> I think ANN is the real thing, and most of the other "AI" solutions that we have give the impression of intelligence, but are simply algorithms that solve problems we have in very well defined ways...ANN is a general intelligence that gets shaped by experience and adapts figure out its own solutions...It isn't some coder banging on the keyboard trying to replicate what a human would do under a specific situation, it is something that truly learns.

It's not ANNs on the one hand and "some coder banging on the keyboard trying to replicate what a human would do" on the other.

Supervised learning is the most common use case for an ANN, and means learning from labelled training data during a training phase and then not changing; it can be done with a number of techniques, including Support Vector Machines, Decision Trees, Bayesian methods, and so on.

Reinforcement Learning on the other hand, is continuous learning from trying things and making mistakes -- experience, in other words. It too can be done a number of ways, like with Evolutionary Algorithms, Markov Decision Processes, Inductive Logic Programming, etc. Hell, PG's spam classifier learns from experience, and it's nothing more than a Naive Bayes classifier ( http://www.paulgraham.com/spam.html ).

Without going on for much longer, my point is that there really is no reason to exalt ANNs the way you have.

Disclaimer: I'm a huge believer in Artificial General Intelligence via Competent Program Search ( see http://metacog.org/research.html + http://www.google.com/url?sa=t&source=web&cd=2&v... + www.idsia.ch/~juergen/ )