This doesn’t seem a surprising or particularly deep result, and perhaps we’re having the wrong arguments about LLMs. I certainly don’t doubt that they’re capturing deep knowledge, my only criticism would be that they’re doing so in a lossy and extremely static way.

I’ve come to think of it this way. A simple Markov chain model trained on language would be the simplest example of something picking up a very shallow model of some text. Let’s call that a Layer One model, and we had fun with them for a while.

Machine translation goes one step further - instead of learning just the text it’s given, a model sees that above words are representations of things and ideas, and structures to render those ideas in multiple languages. That feels like Layer Two, but I’m not aware of traditional machine translation models that will take a piece of poetry, for example, and render it in a new language, perhaps using local idioms to capture the essence, if not the exact translation, of some content. So it’s only really one layer deeper.

Large language models are layers beyond this. They are both wider and deeper. They are showing that much more knowledge than we thought can be captured statically - patterns of patterns of patterns of patterns turn out to be enough to store and process a huge amount of what we previously thought was a privileged part of human intelligence. That’s the truly interesting result - the models still seem dumb to me, but boy, being dumb is much more impressive than we used to think.

We’re focused on training LLMs on larger corpora to store more stuff and more parameters and layers to find deeper patterns. But even though they’re clearly learning world models, it’s still just a static snapshot of knowledge. ChatGPT shows over a short span that a model can integrate new information quite well. What’s missing is some mechanism for _constant_ integration of new information, and some degree of internal rumination about past, present and future knowledge. Something algorithmic, temporal and dynamic, not just a static repository of knowledge. I don’t think this actually requires a great deal of magic, just a slight change in direction (although I’ve no doubt this is being worked on and is probably in all sorts of papers already). Of course, there’s still time for us to decide not to do that, but the hour is close at hand.