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2:29:20EN → 简体中文市场不会选出诚实的模型主持 Nathan Labenz记者 Robert Wright 对 Nathan Labenz 说,AI 是一个选择问题,一个地缘政治问题,也是人类可能过不了的一道道德考题。
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.
2:38:44EN → 简体中文距离自主研究员还有 21 个月,《AI 行动计划》作者加入 OpenAI主持 Nathan LabenzDean Ball 正在 OpenAI 组建 Strategic Futures 团队,此时 OpenAI 公开的时间表显示:三个月后出现 AI 研究实习生,2028 年 3 月出现完全自主的 AI 研究员。
45:00ENLip-Bu Tan took the hardest job in chips to save Intel主持 Sarah Guo, Elad GilThe Cadence veteran and semiconductor investor tells No Priors how he is rebuilding Intel's culture, balance sheet, and foundry, and why he still wants a 10x from here.
38:45ENThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
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.
51:09ENBuild like the model will eat your harness in a yearLogan Kilpatrick, who leads Google AI Studio and the Gemini API, tells Sequoia's Sonya Huang why agent scaffolding is a 12-month asset, why coding already feels like narrow superintelligence, and why Google is optimizing for outcomes instead of eyeballs.
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.
41:20ENA $4 Million Cabinet and a Trillion-Dollar Year: Jensen Huang Turns the AI Factory Into a Manufacturing StoryOn Sequoia's Training Data stage, NVIDIA's CEO walks a sixty-country audience from ChatGPT's parlor tricks to agentic work, a five-layer industrial cake, and why radiology hiring went up.
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.
42:27ENEvery Company Can Operate at the Frontier — If It Owns the Evals主持 Sarah Guo, Elad GilAt Microsoft Build, Satya Nadella tells No Priors and Latent Space why AI is an ecosystem game, why private evals beat public benchmarks, and why the Azure networking team now asks for tokens instead of headcount.
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.
40:22ENBuilding Gets Easier Near AGI. Knowing What to Build Does Not.Listen Labs CEO Alfred Wahlforss on AI interview agents, a 30-million-person audience, and why transcripts beat credit-card data when you need to predict customers.
56:10ENReid Hoffman Pledged a Billion to Free DeepMind. Hassabis Never Played the Card主持 Jacob EffronSebastian Mallaby's biography of Demis Hassabis, discussed with Jacob Effron, is a story of a founder who tried to stop the AI race and then became one of its central players.
2:33:35ENA security researcher audits the AI stack that booked a week of guests主持 Nathan LabenzNathan Labenz walks Daniel Miessler through a 1GB second brain, two named AI employees, and the blast-radius rules that should govern them.
2:53:42EN → 简体中文月亮一直在下落,却总也落不到地球上嘉宾 Biggest Mysteries in Physics · 主持 Lex Fridman费米实验室(Fermilab)物理学家 Don Lincoln 在与 Lex Fridman 的对谈中说,物理学的历史就是一部统一的历史;反物质(antimatter)、暗能量(dark energy)和万物理论(theory of everything)依然远在我们能做的实验之外。
41:09ENAfter Agents Leak Tokens and Wipe Databases, Onyx Trains Small Models to Watch the Big Ones主持 Sarah Guo, Elad GilTwo years ago enterprise security buyers told Maxim Bar Kogan he was too early. Now Fortune 10 companies are calling a sub-100-person Israeli startup because they cannot stop agent adoption — only reduce the chance the next action is illegitimate.
1:41:58ENA thousand people on guard, a million in the sprint主持 Nathan Labenz80,000 Hours founder Ben Todd on how to spend a career in the years when your impact on AI will actually peak.
45:33ENCursor Ships 1TB of Composer Weights Across Oceans in Under a MinuteFederico Cassano and Fireworks' Dima walk through the globally split RL stack that trained Composer 2 on a sparse trillion-parameter MoE.
2:13:11ENThe Models Understand Shutdown. They Just Don't Care.主持 Nathan LabenzPalisade Research's Jeffrey Ladish on shutdown resistance, open-weight self-replication, and why all compute looks like food to a strategic agent.
59:41ENThe GPT moment for video hasn’t arrived, but AGI may already be here主持 Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
30:34ENCerebras Waited Ten Years for a Market That Finally Needed Speed主持 Sarah Guo, Elad GilFounder and CEO Andrew Feldman walks No Priors through wafer-scale chips, a $20 billion OpenAI deal, and why a dinner-plate processor only mattered once AI became an everyday tool.
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