UPDATE June 13, 2017: Last week I posted V1 of our Map of the Canadian AI Ecosystem, and since then Ive been inundated with additions. While its still incomplete, I thought it was important to update the map currently being sent around and reinforce the idea that this ecosystem is in constant flux. Already, our list has mushroomed from about 160 startups to over 550. Goes to show how much is happening just below our attention.

Ive been putting together a map on Canadas AI ecosystem, which I first revealed last week in my keynote on C2 Montreals main stage. As promised, Im publishing that map at the bottom of this post.

Given the speed at which the industry is progressing, this map is constantly evolving, so Ill be sharing updates as we add them. If you have an addition to make, drop me a line!

The talent pool for AI research is tiny; at the office, weve tracked about 5600 researchers globally who are making an impact in the field. This size makes it critical that the industry players build relationships and share knowledge, to create an ecosystem that helps facilitate progress in AI so that were able to better specialize.

In the last couple of years, the Canadian AI ecosystem was pretty fractured, each cluster trying to win the race and get ahead of the pack. Cities like Montreal, Vancouver or Toronto would announce how their city was the place to be: great quality of life, financial incentives, a flourishing venture capital scene, some of the best researchers in the world, etc. The message tended to be that we have the ingredients to be the next hot spot.

Up until recently Canada was not a heavyweight in the artificial intelligence market. The United States dominated (some even calling it a strategic monopoly), with China and Japan holding second and third place. Where Canada shined was fundamental research. Thanks to the Canadian governments willingness to invest in long, difficult pursuits, our universities are the source of some of the big breakthroughs that lead to deep learning and reinforcement learning, two of the most important innovations in AI up to now. Having some of the best universities also means that we train some of the best artificial intelligence specialists in the world. But, without much serious competition here in Canada, much of that talent went south to the tech giants in Silicon Valley.

This is where the new influx in research funding from Ottawa as well as Ontario and Quebeccomes into play. All three governments have chosen to offer massive support for the artificial intelligence scene, giving $125M, $50M and $100M, respectively, to keep this research engine running. Indeed, Edmonton received $35M from Ottawa while Vancouver received none of that federal money, despite having 5x the number of startups that Edmonton has.

The reason is that Edmonton is home to Richard Suttons lab, Amii, where hes done a lot of very influential research in Reinforcement Learning. Meanwhile, its been no secret that Vancouver is just too expensive for a research professor, causing many to leave for other universities or companies. The balance of funding will soon be leaning towards building up tech companies, but those are built on the solid research coming out of our Universities. Edmonton has a great opportunity to build their startup ecosystem before the venture funding really kicks in.

For now, research is what gave Canada its edge and its important we dont lose that before our startup ecosystem matures. But if we want to go beyond research and become big players in the AI market, research is not enough. Thats why we didnt want to ignore Vancouver in our map as the startup scene heats up, and they have historical economic links to East Asia where a lot of the action is for the AI industry.

Read the original:

Mapping the Canadian AI Ecosystem jfgagne