Geoffrey Everest Hinton (b. 1947) is a British-Canadian computer scientist and cognitive psychologist widely regarded as one of the founding figures of modern artificial intelligence. His decades of research on artificial neural networks earned him the popular nickname "the Godfather of AI" and helped bring about the deep-learning revolution, for which he received both the 2018 Turing Award and the 2024 Nobel Prize in Physics.[1]
Early life and education
Hinton was born on 6 December 1947 in Wimbledon, England, into a family with a notable scientific lineage; he is a great-great-grandson of the mathematician and logician George Boole.[1] He studied experimental psychology at King's College, Cambridge, and later earned a PhD in artificial intelligence from the University of Edinburgh in 1978.[2]
Career
After early academic appointments in the United Kingdom and the United States, Hinton joined the faculty of the University of Toronto, where he became a professor in the department of computer science and a leading figure in machine-learning research.[1] From 2013 he also worked at Google, which acquired his neural-network startup, and he became an engineering fellow at Google Brain. He is additionally a founding member of the Vector Institute for Artificial Intelligence in Toronto.[2]
Deep learning and neural networks
Hinton's work helped sustain and revive interest in artificial neural networks during periods when the approach was out of scientific favour. In 1986 he co-authored an influential paper popularising the backpropagation algorithm for training multi-layer networks.[1] In 2012, working with graduate students Alex Krizhevsky and Ilya Sutskever, he developed a deep convolutional neural network, later known as AlexNet, that dramatically outperformed rival methods in the ImageNet image-recognition competition. The result is widely credited with catalysing the modern surge in deep learning.[1]
Recognition and later views
For these contributions Hinton shared the 2018 Turing Award, often called the "Nobel Prize of computing," with Yoshua Bengio and Yann LeCun.[1] In 2024 he shared the Nobel Prize in Physics with John Hopfield for foundational discoveries that enable machine learning with artificial neural networks.[3] In 2023 he stepped back from his role at Google so that he could speak more freely about the potential risks of advanced artificial intelligence, becoming a prominent public voice urging caution about the technology he helped create.[1]
