Mark I Perceptron

The Mark I Perceptron was a pioneering supervised image classification learning system developed by Frank Rosenblatt in 1958.

It differs from the Perceptron which is a software architecture proposed in 1943 by Warren McCulloch and Walter Pitts,[1] which was also employed in Mark I, and enhancements of which have continued to be an integral part of cutting edge AI technologies like the Transformer.

In his 1957 proposal for funding for development of the "Cornell Photoperceptron", Rosenblatt claimed:[4]"Devices of this sort are expected ultimately to be capable of concept formation, language translation, collation of military intelligence, and the solution of problems through inductive logic.

[3] Another experiment distinguished between a square and a diamond for which 100% accuracy was achieved with only 60 training images, with a Perceptron having 1,000 neurons in a single layer.

[3] For distinguishing between the letters E and F, a more challenging problem due to their similarity, the same 1,000 neuron perceptron achieved an accuracy of more than 80% with 60 training images.