[frozenwind]

I am disappointed your comment did not have more responses because I'm very interested in deconstructing this argument I've heard over and over again. ("it just predicts the next words in the sentence"). While explanations of how GPT-style LLMs work involve a layering of structures which encode at the first levels some understanding of syntax, grammar etc. and then as the more levels of transformers are added, eventually some contextual and logical meanings are encoded. I really want to see a developed conversation about this.

What are we humans even doing when zooming out? We're processing the current inputs to determine what best to do in the present, nearest future or even far future. Sometimes, in a more relaxed space (say a "brainstorming" meeting), we relax our prediction capabilities to the point our ideas come from a hallucination realm if no boundaries are imposed. LLMs mimic these things in the spoken language space quite well.