马斯喵Ao retweeted
This episode features an interview with Yao Shunyu @ShunyuYao14 , Research Scientist at Google DeepMind. Yao has held research scientist roles at both Anthropic and Google DeepMind, contributing to the development of key models including Claude 3.7, 4.5, and Gemini 3.
Yao Shunyu is not your typical nerd. Every now and then, he’ll catch you off guard with a flash of irreverence.
“None of the old guard are your relatives — so if you think someone’s being dumb, they’re just being dumb. Say it. No big deal.” (laughs)
“Everyone’s a surfer now, but what really matters is the wave — not the person riding it.”
“AI doesn’t actually require that much brainpower — I mean it genuinely doesn’t — most of this is work any undergrad could do. The most important quality in this industry is reliability: being meticulous, and taking responsibility for what you put out.”
“You don’t need to worry too much about ruffling feathers with your opinions. As long as your views are internally consistent — not just taking random shots at people, but grounded in your own genuine understanding — there are objective standards for how you’re doing in this field. People will respect you for it.”
Let us have a little fun with this one! 😄
youtu.be/ttkd0t5qTD4?si=0uFT…
爆肝制作,全网最细最全的 Claude Code 零基础系统教程!👇👇
这一期跟完,保证你成为Claude Code高手!:
1️⃣ 基础入门:安装、第三方模型接入、权限系统。
2️⃣ 核心进阶:Tools、Hooks、Skills、Subagents 及自动化流程。
3️⃣ 项目实战:用以上所学知识构建一个AI 网页 App。
全程精剪没有废话,每个功能都讲透+实操!
时间戳:
0:00 开场
00:38 1.安装
04:04 2.换模型
06:08 3.终端界面介绍
11:04 4.图形界面介绍
15:05 5.权限系统
19:45 6.Tools
23:02 7.Hooks
26:34 8.Skills
31:47 9.插件
34:33 10.Subagent
40:33 11.自动化
41:58 12.构建网页APP
49:32 13.CLAUDE.md
52:02 总结
马斯喵Ao retweeted
SpaceXAI and @cursor_ai are now working closely together to create the world’s best coding and knowledge work AI.
The combination of Cursor’s leading product and distribution to expert software engineers with SpaceX’s million H100 equivalent Colossus training supercomputer will allow us to build the world’s most useful models.
Cursor has also given SpaceX the right to acquire Cursor later this year for $60 billion or pay $10 billion for our work together.
马斯喵Ao retweeted
Meet Kimi K2.6 agent - Video hero section, WebGL shaders, real backends. From one prompt.
🔹 Video hero sections - cinematic aesthetic, auto-composited
🔹 WebGL shader animations - native GLSL / WGSL, liquid metal, caustics, raymarching
🔹 Motion design - GSAP + Framer Motion
🔹 Backend database: Kimi wires up auth + database + backend in one pass.
🔹 Website stack - React 19 + TypeScript + Vite + Tailwind + shadcn/ui
🔹 3D w/ physically-based lighting - Three.js + React Three Fiber
Hermes Agent真的比OpenClaw更好吗?
今天我们面对面实测对比!
左OpenClaw,右Hermes Agent,
我们反复问同一个问题,
不断纠错同一个地方:
1. 测试两边的回答质量/消耗token数量
2.显性的要求记住,两者记忆逻辑有何不同
3.隐形的纠错/提要求,谁能主动get到沉淀下来
实测完之后会讲:
原理+如何从OpenClaw迁移到Hermes Agent 👇👇
时间戳
00:00 开场与实验设置
00:50 第一轮实测
01:29 显性记忆测试
02:42 文件对比
03:29 连续纠错测试
05:05 Hermes 学会了
05:56 原理解释
08:50 安装 Hermes Agent 10:08 从 OpenClaw 迁移 10:55 总结
马斯喵Ao retweeted
Claude Code 新发布的 routines 功能很强啊!
把云端和本地环境连起来了,可以在云端跑定时任务不需要开机。
跑完的任务本地还能接上,等你工作的时候继续处理。
你可以把「提示词 + 仓库 + 环境 + 连接器」打包成一个云端自动任务,让 Claude 在你电脑关着时也能按计划或事件自动跑。
比如按小时/每天定时、通过 HTTP API 调用、或响应 GitHub 上的 PR / push / issue / workflow 事件。
适合那些无人值守、可重复、目标清晰的工作流。
每次触发都会在云端开一个完整的 Claude Code 会话,能跑 shell、用 repo 里的 skills、访问外部服务。
以后构建 Agent 产品就是得在本地优先的基础上,用云端自动化接管一些基础的重复性的任务。
随着模型能力的提升,任务的范围会越来越大。
Two days ago, Anthropic cut off third-party harnesses from using Claude subscriptions — not surprising. Three days ago, MiMo launched its Token Plan — a design I spent real time on, and what I believe is a serious attempt at getting compute allocation and agent harness development right. Putting these two things together, some thoughts:
1. Claude Code's subscription is a beautifully designed system for balanced compute allocation. My guess — it doesn't make money, possibly bleeds it, unless their API margins are 10-20x, which I doubt. I can't rigorously calculate the losses from third-party harnesses plugging in, but I've looked at OpenClaw's context management up close — it's bad. Within a single user query, it fires off rounds of low-value tool calls as separate API requests, each carrying a long context window (often >100K tokens) — wasteful even with cache hits, and in extreme cases driving up cache miss rates for other queries. The actual request count per query ends up several times higher than Claude Code's own framework. Translated to API pricing, the real cost is probably tens of times the subscription price. That's not a gap — that's a crater.
