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9月25日周五
9月24日周四
  1. NVIDIA Technical Blog(开发者技术博客 · RSS)21

    NVIDIA 如何为生物基础模型实现高效 MoE 训练

    NVIDIA 技术博客解析了生物基础模型的高效 MoE 训练方案:相比每个 token 都要过全部层的稠密 Transformer,MoE 用多个专家子网络、每个 token 只激活其中一小部分,从而降低训练与推理算力开销。文章指出,随着语言模型规模增长,稠密架构的扩展成本越来越高。

  2. Boris Cherny65

    Boris Cherny 介绍 claude.ai 和 Desktop 应用近几周明显变快的原因,团队发布了博文说明做法。@ClaudeDevs 的引用帖称 claude.ai 在两周内快了 3x,博文讲解如何用 Claude 测量、调试和改进性能,并附上提示词和方法,链接为 https://claude.dev/blog/how-we-made-claude-ai-faster/。作者表示博文中有不少对想给自家应用提速的工程师有用的经验与技巧。

    引用ClaudeDevs@ClaudeDevs

    We made claude​.ai 3x faster in two weeks. Here’s how we use Claude to measure, debug and improve performance. Prompts and methods included. https://claude.dev/blog/how-we-made-claude-ai-faster/

    推荐理由:Anthropic 团队分享了用 Claude 测量、调试并让 claude.ai 在两周内提速 3x 的具体方法,文中附带了可直接复用的提示词。

  3. GitHub Blog24

    GitHub Copilot 应用如何渲染超大 pull request

    GitHub Copilot 应用重建了 pull request 视图,用一个含 2200 个文件、超 100 万行改动和 400 多条行内评论的开源 PR 做压力测试。其做法是把文档高度拆成确定性的代码几何与动态评论块两套几何:代码行高提前精确计算,评论高度则按需测量、修正幅度小且锚定在用户当前查看位置,从而避免滚动跳动。

  4. eric zakariasson41

    智能体在工作前后喜欢大量读取以收集上下文,所以针对读取做优化会带来很大差别! 如果你在构建智能体,我强烈推荐读一读这个(或者把它交给你的智能体,让它去实现这些发现)

    引用Cursor@cursor_ai

    We've reduced token costs in Cursor by 7% with no drop in agent quality. Savings came from tighter prompts, selective tool loading, better caching, and compressed file reads.

  5. Simon Willison 博客33

    用可交互示例讲解 Shadow DOM 的 shadow roots

    一篇用可交互示例讲解 shadow roots 的教程,演示了样式封装、继承、slots、parts 以及 JavaScript 访问方式。内容展示 shadow roots 如何创建带有私有样式表和元素的隔离 DOM 树,并以特定且受控的方式与页面 DOM 交互。

9月23日周三
9月22日周二
9月21日周一
  1. MiniMax Design (H3)36

    🔥社区从不停下折腾的脚步。 不只是基于 H3 做开发,还在不断深入内部,寻找让它更聪明的新方法。

    引用Kamimoto(かみもと)@sep_is_heim

    流行のJevをMiniMax H3に組み込んで、動画生成を高速化してみた!Attention処理のスパース化にJevを使用。 ・層ごとにJevが重要度を判定(4step 49層が対象) ・Jevがスパース率1%, 3%, 5%, 10%を選択 RTX4070で6分7秒→3分34秒で41.7%短縮!動画生成中にJevクラウドに問合せしているのに速い!

