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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agi
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