Earlier quoted context omitted.
No. That is NOT what it does at all. Here's a quick explainable in this thread for what it does: https://news.ycombinator.com/item?id=31489463 If you gave 100 well read, English speaking humans the following (very commonly found) sentence and asked them to predict the next character what would they do? "four score and s" Most would predict "e", then "v" etc until you get "seven". That's what a language model does. So…
How do you calculate the "most likely character to appear next", if not by memorizing lots and lots of existing sentences? ML is by essence a copycat that will regurgitate what it has seen before in a new context, no matter how hard you try to hide it under the mathematical shape of the probabilities of single characters in a sequence. Now, there is the philosophical question of whether human creators simply do the s…
Well that's how languages work right? Words are the most common sequence of letters.
But that doesn't mean it's regurgitating parts of sentences it had previously seen anymore than I'm regurgitating when I'm typing this.
Mechanically it has learnt both syntax of language and how concepts relate. So when it starts generating it makes sentence that are syntactically valid but also make sense in terms of concepts.
Thats really different to just combining bits of sentences, and it gives rise to abilities you wouldn't expect in something just cutting and pasting bits of sentences. For example, few shot learning is mostly driven by its conceptual understanding and can't be done by something with no way to relate concepts.