X-Message-Number: 27520
Date: Tue, 24 Jan 2006 03:44:12 EST
Subject: Uploading technology (1.iv.2) Strategy. 

Here seems to be a low tide in cryonet message number, so I start my 3rd  set 
of uploading related messages. Sad to have lost my main contradictor, T.  
Donaldson... :-(
 Uploading technology (1.iv.2) Strategy.

As Spirit at the  summit of Husband hill in the martian Columbia range, we 

can look back at the  path traveled and see the horizon on 360 . At start, there
is a need for a brain  scanner and a computer software to translate the 

picture into something to be  implemented in an electronics system. The question
what system? Here are four  basic possibilities:
- An FPGA network.
- An asic chip set of neuromorphic  elements.
- A computer or special chips running "compressed neurons" using  variational 
lagrangian dynamics models.
- A computer running a set of black  boxes, one for each brain column.
Here, "computer" stands for general purpose computers, it may be a single  

processor machine, a set of interconnected independent computers or a parallel
system, for example an hypercube. It is assumed that each solution is as good 
as  another on the theoretical ground. In practice, one may be cheaper than 
another  or simpler to get.

A strategy would mix these solutions in one way  or another. For example, the 
FPGAs or neuromorphic chips could work on fast  signals and a general 

computer would process the slower ones. A strategy is a  path defined in taking 
account a number of parameters, for example cost,  security, rapidity of 
implementation, performances, and so on.

Take  for example performance, what is the best solution? It seems to be 

dedicated  chips running variational neurons, may be at the microcolumn 
unit.  What are the drawback ? Here are some: High mathematical knowledge, 

complex  programming, use of special chips. To be short: It is a long and costly

As its often the case, when these initial problems are  solved, the 

variational neurochips cive the best result at the lowest cost  because they 
the hardware parts. So this a good choice for advanced  systems in a large 

At the other side, FPGAs are the  simplest solution using off the shelf 

parts. No special knowledge, no special  chips, products readily available... On
the dark side is the low capacity of  current chips. A roden brain could be 

build this way at some cost. The human  cortex would be very costly with them. A
large brain seems in need of some asic  (specialy built) chips mixing digital 
and analogic processing. The simplest  option here would be a TRAC (Totally 

Reconfigurable Analogic Circuit)-like FPGA.  Put simply, an FPGA whose 
cells are an operational amplifier with  eight selectable configurations. 
Given some money at start, this seems the best  choice, a brain could be built 
ten to fifteen years from now.

If  the money is scarce and the time table short, a solution could be the 

general  purpose computer running a set of black boxes. A small FPGA set would 
n a  single neuronal column at a time and define its output. When that would 
be done,  the column would be simulated on the computer as a black box. What 
must be  simulated down at the synaptic level is then something as 100,000 

neurons.  Assume a single neuron simulated at a given instant on a chip and a 
sharing  factor near 10,000. Ten FPGAs would be sufficient for the project.  
The speed would be may be one tenth of the biological system but that is not a 
 major problem. This simulation is not for the exterior world, it is simply 
for  producing the output model of a black box.

So here could be a  strategy in three steps: A) Create a single column 
neurons on an FPGA set and  run the results as black boxes on general purpose 

computers. B) Create a  neuromorphic chip with TRAC technology and run directly 
electronics brain. C)  optimize the electronics brain with variational methods 
for a mass produced  technology.


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