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사나의 냉터뷰 너가 먼저 꼬셨다?💘l EP.20 하투하(H2H) 지우 편 You made the first move, okay?💘l EP.20 Hearts2Hearts (H2H) Jiwoo's Episode 🎬 #TWICE# #트와이스# #SANA# #사나#

谷歌组织架构大洗牌！ Demis Hassabis 卸任 Google Deepmind 的 CEO，转任 GDM 主席兼 Alphabet 首席科学家，同时继续领导 Isomorphic Labs，把主要精力放在 AGI 的长远方向、全球战略以及用 AI 推动科学与医疗突破上； “我们已抵达人类历史上的一个关键时刻。我一生都在为 AGI 努力，现在，就像你们许多人一样，我感觉它近在咫尺” —— Demis Hassabis Koray Kavukcuoglu 从 Deepmind CTO、Google 首席 AI 架构师升任 Google DeepMind 高级副总裁，直接向 Pichai 汇报，全面负责 Gemini 模型研发、前沿 AI 研究以及 Gemini 应用与开发者团队。其实就是接替 Demis 的管理工作，他在 DeepMind 已工作 13 年，，曾主导 WaveNet、DQN 等成果； 在谷歌工作 27 年的 Jeff Dean 将与资深研究员 Sanjay Ghemawat 一起离开，创办一家独立的公益性质公司 Discovery Loop，专注“全自动科学发现的闭环”研究；Google 会作为创始投资方和云服务合作伙伴继续与他们合作。Dean 告诉 NYT，离开 Google 让他有更多余地专注于科学发现； 三位最初的 Gemini 负责人如今全部离职：Noam Shazeer 去了 OpenAI，Dean 和 Vinyals 去了 Discovery Loop。 我如何看待这次调整？ 在 2023 年 Google 合并 Google Brain 与 Deepmind，于是有了 Gemini 的成功；三年后 Google 再次面临大公司病、组织障碍（人才保留上的结构性问题）和工程低效的挑战，于是有了这次必要又意料之外的调整。 部分传言 Demis 因 Gemini 执行不力而被边缘化，换上Koray 是希望把“研究强、产品化慢”这个 Google 的老毛病治好，对比 OpenAI / Anthropic 快速产品化，Google 需要证明也能更快的迭代。所以 Google 全村的希望都在 Gemini 4，内部确认已经有了重大进展。我保留短期观察，长期看好的判断👀 其实 Google 已经证明了目前不用靠模型的能力，只用买算力就能保持盈利优势，Google 是目前唯一的全栈 AI 科技巨头。现在决定内部加速产品化，再利用投资加孵化，既能解决人才保留的问题，又可以抢占 AGI 与科学前沿。 这是 Google 的角色优化，并非危机。执行力与人才保留正在成为新的竞争护城河，技术不再是 Google 的短板，专注和敏捷才是。

1/ Over the past few weeks, we rebuilt CyOps from the inside out. We consolidated 15 branch tips and used a sanitized handoff from another Codex session to preserve decisions, security invariants, test evidence, and remaining risks. Here’s what changed. 🧵

Tomorrow will be my last day at Google after 27 years, and watching it grow from 25 people to 190,000+ has been an amazing journey. Below is a note I shared with many people internally at Google today. An excerpt is: It has been an absolute pleasure to work with you and to help build some of the most widely used and impactful products of all time. As a kid, I dreamed of helping build software that would be used by many people, and Google now has thirteen products used by more than a billion people (amazing!). Our work has had a tremendous impact in the world, and I have been lucky enough to collaborate and form friendships with many colleagues that I deeply admire, respect, and enjoy. It still brings me joy every time I see people out in the world using our products to find information, handle email, translate documents, watch videos, learn new things, navigate and understand the physical world, browse the web, use their phone, run large-scale computations on our infrastructure, ride in an autonomous vehicle, or perform complex tasks with the help of our AI systems. I hope you all share this sense of joy, because it is a shared accomplishment! Thank you to all of my colleagues at Google over many years! Now I'm excited to go start @DiscoLoopAI with my longtime friends and colleagues @Sanjay_Ghemawat, @OriolVinyalsML, and @quocleix. (Updated post: slightly redacted to not have some personal info)

Announcing Discovery Loop! I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor. ♾ Learn more at:

Windows 这次真要慌了。 有人做了一个开源 PowerShell 脚本，GitHub 51K+ stars，专门干一件事： 把 Windows 11 里那些你删不掉、关不掉、还天天恶心你的东西，一次清空。 微软给你塞预装软件、Bing 搜索、Copilot、Xbox、OneDrive 弹窗、定向广告，甚至连开始菜单都不放过。 Win11 Debloat 直接一条命令全部处理： · 批量卸载预装应用、推广软件和无用组件 · 关闭遥测、诊断数据、广告 ID 和个性化追踪 · 移除 Copilot、Recall、Click to Do 等 AI 功能 · 禁用 Bing 网页搜索和 Edge 内置 AI · 恢复 Windows 10 经典右键菜单 · 一键开启 Windows Sandbox 和 WSL · 支持参数化部署，配置还能导出到其他电脑 · MIT 开源，免费、无广告、无捆绑、无追踪 最讽刺的是： 微软花了这么多年，想把 Windows 变成广告入口、搜索入口和 AI 入口。 而这个脚本只用一条命令，就把它重新变回了一台电脑。 没有弹窗，没有推荐，没有监控，也没有那些你根本没想装的东西。 微软负责往里塞。 开源社区负责帮你删。 🔗

Vercel 推出了一款完全开源的远程代理浏览器工具 把 agent-browser 命令行浏览器放进云端 Vercel Sandbox 里跑，让 AI agent 拥有一套远程、可编程、命令共享的浏览器会话。

Okay, the @VulcanBench results for Qwen3.8-Max are in, and it is not what I expected. First, for anyone new to VulcanBench, here's a quick TL;DR on the eval suite: 23 frontier-hard software engineering tasks taken from real merged OSS PRs, run in a Docker sandbox, 3 runs per task across all three of its effort levels. No puzzles, no random abstract stuff, all real things engineering teams would do with these models. It looks like Qwen3.8-Max has a major overthinking problem, it uses a LOT of tokens and is very slow, period, no other way to see it. My cost to run this benchmark was $126.25, to run the exact same eval suite with DeepSeek V4-Flash was only $13.60. This makes Qwen3.8-Max an insanely expensive model. The tasks Qwen genuinely can't solve fail at every effort level, extra reasoning didn't help. The regression is almost all in work it already handles: six tasks that low solves every single time account for 83% of the 26-point drop, three of them collapsing to zero. It's not losing the hard problems. It's losing the ones it already knows how to do. Since Qwen3.8-Max hit a lot of wall clock budget caps, I thought I'd share more about this. - VulcanBench caps both steps (50–200) and wall clock (5–60 min), each scaled by repo size. - This is aligned with how comparable harnesses bound agents, DeepSWE caps rollouts at 100 environment steps, sitting right inside my step range; Terminal-Bench enforces a per-task wall clock; SWE-bench Verified scaffolds typically allow 20–60 min per instance with 250–350 step limits. - Every model on my chart gets the identical budget, and Qwen is the slowest model I've tested at 20–25 min/task. Soooo... Alibaba positions Qwen3.8-Max as trailing only Claude Fable 5. But on the kind of real coding work engineering teams would actually throw at it, under a fixed budget, its best setting lands mid-pack and its default lands last, so common. If you want to optimize for accuracy, Grok 4.5 is the move. If you want accuracy per dollar, DeepSeek V4-Flash is hard to beat, heck it's 10× cheaper than Qwen and you get higher accuracy. Qwen just isn't in the game at this point, this is not a model I could see engineering teams using for daily coding work.

STB × HKTKWW: A key milestone for Sanya’s global communication! On August 3, Sanya Tourism Board (STB) and Hong Kong Ta Kung Wen Wei Media Group (HKTKWW) officially signed a strategic partnership agreement — marking a major step forward in expanding Sanya’s global communication network and sharing Sanya’s stories with the world. Together, we’re building stronger networks, bigger platforms, and better stories — bringing Sanya to the world. 8月3日，三亞市旅遊發展局與香港大公文匯傳媒集團（HKTKWW）正式簽署國際傳播戰略合作協議，標誌著三亞在傳播網絡佈局上的又一重要落子。 未來，雙方將依託全媒體傳播優勢，在港澳及海外市場開展三亞旅遊常態化宣傳，共同推動三亞打造國際知名旅遊目的地！ 拓展網絡，共建平臺，講好故事！