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bojieli/ai-infra-book

《深入理解 AI Infra：量化分析与系统设计》（李博杰 著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验

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Momentum

How fast bojieli/ai-infra-book is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 13 – Nov 5, 2026

Stars +5,827 in 54 days

05001K1.5K
1,120

Forks +592 in 54 days

050100150
143

Merged PRs 28 in 54 days

0510
9

Trendshift Trendingwhere the repository ranked each day it made the top 25

Top 25 overall

119

Top 25 in Python

5413
Sep 13Sep 20Sep 27Oct 4Oct 11Oct 18Oct 25Nov 1
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRsAll languagesPython
Sun, Sep 13, 2026+0+230Not trendingNot trending
Mon, Sep 14, 2026+804+1431#11#5
Tue, Sep 15, 2026+1,120+690#9#4
Wed, Sep 16, 2026+429+371Not trending#13
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Fri, Sep 25, 2026+50+30Not trendingNot trending
Sat, Sep 26, 2026+56+51Not trendingNot trending
Sun, Sep 27, 2026+61+20Not trendingNot trending
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Tue, Sep 29, 2026+110+90Not trendingNot trending
Wed, Sep 30, 2026+71+49Not trendingNot trending
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Tue, Oct 20, 2026+61+70Not trendingNot trending
Wed, Oct 21, 2026+35+50Not trendingNot trending
Thu, Oct 22, 2026+44+90Not trendingNot trending
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Mon, Oct 26, 2026+41+60Not trendingNot trending
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Wed, Nov 4, 2026+35+60Not trendingNot trending
Thu, Nov 5, 2026+21+00Not trendingNot trending
Total+5,827+59228
  • 1#1 on the list
  • 7Rank that day
  • Not trending

    • Mentions and achievements

    Where people are talking about bojieli/ai-infra-book, and every badge it has earned
    1. Oct 251 post

      • 分享 3 本 GitHub 上的开源 AI 宝典，那是相当有真东西。 1、《深入理解 AI Agent：设计原理与工程实践》这本书挺不错的。 这个开源项目包括 PDF、配图、EPUB 和配套实验代码，现在有 4.9 万个 Star，还在持续更新。 开源地址： 2、《深入理解 AI Agent》姊妹篇：在上面《深入理解 AI Agent》之后，开发者博杰又开源了《深入理解 AI…

        Read full on X, posted by @guangGitHub

        @guangGitHub · x.com

    2. 12 days earlier
    3. Oct 131 post

      • 学完这6 本 GitHub 上的开源 AI 宝典，可以入职大厂了吧？ 1.《深入理解 AI Agent》 地址： 2.《深入理解 AI Agent》姊妹篇：《深入理解 AI Infra：量化分析与系统设计》。 地址： 3.蒲公英书《神经网络与深度学习》 地址： 4.《强化学习的数学原理》 地址： 5.在谷歌工作多年的老哥写的《Agentic Design Patterns》，把构建 AI…

        Read full on X, posted by @jieduba26

        @jieduba26 · x.com

    4. 14 days earlier
    5. Sep 291 post

      • • Understand why AI models are slow or costly • Estimate memory and computing needs for models • Learn how hardware affects AI speed and cost

        Read full on X, posted by @the_osps

        @the_osps · x.com

    6. Sep 281 post

      • 很多人每天都在调 API，但根本不知道底层的算力是怎么分配的。 这本书不仅告诉你模型为什么慢，还教你怎么把成本真正降下来。 作者是李博杰大佬（这也是超火的《深入理解 AI Agent》的姊妹篇）。无论你是调包侠想进阶，还是做系统、网络、芯片的工程师，看完都能打通任督二脉 🧠

        Read full on X, posted by @mylifcc

        @mylifcc · x.com

    7. Sep 231 post

      • 《深入理解 AI Infra》社区翻译的英文版和繁体中文版发布啦！感谢社区 tg1482 和 edward821220 的翻译。 书还新增了 MiMo V2.6 前段时间直播的 RL 算例（infra 故障的代价有多大）和 DeepSeek DSec 沙箱平台的资源与状态管理（RL 沙箱跟传统容器云有什么区别）。

        Read full on X, posted by @bojie_li

        @bojie_li · x.com

    8. Sep 191 post

      • 量化分析与系统设计：从约束到架构 See link below 👇

        Read full on X, posted by @RepoGems

        @RepoGems · x.com

    9. Sep 151 post

      • Day About 15/09/2026 - Only Tech

        Read full on Reddit

        r/u_ScreenSharp736

    10. Sep 143 posts

      • 没想到《深入理解 AI Infra》发布首日就突破 2k stars 了，比《深入理解 AI Agent》涨星都快 😂 不少读者问我怎么写出来的，我是上个月写了一份提纲，GPT-6 Astra 发布之后我就开始让 Agent 干活了： 1. 调研最近 3 年主要的几个系统和体系结构会议上的 paper，看哪些适合放在一本 Infra 教科书里的 2. 下载 NVIDIA、昇腾、Apple…

        Read full on X, posted by @bojie_li

        @bojie_li · x.com

      • 为什么一次推理会慢，常常不是“模型不够快”，而是算力、显存、带宽和通信中的某一项先撞墙。 这本书让我更清楚地理解 AI Infra 不是参数调优的背景板，而是从硬件约束反推模型与系统设计。它把 KV 缓存、算子、超节点、网络、训练和调度串成一条量化链路，还附了可复算的计算工具与实验。

        Read full on X, posted by @vintcessun

        @vintcessun · x.com

      • 为什么同一模型换了硬件、上下文长度或并发，成本和延迟会差出数量级？ 这本开源书让我重新理解 AI Infra：不是背优化名词，而是从算力、显存、带宽和通信约束出发，逐项量化推导。KV Cache、算子、超节点到调度都有计算工具和实验；先算物理上限，再找系统损耗，很多“优化经验”终于有了判断坐标。

        Read full on X, posted by @vintcessun

        @vintcessun · x.com

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