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「A demonstration of the non-commutativity of the English language」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
This will be a more frivolous post than usual, in part due to the holiday season.
I recently happened across the following video, which exploits a simple rhetorical trick that I had not seen before:
已知结果和反例
If nothing else, it’s a convincing (albeit unsubtle) demonstration that the English language is non-commutative (or perhaps non-associative); a linguistic analogue of the swindle , if you will.
Of course, the trick relies heavily on sentence fragments that negate or compare; I wonder if it is possible to achieve a comparable effect without using such fragments.
证明或构造的主线
A related trick which I have seen (though I cannot recall any explicit examples right now; perhaps some readers know of some?) is to set up the verses of a song so that the last verse is identical to the first, but now has a completely distinct meaning (e.g. an ironic interpretation rather than a literal one) due to the context of the preceding verses. The ultimate challenge would be to set up a Möbius song, in which each iteration of the song completely reverses the meaning
On a related note: when I was a graduate student in Princeton, I recall John Conway (and another author whose name I forget) producing another light-hearted demonstration that the English language was highly non-commutative, by showing that if one takes the free group with 26 generators and quotients out by all relations given by anagrams (e.g. ) then the resulting group was commutative. Unfortunately I was not able to locate this recreational mathematics paper of Conway (whi
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:This will be a more frivolous post than usual, in part due to the holiday season. I recently happened across the following video, which exploits a simple rhetorical trick that I ha 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:This will be a more frivolous post than usual, in part due to the holiday season.
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:liday season. I recently happened across the following video, which exploits a simple rhetorical trick that I had not seen before: 已知结果和反例 If nothing else, it’s a convincing (albeit unsubtle) demonstration that the Engli
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:se, the trick relies heavily on sentence fragments that negate or compare; I wonder if it is possible to achieve a comparable effect without using such fragments. 证明或构造的主线 A related trick which I have seen (though I cann