Sorry, the correct link is:
http://en.wikipedia.org/wiki/Electromagnetic_theories_of_consciousness

--- On Fri, 12/19/08, Terren Suydam <mmmmba...@yahoo.com> wrote:
Hi Colin,

Looking at 
http://en.wikipedia.org/wiki/Electromagnetic_theories_of_consciousness, does 
your position vary substantially from what is written there?

Thanks,
Terren

--- On Fri, 12/19/08, Colin Hales <c.ha...@pgrad.unimelb.edu.au> wrote:
From: Colin Hales <c.ha...@pgrad.unimelb.edu.au>
Subject: Re: [agi] Building a machine that can learn from experience
To: agi@v2.listbox.com
Date: Friday, December 19, 2008, 1:09 AM




  
YKY (Yan King Yin) wrote:

  
    DARPA buys G.Tononi for 4.9 $Million! .... For what amounts to little more
than vague hopes that any of us here could have dreamed up. Here I am, up to
my armpits in an actual working proposition with a real science basis...
scrounging for pennies. hmmm...maybe if I sidle up and adopt an aging Nobel
prizewinner...maybe that'll do it.

nah. too cynical for the festive season. There's always 2009! You never
know....
    
  
  You talked about building your 'chips'.  Just curious what are you
working on?  Is it hardware-related?

YKY


  

Hi,

I think I covered this in a post a while back but FYI... I am a little
'left-field' in the AGI circuit in that my approach involves literal
replication of the electromagnetic field structure of brain material.
This is in contrast to a computational model of the electromagnetic
field structure. The process involves a completely new chip design
which looks nothing like what we're used to. I have a crucial
experiment to run over the next 2 years. The results should be (I hope)
the basic parameters for early miniaturised prototype. 



The part of my idea that freaks everyone out is that there is no
programming involved. You can adjust the firmware settings for certain
intrinsic properties of the dynamics of the EM fields. But none of
these things correspond in any direct way to 'knowledge' or
intelligence. The chips (will) do what brain material does, but without
all the bio-overheads.



The thing that caught my eye in the thread subject "Building a machine
that can learn from experience"... is that if you asked Tononi or
anyone else exactly where the 'experience' is, they won't be able to
tell you. The EM field approach deals with this very question first.
The net EM field structure expressed in space literally is the
experiences. All learning is grounded in it. (Not input/output signals)



I wonder how anyone can claim that a "machine that learns from
experience" when you haven't really got a cogent,  physical and
biologically plausible, neuroscience informed  view of what
'experience' actually is. But there you go... guys like Tononi get
listened to. And good luck to them!



So I guess my approach is likely to remain a bit of an oddity here
until I get my results into the literature. The machines I plan to
build will be very small and act like biology... I call them
"artificial fauna". My fave is the 'cane toad killer' that gets its
kicks by killing nothing but cane toads (these are a major eco-disaster
in northern australia). They can't reproduce and their learning
capability (used to create them) is switched off. It's a bit like the
twenty-something neural dieback in humans... after that you're set in
your ways.



Initially I want to build something 'ant-like' to enter into robo-cup
as a proof of concept.... anyway that's the plan. 



So the basics are: all hardware. No programming. The chips don't exist
yet, only their design concept (in a provisional patent application
just now). 



I think you get the idea. Thanks for your interest.



cheers

colin







  
    
      
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