Parallel Distributed Processing

In 1986, when the dominant view in artificial intelligence held that intelligence required symbolic rules executed by a central processor, James McClelland and David Rumelhart published two volumes that argued the opposite. The mind’s mechanism, they proposed, is Parallel Distributed Processing: parallel, because many simple units compute simultaneously rather than one processor stepping through instructions; distributed, because knowledge is stored not as symbols at addresses but as patterns spread across connection weights; processing, because cognition is the flow of activation through a network whose weights have been shaped by learning. No central rulebook, no symbol table, no explicit representation of any fact—only units and the strengths between them, and intelligence as what their interaction amounts to when there is enough of it, organized the right way. The claim was made at a moment when the previous generation of neural networks had been declared dead by Minsky and Papert’s Perceptrons (1969), and it required courage to make it. The machines