Edmonton Startup Week 2019 is imminent, and we couldn’t be more excited to participate! From October 21 to 25, attend workshops, socials, and events geared towards building momentum and opportunity around Edmonton’s unique entrepreneurial identity, startup community and culture of innovation. 

Here is where you can catch the Amii team:

Tech on Tap: Machine Learning Mishaps with ATB & Amii

October 21, 4 – 5 p.m. | Mercer Tavern (10363 104 St NW)

Start your Startup Week in the best way possible by joining ATB and Amii for a special happy hour event at Mercer Tavern. Join us for some great conversations, some awesome craft beer, and a light-hearted presentation from Cathy King (Director, Amii Educates) and David Chan (Director, Amii Innovates). RSVP Here!

Artificial Intelligence in Edmonton

October 22, 12 – 1 p.m. | CBC Edmonton Stage (123 City Centre Mall, 10062 102 Ave)

Sit down with Cory Janssen (CEO of AltaML), Craig Knox (CTO of DrugBank) and Patrick Pilarski (Amii Fellow and Associate Professor at UAlberta) to learn about the real life ways that any industry can integrate AI into their company. Whether it be to create internal efficiencies, optimize a business process, or advance and scale their operations, these contributors to AI in Edmonton will chat about unsexy AI and the integral role it plays in innovation. RSVP Here!

Machine Learning 101

October 24, 12 – 1 p.m. | Startup Edmonton (301 – 10359 104 St NW)

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not. How can we make sense of it all? Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business. RSVP Here!

In Search of Edmonton’s Next Tech Unicorn

October 24, 1 – 5 p.m. | World Trade Centre (#200 – 9990 Jasper Avenue)

Are you interested in investing in tech but don’t know where to start? Don’t know the difference between pre-seed, seed or series A, B or C investment rounds? Would you like to hear from veteran tech investors about how to pick winners or winning teams? Interested in meeting some of Edmonton’s leading tech company founders that are at the forefront of Canadian innovation success? Join us for an engaging and interactive afternoon discussing how to invest directly in some of Edmonton’s best technology companies, featuring Amii Fellow and Professor at UAlberta, Rich Sutton! RSVP Here!

AI Seminar: Building Meaningful Educational Testing Software through UX Design and AI

October 25, 12 – 1 p.m. | CSC 3-33, University of Alberta (8900 114 St NW)

These weekly seminars (free pizza lunch provided) give AI enthusiasts a friendly way of engaging with the latest topics and trends in AI research and development. This week, Mike Priest of TenSpeed Technologies presents on their use of AI to provide deeper insights into candidate intelligence while tracking down potential examination fraud. RSVP Here!

Ladies Learning Code: YEGTech Open House (For All Ages)

October 26, 10 a.m. – 4 p.m. | Startup Edmonton (301 – 10359 104 St NW)

This Halloween-themed event gathers together Edmonton tech community groups, meetups, non-profits and businesses – including Amii, represented by Anna Koop (Director, Amii Explores). Try out tons of rad activities while getting to know the people behind Edmonton’s thriving tech community! Look for opportunities to collaborate and possibly recruit new members or employees – plus indulge in some costumes and candy. RSVP Here!

Can’t make it to these events? Join us at Hello, Amii in Calgary on November 6 or Hello, Amii in Edmonton on November 14!


Bonus Event: Launch Party 10

October 24, 6:30 – 10:30 p.m. | Startup Edmonton (301 – 10359 104 St NW)

Many members of the Amii team will be milling about the tenth edition of Launch Party Edmonton, the city’s flagship startup event that celebrates and showcases the hottest startups in town. Launch Party isn’t your typical networking event or trade show. It’s a party designed to celebrate and showcase the rockstar entrepreneurs in our community. Drinks, DJs, and great company all await you at Launch Party! Purchase Tickets Here!

EDMONTON, AB (October 17, 2019) – Applied Pharmaceutical Innovation (API) and Alberta Machine Intelligence Institute (Amii) have announced a collaboration via Memorandum of Understanding to leverage each other’s combined expertise to promote a singular service offering at the intersection of drug development and machine learning/artificial intelligence. Together, API and Amii will explore opportunities to collaborate on an ongoing basis and support each other’s efforts in the development of a broader innovation ecosystem.

