Yoshua Bengio is a grandmaster of modern artificial intelligence. Alongside Geoff Hinton and Yan LeCun, Bengio is famous for championing a technique known as deep learning that in recent years has gone from an academic curiosity to one of the most powerful technologies on the planet. Deep learning involves feeding data to large, crudely-simulated neural networks, and it has proven incredibly powerful and effective for all sorts of practical tasks, from voice recognition and image classification to controlling self-driving cars and automating business decisions. Bengio has resisted the lure of any big tech company. While Hinton and LeCun joined Google and Facebook respectively, he remains a full-time professor at the University of Montreal.
The winners of the 2018 Turing Award have been announced. Geoffrey Hinton, Yann LeCun, and Yoshua Bengio -- sometimes referred to as the "godfathers of artificial intelligence" -- have won the 2018 Turing Award for their work on neural networks. The three artificial intelligence pioneers' work basically laid the foundation for modern AI technologies. In the 1980s and early 1990s, artificial intelligence experienced a renewed popularity within the scientific community. However, by the mid-90s, scientists had failed to make any major advancements in AI, making it harder to secure funding or publish research.
When Geoffrey Hinton started doing graduate student work on artificial intelligence at the University of Edinburgh in 1972, the idea that it could be achieved using neural networks that mimicked the human brain was in disrepute. Computer scientists Marvin Minsky and Seymour Papert had published a book in 1969 on Perceptrons, an early attempt at building a neural net, and it left people in the field with the impression that such devices were nonsense. "It didn't actually say that, but that's how the community interpreted the book," says Hinton who, along with Yoshua Bengio and Yann LeCun, will receive the 2018 ACM A.M. Turing award for their work that led deep neural networks to become an important component of today's computing. "People thought I was just completely crazy to be working on neural nets." Even in the 1980s, when Bengio and LeCun entered graduate school, neural nets were not seen as promising.
Last week, for the first time ever, RE•WORK brought together the'Godfathers of AI' to appear not only at the same event, but on a joint panel discussion. At the Deep Learning Summit in Montreal last week, we saw Yoshua Bengio, Yann LeCunand Geoffrey Hinton come together to share their most cutting edge research progressions as well as discussing the landscape of AI and the deep learning ecosystem in Canada. Joelle Pineau from McGill University who was moderating the discussion began by asking each pioneer to introduce their neighbour, which immediately generated a laugh from the packed auditorium. Yoshua kicked off by saying'here's Yann, I met him doing my masters and he was doing his post doc with Geoff and later Yann invited me to come and work with him and start working in convolutional neural networks, and it's still the hot thing today!' Yann went on to introduce Geoffrey and said'I'll be historical as well, when I was an undergrad I studied neural nets and realised there was no research published in the 70s. I saw a paper entitled Optimal Perceptual Inference and Geoff was one of the three authors.
The breakthrough came in 2006: Hinton led a published paper called A Fast Learning Algorithm for Deep Belief Nets, which first proposed the method of greedy layer-wise training for deep neural networks. In an competition run by ImageNet in 2012, Hinton's UofT team used convolutional neural networks (CNN) for image recognition application. Given the large pool of image datasets and the computation power of GPU processors, the team was on the right track, and their results redefined the field of computer vision. Two of Hinton's earliest correspondents were Yoshua Bengio from the University of Montreal and his own postdoc student Yan Lecun, who joined Hinton's UofT lab in 1987 and now leads AI research at Facebook. The accomplished trio is sometimes jokingly referred to as the "Canadian Mafia" of deep learning.