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27 篇
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2:00:51EN
Cognitive Revolution "How AI Changes Everything"· 2026年10月10日播客Resample Every Token and You Can Watch the Model Decide主持 Nathan LabenzGoodfire's Eric Bigelow on forking paths, in-context learning, and why chain-of-thought monitoring is getting harder to trust.智能体Prompting & in-context learningReasoning & test-time compute+3
2:06:11EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月14日播客Lindy 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.智能体Agent memory上下文工程+3
2:16:29EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2026年8月2日播客从每月两篇到每月六十篇:两周中国行看到的 AI 安全主持 Nathan LabenzNathan Labenz 认为,那句耳熟能详的“中国绝不会慢下来”,一接触到中国真实的 AI 安全生态就站不住了。安全安全与治理AI security+3
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日播客19 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.模型与训练Local inferenceScaling Laws+3
54:26EN
Cognitive Revolution "How AI Changes Everything"· 2026年2月22日播客Ten Billion Active Parameters, and the Unsexy Work of Making Them Agent-Ready主持 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.编程智能体Reinforcement Learning智能体工程+3
1:54:30EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月9日播客From One in Ten Cancer Cells to One in a Million主持 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.企业与战略AI Strategy编程智能体+3
1:18:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年1月1日播客When AI Becomes the Oil Well: Luke Drago on the Intelligence Curse主持 Nathan LabenzThe Workshop Labs co-founder tells the FLI Podcast why a world of non-human production could recreate the resource curse — and how private data, open weights, and moonshot careers might still break it.企业与战略AI Strategy安全与治理+3
1:32:38EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月6日播客Polish Is 1% of Frontier Training Data, So Poland Built Its Own Model主持 Nathan LabenzMarek Kozlowski of Poland's National Information Processing Institute explains how PLLuM uses language adaptation, organic instructions, and on-prem small models to keep a mid-size country in control of its AI.企业与战略Open-weight modelsData quality & curation+3
1:25:54EN
Cognitive Revolution "How AI Changes Everything"· 2025年12月3日播客Hours after training ends, Z.ai puts the weights on the internet主持 Nathan LabenzZixuan Li of Z.ai tells ChinaTalk how a Chinese lab ships GLM, treats open weights as a ticket into Western ecosystems, and still sees itself as an upstart.企业与战略Open-source ecosystemsOpen-weight models+3
2:14:55EN
Cognitive Revolution "How AI Changes Everything"· 2025年7月26日播客From Character AI to a 1% Warning Shot: Gabriel Weil's Case for Liability as AI Governance主持 Nathan LabenzA Touro law professor tells Nathan Labenz how negligence, strict liability, and punitive damages could make frontier labs treat public risk as a hit to their own balance sheet.安全安全与治理AI Regulation+3
1:30:57EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月12日播客Ant's $320 Billion IPO Was Stopped at the Eleventh Hour: Angela Zhang on China's Tech Tightrope主持 Nathan LabenzA USC law professor walks through the dynamic pyramid that governs Chinese tech, from Didi's listing to DeepSeek's price war, and why she thinks the United States is starting to look more like China.企业与战略AI Strategy安全与治理+3
1:08:51EN
Cognitive Revolution "How AI Changes Everything"· 2025年3月1日播客Chip Controls Are Meant to Buy Ten Years, Not Win the AI Race主持 Nathan LabenzEconomist Noah Smith tells Nathan Labenz that U.S. export controls are a piece of conventional deterrence against China — not a plan to kneecap DeepSeek.安全GeopoliticsAI Strategy+2
2:33:39EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2025年2月27日播客攻击者后出手:Nicholas Carlini 为什么总能攻破 AI 防御主持 Nathan Labenz谷歌 DeepMind 安全研究员谈简单的损失函数、70% 的稳健准确率,以及为什么修复必须落在系统层面,单靠模型本身不够。安全AI security安全与治理+3
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· 2025年1月25日播客From 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the Table主持 Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.模型与训练Reinforcement LearningReasoning & test-time compute+3
3:53:49EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2025年1月3日播客数据只有十二分之一,一个开源视觉模型击败了 GPT-4o主持 Nathan LabenzVeratai 的 Will Hardman 带 Nathan Labenz 梳理了两年来的视觉语言模型(VLM),从 ViT 和 CLIP 讲到 InternVL、BLINK 和 Transfusion。多模态与媒体Multimodal AI视觉与视频+3
1:57:00EN
Cognitive Revolution "How AI Changes Everything"· 2024年12月28日播客Less Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI First主持 Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.安全安全与治理AGI Timelines+3
1:49:41EN
Cognitive Revolution "How AI Changes Everything"· 2024年11月21日播客A Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Base主持 Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.模型与训练Post-trainingData quality & curation+3
2:24:18EN
Cognitive Revolution "How AI Changes Everything"· 2024年10月30日播客MMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.主持 Nathan LabenzZyphra’s training lead walks through Zamba 2’s hybrid architecture, the evals that actually matter, and the trade secrets small labs still have to rediscover.模型与训练Local inference评估+3
1:54:01EN
Cognitive Revolution "How AI Changes Everything"· 2024年6月26日播客A Tiny Network Grew a Salt Crystal the Training Data Never Showed主持 Nathan LabenzTim Duignan trained tens of thousands of parameters on salt water. The model invented a crystal — and a continuum solvent theory he had spent a PhD failing to write by hand.模型与训练AI for science机器学习基础+3
1:42:17EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月20日播客The Cheapest Inference Provider Is the Most Dangerous主持 Nathan LabenzFireworks AI cofounders Lin Qiao and Dmytro Ivchenko explain why subsidized GPU bills vanish, how LoRA serving can cut cost a hundredfold, and why OpenAI is the rival that actually matters.基础设施与部署InferenceAI cost & performance+3
2:16:27EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月12日播客Superhuman Go Has a Blind Spot. Balaji Bets on a War of the Gods主持 Nathan LabenzBalaji Srinivasan tells Nathan Labenz why adversarial inputs, missing actuators, and cryptography make a single runaway AI god less likely than a contest among many that still need priests.企业与战略安全与治理Open-weight models+3
1:14:36EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月13日播客Zulu Bypasses GPT-4, and a Hundred Examples Undo the Guardrails主持 Nathan LabenzNathan Labenz reads seven papers — four hopeful, three not — on whether anyone can actually keep a language model under control.安全AI security安全与治理+3
52:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月25日播客OpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the List主持 Nathan LabenzNathan Labenz and Erik Torenberg walk through GPT-3.5 Turbo fine-tuning, why self-hosting still loses on total cost, and what is actually working in code, school, and medicine.模型与训练微调AI cost & performance+3
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023年6月16日播客From $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Product主持 Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.模型与训练微调Pretraining & midtraining+3
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