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10月19日周一
  1. 极客公园30

    端侧 AI 商业化难在哪?麒麟软件、后摩智能等五位一线操盘手讲透了

    后摩智能 10 月 14 日在北京举办生态合作伙伴大会,圆桌环节五位来自操作系统、应用、数据工程、整机集成和芯片领域的从业者讨论端侧 AI 如何成为一门生意。麒麟软件姚翎称涉密场景下本地安全没有商量余地,罗格数据刘学鹏认为企业要把 AI 数字员工招进内部而非放在云端。后摩智能陈仲铭表示正通过 M 系列做大算力和先进封装做大带宽,突破算力、带宽、功耗的「不可能三角」。

10月18日周日
10月16日周五
  1. Microsoft Research60

    微软研究院发布 Magnetar:基于标准哈希函数的通用零知识证明系统

    微软研究院发布零知识虚拟机 Magnetar,可直接证明用 Rust、Go 或 C 编写的程序执行过程,并输出可在约 12 毫秒内验证的简短证明。在 15 个基准程序上,它比同类最快的 zkVM 平均快 10 到 39 倍,在笔记本上每秒可证明 7.2 至 8.7 百万条 RISC-V 指令。

    推荐理由:微软研究院梳理十余年零知识证明研究脉络,说明 Magnetar 如何在通用性、速度与密码学假设之间同时取得进展。

10月15日周四
  1. NVIDIA Blog22

    NVIDIA DLSS 4.5 控制选项登陆 GeForce NOW

    NVIDIA DLSS 4.5 控制选项已在 GeForce NOW 上线,让会员在云端调整支持游戏的画质与性能,无需最新硬件。DLSS Super Resolution、Dynamic Multi Frame Generation 和 Ray Reconstruction 均可在设置中调节,RTX 5080 云主机上的 Ultimate 会员最高可用 4X 动态多帧生成。

10月14日周三
  1. Qwen40

    祝贺 @lightseekorg 取得令人印象深刻的 TokenSpeed 成果!🚀 很高兴看到 Qwen3.8-Flash-Next 在 Nvida GPU 上达到每用户 685 output tokens/s。期待社区进一步释放 Qwen 的推理潜力!

    引用LightSeek Foundation@lightseekorg

    685 output tokens/s per user on @Alibaba_Qwen Qwen3.8-Flash-Next. Running TokenSpeed on 4× NVIDIA GB300 with NVFP4. A look at the kernel and serving optimizations behind the results: 👉 https://lightseek.org/blog/tokenspeed-qwen3-8-flash-next.html ⭐ https://github.com/lightseekorg/tokenspeed

  2. GitHub Blog · AI & ML42

    GitHub 详解密钥检测模型:用更少噪音发现更多密钥

    GitHub 用微调的 ModernBERT 分类器替换原有 LLM 流水线来识别通用密钥,用户接受率提升 11.5%,推送后扫描中位执行时间缩短 86%,服务成本降低超 98%。该方案先用正则高召回生成候选,再由分类器结合文件路径、变量名和上下文判断是否为真实凭据,并已把通用密钥检测扩展到推送保护阶段。

10月10日周六
  1. MiniMax (official)40

    MiniMax M3 现已在 NVIDIA Vera Rubin NVL72 上通过 vLLM 运行!🙌 感谢 @vllm_project、@inferact、@NVIDIAAI、@RedHat_AI 将 MiniMax M3 带到 Rubin 上。

    引用vLLM@vllm_project

    vLLM now supports NVIDIA Vera Rubin. The early results show more than 7.8x the throughput of GB200 on MiniMax M3 on AgentX. @inferact, @NVIDIAAI, @RedHat_AI, and the vLLM community have been bringing vLLM up on Rubin since it was announced. Here is where things stand. 🧵 1/5

10月9日周五
  1. OpenAI Developers58

    OpenAI Developers 宣布为 Windows 版 Codex 构建了基于 Microsoft Execution Containers(MXC)的新沙箱模式,带来更快的配置、更强的网络管控和更细粒度的文件访问控制。该模式需要兼容的 Windows 11 设备。引用内容显示,MXC 已在 Windows 11 上正式可用,用于把智能体限制在操作系统强制的边界内。

    引用Pavan Davuluri@pavandavuluri

    Today, we announced new @Windows platform capabilities and @surface devices built to empower people and organizations for the era of hybrid intelligence. Here are some of the highlights: - It all starts with trust. Microsoft Execution Containers (MXC) is now generally available on Windows 11, keeping agents contained within boundaries the operating system enforces. - HydraFusion brings hybrid intelligence to life, allowing models to run locally while seamlessly accessing the cloud when more scale or capability is needed. We're working with @github to extend HydraFusion to Windows. - This fall, Search on the taskbar adds thousands of quick actions, making it easier to adjust settings and get things done as fast as you can type. - @MSFTCopilot is getting more powerful on Windows. With hybrid intelligence, it can tap into your PC's local capabilities and turn your requests into action, while keeping you in control. - Local agents are coming to Windows too. Muse is on its way as a native Windows app with MXC integration, and Hermes, OpenClaw, and Perplexity are already building local experiences on Windows. - Surface Laptop Ultra, built with NVIDIA RTX Spark, is the most powerful Surface we've ever built. It's available for pre-order today, along with the Surface RTX Spark Dev Box and new RTX Spark PCs from our partners. Call of Duty is coming to RTX Spark in 2027. Read more on the Windows Blog: https://blogs.windows.com/windowsexperience/2026/10/07/building-windows-for-hybrid-intelligence/

