Comment by mrandish

> So exactly inverse to this article, I characterize LLMs as 100% System 2, and would say that what's missing in AI is the more "embodied" System 1 intelligence.

I've read Kahnemann's book and how I've seen System 1 / 2 typically used in the context LLMs often makes them seem like poor fits to what's being referenced. The concept was created to broadly group types of human reasoning but it never struck me as rigorously defined enough to be a technically precise distinction. Applying what was a mildly useful directional thumbnail referencing human thinking styles to LLMs, which can mimic human output but via completely different processes, quickly goes off the rails. As we get more detailed and precise, the System 1 / 2 distinction seems to increasingly diverge from how LLMs behave.

A quick example is how basic Flash-type chat models without 'extended thinking' or MoEs will keep suggesting different solutions instead of stopping after a few failures to step back, gather more context and diagnostic data and evaluate changing approaches or questioning the question. When I do that, the 'interrupt' is often a 'System 1-ish' intuitive feeling like "I suspect I'm barking up the wrong tree" then, once stopped, I'll switch to System 2 to analyze. But in LLMs that "interrupt" behavior typically arises from adding more System 2-ish thinking. N=1 but that's not how I usually 'get there' and is orthogonal to what the System 1 / 2 model suggests.