Geoffrey Hinton: podcast appearances and interviews

Geoffrey Everest Hinton is a British-Canadian computer scientist, cognitive scientist, and cognitive psychologist renowned for his pioneering work on artificial neural networks. His research and contributions have earned him the title of 'the Godfather of AI' and the 2018 Turing Award, which he shared with Yoshua Bengio and Yann LeCun for their work on deep learning. Hinton is also a Nobel Prize laureate in Physics, awarded in 2024 alongside John Hopfield for foundational discoveries related to machine learning with artificial neural networks. He is a University Professor Emeritus at the University of Toronto and has been affiliated with Google Brain, where he worked from 2013 until his departure in May 2023. During his career, Hinton co-authored a highly influential 1986 paper with David Rumelhart and Ronald J. Williams that popularized the backpropagation algorithm for training multi-layer neural networks. His collaborative work on the AlexNet architecture, developed with students Alex Krizhevsky and Ilya Sutskever, marked a milestone in computer vision by significantly advancing image recognition technology during the ImageNet challenge in 2012. Hinton played a foundational role in the deep learning community and co-founded the Vector Institute in Toronto in 2017, serving as its chief scientific advisor. Following his departure from Google, he has openly expressed concerns about the risks posed by artificial intelligence, including potential misuse, technological unemployment, and existential threats from artificial general intelligence. He advocates for cooperative safety guidelines and emphasizes the urgency of research in AI safety to manage systems that could surpass human intelligence.