🚀 go-pugleaf

In article <60f4dc$d4j@andromeda.rutgers.edu>
           ohaneef@andromeda.rutgers.edu "Omar Haneef" writes:


[Your post never made it to my server.  Copied it from DejaNews]

> Louis Savain (savainl@earthlink.net) wrote:
> : In article <60bg0b$cbp$1@now.cirl.uoregon.edu>,
> : deej@now.cirl.uoregon.edu (David Joslin) wrote:
> 
> : >[...]
> : >And now you are back with *another* AI revolution.  Two AI
> : >revolutions in just over two years.  Pretty damned impressive.
> 
> :   No need to get excited, David.  We are not scientists, just computer
> : technologists with some ideas.  Two years ago we got overly enthused
> : by some results we obtained using Boolean networks.  We were wrong.
> : But we continued to work on our ideas and this time, we think we got
> : some important stuff.  You just be patient, amigo.  And, by the way,
> : this is not our revolution.  The temporal neuron revolution is coming
> : from neurophysiology and computational neuroscience.  Do a little
> : search on the web for these names:  Henry Markram, Terrence Sejnowski,
> : Cristof Koch and others.  You AI types should keep up with the
> : hard-science advances in neurophysiology.  Those folks are much closer
> : to the truth than most of you.  Ciao.
> 
> You forgot to mention Sutton and Barto.

  S & B have indeed done excellent work.  More recently however, the
more interesting news are coming from neurophysiology and those in the
field of computational neuroscience (has little to do with traditional
ANNs) who are attempting to model the newest findings.


> And I do hope that this is not yet-another-recurrent-net spinoff.

  Not at all.  There is a recent discovery (little known in AI
circles) by Henry Markram that strongly suggests that a "differential
Hebbian" (A term I borrowed from Dr. Leslie Smith of the University of
Stirling who may have borrowed it from A. H. Klopf) form of learning
is taking place at the single neuron level.  In our humble opinion,
this is a truly revolutionary finding.  What Markram and his team at
the Weizmann institute for Science have found (see January 10, 1997
issue of Science) is that the precise order in which a spike arrives
at a synapse and a retrograde or antidromic spike is generated by a
target neuron, has a dramatic effect on the strengthening or weakening
of the synapse.  If the synaptic potential arrives first (within 10
millisecond), the synapse is strengthened otherwise it is weakened.
Our own model, which is based on causality, predicted as much.  What
neurophysiologists (and everyone else for that matter) are in the dark
about is the precise input conditions that lead to the firing of a
neuron.  There is nothing wishy-washy about them.  The temporal or
causal nature of these conditions is extremely important to learning
and is directly related to Markram's discovery.  We think we know what
these conditions are, as you will all soon be able to judge for
yourselves.

> But here is a question: if it does
> causal relations, it won't be able to do logical form, right? I mean,
> if you represent solely temporally distinct events, what do you do 
> about representing simultaneous properties?

  First of all, let me say that we try to refrain from using the word
"representation".  Representation usually connotes "symbol
manipulation" and we think that the fundamental underpinnings of
intelligence and learning have little to do with symbols.  To answer
your question, note that a network is a distributed, parallel system
and synchronous events are automatically taken care of by the
parallelism.  In our model, simultaneity is handled *laterally* and
sequentiality (deep causality) is extracted *longitudinally*.  As far
as logic is concerned, it is our firm conviction that it is not a
fundamental prerequisite to learning.  It is learned just like
everything else.  IOW, logic emerges.

> (I have the greatest respect
> for Koch and Sejnowski, of course, but I won't take their word -- if it
> exists -- for it).

  What Sejnowski and Koch have brought to the surface more than anyone
else, IMO, is the role that precise signal timing plays in the
operation of the brain.

Regards,

Louis Savain

President, Marengo Media, Inc.


Here are some relevant sites:

http://www.hhmi.org/communic/bulletin/oct95/crack.htm
http://sanjuan.cs.wwu.edu/mobus/
http://www.cs.stir.ac.uk/~lss/AntiDromic/AntiDromic.html
http://www.sciam.com/explorations/020397brain/020397explorations.html
http://www.sat.t.u-tokyo.ac.jp/javier/wsc1.html
http://www.klab.caltech.edu/
http://www.cnl.salk.edu/CNL/