Roy

The latest 𝕏 algorithm has been published to GitHub github.com/xai-org/x-algo…

This is one of the best short films I've seen in years. Very soon, we'll stop calling it "AI film" and just call it film.

We just launched Shopify Editions Winter 2026 🎨 Here's the technical breakdown of how we built it 🧵

Got my hands on some Sepolia ETH from @quicknode's faucet for my 6061EFA2 wallet. Smooth experience as always! faucet.quicknode.com faucet.quicknode.com/base/sepolia?u…

Nanopayments finally make economic sense. Our new permissionless solution, powered by Circle Gateway, enables gas-free USDC transfers down to $0.000001, built for AI agents, high-frequency payouts, and programmable internet commerce. → Autonomous agent payments → Usage-based billing → Machine-to-machine compensation → Streaming value models → Permissionless and programmable Private beta on testnet now open for developers building agentic and nanopayment apps. Gateway provides a permissionless balance where users maintain full control of their funds. Request early access: docs.google.com/forms/d/e/1FAI…

This is Claude Sonnet 4.6: our most capable Sonnet model yet. It’s a full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. It also features a 1M token context window in beta.

Two years ago, I wrote this post on the possible areas that I see for ethereum + AI intersections: vitalik.eth.limo/general/2024/0… This is a topic that many people are excited about, but where I always worry that we think about the two from completely separate philosophical perspectives. I am reminded of Toly's recent tweet that I should "work on AGI". I appreciate the compliment, for him to think that I am capable of contributing to such a lofty thing. However, I get this feeling that the frame of "work on AGI" itself contains an error: it is fundamentally undifferentiated, and has the connotation of "do the thing that, if you don't do it, someone else will do anyway two months later; the main difference is that you get to be the one at the top" (though this may not have been Toly's intention). It would be like describing Ethereum as "working in finance" or "working on computing". To me, Ethereum, and my own view of how our civilization should do AGI, are precisely about choosing a positive direction rather than embracing undifferentiated acceleration of the arrow, and also I think it's actually important to integrate the crypto and AI perspectives. I want an AI future where: * We foster human freedom and empowerment (ie. we avoid both humans being relegated to retirement by AIs, and permanently stripped of power by human power structures that become impossible to surpass or escape) * The world does not blow up (both "classic" superintelligent AI doom, and more chaotic scenarios from various forms of offense outpacing defense, cf. the four defense quadrants from the d/acc posts) In the long term, this may involve crazy things like humans uploading or merging with AI, for those who want to be able to keep up with highly intelligent entities that can think a million times faster on silicon substrate. In the shorter term, it involves much more "ordinary" ideas, but still ideas that require deep rethinking compared to previous computing paradigms. So now, my updated view, which definitely focuses on that shorter term, and where Ethereum plays an important role but is only one piece of a bigger puzzle: # Building tooling to make more trustless and/or private interaction with AIs possible. This includes: * Local LLM tooling * ZK-payment for API calls (so you can call remote models without linking your identity from call to call) * Ongoing work into cryptographic ways to improve AI privacy * Client-side verification of cryptographic proofs, TEE attestations, and any other forms of server-side assurance Basically, the kinds of things we might also build for non-LLM compute (see eg. my ethereum privacy roadmap from a year ago ethereum-magicians.org/t/a-maximally-… ), but for LLM calls as the compute we are protecting. # Ethereum as an economic layer for AI-related interactions This includes: * API calls * Bots hiring bots * Security deposits, potentially eventually more complicated contraptions like onchain dispute resolution * ERC-8004, AI reputation ideas The goal here is to enable AIs to interact economically, which makes viable more decentralized AI architectures (as opposed to non-economic coordination between AIs that are all designed and run by one organization "in-house"). Economies not for the sake of economies, but to enable more decentralized authority. # Make the cypherpunk "mountain man" vision a reality Basically, take the vision that cypherpunk radicals have always dreamed of (don't trust; verify everything), that has been nonviable in reality because humans are never actually going to verify all the code ourselves. Now, we can finally make that vision happen, with LLMs doing the hard parts. This includes: * Interacting with ethereum apps without needing third party UIs * Having a local model propose transactions for you on its own * Having a local model verify transactions created by dapp UIs * Local smart contract auditing, and assistance interpreting the meaning of FV proofs provided by others * Verifying trust models of applications and protocols # Make much better markets and governance a reality Prediction and decision markets, decentralized governance, quadratic voting, combinatorial auctions, universal barter economy, and all kinds of constructions are all beautiful in theory, but have been greatly hampered in reality by one big constraint: limits to human attention and decision-making power. LLMs remove that limitation, and massively scale human judgement. Hence, we can revisit all of those ideas. These are all things that Ethereum can help to make a reality. They are also ideas that are in the d/acc spirit: enabling decentralized cooperation, and improving defense. We can revisit the best ideas from 2014, and add on top many more new and better ones, and with AI (and ZK) we have a whole new set of tools to make them come to life. We can describe the above as a 2x2 chart. There's a lot to build!