2. Third-party harnesses like OpenClaw/OpenCode can still call Claude via API — they just can't ride on subscriptions anymore. Short term, these agent users will feel the pain, costs jumping easily tens of times. But that pressure is exactly what pushes these harnesses to improve context management, maximize prompt cache hit rates to reuse processed context, cut wasteful token burn. Pain eventually converts to engineering discipline.
3. I'd urge LLM companies not to blindly race to the bottom on pricing before figuring out how to price a coding plan without hemorrhaging money. Selling tokens dirt cheap while leaving the door wide open to third-party harnesses looks nice to users, but it's a trap — the same trap Anthropic just walked out of. The deeper problem: if users burn their attention on low-quality agent harnesses, highly unstable and slow inference services, and models downgraded to cut costs, only to find they still can't get anything done — that's not a healthy cycle for user experience or retention.
4. On MiMo Token Plan — it supports third-party harnesses, billed by token quota, same logic as Claude's newly launched extra usage packages. Because what we're going for is long-term stable delivery of high-quality models and services — not getting you to impulse-pay and then abandon ship.
The bigger picture: global compute capacity can't keep up with the token demand agents are creating. The real way forward isn't cheaper tokens — it's co-evolution. "More token-efficient agent harnesses" × "more powerful and efficient models." Anthropic's move, whether they intended it or not, is pushing the entire ecosystem — open source and closed source alike — in that direction. That's probably a good thing. The Agent era doesn't belong to whoever burns the most compute. It belongs to whoever uses it wisely.
OpenAI 关停 Sora,AI 视频明星产品上线半年即告终结
OpenAI 今天宣布关停旗下 AI 视频生成产品 Sora,包括独立 App 和 API 都将下线。Sora 团队在 X 上发帖告别,表示会尽快公布具体时间表和用户作品保存方案。
从去年 9 月高调上线到今天宣布关停,Sora 作为独立产品只存活了大约半年。
去年 10 月 Sora 2 上线后曾冲上 App Store 下载榜第一,用户疯狂生成马里奥、皮卡丘等知名 IP 角色的视频,一度让好莱坞紧张不已。但 OpenAI 很快收紧了 IP 限制,此后用户活跃度急剧下滑,再也没回来。
更尴尬的是迪士尼的处境。去年 12 月迪士尼刚和 OpenAI 签了三年合作协议,计划把旗下 200 多个迪士尼、漫威、皮克斯、星球大战角色授权给 Sora,同时承诺向 OpenAI 投资 10 亿美元。合作产品还没来得及上线,平台就没了。迪士尼回应得很体面,表示理解 OpenAI 调整方向的决定,会继续和其他 AI 平台合作。
Sora 的关停不是孤立事件,而是 OpenAI 一次大规模产品收缩的一部分。
上周《华尔街日报》报道,OpenAI 应用负责人 Fidji Simo 在内部发了一封邮件,承认公司去年把精力分散到了太多产品线上,拖慢了速度,也影响了质量。她的原话是:公司不能再被"支线任务"分心了。
OpenAI 正在开发一个桌面端"超级应用",把 ChatGPT、编程工具 Codex 和自研浏览器 Atlas 合并成一个产品。据报道,Sora 的视频生成能力未来可能以某种形式并入 ChatGPT,而不是作为独立产品存在。
推动这次转型的直接原因是 Anthropic 的崛起。Simo 在内部把 Anthropic 的成功称为一记"警钟",说公司现在处于高度紧急状态。Anthropic 一直专注于企业客户和编程市场,没有碰过音频、图像和视频生成,反而跑得更快。这让 OpenAI 意识到,什么都做不如把核心做好。
OpenAI 目前估值约 7300 亿美元,正在筹备 IPO。砍掉烧钱但没有用户粘性的产品线,把故事讲得更集中,对上市来说也是加分项。
Sora 曾是 AI 视频赛道最轰动的产品,从 2024 年初的惊艳亮相到今天的黯然退场,刚好两年。它的结局说明一件事:在 AI 行业,技术够炫不等于产品立得住,尤其当竞争对手证明了"少即是多"的时候。
We’re saying goodbye to the Sora app. To everyone who created with Sora, shared it, and built community around it: thank you. What you made with Sora mattered, and we know this news is disappointing.
We’ll share more soon, including timelines for the app and API and details on preserving your work. – The Sora Team
马斯喵Ao retweeted
大家好!我们有新的影片出街啦!和大家分享😊
山河醒,燕归来。
我们用 AI 为第十六届北京国际电影节制作了一支官方宣传片,让电影道具和北京地标组成天地片场,让无限连接的四合院组成胶片的长城,希望大家喜欢!
这个春天,相聚北京,共赴光影盛会,来看世界最好的电影。
▶ 出品:北京国际电影节组委会
▶ 创意制作:@simonxxoo & me
折腾半天安装好了OpenClaw后,不知道用OpenClaw干啥?
看看这个仓库,里面有多个实用案例参考: github.com/hesamsheikh/aweso…



























