Ed:Another reason for optimism is Hintons new work described in papers such
as
"Modeling image patches with a directed hierarchy of Markov random fields"
by Simon Osindero and Geoffrey Hinton and the Google Tech Talk at
http://www.youtube.com/watch?v=AyzOUbkUf3M. Hinton has shown how to
automatically learn hierarchical neural nets that have 2000 hidden nodes in
one layer, 500 in the next, and 1000 in the top layer
Comment from a pal on Hinton who was similarly recommended on slashdot:(I'm
ignorant here):
"I also took a closer look at the Hinton stuff that the slashdot poster made
reference to. To call this DBN stuff highly advanced over Hawkins is
ridiculous. I looked at it already a couple of months ago. It took Hinton
***17-years*** - by his own admission - to figure out how to build a
connectionist net that could reliably identify variations of handwritten
numbers 1-9. And it's gonna take him about a MILLION more years to do
general AI with this approach. Gakk.
To me, the biggest problem with connectionist networks is all they ever
solve are toy problems - and it's 20 years after connectionism become
popular again."
-------------------------------------------
agi
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