There are both ML that is not AI, and AI that is not ML.
For example, if you pick them manually, decision trees can be AI but not ML. Video game character behavior is a trivial example.
Eliza for example is also not ML, but could be called AI.
Likewise, there is ML that is not AI. Such is debatable, because you could always argue that using machine-learning on anything results in intelligence. The way I see it, things like image enhancement or voice replacement are not artificial intelligence at all. I probably could not define a hard line where it becomes artificial intelligence though.
I don’t know what the op meant by manually picking but the expert systems of the 80s and case based reasoning systems of the 90s used fairly static decision functions and were explicitly called AI at the time.
for example, mob behavior in Minecraft is often described as AI. It's nothing more than some simple state tracking, task prioritization, pathfinding, etc. and absolutely none of it has been through autodiff.
To me they're the same thing. If there's a bunch of training data that is fed into a system that creates a model, then it's not traditional programming, where someone laboriously writes out if statements by hand. AI and ML aren't, as far as I'm aware, rigorously specifically defined terms. They're words that marketing picked up and ran with it. To me, what matters is: is there a black box somewhere in the system that's a bag of numbers, or is it code that a human could dig in and read.
It is correct to argue about misleading terminology. "AI" contains the word "intelligence", and for instance logistic regression algorithm is not intelligent, while it is clearly ML, since machine learns something. As Machine learning is broader category, it should include Artificial Intelligence, not vice versa.
Also, 'every single course' is perhaps an overstatement - a course that I co-authored tries to get it right from the first principles.
The machine is learning something so that it can produce outputs based on its learned knowledge. At a high level that seems to be very clearly AI. What am I missing here? You’re probably right, I’m asking genuinely.
It's a matter of definitions, but I can at least understand someone wanting to make a distinction between reactive and non-reactive 'AI' (such as data filters).
There's overlap and edge cases, though: Maybe you have a program that summarizes texts. One could argue that's no different from a passive filter. But can you then ask questions about the text? That's unquestionably AI.