9月19日周六
9月18日周五
  1. Gemini Notebook47

    播客好友 @stevenbjohnson 展示了他最喜欢的 Notebook 移动应用用法之一 🤯

    引用Steven Johnson@stevenbjohnson

    The camera feature in the @Gemini_Notebook mobile app is so transformative for on-the-go research. I was up in the Sierras working on a new project, and I just took photos of everything, like this museum display. Then I asked for a detailed report of all the info in the image. The text below is what I got back. (I fact-checked it myself and it was 99% accurate -- and some of the text it transcribed is so blurry in the image that it was hard for me to read it.) Next step is to generate documents like this for all the photos I took, and then ask Notebook to highlight all the information that adds something new to the existing knowledge base of sources I've already collected, or is particularly relevant to my latest writing and outline for the project. Truly magical. Mariposa Museum Exhibit Reference: Mariposa in 1859 & Gold Rush Era This reference document consolidates all text, photographic captions, historical statistics, newspaper clippings, and exhibit overlays displayed on the Mariposa Museum exhibit panel regarding Mariposa during and after the Gold Rush. 1. Exhibit Overview & Key Headlines Main Title: "THIS WAS MARIPOSA IN 1859 – ONLY 10 YEARS AFTER THE GOLD RUSH BEGAN." Historical Context Sub-headline: "PORTIONS OF THE TOWN HAD BEEN REBUILT AFTER THE FIRE OF 1858.. & PARTS OF IT WERE DOOMED TO BE DESTROYED IN 1866" Display Overview: The exhibit centers on a large 1850s panoramic photograph of Mariposa, annotated with street names, landmark locations, and population statistics, flanked by contemporary hotel advertisements, fire reports, medical artifacts, and photographs of civic buildings. 2. Demographic & Real Estate Statistics (1850s vs. Present) MetricHistorical Value (1850s Gold Rush Peak)Modern Value Town Population~3,000 residents~1,800 estimated Entire Mariposa Diggings Area~15,000 residents— Commercial Establishments15 to 20 stores & saloons, plus hotels— Town Lot Prices00 to 00 per lot— 3. Background Photograph & Civic Infrastructure Background Photo Date: Taken in the 1850s, capturing the rapid growth of the settlement following the initial gold strike. 1854 Mariposa County Courthouse: Shown in the background panorama prior to the construction of its iconic clock tower. A separate framed photograph depicts the completed white wood-frame courthouse with a white picket fence and clock tower. Clock Tower History: The clock mechanism was imported from England and is an 8-day, manually wound instrument. It remains operational today, maintained by the Mariposa Public Works Department. Annotated Overlay Locations on Panorama: 1854 Courthouse: Located at the upper edge of town on Jones Street. Jones Street & Bullion Street: Upper residential and civic thoroughfares. Charles Street (Main Street): Primary commercial artery running through the center of the valley floor. Schlageter Hotel Site: Positioned along Main Street. Mariposa Creek: Flowing along the foreground basin of the town diggings. 4. The Fire of 1866: Mariposa's Second Great Conflagration Below is the complete transcript of the Mariposa Gazette report featured on the panel regarding the disaster of August 25, 1866 (following the earlier destructive fire of 1858): Article Text: "FIRE! MARIPOSA'S SECOND GREAT FIRE" A few minutes after 6 p.m. on Saturday, August 25, 1866 Mariposa was again ruined by a disastrous fire (first in 1858). According to the Gazette (the building was damaged but not destroyed), the fire was believed to have started when "a recently imported printer stepped inside the Free Press office and lighted a cigar. The match had evidently been dropped carelessly amongst the papers on the floor. The Free Press office was located near the corner of Main and 7th Streets and by ten minutes the fire had spread through two blocks. The fire crossed Main Street to the Odd Fellows building and the Methodist Church and soon the buildings on the block between 6th and 7th Streets were burning like so much chaff." Seven full blocks, except for four fire-proof buildings, were totally destroyed. "In one hour about 60 buildings and 77,000 worth of property were destroyed." By early Monday morning the men were clearing away debris and by press time the following Saturday, the Gazette reported that several temporary business structures had already been erected and were open for business. Inventory of Buildings Destroyed in the 1866 Fire: Residential & Civic: 14 Dwellings, 1 Church, 1 Odd Fellows and Masons Hall. Media & Printing: 1 Newspaper Office (Free Press), 1 Newspaper Depot. Hospitality & Retail: 3 Hotels, 5 Retail Stores, 1 Saddlery Shop, 9 Liquor Saloons (several equipped with billiard tables). Services & Trades: 2 Livery Stables, 3 Law Offices, 1 Drug Store, 3 Blacksmith Shops, 2 Carpenter Shops, 2 Shoemaker Shops, 1 Tailor Shop, 2 Butchering Establishments. Outbuildings: Numerous outhouses, private stables, and auxiliary structures. 5. Commercial Hotels & Lodging Gallison Hotel (1887 Advertisement) Location: Main Street, Mariposa (center of business district, opposite Odd Fellows' Hall). Proprietor: Winslow Gallison. Management: Mrs. Gallison individually superintended all internal departments of the hotel. Amenities: Newly furnished rooms, first-class table dining. Mariposa Hotel (1887 Card) Location: Corner of Main and Fifth Streets. Proprietor: Charles A. Schlageter. Target Market: Accommodated general travelers as well as Yosemite tourists on short notice. Amenities: Family rooms, well-lighted parlors, good table, and bath facilities. The Schlageter Hotel Date Built: Built in the 1850s. Architecture: Prominent two-story wooden structure featuring full upper and lower covered verandas. 6. Medical Artifacts & 19th-Century Therapeutics Old Mariposa Hospital A framed historical photograph depicts a two-story wood-frame hospital building with a prominent front porch and side wing (annotated "from Chic Allingham"). Dr. D. Jayne's Family Medicines (1880 Display Broadside) 1. Jayne's Specific for Tape-Worm Diagnosis: Describes tapeworm infections as widespread, noting that discharging white or yellowish segments ("resembling gourd seeds") is the only positive diagnostic proof. Pricing & Ordering: .00 per dose, shipped nationwide via mail from 242 Chestnut Street, Philadelphia. Usage Instructions: Dissolve powder in a pint of boiling water, drink in three equal hourly doses on an empty stomach. Follow with Cathartic medicines if bowels do not operate in three hours. 2. Dr. D. Jayne's Sanative Pills Formulation: Concentrated, sugar-coated pills. Sold in 50-pill boxes (-bash.25) or 15-pill specimen packets (-bash.10). Prescribed Ailments: Advertised for liver complaints, gout, jaundice, dyspepsia, rheumatism, kidney affections, fevers, nervousness, skin diseases, melancholy, sick headache, and costiveness (constipation). 3. Exhibit Commentary Note A small museum card mounted below the broadside reads: "A man advertises for 'a competent person to undertake the sale of a new medicine' and adds innocently 'It will prove profitable to the undertaker.'"

