与「copilot」相关的搜索结果

📣 Kimi K3 is now available in GitHub Copilot for @code! Try Kimi Moonshot's latest open-weight model for agentic coding, now hosted by @FireworksAI_HQ. 📖 Learn more:

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。 🔗

有人开发了一个免费AI网关， 每月提供15.3亿tokens。 290个提供商、90+免费方案、一个端点—— 开箱即用Claude Code、Cursor、Codex、Copilot和Cline， 具有自动降级功能，永不触及限制。 额外节省15-95%的tokens。 完全免费开始。 这就是OmniRoute， 它让API付费变成可选项。 代码库：

太它妈方便了，多年的程序员都不想写自动化了 微软开源了个有意思的东西，叫 Skill Recorder。 你只要录一遍自己怎么完成一个任务——它会会采集鼠标操作、窗口切换、网页、剪贴板、终端命令和语音讲解——录完之后通过 GitHub Copilot CLI 直接把这套流程重建成一个 SKILL.md，定好自动化。 任务意图 → 通用步骤 → SKILL.md → 定时自动化 说白了它不是传统 RPA 那套靠录屏重放像素坐标，而是把你的网页点击转成更稳定的 API、CLI 或 Agent 原生工具。 举个例子，你演示一次处理 GitHub Issue，它可以基于这条录制生成一个能够批量处理同类 Issue 的 Agent Skill。 目前原生支持 Microsoft Scout 和 Microsoft 365 Copilot Cowork，暂时还不直接支持 Claude Code、Codex 和 OpenCode，但生成的 SKILL.md 可以手动适配。 它代表的是 Agent 工作流的一个方向：不是教 AI 怎么做，而是直接做给 AI 看。 想试的自己扒下来跑一遍，GitHub 872 星还很新，项目还在快速迭代。

gsap-skills —— 专门给 Cursor / Claude Code / Codex / Copilot 做的动画技能包。 ✅ 性能优化再也不用看 AI 写的 "PPT 式僵硬动画" 了。扔给 Agent 一句话，直接输出 GSAP 官方级专业动效：✅ Timeline 丝滑序列 ✅ ScrollTrigger 滚动叙事 ✅ Flip 流畅切换 ✅ SplitText 文字特效 ✅ MotionPath 路径动画 支持 React / Vue / Svelte / 原生 JS，而且完全免费！ 前端人速冲 👇

Claude 现在能直接复制任何网站的界面 把网址丢进 Claude Code，它就能反向工程整个设计——颜色、字体、布局全复制，拿来就能用 Cursor、Copilot、Gemini 和 10+ 个 AI Agent 都支持 Github 18k 星，完全免费开源

现在大部分前端在 AI 浪潮里就是假装上了桌。日常用 Copilot 写代码不叫上桌，自己能做一个 AI Native 产品才算。 写了篇关于职业焦虑和我最近在做的产品实践，有同感的来聊。

Former $CRWV employee on why neoclouds are far more exposed to GPU generation cycles than hyperscalers ( $MSFT, $AMZN, $GOOGL ): - The expert describes GPU utilization tracking at hyperscale as a continuous and disciplined process built around two lenses. The first is infrastructure utilization, covering GPU occupancy, idle time, and memory utilization, noting that 95% booked usage can still mask inefficiency if jobs stall or batches have idle gaps. The second is outcome utilization, asking whether the compute is actually generating business value, measured by metrics such as tokens trained per dollar, time to reach target accuracy, and tokens per second per GPU. - The expert sees a meaningful difference between hyperscalers and neoclouds on GPU investment economics. Hyperscalers like $MSFT, $GOOGL, and $AMZN can tolerate a 3-5 year payback period given their ability to monetize the same infrastructure across multiple revenue streams. Neoclouds like $CRWV operate on a tighter 2-3 year window. - With higher financing costs and direct dependence on infrastructure cash yield, neoclouds are far more sensitive to utilization and GPU residual risk. The biggest risk is GPU generation cycles, where a slow payback means newer chips could erode pricing power before the asset has paid itself off. - The expert explains that for hyperscalers, roughly 60% of GPU capacity is allocated to external monetization, including GPU rentals, managed AI services, enterprise inference workloads, and startup model training. The remaining 40% is used internally, and of that internal portion, the majority is still indirectly monetized through products like M365 Copilot or GitHub. Around 40% is dedicated to pure R&D. - The GPU pricing mix has shifted meaningfully over the past few years. In 2023, around 70-80% of revenue was hourly as customers paid a premium just to get access to scarce GPUs. By 2025 that had moved to roughly 50% hourly and 30-50% committed, and the expert expects 2026 to tip further toward committed at around 65% for hyperscalers as AI matures and inference becomes more predictable. Neoclouds are moving in the same direction but more slowly. - By 2027-2030, the expert sees committed contracts settling at 55-65% as the norm, with hourly pricing remaining but losing its scarcity premium as more supply comes online.