Snubbed by Nobel, Japan’s AI pioneers being written out of history

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 center 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?

Shun’ichi Amari

In 1967, Shun’ichi Amari proposed a method of adaptive pattern classification, which enables neural networks to self-adjust the way they categorize 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 of rules for carrying out a particular task) that was mathematically equivalent to Hopfield’s 1982 paper cited by the Nobel on associative memory, which allowed neural networks to recognize patterns despite partial or corrupted inputs.

Kunihiko Fukushima

The North American researchers were working separately from groups in Japan, coming to their conclusions independently.

Later, in 1979, Kunihiko Fukushima created the world’s first multilayer convolutional neural network. This technology has been the backbone of the