The Nature of Consciousness

Piero Scaruffi

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These are excerpts and elaborations from my book "The Nature of Consciousness"

Parallel Distributed Computing

One can view a connectionist structure as a new form of computing, a different way of finding a solution to a problem (than searching a solution space). Traditionally, we think of problem solving as an activity in which a set of axioms (of things we know for sure) helps us figure out whether something else is true or false. We derive the "theorem" from the premises through a sequence of logical steps. There is one, well-defined stream of information that flows from the premises to the demonstration of the theorem. This is the approach that mathematicians have refined over the centuries.

On the contrary, a connectionist structure such as our brain works in a non-sequential way: many "nodes" of the network can be triggered at the same time by another node. The result of the “computation” is a product of the parallel processing of many streams of information. There are no axioms and no rules of inference. There are just nodes that exchange messages all the time and adjust their connections depending on the frequency of those messages. No logic whatsoever, no reasoning, no “intelligence” is required. Information does not flow: it gets propagated. Computing (if it can still be called “computing”) occurs everywhere in the network, and it occurs all the time.

The obvious reason to be intrigued by connectionist (or “neural”) computing is that our brain does it, and, if our brain does it, there must be a reason. Another reason is that this form of computing does have advantages over the logical approach. There are many tasks that would be extremely difficult to handle with Logic, but are quite naturally handled by neural computation. For example, what our brain does best: recognizing patterns (whether a face or a sound).

It has been proven that everything that knowledge-based systems do can be done as well with neural networks.

The idea of connectionism, of computing in a network rather than in a formal system, basically  revolutionized the very concept of problem solving. After all, very few real-world problems can be solved in the vacuum of pure logic. From weather forecast to finance, most situations involve countless factors that interact with each other at the same time. One can predict the future only if one knows all the possible interactions. 




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