9月17日周四
  1. jietang66

    唐杰发文复盘,GLM-5.3-Flash 从首次在国内加速器上运行到承接全部生产流量只用两周,端到端吞吐达 3.2 倍,大量工作由 GLM-5.3 驱动的 Infra Agent 完成。

    引用Z.ai@Zai_org

    We’re sharing how GLM-5.3 helped build and optimize the inference infrastructure serving GLM-5.3-Flash. The system went from its first successful run to production readiness in less than two weeks, with end-to-end throughput tripling relative to the initial baseline. The key was dense feedback: local correctness tests, execution traces, microbenchmarks, and end-to-end measurements that enabled targeted hypothesis testing rather than reliance on aggregate performance metrics alone. https://z.ai/blog/glm-built-its-inference-infrastructure

    推荐理由:作者复盘了 GLM-5.3 智能体优化推理基础设施的两周过程,提出了可迁移的分层密集反馈方法与工程师角色转变的判断。

  2. GitHub Blog85

    GitHub Copilot 用 Copilot 把运行时迁移到 Rust:80 万行代码、128 个 PR

    GitHub 用 GitHub Copilot app 和 Copilot CLI 把 Copilot agent runtime 从 TypeScript/Node.js 完全重写为超过 80 万行生产级 Rust,AI 智能体编写了大部分代码,跨 128 个 PR 增量合入 main,性能提升数个数量级,主要由一名开发者几个月内完成。

    推荐理由:GitHub Copilot 运行时迁移 Rust 的完整复盘,给出智能体并行协作、提示缓存与评审流程的可迁移工程方法。

  3. NVIDIA Technical Blog(开发者技术博客 · RSS)41

    如何用 AI 智能体为仿真准备 3D 场景

    NVIDIA 展示了一套智能体 AI 工作流,用于为物理 AI 系统准备和验证数字孪生。智能体可检查 3D 场景、在 OpenUSD 中编写仿真相关数据、添加物理属性、渲染预检视图,并对照 SimReady 要求验证结果。该流程覆盖从 Blender 场景到面向 NVIDIA 的仿真就绪 OpenUSD 交付。

9月16日周三
  1. Together AI 研究与产品博客(RSS)53

    Together AI 详解从闭源模型迁移到开源模型的策略

    Together AI 发布从闭源模型迁移到开源模型的指南,称采用托管服务可将迁移周期从数月到数年缩短为数周到数月。方法分发现、评估、适配、决策、生产五步,核心是用真实流量回放而非通用基准做评估,并按系统提示词、推理参数、上下文工程、微调四个杠杆迭代适配;文中提到部分客户迁移后成本最多降低 70%,可用 10% 流量的金丝雀部署开始上线。

  2. NVIDIA Technical Blog(开发者技术博客 · RSS)34

    Dense 与 MoE 模型对比:活跃参数、吞吐量与选型时机

    NVIDIA 技术博客对比 Dense 与 MoE 两种模型架构,说明参数组织方式对性能的影响。以 Nemotron 3.5 Lightning 为例,该模型总参数 30B,但每个 token 仅激活 3B 参数,依靠 MoE 架构按 token 选择部分参数,从而在保留大模型容量的同时降低单次计算量。文章围绕活跃参数、吞吐量与选型时机展开分析。

9月15日周二
  1. NVIDIA Technical Blog(开发者技术博客 · RSS)28

    NVIDIA FLARE 如何跨 Docker、Kubernetes 和 Slurm 扩展联邦学习

    NVIDIA 技术博客介绍如何用 NVIDIA FLARE 将联邦学习从单服务器、少量客户端的简单部署扩展到跨 Docker、Kubernetes 和 Slurm 的共享基础设施。随着项目规模增长,挑战从运行算法转向运营共享基础设施:按需分配 GPU、隔离多个研究任务,并让每个参与机构保留对自身数据的控制权。

  2. NVIDIA Technical Blog(开发者技术博客 · RSS)33

    NVIDIA Transformer Engine 如何加速 JAX 中的 Dropless MoE 训练

    NVIDIA 技术博客介绍如何用 NVIDIA Transformer Engine 在 JAX 中加速 Dropless MoE 训练。MoE 通过条件计算实现高效训练,DeepSeek、Qwen、Mixtral 等模型以远低于稠密模型的训练算力达到或超越其性能。文章针对传统 MoE 依赖共享稠密 FFN 的做法,给出 Dropless 训练路径。

9月14日周一
9月13日周日