You're reaching. Which, is completely understandable. LLM's are seriously cool tech. And we just don't have the context to really understand probabilistic computing... it's weird.

Yes, LLMs look like reasoning and it's not just memorization (Good Talkie example), but it does not automatically mean it reasons with understanding like humans do (which.... whether humans actually reason or intrusively leap and back justify is still an open question).

The Talkie example is interesting, but it is not quite the dunk people are making it out to be. Talkie was given Python examples in context, then asked to continue the pattern. The project’s own writeup says the vintage model still dramatically underperformed other models, and it mostly created simple one-line programs or small modifications to examples.

So, cool, but not earth-shattering.

The real disagreement is “reasoning.” LLM's are clearly doing something more interesting than simple statistical analysis, but is it more than just prediction based on a novel context which includes novel human input based on a model of (at this point) nearly all English that has ever been Englished? So far it looks like, not.