Edmonton Mayor Don Iveson presides over the signing of a Memorandum of Understanding between Hong Kong AI and Amii.

Amii and the Hong Kong AI Lab (HKAI Lab) are pleased to announce an ongoing collaborative relationship between the two AI-focused institutes. The announcement follows from a brief signing ceremony at Inventure$ today between Amii’s CEO, John Shillington, and Timothy Leung, Executive Director of HKAI Lab.

The relationship, which was formalized through the signing of a Memorandum of Understanding, will explore possibilities for collaboration between the two groups and will encourage new connections between innovators in both Alberta and Hong Kong.

“We’re so thrilled to embark on this new collaboration,” says Shillington. “We see many similarities between the mandates and activities of HKAI Lab and Amii. We both have much to learn from one another, and we can’t wait to begin exploring the possibilities of a much stronger connection between our organizations.”

“We are pleased to be in Canada today to strengthen the relationship between two respectable AI centres,” says Leung. “Both Alberta and Hong Kong have recently emerged as global destinations of AI research and commercialization, and through this mutually-beneficial relationship, we hope to strengthen transpacific collaboration not only for Amii and HKAI Lab but also for our clients and other partners.”

Established in May last year, the HKAI Lab aims to advance the frontier of AI with cutting-edge technologies and expertise, and empowering startups to develop and commercialize their new inventions and technology. Through different seminars, workshops and sharing sessions, HKAI Lab dedicates to inspire startups with new ideas and knowledge among academics, scientists and entrepreneurs in the field of AI. The HKAI Lab is a non-profit initiative that is funded by the Alibaba Hong Kong Entrepreneurs Fund and SenseTime, with support from the Hong Kong Science and Technology Parks Corporation and Alibaba Cloud. Alibaba Hong Kong Entrepreneurs Fund is a non-profit initiative launched by Alibaba Group to help Hong Kong entrepreneurs and young people realize their dreams and visions for Hong Kong. And SenseTime is an artificial intelligence unicorn based in Hong Kong.

In the coming months, Amii and the HKAI Lab will concentrate on groundwork activities, including exploring potential for advanced collaboration and joint projects. The two organizations will also share insights and knowledge about their respective initiatives.

Together with the University of British Columbia, Amii is pleased to welcome two additional Canada CIFAR AI Chairs to our family! Congratulations to Mark Schmidt and Kevin Leyton-Brown as they join a rapidly growing community of world-leading researchers in Canada.

The prestigious Canada CIFAR AI Chairs program, funded by the Federal government with $86.5 million over five years, provides researchers with long-term, dedicated research funding to support their research programs and help them to train the next generation of AI leaders.

Learn more about the brilliant researchers who are helping to drive the future of machine intelligence below:

Using big data to make big decisions

Headshot of Mark Schmidt

The data we collect today – both in the physical and digital world – is vast, and growing exponentially. What can we do with such information? Mark Schmidt, Assistant Professor at the University of British Columbia, has dedicated his career to exploring the challenges that come with learning complicated models from large datasets.

“My work is mainly focused on foundational aspects of machine learning,” explains Schmidt. “In order to improve our ability to deal with larger and larger datasets, I focus on mathematical explainability and on accelerating and verifying fundamental machine learning algorithms.”

Schmidt received his PhD at the University of British Columbia, where he is currently an Assistant Professor in the Department of Computer Science. Originally from Edmonton, Schmidt completed his MSc at the University of Alberta and was one of the first students employed at Amii (then AICML). In 2018, Schmidt received the prestigious Lagrange Prize in Continuous Optimization, awarded once every three years by the Mathematical Optimization Society (MOS) and SIAM for an outstanding contribution in the area of continuous optimization. He is currently an Associate Fellow in the CIFAR Learning in Machines & Brains program and Canada Research Chair in Large-Scale Machine Learning.

Drawing together theoretical tools from different disciplines

Headshot of Kevin Leyton-Brown
Photo Credit: Paul Joseph for UBC Brand and Marketing

You can find Kevin Leyton-Brown at the intersection of computer science and microeconomics. Inspired by interdisciplinary collaboration, Leyton-Brown conducts research in two distinct areas: the design and analysis of markets (“algorithmic game theory”) and the automated construction of algorithms.

“My current research focuses on using machine learning to customize algorithms for different practical settings,” says Leyton-Brown. “Recent projects have included helping to design and to conduct a $20 billion reallocation of radio spectrum across the US and Canada from broadcast television to mobile; helping Ugandan farmers to sell surplus crops using basic phones; designing an open-source peer grading system that incentivizes hard work; and building realistic computational models of human behaviour in strategic settings.”

Leyton-Brown is a professor of Computer Science at the University of British Columbia and an associate member of the Vancouver School of Economics. He holds a PhD and MSc from Stanford University. He has co-written two books and over 100 peer-refereed technical articles. He was elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2017 and ACM Distinguished Member in 2018. With a team of 18 others, he was awarded the INFORMS Franz Edelman Award for Achievement in Operations Research and the Management Sciences, described as “the leading O.R. and analytics award.” He is currently Chair of ACM SIGecom and has served as associate editor for the Artificial Intelligence Journal (AIJ) and the Journal of Artificial Intelligence Research (JAIR).

In 2017, CIFAR was chosen by the federal government to lead the $125M Pan-Canadian Artificial Intelligence Strategy in collaboration with artificial intelligence research centres in Edmonton (Amii), Montreal (Mila), and Toronto (Vector Institute). The 16 newly named Canada CIFAR AI Chairs come from universities from across Canada, including Université de Montréal, McGill University, University of British Columbia, Dalhousie University, University of Waterloo, University of Guelph, as well as the University Hospital Network. The Canada CIFAR AI Chairs Program is expected to grow to more than 60 Chairs by 2020.

Edmonton’s history of global AI dominance

The University of Alberta launched Canada’s first computing science department, dating back to 1964. Recent events—including the announcement of DeepMind’s first international research laboratory—have truly cemented Edmonton’s excellence on the global map. According to the acclaimed CS Rankings, UAlberta ranks within the top five in the world for artificial intelligence and machine learning research.

Amii was founded in 2002 as a joint effort between UAlberta and the Government of Alberta with the goal of creating a world-class machine intelligence research centre. The organization has since spun out from UAlberta, while maintaining a strong partnership, with support from Alberta Innovates, the Government of Alberta and CIFAR—in order to drive new levels of discovery and innovation in AI and machine learning.

Inaugural Summer Institute explores societal impacts of artificial intelligence

What will Artificial Intelligence (AI) mean for society? That’s the question scholars from a variety of disciplines will explore during the inaugural Summer Institute on AI and Society. Summer Institute, co-convened by CIFAR, the AI Pulse Program at UCLA School of Law, and the Alberta Machine Intelligence Institute (Amii), takes place July 21-24, 2019 in Edmonton, Canada.

“Recent advances in AI have brought a surge of attention to the field – both excitement and concern,” says co-organizer and UCLA professor, Edward Parson. “From algorithmic bias to autonomous vehicles, personal privacy to automation replacing jobs. Summer Institute will bring together exceptional people to talk about how humanity can receive the benefits and not get the worst harms from these rapid changes.”

