Geoffrey Hinton
(Photos by Johnny Guatto)
Artificial intelligence deep-learning pioneer Geoffrey Hinton has been honoured with the prestigious Royal Medal from the Royal Society, the U.K.’s national academy of sciences.
Hinton is a University Professor Emeritus in the Department of Computer Science, Chief Scientific Adviser at the Vector Institute, and a Vice President and Engineering Fellow at Google.
Royal Medals have been awarded annually since 1826 for advancements in the physical and biological sciences. A third medal — for applied sciences — has been awarded since 1965. According to the Royal Society, Hinton is being honoured for “pioneering work on algorithms that learn distributed representations in artificial neural networks and their application to speech and vision, leading to a transformation of the international information technology industry.”
“It is a great honour to receive the Royal Medal — a medal previously awarded to intellectual giants like Darwin, Faraday, Boole and G.I. Taylor,” says Hinton. “But unlike them, my success was the result of recruiting and nurturing an extraordinarily talented set of graduate students and postdocs who were responsible for many of the breakthroughs in deep learning that revolutionized artificial intelligence over the last 15 years.”
Hinton adds the medal to a long list of previous honours including the Association for Computing Machinery’s A. M. Turing Award, widely considered the Nobel Prize of computing. He has been a Fellow of the Royal Society since 1998 and a Fellow of the Royal Society of Canada since 1996.
“The Royal Medal is one of the most significant acknowledgements of an individual’s research and career,” says Melanie Woodin, dean of the Faculty of Arts & Science. “And Professor Hinton is truly deserving of the distinction — for his foundational research and for the exceptional contribution he’s made toward shaping the modern world and the future. I am thrilled to congratulate him on this award.”
“I want to congratulate Geoff on this spectacular achievement,” adds Eyal de Lara, chair of the Department of Computer Science. “We are very proud of the seminal contributions he has made to the field of computer science, which are fundamentally reshaping our discipline and impacting society at large.”
Deep learning is a form of artificial intelligence (AI) machine learning that relies on a neural network modelled on the network of neurons in the human brain. In 1986, Hinton and his collaborators developed the breakthrough approach — based on the backpropagation algorithm, a central mechanism by which artificial neural networks learn — that would realize the promise of neural networks and form the current foundation of that technology.
Hinton and his colleagues in Toronto built on that initial work with a number of critical developments that enhanced the potential of AI and helped usher in today’s revolution in deep learning with applications in speech and image recognition, self-driving vehicles, automated diagnosis of images and language, and more.
Says Hinton, “I believe that the spectacular recent progress in large language models, image generation and protein structure prediction is evidence that the deep learning revolution has only just started.”
Original story by Chris Sasaki for Arts & Science News