While McCulloch and Pitts had developed models of the neuron, networks of these artificial neurons could not learn. In the context of biological neurons, Hebb had proposed a mechanism for learning that is often succinctly, but somewhat erroneously, put as “Neurons that fire together wire together.” More precisely, according to this way of thinking, our brains learn because connections between neurons strengthen when one neuron’s output is consistently involved in the firing of another, and they weaken when this is not so. The process is called Hebbian learning. It was Rosenblatt who took the work of these pioneers and synthesized it into a new idea: artificial neurons that reconfigure as they learn, embodying information in the strengths of their connections. — *location: 372* ^ref-4234 ---