I agree -- artificial intelligence modeled on human brains hasn't been explored nearly enough to label it a failure. In addition to advances in artificial neur

I agree -- artificial intelligence modeled on human brains hasn't been explored nearly enough to label it a failure. In addition to advances in artificial neural networks, there has been a lot of progress in more realistic models of the brain (specifically the neocortex). Artificial neural networks started the interest in "brain-like" modeling, but for a while, most neural networks were about as "brain-like" as a 100 component circuit is "computer-like"$ But unlike classical ANNs, new research such as HyperNEAT is exciting because it might reveal the mechanisms by which the wiring of the brain evolved into a structure capable of carrying out robust learning mechanisms. Equally exciting is the research going on in figuring out the specifics of the learning mechanisms themselves. Research groups like the Redwood Center for Theoretical Neuroscience in Berkeley and the Center for Biological and Computational Learning at MIT (and many others) are making progress in understanding neocortical function and companies such as Numenta$$ are developing cortical learning algorithms based on specific mechanisms observed in the neocortex. $ This example is from Jeff Hawkins's book "On Intelligence" $$ Disclosure - I am working there this summer.