**AI推理是真正的推理，还是**

_Is AI Reasoning Right for the Wrong Reasons?_

> The idea that artificial intelligence can “reason” is more intuitive than ever. But intuitions can be wrong, and the science is far from settled. Home Is AI Reasoning Right for the Wrong Reasons? Comment Save Article Read Later Share Facebook Copied! Copy link Email Pocket Reddit Ycombinator Comment Comments Save Article Read Later Read Later Qualia Is AI Reasoning Right for the Wrong Reasons? By John Pavlus July 31, 2026 The idea that artificial intelligence can “reason” is more intuitive than ever. But intuitions can be wrong, and the science is far from settled. Comment Save Article Read Later Celsius Pictor for Quanta Magazine Introduction By John Pavlus Contributing Writer July 31, 2026 View PDF/Print Mode artificial intelligence computer science features large language models machine learning Qualia All topics I ’ll just say it: What the hell is going on with AI “reasoning”? Sorry for the air quotes. That punctuational side-eye was more common in 2024, when the specially trained cousins of LLMs now known as “large reasoning models,” or LRMs, were still new. Nowadays it may seem downright churlish, though, given that a “general-purpose reasoning model” from OpenAI solved a famous open mathematical research problem in one shot in May 2026. Still, I’m not sure how else to acknowledge my intellectual whiplash over the scientific interpretation of what these AI systems are actually doing. Reasoning comes in many technically defined forms , but the basic procedure is easily recognizable: arriving at a sound conclusion by linking together intermediate steps that logically follow from each other. We do this with thoughts; LRMs use so-called chains of thought, a term of art for the streams of synthetic text that the models emit before arriving at an answer to a complex query. One minute, the idea that AI could reason via these chains was being prominently and credibly critiqued (by a team of researchers from Apple) as an “ Illusion of Thinking ” subject to “complete accuracy collapse” under surprisingly simple conditions. The next minute, LRMs were bagging gold medals at the International Mathematical Olympiad, a feat so challenging that “even very successful mathematicians and scientists may well highlight \[it\] on their CVs all their lives,” as the scientist and AI critic Gary Marcus and Ernest Davis wrote in 2025. If that’s not a sign of “real” reasoning, what is? p\]:my-6 \[&\>ul\]:my-6 \[&\>ol\]:my-6 \[&\>p\]:text-3-5 \[&\>p\]:leading-6.5 \[&\>li\]:text-3-5 \[&\>li\]:leading-6.5 \[&\_img.alignleft\]:float-left \[&\_img.alignleft\]:mr-5 \[&\_img.alignleft\]:ml-0 \[&\_img.alignleft\]:my-5 \[&\_img.alignright\]:float-right \[&\_img.alignright\]:ml-5 \[&\_img.alignright\]:mr-0 \[&\_img.alignright\]:my-5 \[&\_figure\]:m-0 \[&\_figcaption\]:relative \[&\_figcaption\]:flex \[&\_figcaption\]:flex-col \[&\_figcaption\]:gap-2 \[&\_figcaption\]:pt-2 \[&\_figcaption\]:pb-4-5 \[&\_figcaption\]:mt-0 \[&\_figcaption\]:mb-6 &\_figcaption\]:font-pangram \[&\_figcaption\]:after:content-\[""\] \[&\_figcaption\]:after:absolute \[&\_figcaption\]:after:bottom-0 \[&\_figcaption\]:after:w-11 \[&\_figcaption\]:after:h-0.5 \[&\_figcaption\]:after:bg-gray-1a1 \[&\_.caption\]:block \[&\_.caption\]:font-pangram \[&\_.caption\]:text-0xxs \[&\_.caption\]:leading-4-5 \[&\_.caption\]:m-0 \[&\_.attribution\]:block \[&\_.attribution\]:font-pangram \[&\_.attribution\]:text-xs \[&\_.attribution\]:leading-4-5 \[&\_.attribution\]:m-0 \[&\_.attribution\]:before:content-none show-dropcap" style="color: \#000000;"\> I n philosophy, “qualia” refers to the subjective qualities of our experience: what it’s like for Alice to see blue or for Bob to feel delighted. Qualia are “the ways things seem to us,” as the late ph...

**来源信息**
- **来源**：Hacker News：AI 热帖
- **分类**：论文
- **发布时间**：2026-07-31 23:29（北京时间）
- **原文**：[打开原文](https://www.quantamagazine.org/is-ai-reasoning-right-for-the-wrong-reasons-20260731)