INDUSTRY INSIDER SERIES VOLUME 2: JAMES BERGSTRA, JENNIFER NGUYEN, MATT FOWLER
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James Bergstra is co-founder and head of AI and research at Kindred AI, focused on developing new learning techniques for robots.
Matt Fowler recently transitioned to a new role as VP, enterprise Machine Learning to develop and lead a new team within Enterprise Data and Analytics to identify new ML opportunities in the business.
Jennifer Nguyen is the Lead Data Scientist at Sun Life Financial’s Analytics Centre of Excellence and partners with the University of Waterloo to support young females pursuing careers in STEM.
HOW DID YOU START A CAREER IN BIG DATA / ARTIFICIAL INTELLIGENCE?
JB: I’ve always been interested in how people think, how they reason, how memories work, how they’re formed, how people can be creative, and how to avoid repetitive work. After bouncing off of philosophy, and cognitive science I landed in the computer science department at the University of Toronto, taking a course on neural networks from Geoff Hinton, who was already on his way to becoming a legendary scientist of our generation, although I just thought neural networks sounded cool. That’s when I started to seriously think about graduate school. I went to the University of Montreal to study machine learning with Yoshua Bengio, and after a PhD, 2 postdocs, and 5 years of entrepreneurship here in Toronto here I am.
MF: As the saying goes – by accident! My last role at TD was to lead a global team of 300 focused on regulatory, control, vendor and data services for TD Securities. When TD acquired leading artificial intelligence company Layer 6, I was tasked with helping to integrate their capabilities into the bank. It’s been an exciting journey—we’re using data and AI to help create new personalized banking experiences that we wouldn’t have even imagined a few years ago.
JN: I became interested in the field during second year at the University of Waterloo. I was majoring in statistics and up until then, everything I learned was around classical statistical concepts, e.g., probability distributions, hypothesis testing, experimental design, etc., until I took a course in linear regression. That was when it dawned on me that we could learn to predict future events by learning from the past. As a kid, I loved magic and this was the closest thing to magic that I knew of—so naturally I wanted to learn how to do it myself. I went on to complete a Master’s in Machine Learning and Computational Statistics at University College London in England, which was useful and timely because when I returned to Canada, the field was starting to gain momentum.
PRACTICALLY EVERY INDUSTRY IS, OR WILL BE, IMPACTED BY AI. WHAT IS ONE OF THE MORE INTERESTING APPLICATIONS OF AI HAPPENING IN YOUR INDUSTRY/LINE OF WORK?
JB: Kindred is developing AI for robots that operate in the retail supply chain. The shift to online shopping has put a lot of pressure on the old ways of moving goods from distributor to household, and the viability of that model depends on technology innovations in the handling and conveyance of goods. It used to be that distributors could work mainly in terms of large rectangular boxes in standard sizes, but now distributors are having to pick individual items (in whatever retail packaging they have) from their warehouses and pack them for shipping directly to customers alongside whatever other random items a person ordered. Innovations in deep learning and deep reinforcement learning are enabling autonomous vehicles and piece-picking robots to interact intelligently with a wide enough variety of situations to be production ready.
MF:In banking, I think one of the most interesting applications for AI is around creating a highly personalized customer experience. I see a future where AI helps us better understand our customers’ needs and proactively provide the right service at the right time and in the right channel.
JN: As an insurance and investment company, Sun Life’s mission is to take care of our client’s physical and financial health. We do this through many ways, one of which is Ella, our virtual advisor. Ella is built on mass amounts of data that we’ve amassed over the years, but it’s only recently did we leverage that data to create Ella. Through data mining, Ella is able to recommend cost-effective health care providers to maximize clients’ benefits.
ON THE OTHER HAND, AI ALSO HAS THE CAPACITY TO COMPLETELY DISRUPT ASPECTS OF EVERYDAY LIFE. WHICH APPLICATION(S) OF AI DO YOU THINK WILL BE MOST DISRUPTIVE TO THE AVERAGE PERSON?
