Steve, here's some input. 

Colin stated: 
"Because
 it's not using neurons it won't automatically mimic brains in 
structure. I have no idea what a brain will look like. Physically its a 
crystalline rock. No actual material growth."

I think Colin is building a generic platform for generative, emergent 
intelligence, aka a system of systems. 

I agree with his approach to rather soft code than hard code future generations 
of AI. I also agree with his non-human matter (non cyborg) approach.  

Colin, if we could agree on my research objectives, which may differ slightly 
from yours, I'd be happy to assist you. 

I think I have the generative algorithmic design you are looking for, but it is 
not fully-matured yet. It would unify rather easily with your approach. 

It probably is useful as it is, but I have lots more maturation work to do on 
it and no "manual" has been written. You'll have to put up with me for a while 
as it is not as self explanatory as one might imagine. The science is solid 
though and would probably withstand an external, critical review. Some parts of 
it already has.          

Rob

Date: Wed, 6 May 2015 01:07:18 -0700
Subject: [agi] Restating Colin's Hypothesis
From: [email protected]
To: [email protected]

Colin,

I'm going to take a shot at restating your hypothesis in a more 
physics-tractable form. The remainder of this posting are what I think you are 
trying to say:

Colin in effect says that the computational unit is NOT the synapse, but rather 
is the ion channel. These are MUCH more numerous than synapses. While the 
voltages seen in extracellular recordings are quite low, the field GRADIENT 
near an active ion channel is HIGH - enough to have major effects on 
nearby/contacting structures. Brains are a lot like a bowl of spaghetti, and 
every place the "noodles" touch becomes a point of high field interaction. We 
don't yet know what those interactions do, but we DO know that there are a lot 
of synapses that interconnect contacting neurons, so at minimum such points of 
contact are probably capable of spawning synapses, if the "data" indicates a 
synapse would be useful.

Then there is the far-field effects from neurons that are near but NOT in 
contact. The activity (or lack thereof) should be an important parameter to use 
in development, because it is an indicator of just how successful learning has 
been throughout the entire system. Where learning has been UNsuccessful, 
neurons should probably be more plastic in their functionality.

Ion channels are capable of fairly complex computation, including memory (from 
ion accumulation and physical alterations), nonlinearities, etc. It has 
previously been presumed that ion channels are just "pumps" that keep neurons 
doing what neurons do, but the prospect for ion channel computation can NOT be 
ignored.

When a neuron becomes active, its many ion channels radiates complex patterns 
of field-gradients, which could affect the operation of other nearby neurons, 
especially if the ion channels in the other neuron were to align themselves 
with a radiating neuron.

While I now grok the importance of field gradients generated by ion channels, I 
still don't see how/why this should affect consciousness any more than it 
affects the many other functions of a neural systems. I am not yet even 
convinced that consciousness exists - except in our minds as a simplistic model 
for whatever happens behind our eyeballs. How do you link consciousness (over 
other neural functions) with EM fields?

C'mon; help me put Colin's hypothesis into a solid physics form.

Steve









  
    
      
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