Design principles for an intelligent machine

This paper discusses the role of prediction as the key process underlying the function of an intelligent machine. A model of a "neuron" is presented which exhibits properties of memory and learning. The formalism of the calculus of probability allows us to interpret the behavior of a neuron in such a way as to justify how a network of such elements can be organized so that it can learn to predict.