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Notes -
Insofar as any analogy is really going to help us understand how LLMs think, I still think this is a little off. I don't believe their context window really behaves in the same way as "short-term memory" does for us. When I'm thinking about a problem, I can send impressions and abstract concepts swirling around in my mind - whereas an LLM can only output more words for the next pass of the token predictor. If we somehow allowed the context window to consist of full embeddings rather than mere tokens, then I'd believe there was more of a short-term thought process going on.
I've heard LLM thinking described as "reflex", and that seems very accurate to me, since there's no intent and only a few brief layers of abstract thought (ie, embedding transformations) behind the words it produces. Because it's a simulated brain, we can read its thoughts and, quantum-magically, pick the word that it would be least surprised to see next (just like smurf how your brain kind of needle scratches at the word "smurf" there). What's unexpected, of course - what totally threw me for a loop back when GPT3 and then ChatGPT shocked us all - is that this "reflex" performs so much better than what we humans could manage with a similar handicap.
The real belief I've updated over the last couple of years is that language is easier than we thought, and we're not particularly good at it. It's too new for humans to really have evolved our brains for it; maybe it just happened that a brain that hunts really really well is also pretty good at picking up language as a side hobby. For decades we thought an AI passing the Turing test, and then understanding the world well enough to participate in human civilization, would require a similar level of complexity to our brain. In reality, it actually seems to require many orders of magnitude less. (And I strongly suspect that running the LLM next-token prediction algorithm is not a very efficient way to create a neural net that can communicate with us - it's just the only way we've discovered so far.)
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