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That's because most of what we hear about "AI" is revolving around content "creation" controversies, but these are successfully used in analyzing wide data sets for scientific purposes, like finding new foldings of proteins, diagnosing cancer, reading ancient burned scrolls via etcxrays
And all of those things are then analyzed and verified before anything is done with them. No reputable scientist is taking those results and dumping it straight into a paper; the deep learning engines are pointing scientists in the right direction; they're taking the haystack and making it a handful. Protein folding is a little different because the results can be directly verified programmatically (I think; I'm not an organic chemist, or biologist, or whoever is doing this research).
The output of LLMs can be great outlines. They can also be wildly, and confidently, wrong.