The announcement of the artificial intelligence researchers John Hopfield and Geoffrey Hinton as this year’s Nobel laureates in physics spurred celebration and consternation over the status of AI in science and society. In Japan, however, another feeling dominates: frustration. “Japanese researchers should also have won,” an editorial in the Asahi Shimbun newspaper proclaimed. Congratulating Hopfield and Hinton, the Japanese Neural Network Society added pointedly: “We must not forget the role played by pioneer Japanese researchers in erecting the foundations of neural network research.” Neural networks are at the centre of contemporary AI. They are models for machines to learn independently through structures that, if often only loosely, are inspired by the human brain. So who are these pioneering Japanese AI researchers? In 1967, Shun’ichi Amari proposed a method of adaptive pattern classification, which enables neural networks to self-adjust the way they categorise patterns, through exposure to repeated training examples. Amari’s research anticipated a similar method known as “backpropagation,” one of Hinton’s key contributions to the field. In 1972, Amari outlined a learning algorithm (a set …