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The “overlap” is that all machine learning is AI, but not all AI is machine learning.
by granzymes 3mo ago
The “overlap” is that all machine learning is AI, but not all AI is machine learning.
- kennywinker 3mo agoAt this point AI is a marketing term not an actual category
- thorbutt 3mo agoSee: Samsung selling "AI" vacuum cleaners and washing machines
- AdieuToLogic 3mo ago> The “overlap” is that all machine learning is AI ... "All machine learning" is not AI, as k-means clustering and linear regression, amongst others, are very much ML without qualifying as AI algorithms.
- solumunus 3mo agoThe 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.
- cygx 3mo agoIt'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.
- ruszki 3mo agohttps://en.wikipedia.org/wiki/Artificial_intelligence https://en.wikipedia.org/wiki/Artificial_intelligence As it is taught literally every single AI/machine learning course on the world, machine learning is very much part of AI completely since inception. I don’t completely understand why it is this important for you to argue against this completely defined fact.
- RuslanL 3mo agoIt 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.
- ruszki 3mo agoIt wasn't misleading for 70 years... How did it become misleading?
- budsniffer952 3mo agoYou're just making up your own definitions. Have at it, but as you've been told: this stuff is not new.
- wqaatwt 3mo ago[dead]
- disgruntledphd2 3mo agoTechnically linear regression is statistics rather than ML, but I feel like the GNU/Linux people whenever I point that out.
- fingerlocks 3mo agoNot even technically. I had to do linear regressions by hand, pencil and paper, in college stats course 20 years ago. No machine necessary
- LoganDark 3mo agoThere 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.
- budsniffer952 3mo ago[flagged]
- kasey_junk 3mo agoI 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.
- LoganDark 3mo agofor 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.
- HappMacDonald 3mo ago> but not all AI is machine learning I will instead pick at this latter part of your claim. What is an example of something that is AI but that is not ML..?
- lukan 3mo agoA chess engine.
- lazide 3mo agoBayes is turning in his grave fast enough to power Manhattan.
- fragmede 3mo agoTo 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.