At the end of the day, all computing is very simple. What's impressing you here is the size of the dataset and the speed of the retrieval, brought about by advances in hardware. Also, we like the well-formed writing which is created by filtering and massaging the parroted text into a new set of sentences.
It is impressive, and people who don't know how it really works will think it's capable of all kinds of things it's not. Of course, this has been true forever. Just ask anyone who writes code about what non-devs think software can do.
Your understanding of GPTs and neural nets in general is consistently flawed.
You are describing a Markov model or at best an SVM model.
Would you make the same types of claims about Stable Diffusion, that it is “piecing together pieces of existing images?” That is not how these models work. Similar to the temporal memory that ChatGPT will appear to have during a conversation, “inpainting” with Stable Diffusion produces entirely novel output with context. Have you tried it out?
I have and I wrote extensively about it after seeing the unpopularity of my original comment. There's a link to my long Medium story about it in another comment.
Would I say that DALL-E, etc. also piece together existing images? Yes, of course, since that is the only way that technically it could work. All of computing is "input-process-output." There is no "create" step in any of computing.
The pieces that DALL-E pieces together are pixels of a certain color and brightness and placement relative to other pixels. Together, we perceive this as an image. If they weren't arranged that way, we'd just see noise or gray.
The same is true with ChatGPT. Unless they're put in a particular order, words just make word salad. It is the order that gives them their perceived meaning in a sentence. ChatGPT crafts "new" sentences by rearranging words from similar sentences it has already seen, just like DALL-E creates new paintings by rearranging pixels from paintings it has already seen.
A recent video from Noam Chomsky explains this from his perspectives on learning and language:
It is impressive, and people who don't know how it really works will think it's capable of all kinds of things it's not. Of course, this has been true forever. Just ask anyone who writes code about what non-devs think software can do.