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So I get passing off if-then statements, mechanical turk/human intervention, or ChatGPT API calls as "AI".

But is there a problem saying that a product that incorporates machine learning techniques is powered by AI? I ask because I'm starting to see people separate "ML" from "AI". Where ML is basically everything pre-generative AI (recommendation systems, computer vision, machine translation) and AI is generative AI. Where as I've always viewed ML as a subcategory of "soft" AI. Is there a generally accepted difference between ML and AI?




From a scientific perspective, AI is the name of the general field that studies systems that try to exhibit intelligent behavior, and ML is a strict subset of that - it's the one that's currently more popular, but the study of, for example, planning algorithms or logic reasoning algorithms are other subfields of AI that have nothing to do with ML.


In my classes, I tell students that "AI" is the general population term for machine learning, data science, and "traditional" AI (pathfinding, planning, logic proofs, etc). They all touch on a part of AI, but the differences are hard to explain to non-tech people. People will interchange ML with AI and still mean the umbrella "all of it" concept. That's one of the reasons the article talks about getting more concrete tools that are used in the workflow. Laypeople might think a switch statement is AI and their potential customers also think its AI, that doesn't mean its really AI.

I'm actually booked to give an AI talk for business managers later this month and this is something I'm planning to cover. The article does a good job at outlining what to look for when you get those "AI for X" sales pitches.




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