“We’re really excited about the collaboration with API,“ says John Shillington, President and CEO of Amii. “Drug development is an enormously complex industry, and many of its challenges can now be tackled using machine intelligence. By working with API we’re thrilled to explore ways of collaborating that leverage our combined expertise in a way that is second to none.”

API builds translational teams in pharmaceutical sciences and drug development to support industry and innovators, training students on industry projects at the pace of industry while pulling together the expertise of Canadian research-intensive institutions. Together with the help of Amii, API will be able to explore applications of AI with API’s industry partners in a wide range of areas from early-stage drug design, to clinical trials and beyond.

The memorandum is one that recognizes Amii and API as global leaders in the space. API’s network of members includes global top fifteen expertise in applied pharmaceutical sciences and drug development. When combined with Amii’s position, helping to make the University of Alberta one of the global top five AI and ML institutes, the two organizations are arguably making Alberta the number one place in the world for the application of AI in drug development.

“The combination of machine intelligence with the drug development process has endless possibilities,” says API CEO Andrew MacIsaac. “Through our agreement with Amii, we want our teams to create and find solutions that will get life-saving drugs to the people that need it faster and more efficiently than ever before.”

About Applied Pharmaceutical Innovation

API is a not-for-profit that works in collaboration with the University of Alberta’s Faculty of Pharmacy and Pharmaceutical Sciences as well as research and post-secondary institutions across Alberta and beyond, with the goal of building a sustainable and vibrant pharmaceutical sector in Canada and establishing Alberta as a world-leading hub for pharmaceutical innovation and commercialization. API draws on an interdisciplinary network of over 30 pharmaceutical scientists, clinicians, regulatory, patent, and market experts in a variety of fields and disease areas to bring life-saving research to the real world.  www.appliedpharma.ca.

About Alberta Machine Intelligence Institute

One of Canada’s leading AI institutes, Amii drives advanced research in machine intelligence at the University of Alberta and other academic institutions and leverages scientific expertise to advance state-of-the-art industry research, enable businesses to build their internal machine learning capabilities and grow Alberta’s AI workforce. Visit amii.ca for more information, or view our fact sheet.

See the original media release on the API website.

One of Canada’s three main institutes for artificial intelligence (AI), the ​Alberta Machine Intelligence Institute (Amii)​ is a global leader in AI and machine learning (ML). Our world-renowned researchers drive fundamental and applied research at the University of Alberta and train some of the world’s top talent while our team of expert applied science team works collaboratively with Alberta-based businesses to generate economic impact. Amii engages with a host of community stakeholders through ongoing workshops, seminars, meetups, and upskilling programs.

We believe machine intelligence is poised to be the primary driver for sustainable growth for Alberta’s economy. As an Amii Data Scientist, you’ll use your skills in programming, statistics, and visual communication to directly impact Alberta businesses by supporting the development of ML models, evaluating data resources, and directing project definition for applied ML. Working closely with our team of Machine Learning Scientists, you will help empower our partner companies (Innovation Affiliates), with the knowledge and skills they need to drive a successful machine intelligence strategy and ensure the right ML resources and techniques are used on their internal projects.

Role Summary

An Amii Data Scientist provides support to the Machine Learning Scientists on data analysis and integration for client engagements. Primary work includes data acquisition, preprocessing, exploratory analysis and documentation of the findings. Asking the right questions and determining an effective path to analyze and interpret the data are key components of the position. An Amii Data Scientist works with current and evolving data science tools and techniques to develop appropriate descriptive and prescriptive analysis.

Problem-solving

Data science requires creative and analytical problem-solving skills with an attention to detail, including experience in understanding the complexity involved in turning data into conclusions. The selected candidate should be able to understand the strengths, weaknesses, and limitations of certain datasets and make inferences on the readiness of the data to build ML solutions.

Relationship with Stakeholders

The selected candidate will work closely with the Machine Learning Scientists and external project partners to ensure that information and deliverables are clearly communicated as required.

