Japanese researchers made fundamental contributions to artificial neural networks that helped establish modern AI, yet their work has been largely overlooked in Western narratives. According to an article by Hansun Hsiung published by The Conversation, scientists like Shun’ichi Amari and Kunihiko Fukushima developed crucial early innovations in machine learning during the 1960s and 70s.
Fukushima created the first multilayer convolutional neural network in 1979, which became essential for today’s deep learning systems, while Amari proposed adaptive pattern classification methods that preceded similar Nobel-winning work by Geoffrey Hinton. The Japanese approach focused more on understanding biological processes and human cognition, differing significantly from Western researchers who prioritized statistical methods and large datasets.