Neurocomputers: a dead end?

The last decade saw a proliferation of research into the design of neurocomputers. Although such work still continues, much of it is never beyond the prototype-machine stage. In this paper, we argue that, on the whole, neurocomputers are no longer viable; like, say, database computers before them, their time has passed before they became a common reality. We consider the implementation of hardware neural networks, from the level of arithmetic to complete individual processors and parallel processors and show that currents trends in computer architecture and implementation are not supportive of a case for custom neurocomputers. We argue that in the future, neural-network processing ought to be mostly restricted to general-purpose processors or to processors that have been designed for other widely-used applications. There are just one or two, rather narrow, exceptions to this.