LLMs themselves are made up of "good old fashioned" components. The public conversation about generative AI seems to assume that it's doing something fundamentally different than what came before. Of course, LLMs are still just deep NNs trained through back propagation to "classify" strings of text into one of many categories corresponding to each possible token. The only thing they do differently is to compute auto-correlation coefficients in each layer and zero some of them out. And of course they take advantage of massive amounts of training data by self-supervising.

LLMs are only a slight variation on the good old fashioned models that already existed at the time they showed up.