Canada’s impending AI revolution and the opportunity for Canadian business February 2017 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission by authors is strictly prohibited
The ability to acquire, organize, and draw conclusions from data with the help of Artificial intelligence will play a transformational role in business Acquire data Organize data Collect additional External data data based supplements Analyze data on decision data set outcomes to drive superior decision AI helps drive Draw making superior decision- conclusion through making and self- based on data iteration improving algorithms Make decision SOURCE: Team analysis; Taylor B. et. al. (2007). The War Against Spam:A report from the front line, Neural Information Processing Systems; Somanchi, S. H. (2015). "The mail you want, not the spam you don’t" 2
Recent advances in deep learning, a subset of AI, have led to an exponential increase in its ability to predict outcomes and make decisions Deep Learning’s ability to tackle problems over time Drivers Complexity Deep Learning capacity frontier Predicted frontier of problems Libratius wins poker tournament against Better Google algorithms independently 4 top players, wins hardware learn about concepts like people and $1.8 million in the cats by watching YouTube videos process The German traffic sign recognition benchmark More data competition is won by an algorithm , attaining better accuracy levels than humans AlphGo beats the world champion Better algo- Google produces at the Chinese rithms and its first self- game of Go training driving car methods 2007 08 09 10 11 12 13 14 15 16 17 18 19 2020 Time SOURCE: Press Search 3
Many technologies are developing and commercializing simultaneously giving rise to significant disruptive forces and a generation of new companies Next-generation Mobile Internet genomics Automation of Energy storage knowledge work The Internet of 3D printing Things Artificial intelligence will underpin the next industrial revolution Advanced Cloud technology materials Advanced oil and Advanced robotics gas exploration and recovery Autonomous and Renewable near-autonomous energy vehicles SOURCE: McKinsey Global Institute analysis 4
AI ECONOMIC IMPLICATIONS Artificial intelligence will create new markets and opportunities in PRELIMINARY industries ranging from healthcare to financial services Industries Example of opportunities ▪ Autonomous vehicles to create a $87bn solutions market Automotive & Transport ▪ Drone systems integration to create $82bn in Artificial intelligence positive economic impact and generate more than Aerospace will deliver most of its 100,000 jobs & Defense economic value by eliminating waste (e.g. asset ▪ Robo-advisors expected to have ~ $2.2tn in AUM underutilization) and by 2025 Financial creating surplus ▪ Personalized / dynamic financial advice and Services opportunities (e.g. planning accident avoidance, ▪ Global market for telehealth to reach $34bn improved medical ▪ Global market for medical robotics to reach $18bn outcomes) Healthcare ▪ Possibility of better diagnostics personalized medicine ▪ Global agribot market to reach $16.3bn ▪ Significant improvements in yield management Agriculture and better environmental management SOURCE: BAML 5
To capture this opportunity, nations and corporations have already begun massively investing to build their own capabilities Nations Corporations $2.3bn by 2016 in Purchased DeepMind, a unclassified AI-related 75-employee company, for ▪ Talent is a global R&D $500mn market being exclusively tapped by a few $1bn in “Cognitive $1.2bn for the early leaders; Technologies”, which development of AI in the ▪ The price tag has next 5 years includes Deep Learning as its core technology gotten so high many organizations are essentially shut Made AI development a Deep Learning has out from building “national strategy” level become the central capabilities from priority (investment technology behind a large scratch numbers not public) part of the service-offer of tech giants such as Google, Facebook, Samsung, IBM, and Panasonic SOURCE: Press Search 6
By working together, Canada has the scale and expertise to win PRELIMINARY against leading global locations, but no single city is large enough on its own Edmonton Toronto Montreal World-class capabilities Non-distinctive capabilities Strong capabilities PhD students graduating in AI per year Montreal Toronto Edmonton Canada Estimation of yearly graduating AI PhDs AI expertise 84 81 Deep Learning 57 51 39 Reinforcement Learning Natural Language Total AI faculty Processing # of faculty researching AI 76 73 Automatic Speech 51 Recognition 46 35 Computer Vision Deep commer- Canada Silicon New Boston London cialization Valley York ecosystem SOURCE: Press Search, Expert Interviews 7
