While simple neural network models had been known since the late 1950s, the field enjoyed a renaissance after the introduction of the backpropagation algorithm, which made it possible to train multi-layered neural networks.24 Such multilayered networks, which have one or more intermediary (“hidden”) layers of neurons between the input and output layers, can learn a much wider range of functions than their simpler predecessors.25
