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A main motivation behind neural networks is the fact that symbolic rules do not reflect reasoning processes performed by humans.

Biological neural systems can capture highly parallel computations based on representations that are distributed over many neurons.

They learn and generalize from training data; no need for programming it all...

They are very noise tolerant – better resistance than symbolic systems.