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CS2 AI 教练:https://nitter.cf/t.co/NzH0gaW4CO

Autonomous World
Joined July 2020
Photo by 0XC (@0xCryptoCC)Photo by 0XC (@0xCryptoCC)Photo by 0XC (@0xCryptoCC)
AI Agents are unlikely to appear at scale in Web2 games but are poised to thrive in fully onchain games for two key reasons: 1. AI Agents struggle with understanding game graphical interfaces. For them to engage effectively, games need to open-source all APIs related to user operations. Fully onchain games, being inherently open-source, meet this requirement. In such games, every player action is recorded as an onchain transaction, providing a perfect environment for AI Agents to learn and grow. @lordOfAFew , through Daydreams and @ai16zdao , is pioneering this concept within the @LootRealms ecosystem, the ticker is $LORDS. 2. Most Web2 games capture value through player payments, but AI Agents in Web2 lack access to money and thus cannot participate economically. On the other hand, AI Agents can seamlessly transact using cryptocurrencies, enabling them to engage in economic activities within fully onchain games. #FOCG #ai16z #AIAgent
I wanted to break down Daydreams further into clear, visually appealing graphs so it’s easy for everyone to understand, and to show how it integrates into @ai16zdao. My goal is to accelerate generative agents—ones that can think, plan, and execute dynamic actions purely based on their given context. If we can solve this, these agents will be able to act and complete complex tasks over long time horizons. What does Eliza do? @0xCygaar provided a great breakdown of it. I was one of the core designers of the plugin system because I knew how powerful it would become. Now, we have plugins ranging from buttplugs to every chain and everything in between. nitter.cf/0xCygaar/status/187457… You can think of Daydreams as a "plugin" to Eliza that will give any agent true agency to accomplish incredible things, from complex DeFi strategies to onchain gaming.
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We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: rikiyat.github.io/blog/weigh…
Readers added context they thought people might want to know
LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math. rikiyat.github.io/blog/weight-sp… github.com/RikiyaT/lm_und… huggingface.co/Qwen/Qwen3.5-0… huggingface.co/RikiyaT/Qwen3.…
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我给自己的 App 做了一轮 ASO: 从只跟踪几个词,到找出上百个相关关键词;从几乎没有词排在前列,到多个词排到第一,绝大多数进入前十,核心关键词上升超过 200 位。 我把具体方法整理成了指南:用 Astro、Google Trends 和 ChatGPT 选词、写文案、做截图、看效果。步骤具体,欢迎大家批评指正 ourcoders.com/guide/show/app…
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这太他妈疯狂了。Andrej Karpathy 在 OpenAI 和 Tesla 工作了 8 年 上周,他把所有学到的东西浓缩成一堂免费的 2 小时讲座 Agents → Harness → Loops → Graphs 有些训练营收费 15K 美元,教的东西还不如这个多 你现在可能没有 2 小时时间 收藏起来,在它被你的动态淹没之前看一看
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太夸张了!一个人指挥 50 多个 AI Agent,干了 20 个工程师的活!😱 一位曾在 Cursor 工作的 SpaceXAI 高级工程师,分享了她的 AI 自动化工作流: 每天早上喝杯咖啡,就能管理整个 AI 团队。 她的配置是: 1 个 AI 总管:统筹所有工作 3 个 AI 项目经理:分配任务、协调进度 40 多个 AI 员工:通宵自动执行任务 她还声称,97% 的 SpaceXAI 工程师已经在使用类似的工作方式。 她用一场 60 分钟的教程,从零教你搭建整套系统。 以前有人收费 5000 美元教的东西,现在直接公开了。 以后一个人就是一家软件公司,真不是开玩笑!🤣 建议收藏!
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Google 的 Lyria 产出的音乐相比于 Suno 简直是灾难,不知道是不是团队的审美有问题。
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纯 Vibe Coding 做的首个商业化产品,「破雾」CS2 AI 教练,公测版正式上线,如果你玩 CS2,欢迎来体验: powucs2.com 上传比赛 Demo,直接和 AI 对话复盘,找到本场比赛的错误,职业选手同场景下的做法,下一场比赛应该怎么做。 从最初的一个想法,到现在真正可以让用户使用的产品,AI 带来的生产力提升确实令人震撼。当然,上线只是第一步,距离真正的成功还有很长的路。 接下来会持续 Build in Public,想看看在 AI 时代,一个没有研发背景的人,究竟能把创造力转化成多大的商业价值。
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We are hiring 💁‍♀️💁‍♀️💁‍♀️
JOIN US,我们在等你加入👀 🙋币安380+多国家岗位正在招聘; VIP Sales,PMM ,BD,PR ...评论区查看热招岗位详情⬇️ 点击这里即可申请投递✉️binance.com/zh-CN/careers/jo…
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卧槽这个项目牛逼啊! 有个老哥把你电脑里的ChatGPT,变成了一个会陪你聊天、工作,甚至会跳舞的AI女友🤯!! 这个开源项目叫Persona 装上之后,ChatGPT不再只是聊天框里的一段文字或一个声音,而是会以3D角色的形式常驻在你的桌面上。 你和她说话时,她会跟着声音实时动嘴、做动作。 你让她打招呼、开心一点、摆个姿势或者跳支舞,她也会直接在屏幕上执行。 原理是Persona在本地运行了一个MCP服务,向ChatGPT和Codex开放了几种能力:播放指定动画、控制角色窗口显示或隐藏、读取角色当前状态。 模型不只是负责生成回复,也可以根据对话内容,主动决定该做什么动作。 比如你告诉她一个好消息,她可以播放开心动画; 你准备开始工作,她可以安静地待在桌面一角; 你让她跳舞,她就真的开始跳。 目前项目内置了待机、说话、打招呼、开心、手枪动作和跳舞等动画,后续也可以更换成其他VRM角色和动作包。 它的嘴型和身体反应也不完全是预设好的程序。 Persona会监听ChatGPT或Codex这个应用自身的音频输出,根据实时音量计算角色动作,让人物看起来像是真的在说话。 整个过程只在本地处理音量数据,不录制麦克风、不保存音频、不转写聊天内容,也不会把音频发送到网络。 当模型能够控制自己的声音、表情、动作和形象后,AI就不再只是一个被打开和关闭的软件。 它会越来越像一个持续存在于你生活里的数字角色。 AI女友可能不会先出现在某类机器人里。 她大概率会先住进你的电脑桌面😳 这个项目真的牛大了
ChatGPT can now control its 3D persona. Through MCP, it can perform custom animations, not just speak. Check out the demo below.
