this post was submitted on 23 Jul 2025
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Right, I'm no expert (and very far from an AI fanboi), but not all "AI" are LLMs. I've heard there's good use cases in protein folding, recognising diagnostic patterns in medical images.
It fits with my understanding that you could train a similar model on more constrained datasets than 'all the English language text on the Internet' and it might be good at certain jobs.
Am I wrong?
Technically, LLMs as used in Generative AI fall under the umbrella term "machine learning"…except that until recently machine learning was mostly known for "the good stuff" you're referring to (finding patterns in massive datasets, classifying data entries like images, machine vision, etc.). So I feel like continuing to use the term ML for the good stuff helps steer the conversation away from what is clearly awful about genAI.
There is no generative AI. It's just progressively more complicated chatbots. The goal is to fool the human into believing it's real.
Its what Frank Herbert was warning us all about in 1965.
Chatbprs are genAI. Any artificial intelligence like NPCs, autopilot, playing games against the machine, playing chess against the machine... All of those have been called AI.
GenAI is a subset where what the AI does is generate text or images instead of taking a deterministic option. GenAI describes pretty well what it does generate a text or image output, no matter the accuracy of the text. The AI is optimised to generate output that looks like what you would expect with the given input, and generally it does exactly that, even if it hallucinated facts to fit the idea of the response that they are supposed to give with the given input.