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The University of Toronto’s Geoffrey Hinton has been honoured with the Royal Society’s prestigious Royal Medal for his pioneering work in deep learning – a field of artificial intelligence that mimics the way humans acquire certain types of knowledge.

The U.K.’s national academy of sciences said it is recognizing Hinton, a Emeritus in the department of computer science in the Faculty of Arts & Science, 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’s the latest in a long list of accolades for Hinton, who is also chief scientific adviser at the Vector Institute for Artificial Intelligence and a vice-president and engineering fellow at Google. Others include the Association for Computing Machinery’s A. M. Turing Award, widely considered the Nobel Prize of computing.

“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,” Hinton says.

“But unlike them, my success was the result of recruiting and nurturing an extraordinarily talented set of graduate students and post-docs who were responsible for many of the breakthroughs in deep learning that revolutionized artificial intelligence over the last 15 years.”

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.

Previous U of T winners of the Royal Medal include Anthony Pawson and Nobel Prize-winner John Polanyi.

Hinton, meanwhile, 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 type of 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.

“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,” Hinton says.