Reach 2025: Geoffrey Hinton
By Liz Do
The long game of AI, and a Nobel Prize to show for it
When Geoffrey Hinton first joined CIFAR in 1987, artificial neural networks – computer systems modeled on the human brain and nervous system – were met with doubt that they would ever work. But Hinton saw a different future.
“My main message is, if you want to do important basic research, you should look for something where you think people are doing it wrong.” He says. “You shouldn’t give up on your belief until you understand why you are wrong.”
CIFAR saw a different future as well. With the longstanding belief that advancing fundamental research is key to transformative impact, CIFAR predicted the potential
AI could have on our world. The organization was an early supporter of Hinton’s research and vision.
“I came to Canada in 1987 partly because CIFAR offered me a fellowship,” he says, adding that it enabled him to pursue his important work alongside his teaching at the University of Toronto.
In 1983, CIFAR launched the program AI, Robotics & Society. Later, in 2004, it launched Learning in Machines & Brains, of which Hinton would become a longtime member alongside fellow AI pioneers Yoshua Bengio and Yann LeCun. In 2018, the three of them were awarded the A.M. Turing Award – considered “the Nobel Prize in computing.”
Over the last 20-plus years, the Learning in Machine & Brains program has helped maintain Canada’s leadership in AI, thanks to the leading-edge work of its members and the connective tissue CIFAR provided – and continues to provide – to spark ideas.
Of course, today, neural networks have revolutionized the world, propelling advancements in health care, transportation and communication, to name just a few – their rise is a testament to playing the long game, and the power of fundamental research.
"Fundamental basic research often doesn't have an effect for many, many years," says Hinton. “Politicians are interested in something they can claim credit for, it's difficult for them to claim credit for the outcomes [if research advancements take many years]. But that's why we need to keep encouraging them to fund it.”
For Hinton, his work took decades to overcome skepticism before becoming revolutionary. He was awarded the Nobel Prize in Physics in 2024 alongside physicist John J. Hopfield, a recognition he describes as "quite satisfying.”
"It basically means all those years ago, when we were working on neural nets, and everybody was saying, this is not the right approach, we were right.”
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