[Neuroscience] Re: The future of psychology, neuroscience, and artificial intelligence

casey via neur-sci%40net.bio.net (by jgkjcasey from yahoo.com.au)
Sat Mar 8 18:04:05 EST 2008

On Mar 9, 3:38 am, feedbackdroid <feedbackdr... from yahoo.com> wrote:

> Unfortunately, current NNs do little more than solve toy problems.
> In the recent presentation by Hinton, he mentioned it took him 17
> years to figure out how to properly make something [boltzmann
> probabilistic networks] that works significantly faster and better
> than backprop networks. And what do his marvelous new networks
> solve? The recognition of the numbers 1 to 9 in various distorted
> forms. 17 more years down the tubes.

So were you impressed by what Donahoe's people have shown as described
in the cool paper that GS recommended?

The brain does implement its action in the form of neural networks
so somehow we know at least biological neural networks have the
right stuff.

I don't know that much about current ANN's and they haven't interested
me much for the reasons you mention above. I have wondered if for any
computational process there is an ANN equivalent. My understanding is
that ANN's do some kind of multivariate statistics?

My reading of the evolution of biological neural nets is that maybe
random neural nets produced computational abilities and the ones that
enhanced the organisms survival were selected. I imagine the first
networks would have been simple reflexes until intermediate nets could
produce useful things like a central pattern generator that could be
modulated by its inputs from external and internal sources.

I have sometimes amused myself with the simple problem of character
recognition using GOFAI and have thought about how any implementation
might be translated into a neural network/s.


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