Summer Institute brings together experts, grad students and researchers from multiple backgrounds to explore the societal, governmental, and ethical implications of AI. A combination of lectures, panels, and participatory problem-solving, this comprehensive interdisciplinary event aims to build understanding and action around these high-stakes issues.

“Machine intelligence is opening transformative opportunities across the world,” says John Shillington, CEO of Amii, “and Amii is excited to bring together our own world-leading researchers with experts from areas such as law, philosophy and ethics for this important discussion. Interdisciplinary perspectives will be essential to the ongoing development of machine intelligence and for ensuring these opportunities have the broadest reach possible.”

Over the three-day program, 30 graduate-level students and early-career researchers will engage with leading experts and researchers including event co-organizers: Western University’s Daniel Lizotte, Amii’s Alona Fyshe and UCLA’s Edward Parson. Participants will also have a chance to shape the curriculum throughout this uniquely interactive event.

Summer Institute takes place prior to Deep Learning and Reinforcement Learning Summer School, and includes a combined event on July 24th for both Summer Institute and Summer School participants.

Visit dlrlsummerschool.ca/the-summer-institute to apply; applications close May 15, 2019. View our Summer Institute Biographies & Boilerplates for more information on confirmed faculty members and co-hosting organizations. Follow the conversation through social media channels using the hashtag #SI2019.

Le premier Institut d’été est consacré aux enjeux sociétaux de l’intelligence artificielle

Comment l’intelligence artificielle (IA) va-t-elle transformer la société ? Voilà la question à laquelle tenteront de répondre des chercheurs de différentes disciplines à l’occasion du premier Institut d’été du CIFAR, qui aura pour thèmes les enjeux de société, de gouvernance et d’éthique de l’IA. L’Institut d’été, coorganisé par le CIFAR, le programme PULSE de la Faculté de droit d’UCLA et l’Amii (Alberta Machine Intelligence Institute), se tiendra du 21 au 24 juillet 2019 à Edmonton, au Canada.

« De récents progrès en matière d’IA ont entraîné un regain d’intérêt pour le domaine et suscitent à la fois l’enthousiasme et l’appréhension, déclare Edward Parson, coorganisateur et professeur à UCLA. L’Institut d’été réunira de brillants cerveaux qui chercheront à déterminer comment l’humanité peut profiter des avantages de ces changements rapides tout en évitant le pire, qu’il concerne les biais algorithmiques, les véhicules autonomes, la protection des renseignements personnels ou l’automatisation des emplois. »

L’Institut d’été accueille des experts, des étudiants diplômés et des chercheurs d’horizons divers afin d’aborder les enjeux sociétaux, gouvernementaux et éthiques de l’IA. Combinant conférences, ateliers et résolution participative de problèmes, cet événement interdisciplinaire complet vise à favoriser une compréhension proactive de ces enjeux de première importance.

« L’intelligence artificielle ouvre la voie à une foule de changements partout sur la planète, affirme John Shillington, PDG d’Amii. Amii se réjouit de réunir ses chercheurs de calibre mondial et des spécialistes du droit, de la philosophie et de l’éthique dans le cadre de cet important débat. L’interdisciplinarité est essentielle pour assurer le développement de l’intelligence artificielle et pour garantir que ces possibilités auront la plus large portée possible. »

Durant 3 jours, 30 étudiants de cycle supérieur et jeunes chercheurs échangeront avec des spécialistes et des universitaires de renom, dont les coorganisateurs de l’événement Daniel Lizotte, de l’Université Western, Alona Fyshe, d’Amii, et Edward Parson, d’UCLA. Les participants pourront en outre modifier en temps réel le programme de cet événement interactif tout à fait unique.

L’Institut d’été a lieu avant l’École d’été consacrée à l’apprentissage profond et à l’apprentissage par renforcement. Les participants des deux écoles se réuniront ensuite le temps d’un événement conjoint qui aura lieu le 24 juillet.

Inscrivez-vous sur dlrlsummerschool.ca/the-summer-institute avant le 15 mai 2019. Obtenez de plus amples renseignements sur les membres du corps professoral qui ont confirmé leur participation à l’Institut d’été et de brèves présentations des coorganisateurs. Suivez la conversation sur les réseaux sociaux à l’aide du mot-clic #SI2019.

International Women’s Day, celebrated every year on March 8, is a global day celebrating the social, economic, cultural and political achievements of those who identify as women. The day also marks a call to action for accelerating gender diversity.

Gender diversity in tech has long been a point of contention, illustrated well by the divisive reactions to the 2017 memo circulated by a Google employee, who argued that biological and personality differences were the main drivers of the gender gap within the company.

History tells a different story. Many pioneers of the field were women. We see this as far back as 1843, when Ada Lovelace became the first computer programmer. However, as the societal perception of tech became more gendered in the mid-to-late 20th century, the narrative and stereotypes were rewritten to become more like what we recognize today.

There have been many women who have defied these harmful tropes to become leaders in their field. Doina Precup, who heads the Montreal office of Deepmind. Foteini Agrafioti, Head/Co-Founder of Borealis AI. And there have been promising initiatives to bring equity to tech. There is CAN-CWiC, toted as “the premiere Canadian computing conference for women in technology.” The Grace Hopper Celebration of Women in Computing continually breaks annual attendance records, bringing together over 20,000 people in 2018.

We are fortunate to have many fascinating and talented women to celebrate in the Amii office, including Anna Koop, Director of Amii Explores. Anna leads the applied machine learning team, monitors and directs the applied scientific endeavours of the organization, and facilitates interactions between our research core (Amii fellows) and industry partners.

Pictured: Director of Amii Explores Anna Koop playing with toys at Amii HQ

We sat down with Anna to ask her about what led her to her current position, and how her gender has affected her journey.

Please note: this interview has been edited and condensed for space

How did you get into researching machine intelligence?

In 2001, I went back to school to get my physics degree. I had done some part-time school, because you cannot keep me away from school — even if I’m in the middle of nowhere in Saskatchewan. I wanted to be a professor eventually, but since I had done some web programming, I did take one computers class. And in that class, Rob Holte let us know about the AI seminars, which were the weekly pizza lunches with guest speakers, students, and professors talking about AI. I started going to those out of curiousity, and found out that there was lots more to computer science than just programming the same task over and over again.

Amii, at the time, had just formed under the name Alberta Innovates Centre for Machine Learning. So now I’ve got to be talking about 2002. They were hiring for the summer, so I talked to them and got hired on to do some web dev. That turned into research collaborations with Rich [Sutton], and then I was hooked; I thought, “Okay, never mind. I can do cool things now. I am going into comp sci hardcore.”

What hooked you?

That computers weren’t all artificial. I had a moment where I was very explicitly thinking, “You can’t do computer science without a computer, and so it’s less real in a way than physics. Physics is going on all around you.” But when I found out about the intelligence research, I thought, “Well, the nature of intelligence is a pretty fundamental question, yet we don’t get it.”

I remember tutoring a student in high school biology. She asked, “Okay, so here’s all these neurotransmitters. Where are our thoughts?” I said, “Don’t know. Isn’t that an interesting question?” And we still don’t know the answer, and that’s still a really interesting question. So that there’s this fundamental truth-of-the-universe question embedded in it; that we can use computers as a tool to discover this, is very exciting.

