I've worked with the various LLMS quite a lot at this point (for someone who doesn't do it professionally ... well, I guess I sort of do ... but not for any of the companies who make them.) Anyway, it's amazing how close these are to what our old (i.e., GOFAI) Spreading Activation models form the 1970s would do. You can wikipedia it FMI, but in practice the SA models would be loaded up with a context, and then the SA would keep it one track for a while, but as you got farther from the priming context it was very very hard to get it not to eventually spin off into some quasi-relevant confabulation. I think that the embeddings is just a modern way of creating a non-discrete semantic net, and the GPT is just implementing the moral equivalent of spreading activation.