陶哲轩博客写数学问题时，通常先把对象定义清楚，再给直觉、反例和证明轮廓。把「Displaying maths online, II」改写成可阅读的中文笔记，重点是：问题在问什么、已知到哪一步、下一步最容易走偏在哪。原站广告、分享条和导航已去掉。
问题在问什么
As the previous discussion on displaying mathematics on the web has become quite lengthy, I am opening a fresh post to continue the topic. I’m leaving the previous thread open for those who wish to respond directly to some specific comments in that thread, but otherwise it would be preferable to start afresh on this thread to make it easier to follow the discussion.
It’s not easy to summarise the discussion so far, but the comments have identified several existing formats for displaying (and marking up) mathematics on the web ( mathML , jsMath , MathJax , OpenMath ), as well as a surprisingly large number of tools for converting mathematics into web friendly formats (e.g. LaTeX2HTML , LaTeXMathML , LaTeX2WP , Windows 7 Math Input , itex2MML , Ritex , Gellmu , mathTeX , WP-LaTeX , TeX4ht , blahtex , plastex , TtH , WebEQ , techexplorer ,
已知结果和反例
It seems that the tools that already exist are enough to improvise a passable way of displaying mathematics in various formats online, though there are still significant issues with accessibility, browser support, and ease of use. Even if all these issues are resolved, though, I still feel that something is still missing. Currently, if I want to transfer some mathematical content from one location to another (e.g. from a LaTeX file to a blog, or from a wiki to a PDF, or from
Anyway, it has been a very interesting and educational discussion for me, and hopefully for others also; I look forward to any further thoughts that readers have on these topics. (Also, feel free to recapitulate some of the points from the previous thread; the discussion has been far too multifaceted for me to attempt a coherent summary by myself.)
证明或构造的主线
先写出对象、假设和失败的例子，再进入证明。没有反例的直觉，很容易把局部技巧当成一般定理。
阅读时建议盯住的点
先写出对象、假设和失败的例子，再进入证明。没有反例的直觉，很容易把局部技巧当成一般定理。
阅读和落地时建议先做的 5 件事
- 用自己的语言重写定义和结论，不看原文能不能说清对象是什么。
- 找一个最小反例或边界情形，确认假设少一条会怎样。
- 把证明拆成可独立检验的引理，每步只保留一个新想法。
- 若涉及计算或形式化，先写可复现的小例子，再谈一般情形。
- 记下尚未解决的缺口：缺估计、缺构造，还是缺正确的范畴。
和智能体、形式化工具怎么接
龙虾PRO做 OpenClaw 落地时，数学笔记最有用的部分往往是「可检验的步骤」：定义、反例、引理边界。智能体适合帮忙展开计算和检索，不适合代替你决定哪条假设能扔。
本文侧重全链路风控方法论。落地时请用自身业务单据做回放验证，不要把示例阈值直接当生产策略。 相关：风控体检 · 方案资源
常见问题 FAQ
什么是AI智能系统？
「AI智能系统」可概括为：As the previous discussion on displaying mathematics on the web has become quite lengthy, I am opening a fresh post to continue the topic. I’m leaving the previous thread open for 本文从定义、方法与实践要点展开说明。
为什么要关注AI智能系统？
关注AI智能系统，是因为它直接影响效率、风险与可复制性。文中指出：As the previous discussion on displaying mathematics on the web has become quite lengthy, I am opening a fresh post to continue the topic. I’m leaving the previous thread open for those who wish to respond directly to some specific comments in th…
如何落地AI智能系统？有哪些关键步骤？
建议按以下路径推进AI智能系统：1) 用自己的语言重写定义和结论，不看原文能不能说清对象是什么。；2) 找一个最小反例或边界情形，确认假设少一条会怎样。；3) 把证明拆成可独立检验的引理，每步只保留一个新想法。；4) 若涉及计算或形式化，先写可复现的小例子，再谈一般情形。；5) 记下尚未解决的缺口：缺估计、缺构造，还是缺正确的范畴。。细节见正文对应章节。
AI智能系统适合哪些人或团队？
AI智能系统更适合：产品/技术负责人、运营与增长团队、需要落地智能体或自动化的中小团队、关注「AI智能系统」方向的读者。若你只需要单次聊天式问答，可先读概念；若要上生产，请重点看步骤、权限与风控相关段落。
关于「问题在问什么」，本文给出了什么结论？
在「问题在问什么」部分，要点是：become quite lengthy, I am opening a fresh post to continue the topic. I’m leaving the previous thread open for those who wish to respond directly to some specific comments in that thread, but otherwise it would be prefe
关于「已知结果和反例」，本文给出了什么结论？
在「已知结果和反例」部分，要点是：support, and ease of use. Even if all these issues are resolved, though, I still feel that something is still missing. Currently, if I want to transfer some mathematical content from one location to another (e.g. from a