Situating Artificial Neural Networks

The role of hardware implementations

One obvious attraction of artificial neural networks is their potential technological applications, for which they serve as early feasibility studies. This is an issue that is better left at this stage to popular journalism. See e.g., [2,3,4]. Inasmuch as an individual neuron is interpreted as a computing device, artificial neural networks may provide answers to some of the outstanding questions of parallel computing – the coherent coordination of a multitude of processors. This motivation will also not be discussed here. Instead, such networks will be described below for several other reasons.

• To provide a physical environment in which any set of simplifying assumptions about neural networks can be literally implemented. This possibility was raised in Section 1.1.3 in the context of the methodological discussion about verifiabilty of the theoretical results. Some of it can, of course, be investigated by computer simulations.

• In addition, there are various uncontrollable variables which are naturally present in a real system, such as various random delays, inhomogeneities of components, etc. In this sense such real networks are one step removed from computer simulation.

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