This chapter concludes our analysis of neural network models with an overview of some hardware implementations proposed in recent years. In the first chapter we discussed how biological organisms process information. We are now interested in finding out how best to process information using electronic devices which in some way emulate the massive parallelism of the biological world. We show that neural networks are an attractive option for engineering applications if the implicit parallelism they offer can be made explicit with appropriate hardware. The important point in any parallel implementation of neural networks is to restrict communication to local data exchanges. The structure of some of those architectures, such as systolic arrays, resembles cellular automata.