
1:47:38EN19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chipホスト Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:29:02ENFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Exploreホスト Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
1:57:46EN30% Consciousness, 47% Bee, 80% Turnover: Putting Numbers on What AI Is Becomingホスト Nathan LabenzA Cognitive Revolution weekly cut that starts inside the model with Cameron Berg, then zooms out through gradual disempowerment, Europe’s bind, and the companies rebuilding around agents.
2:29:20ENThe Market Will Not Choose an Honest Modelホスト Nathan LabenzJournalist Robert Wright tells Nathan Labenz that AI is a selection problem, a geopolitical problem, and a moral test humanity may not pass.
2:14:33ENA 90-Minute Ultimatum, an Emoji Wall, and a Rule: Don't Fight Washingtonホスト Nathan LabenzZvi Mowshowitz reads Fable's system card, then Nathan Labenz stress-tests the export-control fight against lawyers, safety researchers, and builders who did not pause.
2:38:44ENTwenty-one months from an autonomous researcher, the Action Plan's author joins OpenAIホスト Nathan LabenzDean Ball is building Strategic Futures as OpenAI's public timeline counts down to an AI research intern in three months and a full autonomous researcher in March 2028.
1:44:28ENFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overホスト Nathan LabenzNathan Labenz’s AI in the AM highlights reel from June 2026 covers Anthropic’s new frontier model, the founding of Sequent, and a week that settled one argument: AI is not slowing down.
1:06:36ENBills Doubled Overnight. Next, the APIs Might Vanish.ホスト Jacob EffronSix months after their last roundup, Ari Morcos and Rob Toews tell Jacob Efron why coding agents finally work, why near-frontier open weights may have peaked, and why a compute famine could pull the plug on public APIs.
1:45:59EN87% of Workers Use AI. Only 13% Say the Company Got Better.ホスト Nathan LabenzGlean’s Work AI Index names the missing hours: botsitting, botshitting, and a hamster wheel of polished nonsense.
1:22:36ENA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the Brakesホスト Nathan LabenzThe first week of AI in the AM follows OpenAI's timeline for an ML-intern model this year and a human-level AI researcher by early 2028 — and the closed-door meeting where labs admitted they might one day need to slow down together.
2:59:44ENTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.ホスト Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still Missホスト Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
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