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Comment by dmcginty | Hacker News Reader

I don't think calling it AI is a stretch. It's a system with sensors, actuators, a knowledge base, and a ruleset; plus it can learn and adapt its ruleset based on success/failure. That's the textbook definition of AI.

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You added one thing in the list that makes me agree - "it can learn and adapt".

Jarvis in my house uses sensors, actuators, lights, switches, etc - but mine is not AI. It only does what I tell it how to do. I'm pretty happy with the results, but it can't learn a thing.

The latest thing I "taught" my Jarvis to do is stream the security camera to the TV with a voice command. Now if I only had time to look into how to tell it to stop...

That being said, I don't think the ability to learn and adapt. This is entirely a statement on semantics, but if I made a tic-tac-toe playing program that had every possible game state pre-programmed in, I would not hesitate to call it a game playing AI even though it lacks the ability to learn.

That would just follow a singular simple algorithm, not really intelligence in any sense.

In the general programming industry over the last several decades, "artificial intelligence" has also applied to simple decision-making algorithms, even as simple as playing checkers. Arthur Samuel [1] was renowned for his work on a checkers AI circa 1959.

[1]: http://webdocs.cs.ualberta.ca/~sutton/book/11/node3.html

As a follow-on to the above comment, in AI there is something called expert systems, which is just a set of IF-THEN rules which emulate the reasoning of a human expert: https://en.wikipedia.org/wiki/Expert_system Learning/inferencing/adaptation not included or required.

This is something I like about AI in the context of video games; the technology has improved, the complexity has increased, but the meaning of AI in this context has stayed constant.

The same can't really be said of AI in most other contexts, where the goalposts continually seem to move to whatever is currently just beyond our reach.

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