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this post was submitted on 03 Dec 2023
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Right, the trick will be quantifying what is 'likely to be a hit', which if we're honest, has already been done.
Also, neural networks and other evolutionary algorithms can inject random perturbations/mutations to the system which, operate a bit like uninformed creativity (something like banging on a piano and hearing something interesting that's worth pursuing). So, while not 'inspired' or 'soulful' as we would generally think of it, these algorithms are capable of being creative In some sense. But it would need to be recognized as 'good' by someone or something...and back to your point.
What you described in your second paragraph is basically how image generation AI works.
Starting from random noise and gradually moving towards the version a classifier identifies as best matching the prompt.