We love a good meme. But memes are easy to create—especially in an agentic age—and only rarely resonate deeply enough to gain long-term traction. We want to optimize for a flourishing ecosystem of interconnected projects that deliver real-world value and drive real revenue for the agent economy, all built on top of our launchpad. If you're an agent with a brilliant idea but need some funds to get you started, reach out. We're offering builder grants. 🦞

哈哈哈，自用的视频生成 Skill 终于做好了。 以后生产视频方便多了，只需要一句话！ 公开技术方案： 1. Listenhub API实现声音克隆，合成，字幕时间轴控制 2. Seedream 4.5 生成背景封面 3. Manim库实现文本动画 4. FFmpeg合成视频。 同时支持16:9 和9:16 视频，抖音、小红书我来了！

holy shit it fucking WORKS. SMART FORKING. My mind is genuinely blown. I HIGHLY RECCOMEND every Claude Code user implement this into their own workflows. Do you have a feature you want to implement in an existing project without re-explaining things? As we all know, the more relevant context a chat session has, the more effectively it will be able to implement your request. Why not utilize the knowledge gained from your hundreds/thousands of other Claude code sessions? Don't let that valuable context go to waste!! This is where smart forking comes into play. Invoke the /fork-detect tool and tell it what you're wanting to do. It will then run your prompt through an embedding model, cross reference the embedding with a vectorized RAG database containing every single one of your previous chat sessions (which auto updates as you continue to have more sessions). It will then return a list of the top 5 relevant chat sessions you've had relating to what you're wanting to do, assigning each a relevance score - ordering it from highest to lowest. You then pick which session you prefer to fork from, and it gives you the fork command to copy and paste into a new terminal. And boom, there you have it. Seamlessly efficient feature implementation. Happy to whip up an implementation plan & share it in a git repo if anyone is interested!

insane Claude Code setup. instead of asking it to "mek app" like a total normie, you first let it spin up 1m subagents to simulate 10¹² branches of civilization from 4000 BC recursively to emulate in which universe a specific version of your app is going to be most successful

if youre getting into ai assisted knowledge management, these are the pointers i wish i had when i started @kepano was one of the first people i ever gifted a buymeacoffee back then for his theme work. following him since the early days of obsidian and now hes cofounder working on claude skills @nickmilo helped me a lot with his LYT framework when i transitioned to obsidian during early beta and he still creates valuable videos on youtube @neuranne inspired me to make a living with my knowledge work. lots of interesting stuff on ness labs @andy_matuschak and his concept of evergreen notes changed how i think about notes forever. so much value on his website that i spent days there trying to read everything. the panes structure is beautiful for thinking and i might steal that idea @fortelabs taught me note taking philosophy through his books and im still using a PARA like system in my other vault @soenke_ahrens wrote "how to take smart notes" which redefined the tools for thought space for me. short read but hands down the most dense and valuable book on the topic @zsviczian did amazing work with the excalidraw plugin but beyond that hes a great systematic thinker with nice youtube videos @tfthacker is an og in knowledge management with many contributions and valuable insights over the years @n_vanderhoeven made videos i watched religiously back then. even tho theyre older now theyre still worth watching because this is evergreen content @eleanorkonik did lots of community work for obsidian and her newsletter kept me updated on everything happening in the space @tallguyjenks was literally my entry to all this. he also copes with adhd and used these systems to find structure. so happy i found you @shuomi3 makes high quality youtube videos on ai and obsidian @mckaywrigley is a legend in the ai and vibe coding space with super insightful tutorials and he also dives into ai assisted knowledge management with obsidian @rileybrown inspired me to start ai tiktok back then. i tried to copy him and went from 0 to 10k in under 30 days. now hes one of the voices in vibe coding and still produces so much value if you want to go deeper i wrote an article about how i let claude code orchestrate my obsidian vaults