Montreal has been a data science pioneer for the past 40 years A base of leading research institutes in data science ▪ Founded in 1993, 9 faculty professors, 40 students, 5 post-docs and 5 researchers conducting cutting-edge research on artificial intelligence ▪ The Chair’s mission is to combine knowledge acquisition through Machine Learning with decision making through Mathematical Optimization in a unified approach. ▪ Founded in 1971, brings together researchers working in managing logistics, supply chain and transportation networks ▪ Founded in 1979, brings together 70 experts on quantitative management, operational researchers, theoretical computer scientists, mathematicians and engineers ▪ Founded in 1968, brings together 1,500 vising professors every year to work in its thirteen laboratories ▪ Polytechnique – Département A team of 57 researchers working on innovation, operation research, AI, de mathématiques et de génie applied mathematics and engineering. industriel ▪ 32 professors involved in mathematics for management (statistics, operation HEC - Département de research, decision analysis, probabilities and financial mathematics). sciences de la décision ▪ UdeM – Département de Created in 1966 following the founding on the Université de Montréal’s first l’information et de recherche computer laboratory. ▪ opérationnelle Now brings together 40 researchers and 3 Canada Research Chairs. SOURCE: Web search 8
This culminated in 2016 when UdeM/HEC/Poly were awarded the Canada First Research Excellence grant in data science Context Why this matters ▪ UdeM, HEC, and Polytechnique ▪ In September 2016, IVADO received a Awards worked together to secure Montreal’s $93.5 million grant from the Federal leadership position in data science Government for deep learning research research ▪ The award is the largest in the ▪ A jury of academic peers selected universities’ history Montreal, cementing Montreal’s global academic reputation ▪ Andrea Lodi received the Canada Excellence Research Chair in “Data ▪ Montreal has the funding to develop Science for Real- Time Decision Making” world-leading fundamental research in data science and artificial intelligence ▪ IVADO reached out to University of Commitment ▪ Develop fundamental research using massive data sets from which to draw Alberta and McGill to collaborate useful information and develop actionable decisions ▪ Prioritize marketplace applications, industry partnerships and spin-offs in health, transportation, ICT, and energy networks 9
The CFREF grant consecrated the Montreal ecosystem as a leading hub in data science and artificial intelligence #1 university hub in Canada Leading start-ups & scale-ups Strong corporate network ▪ At 900 researchers and ▪ Presence of Element AI, a ▪ Significant investments doctoral students, Montreal from Google, Amazon and world leading applied AI has the biggest and most research company that Microsoft in the past year prestigious group of data with a desire to make launches AI-first solutions in sciences researchers in Montreal a central talent hub partnership with large the world ▪ A robust data infrastructure corporations ▪ World-renowned ▪ Up to 2,600 startups with a system with at least 2,100 academics, including Yosha pool of skilled talent of data specialists Bengio, one of the ▪ 91,000 ICT professionals approximately 8,000 founding fathers of the and ranked 1 st for lowest employees deep learning movement ▪ 125 technology-focused ICT business operating ▪ The Institute for Data cost in software meet-up groups connected Valorisation (IVADO) was to startups and 45,000 development created to make Montréal a ▪ Leading cloud / datacenter members leader in data science and ▪ Large ecosystem of VC market in Canada; Amazon Al&OR recently announced data funds focused on pre-seed ▪ Montreal got $93.5 million center investment to growth equity funding for AI&OR ▪ Grassroots organizations ▪ Headquarters to a number of research funding through large corporates looking to such as MTL Data, Data IVADO in 2016, on top of Driven MTL, MTL Machine invest in data science and $140 million from partners integrate it in their Learning business models SOURCE: Montréal International 10
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