Computing science is also such a young field, and AI is especially young. There’s so much progress to be made everywhere, where on the physics side, it’s a lot harder and takes fancier toys to make progress. There’s so many nearer frontiers in comp sci. Although, to be fair, some of the intersect with philosophy that’s been going on for hundreds of years may be harder to make progress on.

You’re female in a field that has a known gender gap. What has your experience been in that sense?

I only noticed it a year or so into my masters, actually. There was a workshop for women in machine learning that my supervisor found out about, co-located with the Grace Hopper Celebration of Women in Computing. They were talking about the gender gap, which caused me to look around and say, “You’re right, there is. We have a lab of 30 people, I am one of two women. Those are not 51% of odds.”

And kind of exploring some of the less visible, less explicit consequences. I never had anyone tell me I couldn’t do science. But then you look around and realize that 10% of senior scientists are female, and you think, “Well, that’s weird. If there isn’t a gender bias, then what is going on here?” Then you start learning more, and realizing there is bias, it’s just more insidious than we’d like.

I do have colleagues who have been told that they can’t do it because they’re women, or they don’t look like a computer scientist. Even with that removed, there’s still differences in representation, so you don’t think of yourself as fitting into that role, or you think that it will take extreme efforts to be able to do it. Going to Grace Hopper was an eye-opening experience – there’s actual study around this, and empirical data, and it’s not about just what overt messaging is out there. It’s also about the systematic inequalities and how they’re reinforced. We got another group of women to go the next year, and then year after that. Then we started Ada’s Team, the Diversity in Computing Science Group, kind of in response to that.

It’s frustrating to notice. I was happier when it didn’t occur to me that often, because it’s all so, so stupid. The world is shooting itself in the foot. Even for totally selfish reasons, we should make sure we have diverse teams. [Editor’s note: see Why Diverse Teams are Smarter by Harvard Business Review]

Can you illustrate any specific moments where you’ve noticed that your gender has made a difference in your interactions with people?

I think I’ve been lucky, in that I haven’t had that many overt things. There’s just the pattern of feeling like I had more to prove, but you can always dismiss that. It can always be, “It’s not because I’m female, it’s because I’m doing something wrong, or because I’m approaching this in a different way. That’s why.”

The biggest one is probably the burden of being the explainer. I’ve been forwarded questions like, “Why do we need a scholarship for women?” Or, “Why do we need this celebration of women? Shouldn’t we be equal?” So doing a lot of the kind of one-to-one. Introducing concepts, hearing where they’re coming from, and explaining where we’re coming from, and it’s the same argument over and over again. So that gets tiring, but the worst drain is actually deciding when to take action.

For example, there was a game in the game development course where you’re playing as mean girls bullying students. And especially in CS, I’m not comfortable with this being condoned. So deciding to bring that up with the professor, and deciding to push on it when he didn’t see the issue. The pure emotional energy it takes to decide to have the conversations, to carry them out, and to deal with the aftermath when people especially don’t respond well – even when they’re very well intentioned – is just a huge recurring drain.

And it’s invisible, because sometimes ignorance is bliss. If you’re not seeing the problem, you’re not dealing with the ramifications. So becoming more aware has meant actually having a lot more time and energy routed to dealing with it, or trying to make it better, or addressing things that come up, or even being a shoulder to cry on when somebody else is dealing with it.

The other frustrating thing is the delayed reaction time. I’m very cheerful, generally speaking, and sunshine-y. My instinct is to smooth things over, and make everybody happy in the moment. And sometimes that means an hour later, I realize, “Wait a second, I’m furious. I shouldn’t have laughed at that, I should have yelled.” And then you have to decide whether to go back and make a big deal about it, and if so, how to.

I can’t even count up the hours that have been … Not lost, because it’s valuable work, but definitely not devoted to thesis work, because of dealing with this kind of thing.

If you had a piece of advice, or something to say, for future generations of women who are considering entering STEM, or who are presently in STEM programs, what would you say?

Keep growing in all the ways that appeal to you. Don’t feel like there’s only one narrow path, because it turns out, even the path you’re on is probably not the path you’ll stay on. There’s way more possibility in the world than we think about in high school. So pursue the things you’re interested in, and don’t stress about finding exactly the right fit or exactly the right career, because careers are changing all the time. Be open to hearing about other people’s experience; it broadens your world, it also gives you role models and resilience when you start hitting barriers, too. I wish I could go back and learn more about diversity and privilege as a teenager, and start applying it earlier. The broader perspective, that recognizing where you have privilege that others don’t, and where you have challenges that others don’t. That we’re all human and working on things together, I think, is a good way to go through life.

If you’re interested in STEM, go for it. Don’t feel constrained to it, and don’t feel constrained to any specific thing. Investigate all the things you like, and you’ll have some weird patchwork career in the end that integrates a bunch of your interests. I haven’t combined knitting and machine learning yet, but other people have, so it’s possible.

If you are a woman or gender minority who is practicing, studying or interested in the fields of machine learning and data science, support is available through WiMLDS groups. Visit the Edmonton and Calgary chapters for more information. 

Over at Startup Edmonton, Operations Manager Lauren Briske shares some ways you can celebrate and get involved.

Visit internationalwomensday.com to learn more about International Women’s Day and how you can participate.

The Department of Computing Science at the University of Alberta is inviting applications for tenure-track or tenured faculty positions at all levels, with a strong research record in the area of AI.

All applications are to be submitted at https://academicjobsonline.org/ajo/jobs/13233, and complete applications and all reference letters must be received by April 1st, 2019 for full consideration.

Read the posting below or on the UAlberta website for Tenure-track and Tenured Professor Position in Artificial Intelligence:

Tenure-track and Tenured Professor Position in Artificial Intelligence

Department of Computing Science

Competition No.  –   A105038173
Closing Date  –   Will remain open until filled.

The Department of Computing Science at the University of Alberta invites applications for tenure-track or tenured faculty positions at all levels.  Candidates with a strong research record in the area of Artificial Intelligence (AI), in particular (but not limited to) Reinforcement Learning, Machine Learning, Natural Language Processing, Robotics, Computer Games, Security, Algorithmic Game Theory and Ethical AI, will be considered for this position.

Successful candidates may be considered as nominees for a funded/endowed research chair position, e.g., the DeepMind Chair in Artificial Intelligence or a Canada CIFAR Artificial Intelligence Chair in the Faculty of Science, if the appointment advances the strategic considerations of the Department of Computing Science, the Faculty of Science and the University of Alberta.

According to csrankings.org the department is ranked #1 in Canada and averaged #3 in the world in terms of number of publications at top AI venues in the last 10 years, and it is also home to Amii (www.amii.ca), the Alberta Machine Intelligence Institute, formerly known as AICML.  It is noteworthy that the 2017 Government of Canada Budget included an investment of $125 million into a Pan-Canadian Artificial Intelligence Strategy which features a major investment in research at the University of Alberta.  According to the most recent Times Higher Education World University ranking, the department is ranked 3rd in Canada and 67th in the world. The department is home to 46 tenured and tenure-track faculty members, and nearly 300 graduate students in its Ph.D. and M.Sc. programs. The University of Alberta is home to over 31,000 undergraduate students, 7,600 graduate students, and 600 postdoctoral fellows.

