[kalkin]

I think dismissing problem-solving as "smoke and mirrors" based on regurgitating training data will give you a poor predictive model for what else models can do. For example, do you think that if you change the variable names to something statistically likely to be unique in human history, the ability will break?

As for pattern recognition vs intuitive grasp--I don't think I follow. I would call pattern recognition part of intuition, unlike logically calculating out the consequences of a model, but on the other hand I would not say that a desktop calculator "grasps" anything-it is not able on its own to apply its calculating ability to real world instantiations of mathematical problems in the way that humans (and sometimes LLMs) can do.