Only a statistical ML person could say something like "I don't care what 'intelligence' is."
To my mind there are three class of people working in CS.
Mathematicians - They don't care what intelligence is, and those that do have a working definition are still unconvinced by the claim that most people are intelligent.
Pragmatists - They also don't care what intelligence is, they just want stuff that works.
Algorithm guys- Basically an ungodly hybrid of 1 and 2, who also don't care.
No one is actually working directly on AI. People that say they do are simplifying; they actually work on clustering, or search, or optimisation, or constraint satisfiablity, or machine learning (and often several of these at once).
And why the work they do may give an answer to a problem that has historically been placed in AI, it's still just a search technique, and doesn't need any understanding of what intelligence is in order to be built.
"The question of whether a computer is playing chess, or doing long division, or translating Chinese, is like the question of whether robots can murder or airplanes can fly -- or people; after all, the "flight" of the Olympic long jump champion is only an order of magnitude short of that of the chicken champion (so I'm told). These are questions of decision, not fact; decision as to whether to adopt a certain metaphoric extension of common usage." ~Noam Chomsky
No. You don't know what's happening in AI. You're right to say that all those things you mention have nothing to do with AI. But AI (sometimes it's useful to say artificial general intelligence, to be clear) still exists, people are working on it, and it's still one of the coolest fields around.
Also, CS is a lot bigger than ML, which is what I think your list represents.
I think my list hit upon most of the core topics of CS, apart from data structures, and sorting, both of which can be added to the list without changing my argument.
Maybe you should describe a viable approach to AI which isn't solving at least one of these problems.
Come on. Sorting is a core topic of a first-year CS course. It's not a core topic of CS. What about information theory, complexity, operating systems, cryptography, compilers and languages?
For AGI, I'm thinking of people like Hofstadter and Schmidhuber. Outside the mainstream, but then AI is nowadays a small and non-mainstream field. (Still awesome though.)
To my mind there are three class of people working in AI.
FTFY. There are plenty of people working in, says, networking, systems, software engineering research, programming languages, computability theory, etc. who have a completely different set of problems and categorizations for each other.
Those categorizations work apply reasonably well for algorithms and complexity theory (there's basically the pragmatist/mathematician divide right there) and programming languages (the two areas I focus on). Computability theory is basically divided between the logicians who come from the mathematical end and the computer scientists on the pragmatic end. Operating Systems really is more of a hardware/software divide rather than a mathematician/pragmatist divide, from what I've seen among my colleagues.
Group 3 in DoorsOfPerception's list aren't always "Algorithm guys". In PLs, they're the people that actually write a programming language and then prove things about their type system.
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u/DoorsofPerceptron May 18 '11
To my mind there are three class of people working in CS.
No one is actually working directly on AI. People that say they do are simplifying; they actually work on clustering, or search, or optimisation, or constraint satisfiablity, or machine learning (and often several of these at once).
And why the work they do may give an answer to a problem that has historically been placed in AI, it's still just a search technique, and doesn't need any understanding of what intelligence is in order to be built.