The study of human memory was greatly changed in 1943, When Warren McCulloch and Walter pitts wrote a paper on the how neuron might work. six years later, D.O Hebb described the strengthening of the neural connections that occurred each time they were used.
In the early days of artificial intelligence research Frank Rosenblatt a computer scientist at central Cornell Aeronautical Laboratory in New York-was studying how the eyes of fly work. Rosenblatt observed that when a fly perceives danger,its reaction occurs danger,its reaction occurs faster than the information can be processed by its brain .He then produced the perceptron, the first computer to learn new skills using a neural network mimicking human thought process. The preceptron had a layer of interconnected input and output nodes. Each connection is "weighted" to make it more or less likely to stimulate another node. Rosenblatt's mark 1 perceptron followed in 1960, the first machine to "learn" to recognize and identify optical patterns.
Practically grew with the advent of "backprop" perceptons, which include "hidden"layers that greatly increase the complexity. John Hopfield then introduced his model of patterns so that when the presented with even partial information , it can retrieve the full-pattern rather like humans
Today, neural network are the foundation for the optical recognition employed in scanners, weather forecasts, bomb detectors, and even financial market predictions.
