> I also don't understand the claims that it doesn't generalize. I currently use it to solve problems that I can absolutely guarantee were not in its training s

> I also don't understand the claims that it doesn't generalize. I currently use it to solve problems that I can absolutely guarantee were not in its training set, and it generalizes well enough. I also think that one of the easiest ways to get it to generalize better would simply be through giving it synthetic data which demonstrates the process of generalizing. I don't think what LLMs are currently doing is really generalizing, but rather: 1) Multiple occurrences of something in the dataset are mutually statistically reinforcing. This isn't generalization (abstraction) but rather reinforcement through repetition. 2) Multiple different statistical patterns are being recalled/combined in novel ways such that it seems able to "correctly" respond to things out of dataset, but really this only due to these novel combinations, not due to it having abstracted it's knowledge and applying a more general (or analogical) rule than present in it's individual training points.