this post was submitted on 13 Jan 2024
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I think maybe people are running into a misunderstanding between LLMs and neural nets or machine kearning in general? AI has become too big of an umbrella term. We've been using NNs for a while now to produce entirely new ways to go about things. They can find bugs in games that humans can't, been used to design new wind turbine blades (even made several asymmetrical ones which humans just don't really do), or plot out entirely new ways of locomotion when given physical bodies. Machine learning is fascinating and can produce very unique results partly because it can be set up to not have existing design biases like humans do
And the nature of computers is that they are magnitudes better than humans at brute forcing. Machine learning can brute force (depending on the technique, it can be smarter than brute forcing, being more efficient) test many many many more designs and techniques than we could manually do. Sure it'll fail many times, but it's just a numbers game, and it can pump those numbers. It'll try a lot of weird and unique stuff we wouldn't even think to try, with varying degrees of success.