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10月5日周一
  1. Emad20

    是啊。这也是税收型UBI行不通的原因之一,美国税收中劳动份额约占80%

    引用The Economist@TheEconomist

    What if AI cut labour’s share of national income by ten percentage points? Our analysis finds that a majority of governments that rely on taxing workers would be crippled https://www.economist.com/finance-and-economics/2026/09/29/how-the-ai-boom-could-worsen-the-rich-worlds-fiscal-crunch?taid=6ac24471d67e050001c6dac6&utm_campaign=trueanthem&utm_medium=social&utm_source=twitter

10月4日周日
  1. Emad17

    Meta 其实输了这场官司,被罚 180 亿美元,耸耸肩就继续了 史上最大的反垄断赔偿是 55 亿美元(Visa 和 Mastercard) 任何因放缓 AI 而生的罚款都只是这个数的一小部分 如果 AI 不协调就会违法/造成伤害,那这算不上反对协调的严肃论据

    引用David Krueger 🦥 ⏸️ ⏹️ ⏪@DavidSKrueger

    People at Anthropic keep telling me they can't coordinate to slow down because of anti-trust, but I've talked to leading lawyers who disagree. Meta spent $2,400,000,000 on lawyers in a single quarter fighting charges that its products hurt kids. How much has Anthropic spent on this anti-trust thing?

10月3日周六
10月2日周五
  1. Sam Altman23

    你应该能在任何需要的地方使用你的 AI 订阅:

    引用Vignesh@vigyso

    I am going to try and answer a bunch of questions that people have raised about Sign in with ChatGPT in the next couple of days. Before that, I want to let you all in to why we shipped Sign in with ChatGPT (SIWC) in the first place. Clarify our intentions here before getting to the specifics.

9月29日周二
9月23日周三
  1. Sam Altman15

    初创公司天生擅长这一点;但要让一家更大的公司也保持这种能力却很难,我认为这是一个尚未被充分探索的领域。

    引用pranav@prd_008

    OpenAI's superpower is the ability to swiftly assemble an empowered group of highly capable people to work on the most important and urgent thing at any point of time. No one really cares for org lines. It's how we stay nimble, seize opportunities, and recover from mistakes.

9月12日周六
8月15日周六
8月2日周日
8月1日周六
  1. Mira Murati42

    我们分享了对开放权重发布的思路、我们如何评估 Inkling、为什么安全取决于模型及其所进入的生态系统、以及测试、分阶段访问和更强的防御如何能开辟一条通往更大开放度的道路。

    引用Thinking Machines@thinkymachines

    Releasing weights indiscriminately isn't safe. Neither is keeping capable models inside a few labs. We think there's a path between them. We haven't mapped all of it. Our new post covers the part we can see: how we assessed Inkling, and why access should widen in stages. https://thinkingmachines.ai/blog/a-safe-path-to-open-weights

7月25日周六
  1. Mira Murati22

    让 AI 变得有用的知识是分散的。它存在于科学家、工程师、临床医生和企业之中。要让 AI 从分布式知识中受益,它自身也必须是分布式的。同意 Jensen 的观点,这是一个值得建设的未来。

    引用Jensen Huang@JensenHuang

    For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. https://images.nvidia.com/pdf/Open-Weights-and-American-AI-Leadership.pdf

7月7日周二
  1. Berkeley AI Research42

    智能免费之后怎么办?面向智能体、由智能体构建的数据系统

    UC Berkeley 团队提出,推理成本已从 GPT-4 级约 $30/百万 token 降至不足 $1,部分厂商低于 $0.10,基准测试中推理价格每年下降 9x 至 900x、中位数约 50x。作者据此提出三类数据系统挑战:为智能体设计的数据系统、支撑智能体群体运行的数据系统、以及由智能体合成的数据系统。

6月24日周三
  1. Andrej Karpathy58

    Anthropic 推出 Claude Tag,团队可在 Slack 中把 Claude 加为团队成员,让它访问指定频道和工具并委派任务。Andrej Karpathy 认为这是 LLM 交互界面的第三次重大重构,前两次分别是网页和桌面应用,这一次 Claude 成为拥有组织级工具与上下文的持久异步实体。

    引用Claude@claudeai

    Introducing Claude Tag, a new way for teams to work with Claude. In Slack, Claude joins as a team member with access to the channels and tools you choose. Tag Claude in and delegate tasks to it while you focus on other work.

6月10日周三
  1. Andrej Karpathy82

    Andrej Karpathy 评价 Claude Fable 5 发布,称其与 Mythos 是同一底层模型但增加了安全防护,基准测试全面 SOTA 且领先明显。

    引用Claude@claudeai

    Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision. The longer and more complex the task, the larger Fable 5’s lead over our other models.

