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VirtualHat t1_j456msu wrote

Definitions shift a bit, and people disagree, but this is what I stick to...

AI: Any system that responds 'intelligently' to its environment. A thermostat is, therefore, AI.

ML: A system that gets better at a task with more data.

Therefore ML is a subset of AI, one specific way of achieving the goal.


I_will_delete_myself t1_j46jn9e wrote

Ok thank you. I kind of hate the mob mentality of this site though. It discourages learning and experimenting.


[deleted] t1_j45cnht wrote



VirtualHat t1_j45dklv wrote

I think Russell and Norvig is a good place to start if you want to read more. The AI defintion is a taken from their textbook which is one of the most cited references I've ever seen. I do agree however that the first defintion has a problem. Namely with what 'intellegently' means.

The second defintion is just the textbook defintion of ML. Hard to argue with that one. It's taken from Tom Mitchell. Formally “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” (Machine Learning, Tom Mitchell, McGraw Hill, 1997).

I'd be curious to know what your thoughts on a good defintion for AI would be? This is an actively debated topic, and so far no one really has a great defintion (that I know of).


tell-me-the-truth- t1_j45e4gv wrote

yeah I can see the point behind ML definition.. i guess i was trying to say you don’t always get better with more data. the performance might saturate at some point or the new data you add could be garbage.. so i found it a bit odd to tie definition of ML to the quantity of data.. the definition you linked talks about experience.. i’m not sure how it’s defined.


VirtualHat t1_j45em2b wrote

Yes true! Most models will eventually saturate and perhaps and even become worse. I guess it's our job then to just make the algorithms better :). A great example of this is the new Large Langauge Models (LLM), which are trained on billions if not trillions of tokens, and still keep getting better :)


MustachedLobster t1_j45dp6k wrote

A thermostat responds to the environment. It turns on the heating when it gets too cold.

and the ML definition is just repeating the formal definition by Mitchell:

> A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”,simple%20example%20to%20understand%20better%20.


tell-me-the-truth- t1_j45eidu wrote

oh i mixed thermometer with thermostat.. yeah then i agree thermostat can be AI..


[deleted] t1_j45dk5m wrote



VirtualHat t1_j45e2rs wrote

Everything is new in its current form :) AI, however, goes back a long way... perhaps Turing would be a reasonable starting point, though, with him writing about COMPUTING MACHINERY AND INTELLIGENCE back in 1950.

edit: gramma.


[deleted] t1_j45ek1n wrote



VirtualHat t1_j45faub wrote

Genetic algorithms are a type of evolutionary algorithm, which are themselves a part of AI. Have a look at the wiki page.

I think I can see your point though. The term AI is used quite differently in research than in the popular meaning. We sometimes joke that the cultural definition of AI is "everything that can't yet be done with a computer" :)

This is a bit of a running joke in the field. Chess was AI, until we solved it, then it wasn't. Asking a computer random questions and getting an answer Star Trek style was AI until Google then it was just 'searching the internet'. The list goes on...


deustrader t1_j46zi5j wrote

I guess I would be concerned with claiming that evolutionary algorithms are AI, because that’s not how most people understand the current AI. And right now pretty much everything is being advertised as AI for marketing purposes, without being able to distinguish one solution from another. But you’ve made a good point.