Successful candidates will have strong communications skills and also demonstrate a commitment to highly effective graduate and undergraduate teaching.  They will establish their own funded research programs, supervise graduate students, and teach graduate and undergraduate courses. Strong potential for productive interactions with researchers in the department or in other disciplines at the University of Alberta will be considered an asset.  The candidate must hold a Ph.D. (or equivalent) degree by the appointment date.

Applicants are asked to submit the following (all files must be submitted in PDF format):

  • a full curriculum vitae,
  • a 1-2 page research statement which should (1) highlight contributions to their field of research, (2) present an overview of their planned research program for ~5 years after initial appointment, and (3) describe how the candidate will interact, collaborate with and complement other researchers at the University of Alberta,
  • a 1-page teaching statement including their experience and interests, and
  • their most significant peer-reviewed published contribution to their field of research

Each applicant must also ensure that three referees will submit (through the submission website) confidential reference letters about their accomplishments and their potential as an independent researcher.   

All applications are to be submitted at https://academicjobsonline.org/ajo/jobs/13233, and complete applications and all reference letters must be received by April 1st, 2019. for full consideration.  

For further information please email the Department Chair’s Executive Assistant at cs.ea@ualberta.ca (please use “AI Faculty Position” as the email’s subject).

To assist the University in complying with mandatory reporting requirements of the Immigration and Refugee Protection Act (R203(3)(e), please include the first digit of your Canadian Social Insurance Number in your application (within your cover letter). If you do not have a Canadian Social Insurance Number, please indicate this in your application (within the cover letter).

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. If suitable Canadian citizens or permanent residents cannot be found, other individuals will be considered.

The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.

Want to learn more about Edmonton-based contributions to AI research? Visit Amii’s Our Impact page for a selection of highlights.

Amii is proud to be part of today’s announcement of $100 million in funding from the Government of Alberta to invest in Alberta’s high-tech industries. This timely investment in programs at Amii, as well as our friends at Alberta Innovates, will enable Alberta businesses of all kinds to seize the opportunities presented by machine intelligence.

“This landmark investment will catalyze economic growth stretching beyond Alberta’s machine intelligence sector,” says John Shillington, President & CEO of Amii. “Businesses around the world are turning to machine learning and artificial intelligence as key drivers of innovation across every industry sector. With this renewed support from the Government of Alberta, Amii will advance transformational business programs offering scientific mentorship and educational opportunities. Together, we’re helping Alberta businesses seize the opportunities presented by machine intelligence.”

The announcement builds upon a 17-year history of investment by the Government of Alberta that has amounted to $44 million being put into machine intelligence related research at UAlberta and Amii. Notably, Amii has also received $2 million in support from Alberta Innovates to establish an office in downtown Edmonton and $25 million in funding from CIFAR as part of the Pan-Canadian AI Strategy.

Amii would like to extend a sincere thank you to our Amii Fellows, without whom none of this would be possible.

Learn more about today’s announcement in the media release below from the Government of Alberta:

Alberta invests in innovation to fuel the future

A historic investment in high-tech industries will create thousands of jobs, attract millions in new investment and help diversify Alberta’s economy.

The Alberta government is investing $100 million to attract more artificial intelligence-based high-tech companies to invest in Alberta. Coupled with last year’s investment of $50 million to create 3,000 new high-tech training seats at post-secondary institutions across the province, this represents a significant diversification initiative.

“Innovation is a critical tool for competitiveness in nearly every sector of the economy, including energy. By investing in technology and the talent that powers it, we are ensuring Alberta continues to be a world leader in clean, efficient energy production and that our economy is more resilient and diversified for the future.”  
Rachel Notley, Premier

The province’s investment in technology will build the industry and business capacity needed to help talented Albertans find jobs here at home. This investment in both Alberta Innovates and the Alberta Machine Intelligence Institute (Amii) will leverage partnerships with Alberta’s leading research universities and support long-term research and job creation.

The overall investment is estimated to result in:

  • more than 6,000 trained, skilled Albertans
  • the creation of over 140 new companies
  • over 30 new multi-national offices, labs in Alberta
  • over $207 million in leveraged investments by industry
  • increased competitiveness and productivity of at least 150 Alberta businesses through the use of artificial intelligence (AI)

“By investing today, we are setting Alberta up for long-term economic diversification and success, while creating thousands of jobs and generating millions in value in the near term.”
Deron Bilous, Minister of Economic Development and Trade

An initial investment of $27 million will allow Alberta non-profit Amii to develop a new program that supports companies looking to build their in-house AI capacity, incorporate innovative solutions and drive benefits. It also means the Edmonton-based organization can expand its presence and open a new Calgary office. This new investment, along with the federal government’s commitment of $25 million, will accelerate the positive impact of artificial intelligence and machine learning on the Alberta economy.

Amii is already home to some of the world’s top talent in AI. Estimates from across the high-tech community suggest this funding will result in about 5,600 new high-paid jobs and roughly $1.5 billion in overall value to Alberta businesses and Amii-affiliated startups.

“This landmark investment will catalyze economic growth stretching beyond Alberta’s machine intelligence sector. Businesses around the world are turning to machine learning and artificial intelligence as key drivers of innovation across every industry sector. With this renewed support from the Government of Alberta, Amii will advance transformational business programs offering scientific mentorship and educational opportunities. Together, we’re helping Alberta businesses seize the opportunities presented by machine intelligence.”
John Shillington, CEO, Alberta Machine Intelligence Institute

The funding will also support Alberta Innovates with work focused on company growth and acceleration, applied research and development, industry solutions and establishing a stronger global market presence for Alberta.

“The support for these programs demonstrates the shift in how Alberta Innovates drives innovation and builds on past expertise to accelerate Alberta’s digital transformation towards a data-enabled economy.”
Laura Kilcrease, CEO, Alberta Innovates

Alberta is attracting top-level talent and investment from around the world, including Google DeepMind, the Royal Bank of Canada and Mitsubishi which have all opened research facilities here. Interest from other major high-tech industry leaders is anticipated which will mean additional millions in new private-sector investment in the province and hundreds of new jobs for Albertans.

If you’re interested in learning how Amii can help your business build in-house machine intelligence capacity, we invite you to attend our next Hello, Amii! Info session in Edmonton, or our next Hello, Amii! Info session in Calgary.

The Alberta Machine Intelligence Institute (Amii) has launched applications for the 11th annual Deep Learning and Reinforcement Learning Summer School, happening July 24 – August 2, 2019 at the University of Alberta in Edmonton, Canada. Hosted in partnership with CIFAR, the Summer School brings together graduate students, post-doctoral fellows and industry professionals to explore the latest AI techniques, build research networks and open collaborative opportunities.

“We’re excited to be hosting this year’s Summer School here in Edmonton and to welcome the future experts of our industry from across the world,” says John Shillington, CEO of Amii. “It’s often a surprise for people to learn that Edmonton is a hub for AI research and home to some of the brightest minds in the field, so we’re thrilled to be able to show the world all the things this unique research community has to offer.”

