|Mark I Perceptron displayed at the Smithsonian museum|
Perceptron as supposed to be a machine, but it began as an algorithm and is still used in that context. It is a piece of tech history from the early days of artificial intelligence (AI).
The perceptron algorithm was invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt, funded by the United States Office of Naval Research.
Its first implementation was in software for the IBM 704, and it was subsequently implemented in some custom-built hardware known as the "Mark 1 perceptron." It was one of the first artificial neural networks to be produced.
The Mark 1 perceptron was designed for image recognition and used 400 photocells connected to the "neurons." Still to this day, perceptrons are used generically as a basic neural network.
The algorithm's use was not without controversy. At a 1958 US Navy press conference, some of Rosenblatt's comments opened a controversy among the fledgling AI community. The New York Times picked up on this and reported that the perceptron would be "the embryo of an electronic computer that [the Navy] expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence."
This fear about "machine learning" was, and still is, feared by many people. Giving computers the ability to learn on their own without being explicitly programmed strikes some people as technology gone wild.
AI has met with ethical and technical hurdles. Steven Pinker has said that trying to duplicate the way the human brain works shows that for computers "Hard is easy. Easy is hard." Computers can do very complex calculations. They can calculate the depth of the ocean and project the outcomes of complicated experiments. But they have trouble answering a question such as "Can a shark play baseball?" which even a child could answer.