Comment by wavefrontbakc

>While I wouldn't trust current setups, there's no obvious reason why even a mere LLM cannot be used to explore the design space when the output can be simulated to test its suitability as a solution

Having to test every assertation sounds like a not particularly useful application, and the more variables there are the more it seems to be about throwing completely random things at the wall and hoping it works

You should use a tool for it's purpose, relying on text prediction to predict clarity is like relying on teams icons being green to actual productivity; a very vague, incidentally sometimes coinciding factor.

You could use text predictor for things that rely on "how would this sentence usually complete" and get right answers. But that is a very narrow field, I can mostly imagine entertainment benefiting a lot.

You could misuse text predictor for things like "is this <symptom> alarming?" and get a response that is statistically likely in the training material, but could be completely inverse for the person asking, again having very high cost for failing to do what it was never meant to. You can often demonstrate the trap by re-rolling your answer for any question a couple times and seeing how the answer often varies mild-to-completely-reverse depending on whatever seed you land.