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Agreed, although the code examples in python ( http://code.google.com/p/aima-python/ ) and lisp ( http://aima.cs.berkeley.edu/lisp/doc/overview.html ) are worth pointing out.



Does AI + Python have any practical use in production?

Most of the algorithms I've tested seem pretty slow. Although the linked examples are for learning.

From my research AI seems to be primarily LISP in academia and C in production.


I actually use a blend of C & Python, C for doing the heavy lifting and Python for the rapid prototyping.

Most AI algorithms have clearly defined segments that are very CPU intensive, by only using C in those areas I get the optimal balance of development speed and execution speed.


Ever since I learnt Cython, this has been my preferred combination as well. I can't overstate enough how great it is to be able to get the rapid prototyping of Python combined with being able to offload the heavy stuff to C.


Increasingly these days academic AI is done in Matlab or similar systems.




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