Over the 10-day intensive program, participants will learn directly from world-renowned AI researchers including Amii’s own Richard Sutton and Martha White and other global leaders like Yoshua Bengio of the University of Montreal. Programming also includes an AI Career Fair and social events, meant to ignite conversations around the major questions across multiple sectors.

“The Summer School has become a beacon for top AI students and experts from around the world,” says Elissa Strome, Executive Director of the Pan-Canadian AI Strategy at CIFAR. “We’re excited to showcase what makes Canada a global leader in the field of AI.”

2018 DLRL Summer School
Photo Credit: The Vector Institute and CIFAR

Amii and CIFAR are also pleased to present a new event in coordination with the 2019 Summer School: the Summer Institute on AI Societal Impacts, Governance, and Ethics from July 22 – 23. The Summer Institute will host scholars from a variety of disciplines to examine the societal, governmental, and ethical implications of AI.

The Deep Learning and Reinforcement Learning Summer School takes place July 24 – August 2, 2019 at the University of Alberta in Edmonton, Canada, and is hosted by Amii and CIFAR, with participation and support from Canada’s other AI hubs: Toronto’s Vector Institute and Mila in Montreal.

Visit www.dlrlsummerschool.ca to apply and for more information. Follow the conversation through social media channels using the hashtag #DLRLSS2019.

Please click here to access the French translation.

Together with the University of Alberta (UAlberta) and Simon Fraser University, Amii is pleased to welcome four new Canada CIFAR AI (CCAI) Chairs to our family! Congratulations to Angel Chang, Alona Fyshe, Martha White and James Wright as they join a rapidly growing community of world-leading researchers in Canada.

Check out the following post from our friends at UAlberta’s Faculty of Science (with some additions from our team) and learn more about the brilliant researchers who are helping to drive the future of machine intelligence.

Building smarter computers and maximizing human capacity:

New artificial intelligence research chairs will push the field forward, with critical funding infusion

From helping humans make better decisions informed by machine intelligence models to building better computers using human brain models, the future has never looked brighter for AI’s influence in society. The slow but steady build of the critical mass of Edmonton’s artificial intelligence brainpower on the global scene has tipped into an explosion in Canadians’ consciousness.

So how do you draw some of the world’s most in-demand minds to a landlocked winter city and keep them here past the first blizzard?

Designed to attract and retain the brains behind the drive to integrate AI into sustainable solutions for our increasingly data-driven society, the first cohort of the Canada CIFAR AI Chairs was announced this morning in Montreal. The illustrious list includes four promising early-career researchers at Amii.

Meet the new chairs supported by Amii, three of whom are assistant professors in the UAlberta’s Faculty of Science, who will collectively receive roughly $3M over the next five years to support their research:

Creating brilliant computers using the human brain

Alona FysheWhat is the best way to improve computers? Study humans, said Alona Fyshe, assistant professor cross-appointed between the Departments of Computing Science and Psychology and Amii fellow. Fyshe applies her expertise in machine learning to brain imaging data, with the purpose of understanding how humans create meaning and use that meaning to make inferences about the world around them.

“What I try to figure out is how we go from words on a page, or pixels on a screen, to higher order meaning,” explained Fyshe. “Right now, computers aren’t very good at that. I’m interested in studying how people make meaning in order to improve how computers do the same thing.”

Fyshe, a UAlberta alumna, returns to her alma mater after time spent on faculty at the University of Victoria and Google. She completed graduate studies with University of Alberta professors Paul Lu, Duane Szafron, and renowned AI researcher and Amii fellow Russ Greiner, whose research drives progress in the field of precision health.

Fundamental research that’s anything but basic

Martha WhiteHow do you help humans make better decisions? You turn a bunch of raw data into complex models that generate accurate predictions. But how exactly do you tackle that technical task? Enter Martha White, Amii fellow and assistant professor in the Department of Computing Science, whose research is dedicated to fundamental algorithms using artificial intelligence and machine learning.

“It’s about supporting humans in making better decisions,” said White of artificial intelligence and machine learning. “AI isn’t scary. It’s just helpful. I’m excited about the answering the interesting questions we’ve had all along in AI. How do we get our agents to explore well, and how do we build good representations of the world? People are excited, which means we now have more access to students and to data and computational resources.”

White, also a graduate of UAlberta, completed her graduate studies with UAlberta professor and Amii fellow Michael Bowling, known for his landmark work with computer poker research and as a research scientist with DeepMind, as well as Dale Schuurmans (UAlberta professor and Amii fellow), a highly influential mind in the AI world. White returned to her alma mater following a professorial position at Indiana State University.

Using game theory to predict human behaviour

James WrightWhy would you look to game theory to better understand how humans make choices? That is the question driving James Wright’s research, one that sees him constructing data-driven models to improve the effectiveness of real systems by accurately predicting human decision making.

“Agents that interact with people in strategic systems will do a much better job if they can predict how people will react,” said Wright, assistant professor in the Department of Computing Science. “Similarly, a policy will achieve its goals more effectively when it takes into account how people will respond to policy. When new policies have unintended consequences, it’s often because they were designed without thinking about these kinds of strategic questions.”

Wright returned to Canada following time spent as a postdoctoral researcher at the Microsoft Research Lab in New York City, joining the computing scientists at UAlberta and contributing to Edmonton’s world-class power on the AI stage.

Developing a common understanding

Angel ChangHow can we help humans and computers better work together? If you’re Angel Chang, CCAI Chair at Amii and incoming assistant professor in the School of Computing Science at Simon Fraser University, you develop ways of using language to help computers understand and interact with our everyday world.

“I’m interested in developing AI that has a more robust and human-relatable understanding of our world,” says Chang. “My work – at the intersection of natural language understanding, computer graphics and AI – explores the representation and acquisition of common sense knowledge and how the semantics of shapes and scenes can be used to connect language to visual and 3D representations of the world.”

Chang, who received her PhD in Computer Science from Stanford University under the supervision of Chris Manning, will be joining Simon Fraser University in 2019. She is currently a research scientist at Eloquent Labs working on developing conversational AI that can understand and assist people. Previously, she was a postdoctoral scholar at Princeton University where she developed large-scale 3D datasets for deep learning and 3D scene understanding.

In 2017, CIFAR was chosen by the federal government to lead the $125M Pan-Canadian Artificial Intelligence Strategy in collaboration with artificial intelligence research centres in Edmonton (Amii), Montreal (Mila), and Toronto (Vector Institute). Support for these new chairs—including 29 across Canada—is part of a larger strategy including training opportunities, research funding, and workshops on the societal implications of AI designed to build on Canadian leadership in artificial intelligence.

Edmonton’s history of global AI dominance

The University of Alberta launched Canada’s first computing science department, dating back to 1964. Recent events—including the announcement of DeepMind’s first international research laboratory—have truly cemented Edmonton’s excellence on the global map. According to the acclaimed CS Rankings, UAlberta ranks third in the world for artificial intelligence and machine learning research.

Amii was founded in 2002 as a joint effort between UAlberta and the Government of Alberta with the goal of creating a world-class machine intelligence research centre. The organization has since spun out from UAlberta, while maintaining a strong partnership, with support from Alberta Innovates, the Government of Alberta and CIFAR—in order to drive new levels of discovery and innovation in AI and machine learning.

