筛选结果
217 篇排序
1:08:02ENAlphaGo Took Two Years. AlphaZero Took Hours. Silver Is Making the Same Bet on SuperintelligenceDavid Silver and Lasse Espeholt left DeepMind to build Ineffable Intelligence, a twenty-person lab that wants a superlearner to discover science, math, and language from experience rather than from a pre-training run.
31:00EN → 简体中文为什么 AI 实验室自己警告会出重大事故,却还在继续竞赛Sam Altman, John Schulman · OpenAIAI Explained 梳理正在变弱的安全防护、前沿竞赛背后的激励,以及研究突破为何让未来 18 个月更难预测。
2:00:51ENResample 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.
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2主持 Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
2:13:27EN → 简体中文他写书要叫停 AI 竞赛,自己却差点对 Claude 上了瘾主持 Nathan Labenz记者 Garrison Lovely 相信 AGI 实验室说的话,拒绝“泡沫论”的说法,并主张冻结前沿研发,直到公众真正表示同意。
51:55EN → 简体中文AI 解不出的最后一道 IMO 题Grant Sanderson · 3Blue1BrownGrant Sanderson 带你走一遍 2025 年 IMO 第 6 题——前沿模型没做出来的铺砖谜题——以及要证明一种构造最优,需要怎样的视觉耐心。
38:14ENDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom Silicon主持 Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
2:10:42EN → 简体中文没人审核的考卷主持 Nathan Labenz前沿实验室从一群小供应商那里购买强化学习(reinforcement learning)环境,却几乎没人核查这些测试是否贴合真实工作。
2:13:09EN → 简体中文一条思维链,1 亿 Token:强化学习真让人上瘾主持 Nathan LabenzApollo Research 的 Bronson Schoen 谈追逐奖励的模型、模型自创的俚语,以及为什么思维链监控救不了我们。
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.
2:16:29EN → 简体中文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。
49:12ENThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
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.
1:57:46EN → 简体中文意识 30%、蜜蜂 47%、人员更替 80%:用数字衡量 AI 正在变成什么主持 Nathan Labenz《The Cognitive Revolution》的周度精选,先从 Cameron Berg 谈模型内部开始,再拉远到“逐步剥夺人类权力”(gradual disempowerment)、欧洲的两难处境,以及围绕智能体(Agent)重新搭建业务的公司。
36:19ENThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score Models主持 Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
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.
1:22:36EN → 简体中文一千名研究员、一百万个 AI:前沿实验室开始谈论刹车主持 Nathan Labenz《AI in the AM》的第一周跟踪了 OpenAI 的时间表:今年推出 ML 实习生模型,2028 年初出现人类水平的 AI 研究员。同时还有一场闭门会议,实验室在会上承认,将来也许需要一起放慢速度。
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.
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.
1:21:56EN → 简体中文Yann LeCun 离开 Meta:大语言模型通向不了智能主持 Jacob Effron这位图灵奖得主对 Jacob Effron 讲述了他为何从 Meta 分拆出 AMI Labs,为何类 JEPA 的世界模型胜过像素生成器,以及他为何认为 Hinton 在 2023 年改变了看法。
3:36:29EN → 简体中文Claude 给自己的福利打了 4.49 分:首个越过中性线的版本主持 Nathan LabenzCameron Berg 再次做客《The Cognitive Revolution》,梳理六个月来在内省、功能性情绪和模型福利(model welfare)方面的研究,并介绍一项尚未发表的案例:学习与感受也许是同一种现象。
3:10:49EN → 简体中文冲刺时刻:Ajeya Cotra 为超级智能到来前的几个月准备的剧本主持 Nathan Labenz一场关于递归自我改进(recursive self-improvement)、公众预警系统,以及用每一代 AI 去对齐(alignment)和控制下一代的对话。
58:46ENTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028主持 Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
1:49:53ENDon't Fight Backprop: Goodfire's Bet on Designing What Models Learn主持 Nathan LabenzDan Balsam and Tom McGrath return to The Cognitive Revolution with a $150 million Series B, a new research pillar called intentional design, and a rule for anyone who wants to steer training: stop trying to out-muscle gradient descent.
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