Do reasoning models really “think” or not? Apple research sparks lively debate, response

Apple’s machine-learning group set off a rhetorical firestorm earlier this month with its release of “The Illusion of Thinking,” a 53-page research paper arguing that so-called large reasoning models (LRMs) or reasoning large language models (reasoning LLMs) such as OpenAI’s “o” series and Google’s Gemini-2.5 Pro and Flash Thinking don’t actually engage in independent “thinking” or “reasoning” from generalized first principles learned from their training data.

Instead, the authors contend, these reasoning LLMs are actually performing a kind of “pattern matching” and their apparent reasoning ability seems to fall apart once a task becomes too complex, suggesting that their architecture and performance is not a viable path to improving generative AI to the point that it is artificial generalized intelligence (AGI), which OpenAI defines as a model that outperforms humans at most economically valuable work, or superintelligence, AI even smarter ...