You're right: I haven't seen evidence of LLM novel pattern output that is basically creative.
It can find and remix patterns where there are pre-existing rules and maps that detail where they are and how to use them (ie: grammar, phonics, or an index). But it can't, whatsoever, expose new patterns. At least public facing LLM's can't. They can't abstract.
I think that this is an important distinction when speaking of AI pattern finding, as the language tends to imply AGI behavior.
But abstraction (as perhaps the actual marker of AGI) is so different from what they can do now that it essentially seems to be futurism whose footpath hasn't yet been found let alone traversed.
When they can find novel patterns across prior seemingly unconnected concepts, then they will be onto something. When "AI" begins to see the hidden mirrors so to speak.
You're right: I haven't seen evidence of LLM novel pattern output that is basically creative.
It can find and remix patterns where there are pre-existing rules and maps that detail where they are and how to use them (ie: grammar, phonics, or an index). But it can't, whatsoever, expose new patterns. At least public facing LLM's can't. They can't abstract.
I think that this is an important distinction when speaking of AI pattern finding, as the language tends to imply AGI behavior.
But abstraction (as perhaps the actual marker of AGI) is so different from what they can do now that it essentially seems to be futurism whose footpath hasn't yet been found let alone traversed.
When they can find novel patterns across prior seemingly unconnected concepts, then they will be onto something. When "AI" begins to see the hidden mirrors so to speak.