Localist representations
	• The simplest way to represent things with neural networks is to dedicate one neuron to each thing. – Easy to understand. – Easy to code by hand • Often used to represent inputs to a net – Easy to learn • This is what mixture models do. • Each cluster corresponds to one neuron – Easy to associate with other representations or responses. • But localist models are very inefficient whenever the data has componential structure.