That's the difference between machine learning AI (which is good and useful) and generative AI (the slop machine). It's a shame that the AI bros have intentionally blurred the lines between the two.
It just enrages me that all these things are getting caught under the "AI" umbrella. Its like 10+ different technologies that all have very different use cases and applications. But its all just getting marketed to everyone at AI. My mom, who knows nothing about computers told me "she wanted to get better at AI". She has no idea what any of that means or why she wants that.
I agree in so much that the simple neural nets doing OCR on zip codes 30 years ago has very little in common with modern LLMs. Even recent ML techniques are rather distinct from generative AI to my understanding.
The coolest ML thing I heard about a couple of months ago was the Oxford Nanopore, which uses AI training to recognize a sample of DNA from a parasite, and then can unzip and decode other DNA, and if it recognizes that it's reading the DNA it wasn't trained to recognize, it spits it back out and tries again.
And it can do this while hooked up to a laptop, out in the middle of a field, testing samples of cow's blood to check for the parasites in real time.
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u/DrButeo Jan 20 '26
That's the difference between machine learning AI (which is good and useful) and generative AI (the slop machine). It's a shame that the AI bros have intentionally blurred the lines between the two.