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I'm not sure what exactly you're referring to, but one avenue to implement AI is genetic programming, where programs are manipulated to reach a goal.

Lisp languages are great for these manipulations, since the AST being manipulated is the same data structure (a list) as everything else. In other words, genetic programming can lean into Lisp's "code is data" paradigm.

As others mentioned, today everything is based on neural networks, so people aren't learning these other techniques.



I'm referring to the fundamental idea in AI of knowledge representation. Lisp is ideal for chapters 1 through 4 of AIMA, and TensorFlow has shown that NN can be solved well with a domain specific language which lisp is known to be great for.

In fact, the first edition of AIMA even had a NN and Perceptron implementation in Common Lisp. (https://github.com/aimacode/aima-lisp/blob/master/learning/a...)




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