Classical optical information processing and classical neural networks can be adapted and combined to create optical neural networks which offer significant and fundamental advantages over electronic neural networks in various well-defined cases. A systematic morphology of optical neural networks is presented. Special problems they create are discussed. The state of the art of their implementation is indicated, and some supportable speculations on their future are given. >