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「It ought to be common knowledge that Donald Trump is not fit for the presidency of the Uni」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

In logic, there is a subtle but important distinction between the concept of mutual knowledge – information that everyone (or almost everyone) knows – and common knowledge , which is not only knowledge that (almost) everyone knows, but something that (almost) everyone knows that everyone else knows (and that everyone knows that everyone else knows that everyone else knows, and so forth). A classic example arises from Hans Christian Andersens’ fable of the Emperor’s New Clothe

I believe that there is now a real-life instance of this situation in the US presidential election, regarding the following

已知结果和反例

Proposition 1 . The presumptive nominee of the Republican Party, Donald Trump, is not even remotely qualified to carry out the duties of the presidency of the United States of America.

Proposition 1 is a statement which I think is approaching the level of mutual knowledge amongst the US population (and probably a large proportion of people following US politics overseas): even many of Trump’s nominal supporters secretly suspect that this proposition is true, even if they are hesitant to say it out loud . And there have been many prominent people, from both major parties, that have made the case for Proposition 1: for instance Mitt Romney, the Republican pre

证明或构造的主线

I highly recommend watching the entirety of the (35 mins or so) speech, followed by the entirety of Trump’s rebuttal .

However, even if Proposition 1 is approaching the status of “mutual knowledge”, it does not yet seem to be close to the status of “common knowledge”: one may secretly believe that Trump cannot be considered as a serious candidate for the US presidency, but must continue to entertain this possibility, because they feel that others around them, or in politics or the media, appear to be doing so. To reconcile these views can require taking on some implausible hypotheses that are

阅读时建议盯住的点

I feel that it is time for the charade to end: Trump is unfit to be president, and everybody knows it. But more people need to say so, openly.

Important note : I anticipate there will be any number of “ tu quoque ” responses, asserting for instance that Hillary Clinton is also unfit to be the US president. I personally do not believe that to be the case (and certainly not to the extent that Trump exhibits), but in any event such an assertion has no logical bearing on the qualification of Trump for the presidency. As such, any comments that are purely of this “tu quoque” nature, and which do not directly address the

阅读和落地时建议先做的 5 件事

  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。

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。

效率龙虾 会带着下面这段开聊

按文章《「It ought to be common knowledge that …》把卡点收成可执行步骤:先做什么、别踩哪条、怎么验证。

用效率龙虾试这篇

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:In logic, there is a subtle but important distinction between the concept of mutual knowledge – information that everyone (or almost everyone) knows – and common knowledge, which i 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:In logic, there is a subtle but important distinction between the concept of mutual knowledge – information that everyone (or almost everyone) knows – and common knowledge , which is not only knowledge that (almost) everyone knows, but something …

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:ncept of mutual knowledge – information that everyone (or almost everyone) knows – and common knowledge , which is not only knowledge that (almost) everyone knows, but something that (almost) everyone knows that everyone

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:ment which I think is approaching the level of mutual knowledge amongst the US population (and probably a large proportion of people following US politics overseas): even many of Trump’s nominal supporters secretly suspe