“Expert systems and neural nets are nonspecific programming techniques for encoding decision criteria and learning input-output relationships, that are often inferior to more problem-specific encoding, inference and learning algorithms. It is highly improbable that future fully intelligent machines will be built with either technique alone, though both may be used in places. Blind biological evolution may be stuck with solutions once chosen, but intelligence-guided technology is not so limited.”
Even Kurzweil talks about the role of the conventional AI toolbox:
“There are many intricate ways to combine the varied methods in AI’s toolbox. For example, one can use a genetic algorithm to evolve the optimal topology (organization of nodes and connections) for a neural net or a Markov model. The final output of the GA-evolved neural net can then be used to control the parameters of a recursive search algorithm. We can add in powerful signal- and image-processing techniques that have been developed for pattern-processing systems. Each specific application calls for a different architecture.”
Moravec on a related issue:
“Expert systems and neural nets are nonspecific programming techniques for encoding decision criteria and learning input-output relationships, that are often inferior to more problem-specific encoding, inference and learning algorithms. It is highly improbable that future fully intelligent machines will be built with either technique alone, though both may be used in places. Blind biological evolution may be stuck with solutions once chosen, but intelligence-guided technology is not so limited.”
http://www.frc.ri.cmu.edu/~hpm/project.archive/general.articles/1994/940430.Brainmakers.review.html
Even Kurzweil talks about the role of the conventional AI toolbox:
“There are many intricate ways to combine the varied methods in AI’s toolbox. For example, one can use a genetic algorithm to evolve the optimal topology (organization of nodes and connections) for a neural net or a Markov model. The final output of the GA-evolved neural net can then be used to control the parameters of a recursive search algorithm. We can add in powerful signal- and image-processing techniques that have been developed for pattern-processing systems. Each specific application calls for a different architecture.”
Ray Kurzweil on http://www.kurzweilai.net/articles/art0683.html?printable=1