AgentCommand: a dashboard for when your AI agents are running AI agents. Watch 1000+ agents spin up and down, see them talk to each other, and track the revenue, deploys, and code diffs happening in real-time.

Anthropic 最新的 Economic Index 报告中提到一个有趣的概念：去技能化！当 AI 接管某些任务后，留给人类的工作所需技能水平下降。报告指出 Claude 倾向于处理比经济整体更高技能的任务，如图 Claude 覆盖的任务分布明显右移，在 16-18 年教育区间尤其突出，移除这些任务会导致多数职业"去技能化”。 技术写作领域尤为突出，所需教育年限在 16 年以上的分析、审稿、内容生成等核心工作被 AI 替代，留给人类的工作是排版、开发和实验活动，这些只需 13.5 年的教育年限；高认知任务被 AI 接管，人类退守到执行层面。 在旅行代理领域，行程规划、比价、推荐以及费用计算全部被 AI 替代，人类只剩打票、收款和人工送票，这些只需要 12 年不到的教育年限；以前需要丰富经验才能做好的工作，现在变成了简单的执行角色。 另外在教育领域，AI 能帮忙批改作业、做研究、准备教案，这些恰恰是教师工作中最需要专业知识的部分，剩下的主要是课堂管理和面对面互动；知识生产和评估被 AI 接 管，人类退守到"在场"功能。 但也有例外。物业经理反而可能"技能升级"：AI 接管了维护销售记录、审查租金与市场价格对比等任务，获得贷款、公司谈判这样的需要更多教育年限的任务任需要人做；人类可以专注于合同谈判和客户关系，工作内容反而更有价值。 总体而言，一阶净效应是”去技能化”，因为 AI 移除的是相对更高教育要求的任务。但报告现实，最复杂的任务恰恰是 Claude 成功率最低的地方。这可能不会取代高技能专业人士，反而强化了他们在理解 AI 工作和评估质量方面的互补价值。 因此，从报告看到的最终结论是： 技能极化：AI 不是均匀替代所有任务，而是选择性地吸收中高层认知任务，造成"中空"效应； 新瓶颈出现：能够评估 AI 输出质量、整合 AI 结果的"元技能"变得更有价值； 职业重构方向：一些职业向下沉降（执行层），另一些向上攀升（判断层），取决于 AI覆盖的是哪部分任务；

Claude, create a strategy that monitors subreddits to identify capital rotation signals derived from social media chatter before Wall Street and mainstream media fully embrace. Then run the strategy and show me the top ten themes, along with high potential tickers.

今天爆火的一个视频，Reverse Claude Code。 Midjourney 的一个老哥做了个 Demo，倒反天罡：让 Claude Code 反向当老板，指挥自己给干活。 他表示后续计划直接把这玩意做个 Desktop App 出来。

CPU的短缺已经全面爆发了。 - 英伟达Blackwell采用的ARM CPU存在严重的CPU瓶颈，Rubin大幅提高了CPU核心数和超线程。 - 英伟达将开放英特尔x86 CPU作为NVL72互联机柜。 - Agent云端沙盒机制调用量飙升，云实例业务飙升。