JB: I’m looking forward to the self-driving car, especially in terms of the self-driving taxi. I think about the amount of urban real estate that’s dedicated to parked empty cars, and the limited way that bus routes connect with the highest-density rail-based systems, and when I look back at photos of cities from the 19th century with horses and markets, and it all looks kind of impossible to imagine living there but also kind of charming – I’m hopeful that public transit with autonomous electric cars might make a big lifestyle difference and enable a future where cities are nicer places to live.
MF: Well, we like to look at the positive aspects of change—and how a more seamless banking experience could help empower people to reach their financial goals more easily, and ultimately help them live better lives.
JN: Jack Ma, founder of Alibaba, said at the 2018 World Economic Forum on the future of education that we should focus on teaching future generations soft skills, like emotional intelligence and teamwork, and I agree. AI has the potential to replace humans in roles where the duties are repetitive and highly structured, e.g., customer care representatives, sanitation engineers—even some aspects of a data scientist’s responsibilities. To remain competitive and future-proof, I believe we should build on our strengths as humans and let the machines do what they do best. That is, going back to first principles of cooperation, communication and curiosity.
CAN YOU GIVE US AN EXAMPLE OF AI “HYPE” THAT YOU THINK IS OVERBLOWN IN THE MEDIA?
JB: Job losses. A headline like “is AI going to take your job??” is obviously going to get a certain amount of hype-based attention, but folks in governments in countries like Canada, the US and China are obviously watching this very carefully and not seeing a correlation between AI and job losses right now. AI innovations are interacting with different industries in different ways, and it seems to be on one hand a complicated story to say exactly what the impact of changes in AI is already, much less what it might be in the future. So far, the government of Canada is investing strongly in AI research and commercialization because I presume they are expecting to see a positive overall effect.
MF: I think we should talk more about the great work that’s happening across industries to use AI for social good. For example, Layer 6, TD’s artificial intelligence team, is supporting research at the University of Toronto to help develop advanced machine learning models to improve the health outcomes of people living with diabetes in Canada. As part of TD’s acquisition of Layer 6, both organizations pledged to dedicate time and talent to put the power of AI to work for social good.
FINAL THOUGHTS: WHAT IS CANADA’S COMPETITIVE ADVANTAGE IN THE GLOBAL AI RACE?
JB: Canada has been a leader in AI research for decades. Our universities and private research investments have allocated their resources well in terms of AI, and Canada has a disproportionate number of world-leading research labs and graduates. The AI race is heating up, and the pool of talent that trained in Canada has suffered enormously from brain-drain, but even those who left have a professional network here in Canada. The breadth and depth of engineering and scientific experience is our competitive advantage.
The challenge for Canada is to leverage that domestic and international talent pool to improve the quality of life in Canada – to capture the value of innovative AI, both directly, as improved products and services that Canadians (as well as international customers) can enjoy, and indirectly, as successful companies and professionals pay tax that goes to maintain and improve health care, education, infrastructure, and so on.
MF: Canada has some of the best AI talent and an amazing ecosystem to support innovation. World-class research institutions like the Vector Institute for Artificial Intelligence, of which TD is a founding member, helps attract students and researchers to Canada. This year, two Canadians were among the winners of the Turing Award—the world’s top award in computer science—for their pivotal contributions to the artificial intelligence community. If that doesn’t prove Canada is a leader in AI, I don’t know what does!
JN: Canada has a few things going for it in this space. One, we have top tier universities and think tanks that are doing novel research and making advances in the field. These academic and research centres train and attract talented individuals within Canada and from around the world. This in turn helps to incentivize companies to set up shop in Canada and take advantage of the talent pool. Secondly, Canada’s immigration policy makes it easier for companies to hire international employees than say the United States.
JENNIFER, JAMES AND MATT WILL BE SPEAKING AT BIG DATA AND AI TORONTO 2019!