The Board of Directors of the Alberta Machine Intelligence Institute (Amii) announced Thursday the appointment of John Shillington as the institute’s first CEO. His appointment began on October 1, 2018.

As head of one Canada’s three AI institutes, Shillington will focus on further developing Alberta as a premier global destination for both foundational research and innovative commercial applications of artificial intelligence (AI) and machine learning technologies.

“With years of experience at the intersection of industry and academia, John is perfectly placed to lead Amii in growing Alberta into the world’s leading destination for AI and machine learning,” says Bruce Johnson, Chair of Amii’s Board of Directors. “He has an established record as a leader and builder of high-performing teams; he has in-depth knowledge of technology commercialization; and he is passionate about building a bright, AI-enabled future right here in Alberta.”

Shillington will work to boost Alberta’s global AI leadership through Amii’s four key focus areas: supporting world-class research and training at the University of Alberta (UAlberta), growing AI capacity in Alberta-based companies, attracting corporate research labs and upskilling Alberta’s workforce for AI literacy.

“I’m beyond excited to be joining such an amazing team of world-class researchers, staff and students,” says Shillington. “I look forward to leading the next stage of Amii’s growth as a not-for-profit, helping Alberta businesses realize the transformative potential of AI and accelerating our province’s global economic advantage.”

Shillington brings with him over 30 years of expertise as a technology leader with deep experience helping companies improve their competitive advantage and driving their next stage of growth. Much of his career has focused on helping organizations bridge the chasm between academic research and its applications in the public, private and not-for-profit sectors.

Elissa Strome, Executive Director of CIFAR’s Pan-Canadian AI Strategy echoes Johnson’s praise of Shillington: “We’re thrilled at the selection of John Shillington as leader of the Alberta Machine Intelligence Institute. Amii is already one of Canada’s AI research powerhouses, and we’re confident that John’s years of experience in the tech sector will provide the knowledge and vision needed to help further cement Canada’s reputation as one of the world’s premier locations for AI research and investment.”

Prior to joining Amii, Shillington was Vice President, Technology at Cybera, a not-for-profit technical agency helping Alberta advance its IT frontiers. He has also held senior executive and technical management positions at several international technology firms in addition to starting up a UAlberta-based spin-off company.

(Amii’s Russ Greiner is part of a team of researchers from the University of Alberta and IBM who are using machine learning to help predict  schizophrenia .)

Pioneering research in “computational psychiatry” uses AI to explore disease prediction and assessment

IBM (NYSE: IBM) scientists and the University of Alberta in Edmonton, Canada, have published new data in Nature‘s partner journal, Schizophrenia, demonstrating that AI and machine learning algorithms helped predict instances of schizophrenia with 74% accuracy. This retrospective analysis also showed the technology predicted the severity of specific symptoms in schizophrenia patients with significant correlation, based on correlations between activity observed across different regions of the brain. This pioneering research could also help scientists identify more reliable objective neuroimaging biomarkers that could be used to predict schizophrenia and its severity.

Schizophrenia is a chronic and debilitating neurological disorder that affects 7 or 8 out of every 1,000 people. Those with schizophrenia can experience hallucinations, delusions or thought disorders, along with cognitive impairments, such as an inability to pay attention and physical impairments, such as movement disorders.

“This unique, innovative multidisciplinary approach opens new insights and advances our understanding of the neurobiology of schizophrenia, which may help to improve the treatment and management of the disease,” says Dr. Serdar Dursun, a Professor of Psychiatry & Neuroscience with the University of Alberta. “We’ve discovered a number of significant abnormal connections in the brain that can be explored in future studies, and AI-created models bring us one step closer to finding objective neuroimaging-based patterns that are diagnostic and prognostic markers of schizophrenia.”

In the paper, researchers analyzed de-identified brain functional Magnetic Resonance Imaging (fMRI) data from the open data set, Function Biomedical Informatics Research Network (fBIRN) for patients with schizophrenia and schizoaffective disorders, as well as a healthy control group. fMRI measures brain activity through blood flow changes in particular areas of the brain. Specifically, the fBIRN data set reflects research done on brain networks at different levels of resolution, from data gathered while study participants conducted a common auditory test. Examining scans from 95 participants, researchers used machine learning techniques to develop a model of schizophrenia that identifies the connections in the brain most associated with the illness.

Regions of the brain that showed a statistically significant difference between patients with schizophrenia and patients without it. (Arrow 1 identifies the precentral gyrus, or the motor cortex, and arrow 5 marks the precuneus, which involves processing visual information.)

The results of the IBM and University of Alberta research demonstrated that, even on more challenging neuroimaging data collected from multiple sites (different machines, across different groups of subjects etc.) the machine learning algorithm was able to discriminate between patients with schizophrenia and the control group with 74% accuracy using the correlations in activity across different areas of the brain.

Additionally, the research showed that functional network connectivity could also help determine the severity of several symptoms after they have manifested in the patient, including inattentiveness, bizarre behavior and formal thought disorder, as well as alogia, (poverty of speech) and lack of motivation. The prediction of symptom severity could lead to a more quantitative, measurement-based characterization of schizophrenia; viewing the disease on a spectrum, as opposed to a binary label of diagnosis or non-diagnosis. This objective, data-driven approach to severity analysis could eventually help clinicians identify treatment plans that are customized to the individual.

“The ultimate goal of this research effort is to identify and develop objective, data-driven measures for characterizing mental states, and apply them to psychiatric and neurological disorders” said Ajay Royyuru, Vice President of Healthcare & Life Sciences, IBM Research. “We also hope to offer new insights into how AI and machine learning can be used to analyze psychiatric and neurological disorders to aid psychiatrists in their assessment and treatment of patients.”

The Research Domain Criteria (RDoC) initiative of NIMH emphasizes the importance of objective measurements in psychiatry. This field, often referred to as “computational psychiatry”, aims to use modern technology and data driven approaches to improve evidence-based medical decision making in psychiatry, a field that often relies upon subjective evaluation approaches.

As part of the ongoing partnership, researchers will continue to investigate areas and connections in the brain that hold significant links to schizophrenia. Work will continue on improving the algorithms by conducting machine learning analysis on larger datasets, and by exploring ways to extend these techniques to other psychiatric disorders such as depression or post-traumatic stress disorder.

UAlberta Expertise Brings DeepMind Lab to Edmonton

In an historic move for the AI community, one of the world’s leading AI research companies, DeepMind, will open its first international research base outside the United Kingdom later this month. The lab will be based in Edmonton and have close ties to the University of Alberta, a research-intensive university with an illustrious record of AI research excellence.

The new lab, to be called DeepMind Alberta, demonstrates DeepMind’s commitment to accelerating Alberta’s and Canada’s AI research community. It also signals the strength of ties between the University of Alberta and one of the world’s leading AI companies. Having been acquired by Google in 2014, DeepMind is now part of Alphabet. DeepMind is on a scientific mission to push the boundaries of AI, developing programs that can learn to solve complex problems without being taught how. DeepMind Alberta will open with 10 employees.

