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Salute to the Qwen team 🫡 We tested Qwen 3.7-Max, Gemini 3.5 Flash, GPT-5.5, and Claude Opus 4.7. The biggest shock came from Qwen. In less than a month (3.6 Max dropped April 20), Qwen went from the worst multimodal output on our sakura tree test, barely keeping up with Gemini, GPT, and Claude , to matching Gemini 3.5 Flash frame for frame on this soccer test, and outperforming GPT-5.5 and Claude Opus 4.7. It rendered a perfectly proportioned soccer player and the most lifelike ball in the entire test. Remarkable spatial reasoning. Also: Gemini 3.5 Flash is now faster than GPT-5.5, which used to be the fastest in our past tests. Video

Very well written blog. I think of RL as learning from interventions, and it kinda explains why it's more powerful as a paradigm than supervised learning. Now learning from counterfactuals is something we haven't been historically good at but maybe world modelling+ RL can get us there.

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Claude Code feels completely different once you install this. Anthropic quietly released an official plugin called claude-code-setup and it basically turns Claude Code from “pretty good” into an actual AI dev environment. It scans your project and recommends: → hooks → skills → MCP servers → subagents → automations Then sets everything up step-by-step for you. Most people are using Claude Code completely vanilla… which is why their experience feels messy. The real power comes from the ecosystem around it. Install: /plugin install claude-code-setup@claude-plugins-official Bookmark this before you forget it. Video

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Meet Colin, Lexi, and Gizmo. One is part of Gradium's GTM team. One is his dog. And one is the AI assistant he built himself. This is their day in Paris. Video

经过一个月的持续迭代，第一套GEO系统“GEOFlow 2.0”正式上线，GitHub地址见文末 一个月前，GEOFlow 1.0 上线，到现在，刚好过去一个月，Star数已经超过1.6k，这一个月来，收到了不少朋友的反馈和落地实践案例 这次2.0升级，我觉得是GEOFlow从“开源内容生产系统”走向“GEO内容工程基础设施”的一个关键版本 几个核心变化： 1、基于Laravel框架进行了系统性重构 底层架构更清晰，后台、任务、队列、分发、数据分析等模块都更适合长期迭代和真实部署 2、从单站点走向多站点、多Agent 过去更多是管理一个站点的内容生产，现在可以用一个后台，管理多个渠道站点的内容分发、远端同步和运行状态，并保留了多渠道API接入的端口 3、AI知识库能力进一步强化 围绕知识库、素材库、向量化检索、AI生成和内容调用做了持续优化，让系统更适合企业沉淀内部知识资产，也更适合GEO场景下的内容生产与持续更新 4、多站点分发能力进入可运行闭环 支持分发渠道管理、Agent密钥、测试连接、目标站点包下载、分发队列、分发日志、远端文章编辑与删除 这意味着，GEOFlow开始具备“中心后台+多个目标站点”的内容分发能力 5、目标渠道站点包上线 每个渠道都可以生成预配置的目标站点包，内置PHP Agent、首页、文章详情页、静态资源、sitemap、TXT地图和Schema结构化数据 对于GEO来说，这一步很关键，因为AI不仅需要内容，也需要更稳定、更结构化、更易抓取的信源表达 6、新增数据分析页面 系统总览、单站运营、多站分发、访问日志、Top文章、Top渠道站点、AI爬虫识别等数据，开始统一进入后台 GEO运营不能只看“发了多少内容”，更要看内容有没有被访问、被抓取、被分发、被持续维护 7、部署、安全和测试覆盖继续增强 包括Docker生产部署优化、默认管理员初始化改进、多语言补齐，以及更多分发管理、数据分析、访问日志相关测试 过去这段时间，也有不少朋友给我反馈： 有朋友基于GEOFlow做了二开，开始探索商业化服务； 有朋友用它管理企业内部的AI知识库和内容资产，显著提升了内容生产与协作效率； 也有朋友把它作为GEO项目的基础系统，用来承载知识库、内容生成、多站点发布和效果追踪 我觉得GEO的一个关键核心，就是“持续建设可信内容资产”，在GEOFlow系统里，也融入了很多这样的理念和设计 如何把真实、可信、可核验的资料，变成可管理、可生成、可发布、可追踪、可同步到多端的GEO内容资产 欢迎大家体验，也欢迎Star、Fork和一起共建 2.0 GitHub地址： github.com/yaojingang/GEOFlo…

兄弟们，今天我不装了。 摊牌了～ 之前一直有朋友说你这套提示词生成的海报这么好看，而且非常丝滑。 捣鼓了一套万能产品、人文、科技、展会等等 都可以快速出图的提示词。 但是，很多人还是用不来觉得麻烦。 于是我，我把它在Bloome 做了个海报设计Agent。 你直接对话就可以生成，现在是为了避免白嫖怪直接1 刀解锁，好像可以生成100 张图？ 我没有记错的话，限时一周。 👇地址见评论区～

Last month we launched Project Glasswing, our collaborative AI cybersecurity initiative. Since then, we and our partners have found more than ten thousand high- or critical-severity vulnerabilities in essential software.

Jack Clark: - AI will make a Nobel Prize-winning discovery within 12 months (working collaboratively with humans) - Bipedal robots will help with enterprise work ("tradespeople") in 2 years - AI systems will be able to design their own successors by year-end 2028 (i.e., RSI) - Companies run solely by AI will be generating millions of USD in revenue within 18 months - Clark's most conservative prediction is that vast swathes of the economy and society will go through profound changes, potentially including "a machine economy decoupling from the human economy, robots gaining brains, science progressing without humans, and scientific equipment that people hadn't conveived of but which worked".

The startups joining us at #MSBuild 2026 are working on the problems that sit between a promising AI demo and something that actually runs in production. Meet the cohort building on Azure. 🔗 msft.it/6016vVpM2

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working on a "take this vibecoded slop app and make it a production-ready, e2e tested, maintainable, parallelizable agent repo" skill. this thing ran for ~16 hours yesterday and made 103 commits all told and i ended up with exactly the same app but instead of fragile mvp it now looks like a codebase i can actually build on for th elong run

You can also connect to inference endpoints that follow the OpenAI Chat Completions API. This includes @OpenRouter, @LiteLLM, @Zai_org, @deepseek_ai, and more. Here's engineer Dagm Assefa showing how to connect to DeepSeek and OpenRouter. Docs: docs.warp.dev/agent-platform… 🔖 Video

We are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