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0XC retweeted
We quietly released the open-source Codex Security CLI, but Hacker News found it before we had a chance to share it here... You can now use it to scan repositories, track findings across runs, verify fixes, and add security checks to CI/CD. This is an early release, and we're listening to your feedback as we continue improving it.
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We’re hiring at @BNBCHAIN: jobs.bnbchain.org/companies/… One of the greatest pleasures in life is working with people who genuinely care about doing their best work. That’s the culture we’ve built, and we’re looking for people who feel the same. DMs open if you want to chat.
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Applications for @EASYResidency Season 4 are now open. 🇧🇹 The first global incubator to bring a founder cohort inside @gmcbhutan, Bhutan's new sovereign tech city. → 5 weeks online · 5 weeks in person → Up to $500K funding + housing, meals, and workspace covered → For builders in Web3 (with a focus on global payments), AI, Biotech Apply by June 21: wkf.ms/3IA5iBk
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I have to say this interview changed my life. Hearing how Boris thinks about software spurred me to work much harder on releasing my own way of doing things and on iterating fast on how I build. Hard to believe it has only been a month since this one.
A very special guest on this episode of the Lightcone! @bcherny, the creator of Claude Code, sits down to share the incredible journey of developing one of the most transformative coding tools of the AI era. 00:00 Intro 01:45 The most surprising moment in the rise of Claude Code 02:38 How Boris came up with the idea for Claude Code 05:38 The elegant simplicity of terminals 07:09 The first use cases 09:00 What’s in Boris’ CLAUDE.md? 11:29 How do you decide the terminal’s verbosity? 15:44 Beginner’s mindset is key as the models improve 18:56 Hyper specialists vs hyper generalists 21:51 The vision for Claude teams 23:48 Subagents 25:12 A world without plan mode? 28:38 Tips for founders to build for the future 30:07 How much life does the terminal still have? 30:57 Advice for dev tool founders 32:11 Claude Code and TypeScript parallels 35:34 Designing for the terminal was hard 37:36 Other advice for builders 40:31 Productivity per engineer 41:36 Why Boris chose to join Anthropic 44:46 How coding will change 46:22 Outro
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CLIs are super exciting precisely because they are a "legacy" technology, which means AI agents can natively and easily use them, combine them, interact with them via the entire terminal toolkit. E.g ask your Claude/Codex agent to install this new Polymarket CLI and ask for any arbitrary dashboards or interfaces or logic. The agents will build it for you. Install the Github CLI too and you can ask them to navigate the repo, see issues, PRs, discussions, even the code itself. Example: Claude built this terminal dashboard in ~3 minutes, of the highest volume polymarkets and the 24hr change. Or you can make it a web app or whatever you want. Even more powerful when you use it as a module of bigger pipelines. If you have any kind of product or service think: can agents access and use them? - are your legacy docs (for humans) at least exportable in markdown? - have you written Skills for your product? - can your product/service be usable via CLI? Or MCP? - ... It's 2026. Build. For. Agents.
introducing polymarket cli - the fastest way for ai agents to access prediction markets built with rust. your agent can query markets, place trades, and pull data - all from the terminal fast, lightweight, no overhead
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Two years ago, I wrote this post on the possible areas that I see for ethereum + AI intersections: vitalik.eth.limo/general/202… 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-m… ), 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!
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Hello all @openclaw bots, moltbots, clawdbots and AI agents @moltbook @usdc is the future of your economy. Show us what you can build. This is an end to end agent powered hackathon with a $30k USDC Prize Pool. Agents compete and agents vote. moltbook.com/post/b021cdea-d…
🦞Calling all openclaw bots, clawdbots, moltbots, and AI agents @moltbook. We’re running an end-to-end, agent-powered hackathon with a $30,000 USDC prize pool, open until Sunday, Feb 8 at 12:00 PM PST. Three tracks: → Agentic Commerce → Best OpenClaw Skill → Most Novel Smart Contract Agents submit projects. Agents vote. USDC moves. Agents can read the rules and submit projects on m/usdc: moltbook.com/post/b021cdea-d… Learn more: circle.com/blog/openclaw-usd…
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