Like many artificial intelligence companies in Canada, PeopleAnalytics.ai was happy to see the federal government's launch of its Pan-Canadian Artificial lntelligence Strategy for research and talent as part of the federal budget this year.
The $125-million that the Liberals are committing to the project, to be administered through the Canadian Institute For Advanced Research (CIFAR), is expected to help to attract and retain top academic talent in this country.
With the market for AI-related ideas and products expected to reach $47-billion by 2020, according to CIFAR, the sector has already attracted major investment from Facebook and Google, among others.
For PeopleAnalytics.ai, based out of Toronto's MaRS Discovery District, Canada is at a crossroads where it has the ability to define exactly how it wants to mould its focus on AI.
Mark Chaikelson, below, vice-president of product for PeopleAnalytics.ai, says the success of the government's plan, particularly in the AI clusters in Montreal, Toronto-Waterloo and Edmonton, will come down to three things: capital, customers and talent.
(Glenn Lowson/The Globe and Mail)
"Ultimately what wraps around that entire thing is policy," he says. "What the government is doing is they are stepping in and saying, 'We are developing policy and we are going to put our money where our mouths are.'"
Canada has the potential to lead globally in this field.
Recent figures from consulting firm Accenture suggest that just 17 per cent of companies globally are using AI optimally, while most – 57 per cent – are considered AI "observers."
In Canada, the number of funded AI startups grew to 45 from three over the 2010-16 time period, placing it fourth among G20 countries, according to Accenture's study. Canada placed fourth in total funded AI startups (45 total) in 2016, versus nine other nations with significant AI infrastructures.
PeopleAnalytics.ai uses AI and language psychology to understand group dynamics and social hierarchies among work forces to cut down on problems such as employee violence and staff turnover.
For the company, like most in the AI field, talent is highly sought-after, and Canada often struggles with retaining home-grown experts and attracting top talent from abroad.
PeopleAnalytics.ai has close ties to the academic community in the university town of Austin, Tex., where it does some of its research, and finding the right talent often requires bringing people in from outside of Canada. As Mr. Chaikelson explains, because of the work it does, PeopleAnalytics.ai is looking for people with "very specific technical expertise."
While the company brought a team member from Texas to work in Canada last year, that kind of move hasn't always been so easy to expedite, and in the past has proved insurmountable.
"Now, with some of the new policies in the budget that talk about accelerating visas for skilled individuals, that's the type of thing that can really open us up," Mr. Chaikelson says.
On top of talent acquisition, he says Canada needs to continue to provide access to capital for companies like PeopleAnalytics.ai, supporting the private markets by "giving them the necessary tax incentives for them to invest funds and invest in programs."
He points to AI programs such as those launched by Royal Bank of Canada, in conjunction with the Alberta Machine Intelligence Institute, and Canadian Imperial Bank of Commerce, which is increasing spending on developing financial technologies, as leaders in this space.
As a partner with the government in the development of the Pan-Canadian AI Strategy, CIFAR says the best way to stimulate great innovation in this country is by funding great science.
But according to Alan Bernstein, the chief executive officer of CIFAR, the core of that strategy and program is people, in particular the chairs at the three main centres of AI in this country.
He points to Geoffrey Hinton, whom he calls "the godfather of deep learning," as a prime example. A computer science professor who splits his time between the University of Toronto and Google, Dr. Hinton was recently named chief scientific advisor to the new Vector Institute in Toronto, the creation of which is designed to help further Toronto's transformation into a global hub for AI.
But while he is happy to see the government's investment in AI, Dr. Bernstein says it is important that Canada take advantage of the current political climate worldwide, where the isolationist attitudes of U.S. President Donald Trump and Britain's continuing Brexit steer countries away from immigration, to bring the best talent to Canada.
"The rest of the world is sort of shutting its doors," he says. "Look at what's happening in the U.S., the U.K. and the rest of the world, so I think this is Canada's moment."
Canada's upswell in the area of AI is certainly getting noticed by Canada's neighbour to the south.
Rajeev Dutt, a Toronto native educated at the University of Toronto, ventured to the state of Washington to work for Microsoft and ended up co-founding his own company, Dimensional Mechanics, which helps make AI accessible to companies without in-house expertise in the area.
While he says Canada's reputation, formed around AI experts such as Dr. Hinton and U of T alumnus Ilya Sutskever at OpenAI and Yoshua Bengio at the Montreal Institute for Learning Algorithms, attracts a lot of talent, newer developments have caused ripples.
"I think Canada has made a lot of progress," he says, referring to the investment Canada is making in the AI sector.
He says that one of the privileges of being based in the Seattle area of Washington – Dimensional Mechanics is based in Bellevue – is that Seattle itself is becoming a hub of activity, and this spills over into surrounding areas, including Vancouver. As a result, he says, there is a significant investment being made by many of the big players, such as Google and Microsoft, in the Vancouver area.
"We're a startup but just to get around some of the issues like talent acquisition, we are looking at options in Vancouver," he says.
Like others in his position, he was encouraged to see the latest budget and the investment Canada is making in AI. He believes it adds momentum to the "giant pool of talent" that is already forming in the country, and that could pay further dividends down the road.
He talks about the economic theory behind co-location, where a lot of companies doing the same thing in one area develop a synergistic connection between one another as talent moves from one company to the next, much like in California's Silicon Valley.
"One of the attractive things in Canada is you're seeing this is actually becoming a bigger component of how companies operate," he says. "So it could be … sort of a Silicon Valley for AI and I think it will keep attracting talent."