When it comes to LLMs doing novel things, is it just the infinite monkey theorem[0] playing out at an accelerated rate, helped along by the key presses not being truly random?

Surely if we tell the LLM to do enough stuff, something will look novel, but how much confirmation bias is at play? Tens of millions of people are using AI and the biggest complaint is hallucinations. From the LLMs perspective, is there any difference between a novel solution and a hallucination, other than dumb luck of the hallucination being right?

[0] https://en.wikipedia.org/wiki/Infinite_monkey_theorem

To have a proper discussion we would have to define the word "novel" and that's a challenge in itself. In any case, millions of poeple tried to ask LLMs to do something creative and the results were bland. Hence my conclusion LLMs aren't good for that. But I'm also open they can be an element of a longer chain that could demonstrate some creativity - we'll see.

Novel is a tricky word. In this case, the LLM produced a python program that was similar to other programs in its corpus, and this oython program generated examples of hypergraphs that hadn't been seen before.

That's a new result, but I don't know about novel. The technique was the same as earlier work in this vein. And it seems like not much computational power was needed at all. (The article mentions that an undergrad left a laptop running overnight to produce one of the previous results, that's absolute peanuts when compared to most computational research).

re-read your post - it's just a bunch of nonsense, no actual reasoning in there