Rosenblatt has a deck of flash cards, each of which has a colored square on it, either on the left side of the card or on the right. He pulls one card out of the deck and places it in front of the perceptron’s camera. The perceptron takes it in as a black-and-white, 20-by-20-pixel image, and each of those four hundred pixels is turned into a binary number: 0 or 1, dark or light. The four hundred numbers, in turn, are fed into a rudimentary neural network, the kind that McCulloch and Pitts had imagined in the early 1940s. Each of these binary pixel values is multiplied by an individual negative or positive “weight,” and then they are all added together. If the total is negative, it will output a −1 (meaning the square is on the left), and if it’s positive, it will output a 1 (meaning the square is on the right).

Brian Christian, The Alignment Problem, loc. 26124