In a recent interview with Forbes, Canadian computer scientist Yoshua Bengio said that Montreal has emerged as an artificial intelligence powerhouse. In the interview with Peter High, President of Metis Strategy, a business and IT advisory firm, Bengio spoke about his work in the field of AI and how artificial intelligence is the future.
Yoshua Bengio chose Artificial Intelligence as a field of study during the 1980s, in the throes of what some referred to as the AI winter, seeing through a period when money and enthusiasm for artificial intelligence had dried up, High wrote in his introduction, referring to Bengio as one of the foremost thinkers in a field within artificial intelligence known as artificial neural networks and deep learning.
Bengio co-founded Element AI in 2016, which has a stated mission to “turn the world’s leading AI research into transformative business applications.” Element AI aims to foster partnership between the private sector and academia to help push the expansion of AI. His book Deep Learning has been referred to as “the definitive textbook on deep learning” by Elon Musk.
Canada’s ethos of cooperation among elite minds and Montreal’s great universities and companies both from across the border and home grown are the reason Montreal has emerged as a powerhouse in the field of Artificial Intelligence, Bengio feels.
Artificial intelligence is seeing a lot of progress being made with supervised learning and unsupervised learning, both different ways in which a computer can learn. Combining both unsupervised deep learning and reinforcement learning is one of the things that Bengio is currently working on.
In the former method, machines are taught by essentially imitating humans and in unsupervised learning, or what is also known as reinforcement learning, the learner is not merely passively observing the world, or how humans do things, but interacts with the environment and gets feedback.
To reach the more fully realized version of unsupervised learning, it is important to understand the algorithms and the phenomena that is studied, Bengio said. “Humans have a deeper understanding that allows us to survive better than animals and to trick animals into doing things, the same way we are now able to trick neural nets into producing the wrong answers,”
Bengio also spoke about a concept called ‘Disentangled’ which separates the different concepts and different explanations or factors that explain the data, that explain what the agent sees around it, and that explain how the agent patrols the world. Disentangled captures some of the causality that explains what we are seeing and what the computer is seeing.
When asked about his company Element AI, Bengio said it aimed at creating a new ecosystem that includes both research and innovation elements. And to further that goal, it is developing a network of internal and external researchers who conduct AI, machine learning, and deep learning research. This network of researchers within universities and Element AI is free to explore any new idea. They also collaborate with the applied researchers at Element AI so that they can be at the forefront of what is going on in the field for their applications.
The type of response that has come from all sectors has been great, he added. “There is more demand than our current team can handle. A lot of what we are doing right now is recruiting new people. Currently, Element AI is not focused on one particular sector, but is exploring all of the possibilities and starting projects in many areas.”
In spite of being an entrepreneur, Bengio defines himself as an academic. “I am full time at the university. I advise Element AI and other companies. The work that I do with Element AI and companies like Microsoft, for example, is primarily about the long-term aspect. That is my strength and what I can offer. I am not into the nitty-gritty of the commercial things in a company.” He said.
The community aspect is essential in this field, Bengio said. Researchers with our expertise are in such high demand that we have to treat them like gold. We give them the freedom to find their place in the community so that they can be as motivated as possible to contribute and create something with their talent. Also, the Quebec culture is less individualistic and competitive than the culture of much of North America. We are more likely to collaborate and work together to build something, he said.
This is what has led Montreal to be a great destination to be the home of Artificial Intelligence, he feels. “It started with the University of Montreal trusting our vision and allowing us to recruit more professors, in a field that was not yet popular. Then there was a snowball effect. Better researchers brought in better students and better postdocs. This meant we were able to publish better papers, so we attracted more international visibility, which meant we could recruit even better people.”
As large companies like Microsoft, Google, Facebook, and others came to Montreal, it became even more visible to the scientific and investor communities. All of this stimulated entrepreneurship. Investors used to ask entrepreneurs to go to the Valley, but now they are happy with them staying in Canada.
Montreal is not the only place gaining from this, Toronto too is moving on a similarly fast track. There is collaboration between the Vector Institute in Toronto, the MILA in Montreal, and the Alberta Machine Intelligence Institute in Edmonton. The goal is to put Canada on the map scientifically and as the country for AI. Canada may be a small player compared to the U.S. and China, but the critical mass is making a big difference. Silicon Valley is not a big place in terms of the number of people, but it is a center for innovation because of the critical mass effect, Bengio said.