    推荐理由:Karpathy 以第一手使用体验评价 Claude Fable 5 在长任务和复杂问题上的跃升,并给出对软件需求变化的判断。

5月12日周二
5月8日周五
  1. Berkeley AI Research36

    自适应并行推理:高效推理扩展的下一个范式

    伯克利 AI 研究团队综述并行推理进展,重点分析自适应并行推理——让模型自行决定何时分解并并行化子任务、开多少并发线程以及如何协调。现有方法如 self-consistency、Best-of-N、Tree of Thoughts、MCTS、ParaThinker、GroupThink 和 Hogwild! Inference 的并行结构多由外部设定,而非模型自主选择。

5月1日周五
  1. Andrej Karpathy38

    Karpathy 在 Sequoia Ascent 2026 炉边对话中提出,LLM 的价值远不止加速现有编码工作,并给出三个新场景:完全由 LLM 承载、无需传统代码的 menugen 应用;用 .md 技能替代 .sh 安装脚本;以及传统代码无法实现、对非结构化知识做计算的 LLM 知识库。

    引用Stephanie Zhan@stephzhan

    @karpathy and I are back! At @sequoia AI Ascent 2026. And a lot has changed. Last year, he coined “vibe coding”. This year, he’s never felt more behind as a programmer. The big shift: vibe coding raised the floor. Agentic engineering raises the ceiling. We talk about what it means to build seriously in the agent era. Not just moving faster. Building new things, with new tools, while preserving the parts that still require human taste, judgment, and understanding.

4月10日周五
4月5日周日
  1. Andrej Karpathy60

    Karpathy 转发并点评 Farza 用 LLM 把 2,500 条日记、Apple Notes 和 iMessage 记录整理成含 400 篇文章的个人 Wiki(Farzapedia),认为这是个人化 AI 的好范例。

    引用Farza 🇵🇰🇺🇸@FarzaTV

    This is Farzapedia. I had an LLM take 2,500 entries from my diary, Apple Notes, and some iMessage convos to create a personal Wikipedia for me. It made 400 detailed articles for my friends, my startups, research areas, and even my favorite animes and their impact on me complete with backlinks. But, this Wiki was not built for me! I built it for my agent! The structure of the wiki files and how it's all backlinked is very easily crawlable by any agent + makes it a truly useful knowledge base. I can spin up Claude Code on the wiki and starting at index.md (a catalog of all my articles) the agent does a really good job at drilling into the specific pages on my wiki it needs context on when I have a query. For example, when trying to cook up a new landing page I may ask: "I'm trying to design this landing page for a new idea I have. Please look into the images and films that inspired me recently and give me ideas for new copy and aesthetics". In my diary I kept track of everything from: learnings, people, inspo, interesting links, images. So the agent reads my wiki and pulls up my "Philosophy" articles from notes on a Studio Ghibli documentary, "Competitor" articles with YC companies whose landing pages I screenshotted, and pics of 1970s Beatles merch I saved years ago. And it delivers a great answer. I built a similar system to this a year ago with RAG but it was ass. A knowledge base that lets an agent find what it needs via a file system it actually understands just works better. The most magical thing now is as I add new things to my wiki (articles, images of inspo, meeting notes) the system will likely update 2-3 different articles where it feels that context belongs, or, just creates a new article. It's like this super genius librarian for your brain that's always filing stuff for your perfectly and also let's you easily query the knowledge for tasks useful to you (ex. design, product, writing, etc) and it never gets tired. I might spend next week productizing this, if that's of interest to you DM me + tell me your usecase!

  2. Andrej Karpathy22

    Karpathy 表示看好被 AI 赋能的公众提升政府的可见性、可读性与问责制。他认为政府问责的瓶颈从来不是数据获取,而是处理海量原始数据并提炼洞察的智能,4000 页综合法案对多数人只是名义上透明。AI 可让支出预算核算、立法 diff 追踪、游说关系图谱等分析不再只由调查记者承担,但他也提醒同一工具同样可能被反向利用。

    引用Harry Rushworth@Hrushworth

    The British Government is a complicated beast. Dozens of departments, hundreds of public bodies, more corporations than one can count... Such is its complexity that there isn't an org chart for it. Well, there wasn't... Introducing ⚙️Machinery of Government⚙️

3月28日周六
3月27日周五
  1. Andrej Karpathy58

    Andrej Karpathy 回顾约一年前搭建 menugen 的经历,认为最难的不是代码本身,而是服务、支付、认证、数据库、安全、域名等一整套 DevOps 组装。

    引用Patrick Collison@patrickc

    When @karpathy built MenuGen (https://karpathy.bearblog.dev/vibe-coding-menugen/), he said: "Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services, docs, API keys, configurations, dev/prod deployments, team and security features, rate limits, pricing tiers." We've all run into this issue when building with agents: you have to scurry off to establish accounts, clicking things in the browser as though it's the antediluvian days of 2023, in order to unblock its superintelligent progress. So we decided to build Stripe Projects to help agents instantly provision services from the CLI. For example, simply run: $ stripe projects add posthog/analytics And it'll create a PostHog account, get an API key, and (as needed) set up billing. Projects is launching today as a developer preview. You can register for access (we'll make it available to everyone soon) at http://projects.dev. We're also rolling out support for many new providers over the coming weeks. (Get in touch if you'd like to make your service available.) https://projects.dev