The DeepMind Alberta team will be led by UAlberta computing science professors Richard Sutton, Michael Bowling, and Patrick Pilarski. All three, who will remain with the Alberta Machine Intelligence Institute at UAlberta, will also continue teaching and supervising graduate students at the university to further foster the Canadian AI talent pipeline and grow the country’s technology ecosystem. The team will be completed by seven more researchers, many of whom were also authors on the influential DeepStack paper published earlier this year in Science.

UAlberta’s connections to DeepMind run deep with roughly a dozen UAlberta alumni already working at the company, some of whom played important roles in some of DeepMind’s signature advances with reinforcement learning in AlphaGo and Atari. In addition, one of the world’s most renowned computing scientists, Sutton was DeepMind’s first advisor when the company was just a handful of people.

“I first met with Rich—our first ever advisor—seven years ago when DeepMind was just a handful of people with a big idea. He saw our potential and encouraged us from day one. So when we chose to set up our first international AI research office, the obvious choice was his base in Edmonton, in close collaboration with the University of Alberta, which has become a leader in reinforcement learning research thanks to his pioneering work,” said Demis Hassabis, CEO and co-founder of DeepMind. “I am very excited to be working with Rich, Mike, Patrick and their team, together with UAlberta, and I look forward to us making many more scientific breakthroughs together in the years ahead.”

Sutton is excited about the opportunity to combine the strength of DeepMind’s work in reinforcement learning with UAlberta’s academic excellence, all without having to leave Edmonton.

“DeepMind has taken this reinforcement learning approach right from the very beginning, and the University of Alberta is the world’s academic leader in reinforcement learning, so it’s very natural that we should work together,” said Sutton. “And as a bonus, we get to do it without moving.”

Working with Hassabis and the DeepMind team both in London and Edmonton, Sutton, Bowling, and Pilarski will combine their staggering academic strength in reinforcement learning to focus on basic AI research. Reinforcement learning functions similarly to the same way humans learn, trying to replicate good outcomes and avoid bad outcomes based on learned experiences.

The DeepMind Alberta announcement is the latest in a slate of AI-related successes for UAlberta. The recent major funding infusion via the federal government’s Pan-Canadian Artificial Intelligence Strategy strengthens the Alberta government’s 15-year investment of more than $40 million. DeepMind Alberta is a further signal that industry is taking notice of UAlberta and its boundary-pushing research.

About the Researchers

A professor in the Department of Computing Science in the University of Alberta’s Faculty of Science, Michael Bowling is best known for his research in poker, most notably with two milestone discoveries, both published in Science, Cepheus in 2015, which solved heads-up limit Texas hold’em followed by DeepStack in late 2016, which achieves professional-level play in heads-up no limit Texas hold’em.

Patrick Pilarski is the Canada Research Chair in Machine Intelligence for Rehabilitation and an assistant professor in the Department of Medicine (Division of Physical Medicine and Rehabilitation). His research interests include reinforcement learning, real-time machine learning, human-machine interaction, rehabilitation technology, and assistive robotics.

A professor in the Department of Computing Science in the University of Alberta’s Faculty of Science, Richard Sutton is world-renowned for his foundational research in reinforcement learning –he literally wrote the textbook–in which machines learn based on their environment. His landmark work has developed the area of temporal difference learning, which uses the future as a source of information for predictions, and also explores off-policy learning, or learning from actions not taken.

University of Alberta computing science professors and artificial intelligence researchers (L to R) Richard Sutton, Michael Bowling, and Patrick Pilarski are working with DeepMind to open the AI powerhouse company’s first research lab outside the United Kingdom in Edmonton, Canada.
Credit: John Ulan

UAlberta to Push Critical Areas of Research for the Future of All Canadians

EDMONTON (March 23, 2017)—In a move that will boost artificial intelligence (AI) research across the country, the Government of Canada announced Wednesday the funding of a pan-Canadian AI Strategy to enhance research and recruit talent. Administered through the Canadian Institute for Advanced Research (CIFAR), the $125 million program will promote collaboration between post-secondary institutions in Montréal, Toronto-Waterloo, and Edmonton.

“Our University of Alberta researchers have been world leaders in artificial intelligence for decades. I’m very pleased the government has moved forward and invested in this absolutely critical area for the future of all Canadians,” says University of Alberta President David Turpin.

With applications as diverse as enhanced medical diagnoses to self-driving cars, artificial intelligence is a continually growing area of research with the potential to transform all facets of society. The field already attracts investment from major technology players like Google, Facebook and Amazon. The global market for artificial intelligence-related products is expected to reach $47 billion by 2020.

“Canadian universities train some of the best AI researchers in the world,” says Cameron Schuler, Executive Director of the Alberta Machine Intelligence Institute (Amii), housed at the University of Alberta. “With this latest investment, Canada will build on existing strengths to retain and attract talented individuals, drive innovation and advances in industry, and take our place on the global stage as leaders in AI.”

The strategy aims to further develop Canada’s AI ecosystem and position the country as a world-leading destination for companies seeking to invest in artificial intelligence and innovation. “This investment in deep AI builds on Canada’s strength as a pioneer in AI research and will provide a strong foundation for Canada to build on its global leadership in this important and exciting field,” says Alan Bernstein, President and CEO of CIFAR.

In addition to retaining top talent, enhancing recruitment and training across Canada, the new funding will enable further collaborations between industry and academic institutions. Some of the recent industry collaborations at the University of Alberta include research partnerships, with large companies like RBC, and project-based ones, such as optimizing control systems with Edmonton-based companies like ISL Engineering and Willowglen Systems.

“There is some truly fascinating AI research coming out of Canada,” says Richard Sutton, professor of computing science in the University of Alberta’s Faculty of Science and researcher at Amii, world-renowned for his boundary pushing research in reinforcement learning. “Canada is punching above its weight in the field, and we’re thrilled the federal government is committed to building on this strong base. We’ve only scratched the surface of what AI can do and are excited to unleash even greater possibilities in deep reinforcement learning.”

Skill Trumps Luck: DeepStack the First Computer Program to Outplay Human Professionals at Heads-Up No-Limit Texas Hold’em Poker

EDMONTON (March 2, 2017)—A team of computing scientists from the University of Alberta’s Computer Poker Research Group is once again capturing the world’s collective fascination with artificial intelligence. In a historic result for the flourishing AI research community, the team—which includes researchers from Charles University and Czech Technical University in Prague—has developed an AI system called DeepStack that defeated professional poker players in December 2016.  The landmark findings have just been published in Science, one of the world’s most prestigious peer-reviewed scientific journals.

DeepStack bridges the gap between approaches used for games of perfect information—like those used in checkers, chess, and Go—with those used for imperfect information games, reasoning while it plays using “intuition” honed through deep learning to reassess its strategy with each decision.

“Poker has been a longstanding challenge problem in artificial intelligence,” says Michael Bowling, professor in the University of Alberta’s Faculty of Science and principal investigator on the study. “It is the quintessential game of imperfect information in the sense that the players don’t have the same information or share the same perspective while they’re playing.”

Don’t let the name fool you: imperfect information games are serious business. These “games” are a general mathematical model that describe how decision-makers interact. Artificial intelligence research has a storied history of using parlour games to study these models, but attention has been focused primarily on perfect information games. “We need new AI techniques that can handle cases where decision-makers have different perspectives,” says Bowling, explaining that developing techniques to solve imperfect information games will have applications well beyond the poker table.

