Deep Learning Pioneer Geoffrey Hinton Receives Prestigious Royal Medal from the Royal Society

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

The UK’s National Academy of Sciences said it recognizes Hinton, Emeritus University Professor in the Department of Computing at the Faculty of Arts and Science, for “pioneering work on algorithms that learn from 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 science adviser at the Vector Institute for Artificial Intelligence and vice president and engineer at Google. Others include the AM Turing Award from the Association for Computing Machinery, widely regarded as the Nobel Prize in computing.

“It is a great honor to receive the Royal Medal – a medal previously awarded to such intellectual giants as Darwin, Faraday, Boole and GI Taylor,” Hinton said.

“But unlike them, my success is the result of recruiting and nurturing an extraordinarily talented group of graduate students and post-docs who have been responsible for many of the learning breakthroughs in depth that have revolutionized artificial intelligence over the past 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.

Past recipients of the U of T Royal Medal include Anthony Pawson and Nobel Prize 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 important recognitions of an individual’s research and career,” says Melanie Woodin, Dean of the Faculty of Arts and Sciences. “And Professor Hinton truly deserves this honor – for his fundamental research and for the outstanding contribution he has made to shaping the modern world and the future. I am delighted to congratulate him on this award.

“I would like to congratulate Geoff on this spectacular achievement,” adds Lara’s Eyal, director of the IT department. “We are very proud of the seminal contributions he has made to the field of computing, which are fundamentally reshaping our discipline and impacting society as a whole.”

Deep learning is a type of machine learning that relies on a neural network modeled after the neural network of the human brain. In 1986, Hinton and his collaborators developed the revolutionary 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 basis of this technology. .

Hinton and his colleagues in Toronto built on this initial work with a number of critical developments that enhanced the potential of AI and helped usher in the current deep learning revolution with applications in pattern recognition. speech and images, autonomous vehicles, automated diagnosis of images and language, and more.

“I believe recent dramatic advances in big language models, image generation, and protein structure prediction are proof that the deep learning revolution is just beginning,” says Hinton.

Comments are closed.