10月8日周四
  1. Microsoft Research66

    微软研究院开源 Agent Lightning v1.0:约 3500 行的轻量 Agentic RL 框架

    微软研究院开源 Agent Lightning v1.0,这是一个约 3500 行代码的轻量 Agentic RL 框架,提出 Harnessed Agentic RL 范式,让部署时使用的 agent harness 直接参与强化学习,无需在训练框架内重写 agent。

    推荐理由:微软研究院开源约 3500 行的 Agent RL 框架,用真实 harness 参与训练,并给出 6000 样本提升 14.6 个点的完整流程。

10月2日周五
10月1日周四
9月30日周三
9月22日周二
9月21日周一
  1. Qwen42

    感谢 @sgl_project 的 day-0 支持!🙌 SGLang-Diffusion 现已支持 Qwen-Image-2.1:文生图、多图编辑和透明 RGBA 输出。快来试试!🎨

    引用SGLang@sgl_project

    Day-0 support for @Alibaba_Qwen’s Qwen-Image 2.1 is here in SGLang-Diffusion! 🖥️ Native precision on a single RTX 4090 24GB with CPU offload - 1024×1024 generation in 18.7s and image editing in 21.7s with 22.7 GiB peak GPU memory during requests. - On an RTX PRO 6000 96GB: 8.0s generation and 9.6s editing. 🎨 Text-to-image, multi-image editing, and transparent RGBA output—all with one checkpoint. ⚡ Native inference with TP/SP, LoRA, and OpenAI-compatible APIs. 40 denoising steps, one image per request, warmed HTTP latency including PNG output. No quantization. Cookbook and GPU-specific commands below 👇

9月20日周日
  1. Qwen58

    Qwen 宣布 Qwen-Image-2.1 在 vLLM-Omni 获得 day-0 支持,可在一个模型中完成图像生成、编辑与透明图输出。据 vLLM 项目介绍,该模型由 7.1B 的 DiT 与 Qwen3-VL-8B 组成,配置与支持的组合见 recipes.vllm.ai/Qwen/Qwen-Image-2.1。

    引用vLLM@vllm_project

    Qwen-Image-2.1 from @Alibaba_Qwen has day-0 support in vLLM-Omni. 🎉 Generate, edit, and create transparent images with one model: a 7.1B DiT paired with Qwen3-VL-8B. Setup and supported combinations 👇 https://recipes.vllm.ai/Qwen/Qwen-Image-2.1

9月12日周六
7月30日周四
7月29日周三
7月7日周二
  1. Berkeley AI Research42

    智能免费之后怎么办?面向智能体、由智能体构建的数据系统

    UC Berkeley 团队提出,推理成本已从 GPT-4 级约 $30/百万 token 降至不足 $1,部分厂商低于 $0.10,基准测试中推理价格每年下降 9x 至 900x、中位数约 50x。作者据此提出三类数据系统挑战:为智能体设计的数据系统、支撑智能体群体运行的数据系统、以及由智能体合成的数据系统。

5月8日周五
  1. Berkeley AI Research36

    自适应并行推理:高效推理扩展的下一个范式

    伯克利 AI 研究团队综述并行推理进展,重点分析自适应并行推理——让模型自行决定何时分解并并行化子任务、开多少并发线程以及如何协调。现有方法如 self-consistency、Best-of-N、Tree of Thoughts、MCTS、ParaThinker、GroupThink 和 Hogwild! Inference 的并行结构多由外部设定,而非模型自主选择。

4月29日周三
  1. DeepSeek40

    DeepSeek-V4-Pro 折扣已延长至 2026 年 5 月 31 日 15:59 UTC!

    引用DeepSeek@deepseek_ai

    🔥DeepSeek-V4-Pro API is 75% OFF until May 5th, 2026, 15:59 (UTC Time)! Don't miss out on this massive discount. 🛠️Integration Updates: 🔹Claude Code: Set model to deepseek-v4-pro[1m] to unlock 1M context! 🔹OpenCode: Update to v1.14.24+ 🔹OpenClaw: Update to v2026.4.24+ Check the latest official API docs for full details: https://api-docs.deepseek.com/quick_start/pricing

4月27日周一
4月25日周六
3月27日周五
  1. Andrej Karpathy58

    Andrej Karpathy 回顾约一年前搭建 menugen 的经历,认为最难的不是代码本身,而是服务、支付、认证、数据库、安全、域名等一整套 DevOps 组装。

    引用Patrick Collison@patrickc

    When @karpathy built MenuGen (https://karpathy.bearblog.dev/vibe-coding-menugen/), he said: "Vibe coding menugen was exhilarating and fun escapade as a local demo, but a bit of a painful slog as a deployed, real app. Building a modern app is a bit like assembling IKEA future. There are all these services, docs, API keys, configurations, dev/prod deployments, team and security features, rate limits, pricing tiers." We've all run into this issue when building with agents: you have to scurry off to establish accounts, clicking things in the browser as though it's the antediluvian days of 2023, in order to unblock its superintelligent progress. So we decided to build Stripe Projects to help agents instantly provision services from the CLI. For example, simply run: $ stripe projects add posthog/analytics And it'll create a PostHog account, get an API key, and (as needed) set up billing. Projects is launching today as a developer preview. You can register for access (we'll make it available to everyone soon) at http://projects.dev. We're also rolling out support for many new providers over the coming weeks. (Get in touch if you'd like to make your service available.) https://projects.dev

3月10日周二