Yoshua Benhio, Co-Founder or Element Ai, Pioneer of Deep Learning and Director at MILA (Montreal Institut for Learning Algorithms)
Yoshua Benhio, Co-Founder or Element Ai, Pioneer of Deep Learning and Director at MILA (Montreal Institut for Learning Algorithms)

Montreal, Canada – The new AI super-cluster

For many people, this blog’s title might seem bold or crazy, but many key players in Montreal’s rapidly growing artificial-intelligence sector are working hard on transforming the city into a Silicon Valley of AI.

Yes, you read it right, Montreal…
For those who are already lost, I’m talking about Montreal, a city located in the province of Quebec, in the east of Canada. But how Montreal could be the next Artificial Intelligence hub, you’ll ask?
Good question, let me explain!

First, you’ll need to understand some basic concepts about AI to be able to read the rest of this blog article.


AI, Machine Learning & Deep Learning – Basic concepts & differences

Every time a new product or technology is invented, new buzz words follow. With AI, a lot of buzz words are too often used in the wrong context. The three most common misused words are AI, Machine Learning, and Deep Learning. Business gurus, marketers and even the techies love these words and throw them around whether or not they understand the differences.

Let’s start with a simple definition of AI.
Artificial Intelligence is the capability of a machine to imitate intelligent human behavior. You need to understand that Machine learning and Deep Learning are two applications of AI. In fact, you’ll soon understand that in Deep learning is an application of the Machine learning that goes deeper in the learning.

Now, Machine learning concretely is an application of artificial intelligence (AI) that provides systems the ability to learn and improve from experience without being explicitly programmed automatically. By analyzing data, using Machine Learning concepts, you can make a prediction/truth/determination depending on the scenario.
There are two types of Machine Learning algorithms, the supervised and the unsupervised learning.
The supervised learning requires a human to input the data and the solution of the problem, but let the machine figure out the relationship between these two.
The unsupervised learning, on the other hand, consists of putting random data for a precise situation and asking the machine to find the relationship and the solution for that problem.

The biggest difference between Machine Learning (ML) and Deep Learning (DL) is that DL is crunching a lot more data than ML. Deep Learning algorithms are super powerful and they need a lot of data to give you the best output. Like I said earlier, DL is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.


But, what’s the link between AI, ML, DL, and Montreal?

Back to the Montreal ecosystem, I can easily understand that you are trying to find a link between all theses AI concepts and Montreal.
Deep Learning was mainly invented/popularized by 3 AI researchers. Called by many people the “Canadian Mafia”, the trio is composed of Geoffrey Hinton, Yann LeCun and Yoshua Bengio. Hinton is directing the AI team at Google, LeCun at Facebook, and Bengio is the only one still in the “public sector”, he’s directing the MILA (Montreal Institut for Learning Algorithms) at the University of Montreal.
More recently Bengio also co-founded Element Ai, a Montreal-based company that helps large enterprises that might not have much experience in AI start using the technology to change the way they do business.

(Now you should start to see a link between AI and Montreal… )

The fact that Bengio is one of the greatest AI pioneer not working for a big tech company attracted a lot of money in Montreal. Starting with the Canadian Government, back in September, that invested more than 200 million in 3 specific universities in Montreal to accelerate the AI research. Followed by 100 million from the Quebec Government, Google and Microsoft also announced big investments in Montreal initiatives. They both announced expansions of their Montreal AI research groups alongside big investments in research labs like MILA.

Element Ai

Finally, more recent news, in June, Element Ai, announced that they raised 135 million from world’s biggest technology companies, like Microsoft, Intel and Nvidia, and other big venture capital firms. The company is now composed of 100 AI specialists in Montreal, and they announced that they would hire 250 new employees by next January. A hundred will be based in Montreal, 100 in the new Toronto office and the remaining 50 employees for the Element Ai office in Asia.


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  2. CBC News. (2017). Uber launching Toronto branch of self-driving car research group . [online] Available at: http://www.cbc.ca/news/canada/toronto/uber-launching-toronto-branch-of-self-driving-car-research-group-1.4104330 [Accessed 4 Aug. 2017].
  3. CBC News. (2017). Google to invest in Montreal artificial intelligence research lab . [online] Available at: http://www.cbc.ca/news/canada/montreal/montreal-institute-learning-algorithms-1.3859460 [Accessed 4 Aug. 2017].
  4. Bertrand Marotte, S. (2017). How Montreal aims to become a world centre of artificial intelligence. [online] Montreal Gazette. Available at: http://montrealgazette.com/business/how-montreal-aims-to-become-a-world-centre-of-artificial-intelligence [Accessed 4 Aug. 2017].
  5. Paddon, D. (2017). Tech industry invests $135 million in Montreal startup Element AI | Toronto Star. [online] thestar.com. Available at: https://www.thestar.com/business/tech_news/2017/06/14/tech-industry-invests-135-million-in-montreal-startup-element-ai.html [Accessed 4 Aug. 2017].
  6. Nouvelles.umontreal.ca. (2017). IBM to open an AI lab in Montreal to better collaborate with MILA. [online] Available at: http://nouvelles.umontreal.ca/en/article/2017/04/20/ibm-to-open-an-ai-lab-in-montreal-to-better-collaborate-with-mila/ [Accessed 4 Aug. 2017].
  7. Leone, G. (2017). Kairos: Machine Learning and Deep Learning explained.. [online] Kairos. Available at: https://www.kairos.com/blog/the-best-explanation-machine-learning-vs-deep-learning [Accessed 4 Aug. 2017].