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machine brains

Alexander Solntsev solntsev at wt.net
Thu Nov 13 11:57:04 EST 1997


I want to make a couple of points.

First on the subject of neural nets: one should not try to extend the 
capabilities of such computing device to its use as a model of a brain 
simply on the basis both apply similar terminology. For it is exactly that 
which some researchers (and others) appear to be doing. A neural net is an 
interesting computing device that is both inartistically parallel and 
distributed. Its operation is determined by multiple interconnected nodes, 
not unlike that of a brain. Yet it is not the only device that exhibits 
such properties. Actually, any system of multiple cooperating 
interconnected nodes could look like a brain. We should avoid making 
parallels between computing devices and brain unless we can reasonably show 
such devices as explaining more than one aspect of brain’s operation.

Second on the subject of linearity: most of us have became trapped in the 
Von Neumann world of sequential computation with only neural nets seen as 
the way out. Well, thank goodness, there are additional inherently parallel 
and distributed computing devices that could save the day. While there are 
several such devices, I will name the Dataflow computers specifically for I 
find them most usefull. Actually, a neural net could be considered a 
special case of a Dataflow computer. What is a Dataflow computer? It is a 
device composed on multiple cooperating interconnected nodes that represent 
a dataflow graph of the computation they perform. Each node can have 
multiple inputs and outputs connecting it to other nodes. Each node 
represents a computing function based on those inputs, and that function is 
executed when these inputs become available. All nodes exchange information 
using messages that could represent complex data structures.

Just a couple of points (for now as this message is getting too long :-))

Alex

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