In this episode, we return to the unfolding debate around AI’s so-called ability to “think.” Building on last week’s discussion of Apple’s controversial paper The Illusion of Thinking, we now explore the equally provocative rebuttal by Anthropic, the company behind Claude. Their paper, pointedly titled The Illusion of the Illusion of Thinking, argues that Apple’s findings say more about poor experimental design than any real limits in AI reasoning. So who’s right? Or are both missing the point? We unpack the technical details, the debate, and the AI community backlash — including criticisms that Apple may be using this research to explain away its slower pace in AI development. But more importantly, we tackle the deeper question hiding underneath it all: what do we actually mean by “reasoning” in machines? And are we setting the right benchmarks when we measure AI against human thought? If you’ve ever wondered where the line is between token prediction and true intelligence, or if you’re curious about how models like Claude, GPT, and Gemini really handle complex problems, this is a conversation that pulls back the curtain. It’s not just about who’s right — it’s about whether our entire framework for evaluating AI thinking needs to change.