July 31, 2026
Brainstorm or brain glitch?
Is AI Reasoning Right for the Wrong Reasons?
AI might be crushing puzzles, but the internet still thinks nobody knows why
TLDR: Researchers are split over whether AI is truly thinking or merely producing impressive answers by pattern-matching, even as it racks up major math wins. In the comments, skeptics call the hype magical thinking, while supporters say the tools work so well that the debate is starting to sound like sour grapes.
The latest Quanta deep dive asks a spicy question: when artificial intelligence gets the right answer, is it actually thinking, or just doing a spectacularly convincing impression of thinking? That debate is extra messy now because these newer AI systems have done jaw-dropping things — from solving a famous math problem to scoring at elite competition levels — while also face-planting on simpler tasks in ways that make researchers wonder if the whole show is being held together with digital duct tape.
And wow, the comments came ready to fight. One camp is deeply skeptical, basically yelling, "stop romanticizing autocomplete!" User baxtr compared AI "reasoning" talk to Oprah-style manifesting, which is easily the funniest burn in the thread. AsyncBanana delivered the purest vibe check of all: the more they read, the more it feels like nobody really knows what is going on. On the other side, zuzululu is exhausted by what they see as endless anti-AI gatekeeping, arguing the tools are already useful, already changing jobs, and already paying bills — flex included: three remote jobs with AI help. Meanwhile, sobiolite pushed back on the idea that AI can just fake the shape of a proof and accidentally land on real math, calling that explanation flat-out dubious.
So the real drama isn’t just whether AI can reason. It’s whether the experts are carefully defining reality — or just trying to keep up while the machines keep winning anyway.
Key Points
- •The article examines whether large reasoning models genuinely reason or only produce outputs that resemble reasoning.
- •It cites a May 2026 OpenAI result in which a general-purpose reasoning model reportedly solved a famous open mathematical research problem in one shot.
- •It references Apple researchers’ “Illusion of Thinking,” which argued that AI reasoning claims can break down under simple test conditions.
- •It describes Santa Fe Institute research suggesting LRMs can excel on reasoning benchmarks such as ARC-style puzzles by exploiting surface-level shortcuts.
- •It also highlights Google DeepMind and Terence Tao’s AI-assisted work on 67 mathematics problems while noting separate evidence of persistent failure modes in LRMs.