“Think of any real world problem. We all have a slightly different perspective of what’s going on, much like each player only knowing their own cards in a game of poker.” Immediate applications include making robust medical treatment recommendations, strategic defense planning, and negotiation.

This latest discovery builds on an already impressive body of research findings about artificial intelligence and imperfect information games that stretches back to the creation of the University of Alberta’s Computer Poker Research Group in 1996. Bowling, who became the group’s principal investigator in 2006, has led the group to several milestones for artificial intelligence. He and his colleagues developed Polaris in 2008, beating top poker players at heads-up limit Texas hold’em poker. They then went on to solve heads-up limit hold’em with Cepheus, published in 2015 in Science.

DeepStack extends the ability to think about each situation during play—which has been famously successful in games like checkers, chess, and Go—to imperfect information games using a technique called continual re-solving. This allows DeepStack to determine the correct strategy for a particular poker situation without thinking about the entire game by using its “intuition” to evaluate how the game might play out in the near future.

“We train our system to learn the value of situations,” says Bowling. “Each situation itself is a mini poker game. Instead of solving one big poker game, it solves millions of these little poker games, each one helping the system to refine its intuition of how the game of poker works.  And this intuition is the fuel behind how DeepStack plays the full game.”

Thinking about each situation as it arises is important for complex problems like heads-up no-limit hold’em, which has vastly more unique situations than there are atoms in the universe, largely due to players’ ability to wager different amounts including the dramatic “all-in.” Despite the game’s complexity, DeepStack takes action at human speed—with an average of only three seconds of “thinking” time—and can run on a simple gaming laptop using an Nvidia GPU for computation.

To test the approach, DeepStack played against a pool of professional poker players in December, 2016, recruited by the International Federation of Poker. Thirty-three players from 17 countries were recruited, with each asked to play a 3000-hand match over a period of four weeks. DeepStack beat each of the 11 players who finished their match, with only one outside the margin of statistical significance, making it the first computer program to beat professional players in heads-up no-limit Texas hold’em poker.

“DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker” was published online by the journal Science on Thursday, March 2, 2017.

TORONTO, January 18, 2017 — Following recent investments in artificial intelligence (AI) and machine learning, RBC today announced Dr. Richard S. Sutton, one of the modern day pioneers of AI, as head academic advisor to RBC Research in machine learning. RBC Research will establish a new lab and plan to work with the Alberta Machine Intelligence Institute (Amii), based at the University of Alberta, to identify and pursue further research collaboration opportunities on an ongoing basis.

“We are thrilled to be opening a lab in Edmonton and to collaborate with world-class scientists like Dr. Sutton and the other researchers at Amii,” said Dr. Foteini Agrafioti, head of RBC Research. “RBC Research has built strong capabilities in deep-learning, and with this expansion, we are well poised to play a major role in advancing research in AI and impact the future of banking.”

Dr. Sutton is widely recognized for his work in reinforcement learning, an area of machine learning that focuses on making predictions without historical data or explicit examples. Reinforcement learning techniques have been shown to be particularly powerful in determining ideal behaviours in complex environments. Most recently, the techniques were used to secure a first-ever victory over a human world-champion in the game of Go, as well as recent applications in robotics and self-driving cars.

“The collaboration between RBC Research and Amii will help support the development of an AI ecosystem in Canada that will push the boundaries of academic knowledge,” said Dr. Sutton. “With RBC’s continued support, we will cultivate the next generation of computer scientists who will develop innovative solutions to the toughest challenges facing Canada and beyond. We’ve only scratched the surface of what reinforcement learning can do in finance and are excited to unleash even greater possibilities with this collaboration between RBC Research and Amii.”

“RBC is committed to helping build Canada’s digital future and our significant investments in AI represent part of that commitment,” said Gabriel Woo, vice-president of innovation at RBC. “We believe AI has the potential to bring about major improvements in areas such as client service, fraud prevention and risk management; advancements that will have far-reaching benefits in financial services and beyond. Partnering with a leading institution like the University of Alberta is an important step forward as we continue to explore this emerging technology.”

RBC Research is also collaborating with the University of Alberta to provide opportunities like internships, academic collaborations and exchanges with the Toronto-based research team to students and researchers. Dr. Eirene Seiradaki, academic partnerships lead at RBC, will be the key contact between RBC Research and professors, researchers and students interested in using machine learning to drive innovation in banking. With almost 20 years of experience in academics, Dr. Seiradaki joined RBC in 2016 and brings a strong commitment to fostering innovation and supporting the academic community.

RBC recently announced two additional initiatives in collaboration with the University of Toronto, ensuring Canada remains a leading centre of development in machine learning and AI.

Amii News

From AICML to Amii

Introducing Amii

We’re thrilled to introduce you to Amii, the Alberta Machine Intelligence Institute, a world-leading team of machine intelligence researchers housed at the University of Alberta.

We originally started in 2002 as AICML (the Alberta Innovates Centre for Machine Learning), specializing in advanced research and development in the fields of artificial intelligence (AI) and machine learning, together called machine intelligence.

As a research institute based out of the Department of Computing Science, we push the bounds of academic knowledge and develop innovative solutions for some of the toughest challenges facing Alberta and beyond.

With the launch of our new brand, we are reaffirming our commitment to creating and discovering the future of machine intelligence.

Driving Innovations in Research

Our team of 11 researchers conduct advanced research in areas such as reinforcement learning, algorithmic game theory, data science and health informatics, among others.

Many will recognize our team’s contributions to the varied field of machine intelligence.

In 2007, we solved checkers, a long-standing challenge problem for AI researchers, and in 2015, we produced the first AI agent capable of playing an essentially-perfect game of heads-up limit hold’em poker. Through the Arcade Learning Environment, we’ve encouraged researchers around the world to adopt a new challenge problem focused on Atari 2600 games.

Outside of AI challenge problems, we recently launched PFM Scheduling Services, which revolutionizes the way scheduling is done in union environments. We’ve also produced leading-edge innovations toward the diagnosis of tuberculosis and ADHD, and we work to enhance the lives of people with upper-body amputations through intelligent artificial limbs.

Through these and a number of other projects, we continue to push forward fundamental understanding of machine intelligence algorithms, architectures and applications.

Delivering Intelligent Business Solutions

In launching our new website, www.amii.ca, we’re also stepping up our efforts to deliver innovative applications of machine intelligence to businesses in Alberta and beyond.

We collaborate with organizations of all types and sizes to develop machine intelligence solutions that meet specific business challenges. And we provide intelligent tools that can enable an organization to predict trends and patterns, analyze and classify data or optimize and automate processes.

We also recently launched our Industrial Affiliate Program, which provides an opportunity for a deeper level of engagement with Amii’s experts. Through facilitated interactions, Affiliates can gain enhanced access to our world-leading researchers and students and also discover the latest advancements in machine intelligence from the international research community.

Whether you’re looking to enhance your business, enable scientific discovery or understand the next wave of advanced computing, Amii can help.

Contact us and discover the future of machine intelligence.