Gary Marcus(@GaryMarcus)

The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. ...

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The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. ...

TL;DR · AI 摘要

OpenAI报告缺乏关键科学细节，导致AI成果的可推广性存疑，且X平台用户普遍缺乏批判性思考。

核心要点

  • OpenAI未披露模型架构与训练细节，无法验证结果可靠性
  • AI研究需遵循科学方法论，当前行业透明度不足
  • X平台用户对AI进展的盲目支持可能阻碍技术理性发展

结构提纲

按章节快速跳转。

  1. §引言

    指出当前AI研究缺乏科学严谨性的核心问题。

  2. ·OpenAI报告缺陷

    未披露模型架构、训练流程及失败率等关键信息。

  3. ›科学方法缺失

    未说明证明生成方式及迭代过程，影响结果可信度。

  4. ·X平台反应

    用户群体对AI进展缺乏基本科学问题的探讨。

  5. ›行业影响

    盲目支持可能阻碍AI技术的理性发展与改进。

思维导图

用一张图看清主题之间的关系。

查看大纲文本（无障碍 / 无 JS 友好）
  • AI研究透明度危机
    • OpenAI报告缺陷
      • 未披露架构细节
      • 缺乏训练流程说明
      • 未报告失败率数据
    • 行业影响
      • X平台盲目欢呼
      • 阻碍科学验证
      • AGI发展不确定性

金句 / Highlights

值得收藏与分享的关键句。

#AI#科学方法#OpenAI#透明度#批判性思维
打开原文

Gary Marcus on X: "The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. Now we get stuff like the completely vague report from OpenAI below, and a lot of ignorant questions from people who don’t know how to think critically. “Same procedure”? “using a… / X

Gary Marcus

@GaryMarcus

The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. Now we get stuff like the completely vague report from OpenAI below, and a lot of ignorant questions from people who don’t know how to think critically. “Same procedure”? “using an unreleased model”? This would never pass peer review. We don’t know what the procedure was. We know nothing about the architecture (e.g., were proofs generated in one shot, and then verified by Lean? was there an iterative process?). We know nothing about the failure rate. We know nothing about the training/post training/data agumentation. 2. As a result we have zero idea of how generalizable the result is outside math. 3. A lot of X has been reduced to an ignorant cheering section that applauds without knowing what it is applauding or what it might mean — without ever asking basic scientific questions. The new system could be a legitimate step towards AGI or just a clever leveraging of Lean and synthetic data in a verifiable domain with no generality whatsoever; from this report we can tell almost nothing.

Last edited

4:12 PM · Oct 7, 2026

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