Recent proposals for neural network models indicate that an array of amplifiers coupled to a lattice of wires with resistive components at the crosspoints can perform calculations using collective properties similar to those observed in biological systems. Such a network can perform both memory and processing functions. The promise of the connection matrix processor lies in its very high density, fault tolerance, and massively parallel operation. This paper describes the operation of a neural network and exploratory fabrication techniques for its implementation.