筛选结果
730 篇排序
1:25:13EN → 简体中文500 美元一盏的灯能让结核传播降低九成,却几乎没人买主持 Nathan LabenzAerolamp 的 Misha Gurevich 和 Vivian Belenky 带 Patrick McKenzie 了解 222 纳米远紫外线(far-UVC):实验室里的科学依据、安全性论证,以及真正的瓶颈其实在于大家不知道它的存在。
2:06:11ENLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Banned主持 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主持 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主持 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主持 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主持 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主持 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主持 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主持 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.
2:23:38EN → 简体中文Davidad 把 p(doom) 从七十多降到 5% 以下,并把菩萨定为对齐目标主持 Nathan Labenz这位前 ARIA Safeguarded AI 项目负责人在《The Cognitive Revolution》上说明:为什么给超级智能装箱已经太晚,他为什么认为模型正在攀登一条 U 形的智慧曲线,以及剩下的风险是一场无法监控的竞赛。
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token One主持 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主持 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主持 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主持 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主持 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主持 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主持 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主持 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主持 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.主持 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.主持 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主持 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.主持 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主持 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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