Toronto, Tuesday, December 15, 2015

What a pleasure to join you for the opening of this important conference on machine learning and the intelligence market.

I begin by welcoming those of you who have travelled to Toronto from abroad and from across Canada for this special event.

I just know that I’m looking out at a roomful of big thinkers and visionaries right now! To borrow from President Kennedy: not since Thomas Jefferson dined alone at the White House has there been such an extraordinary gathering of knowledge and talent!

We truly do need creative minds and inspired groups of people to move us ahead in these transformative times.

And as you well know, there are few spheres in which the transformation is of greater potential impact than in the realm of machine learning and artificial intelligence.

But as Marshall McLuhan once said of the electronic age he foresaw:

“To bring order into this jangled sphere man must find its centre.”

That’s what you’re here to do in regards to machine learning and intelligence.

You’re here to locate the opportunities and the challenges that attend this new frontier.

To explore the societal implications and the commercial possibilities.

To share insights and experiences and form networks for success.

This field has the potential to significantly impact our lives and societies. The arrival of machine intelligence has been compared to that of the Internet, but what we don’t know is precisely where we are in the timeline. Is this period like the 1980s, when the Internet was largely a tool of academics and specialists? Or is this the early 1990s, when the Internet was about to explode into the mainstream and change everything?

We don’t yet know. But what we do increasingly sense is that machine learning and artificial intelligence are likely to emerge reasonably soon, and when they do, we know the impact will be significant.

So what role can we play? And how do we maximize the opportunities of this new technology and minimize the challenges that arise?

These are questions that are rightly preoccupying those of you who are working in this field.

As many of you know, Canadians have been at the forefront of some exciting new developments in machine learning. A number of key breakthroughs have come out of Canadian universities and research institutions, and some of our top minds have been recruited by American high-tech companies to advance the effort.

This is very exciting. Canada is helping to lead the way, and one of our challenges now is to find commercial applications for this exciting and quite possibly revolutionary technology.

One advantage we all have in this is the fact that university-industry linkages are strong in this sphere. As we saw the development of semiconductors in the 1960s or biotechnology in the 1980s, the line between industry and academia is blurred when it comes to machine learning and artificial intelligence.

One prominent, and very local, example is of course Dr. Geoffrey Hinton, who divides his time between the University of Toronto and Google in Mountain View, California.

Another example from south of the border would be Yann LeCun, who researches machine learning at both New York University and Facebook.

These cross-appointments point to the complexity of the work to be done, as well as the way forward: through collaboration and partnership. And that’s why this gathering is so very useful and important.

As with previous technological revolutions, we must recognize and adapt to new realities. The challenges are many, but so are the opportunities, and I thank you all for paying close attention to each.

Have a productive and enlightening conference.

Thank you.