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in AI and Deep Learning by (17.6k points)

Now since i've taken a class 3 years ago in A.I. im clearly proficient enough to ask this question......just kidding just kidding ;)

but seriously, what is it about these languages that make them so popular for A.I. research. Even though A.I. research is "old"...it's came probably the longest way in the past 5-10 years it seems like.... Is it because the languages were somewhat "designed" around the concept of A.I. , or just that we have nothing really better to use right now?

I ask this because I've always found it quite interesting, and Im just kinda curious. If im entirely wrong and they use different languages I would love to know what all they use. I mean i can understand prolog, especially with Sentient/Propositional Logic and Fuzzy logic. but I dont understand "Why" we would use Lisp...and even what else A.I. researchers would use to do machine learning etc.

Any articles/books on the subject matter is helpful too :)

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Lisp had a benefit when we thought Artifical Intelligence was symbol manipulation and stuff like Ontologies. Prolog had a benefit when we thought Artificial Intelligence as reasoning, and Unification was the complex process. But neither of these give any advantage for the popular contenders for "Artificial Intelligence": Statistical AI is about sparse arrays.

Neural networks of all varieties, including deep learning, is regarding oceans of nodes joined with links. Model-Free Methods (such as machine learning, evolutionary methods, etc) are also very easy. In either of the cases, any general-purpose language will do. Discussions can also be presented that most Neural Network methods are so simple that C++ would be a slaughter.

So, involve the language that enables you to quickly hire the most skilled programmers for the job.

Learn more about Lisp and Prolog for Artificial Intelligence in the course on Artificial Intelligence.

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