Qualifications
  • At least one year of MSc. or PhD. in CS
  • Proficient in Python and Jupyter Notebooks
  • Solid understanding of data exploration techniques – specifically data pre-processing, data validation and exploratory data analysis
  • Ability to quickly grasp the business problem and arrive at solutions for making data-driven decisions
  • Industrial experience in data engineering, software development and/or data analysis is an added advantage 
  • Good oral and written communication skills
  • Team player enthusiastic about working together to achieve excellence
  • Capable of critical and independent thinking, with a sense of  curiosity and the desire to learn new things, techniques, and technologies

Job Type: 4-5 weeks contract position

Salary: $50/hr

Work Duration: Expected 20 hours per week

How to Apply: Send your resume to luke@amii.ca with the subject “Amii-DS-PVP”

Community & Events

Event Round-Up | October 2019

Amii Events

Meet members of the Amii team, connect with like-minded people, and learn the latest about what’s happening in machine intelligence at Amii events! Here’s where we’ll be this month:

Hello Amii!

Our Amii Innovates program has one goal: to build your internal capacity for machine learning. Business adoption of machine intelligence has grown by 270% in the past four years with an estimated 37% of companies implementing machine intelligence in some form. Join us at Hello Amii to discover whether you’re ready to join their ranks and take the next steps of building your business’ internal capacity.

October 15 – Calgary
Register today!
12 – 1 p.m. 
University of Alberta – Calgary Centre 
333 5 Ave SW 
Calgary, AB T2P 3B6  

October 17 – Edmonton
Register today!
12 – 1 p.m. 
Amii HQ 
#1101, 10065 Jasper Ave
Edmonton, AB T5J 3B1

Machine Learning 101

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not. How can we make sense of it all? Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

October 24 – Edmonton
Register today!
12 – 1 p.m. 
Startup Edmonton 
#301, 10359 104 St NW 
Edmonton, AB T5J 3B1  


In the Community

Members of the Amii team are proud to support Alberta’s innovation community. You can find us at the following events:

Eric Geddes Lecture – Artificial Intelligence: Using AI in Your Business

The Geddes Lecture Series features leaders from both the private and public sectors, in addition to bringing some of Alberta’s world-class researchers and their findings to the community, with the goal of promoting awareness and discussion on timely, impactful, and relevant business topics. This talk will feature Amii’s Director of Amii Explores, Anna Koop, Amii Fellow Patrick Pilarski, as well as AltaML Co-founder/CEO Cory Janssen and ATB President and CEO Curtis Stange.

October 3 – Edmonton
RSVP today!
11:30 a.m. – 1:30 p.m. 
Royal Alberta Museum 
9810 103 A Ave NW, Edmonton 

Edmonton Startup Week

Amii will be involved in several events during Edmonton Startup Week, happening October 21 – 25, 2019. Now in its tenth year, Edmonton Startup Week features workshops, socials and events which build momentum and opportunity around our city’s unique entrepreneurial identity, startup community and culture of innovation. We will be doing a special post on Startup Week as it draws closer, so stay tuned!


Educational Opportunities

Amii Educates aims to boost machine intelligence skills and literacy. Here are the programs currently being offered:

Amii & UAlberta Faculty of Extension – Preparing Your Business for Machine Learning

What areas of your business can benefit from Machine Learning? What factors should you take into account when exploring a ML project for your organization? Gain conceptual and practical knowledge of ML management as you learn how to define an ML problem, understand risk and data needs, and get ready to plan for ML business applications. By the end of this course you will have a working knowledge of the Machine Learning Canvas process.

October 23 – 25 – Edmonton
Register today!
8:30 a.m. – 5 p.m.
10230 Jasper Ave
University of Alberta Extension
Edmonton, AB T5J 4P6

Coursera – Machine Learning: Algorithms in the Real World Specialization

Taught by Director of Amii Explores, Anna Koop, this specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.

Register today!


AI Seminars

Keep up to date on research coming out of the University of Alberta and beyond! The Artificial Intelligence Seminar is a weekly meeting where researchers interested in AI can share their research. Organized by and hosted at the University of Alberta, each AI Seminar happens (unless otherwise specified) at 12 – 1 pm in the Computing Science Center, CSC B-10 (floorplan). Plus, pizza is provided for all attendees!

Keep up to date with the AI Seminars by subscribing to the AI Seminar Speakers Google Calendar.

Amii Innovates launches, guides AI adoption in Alberta businesses

Amii announces first cohort of Innovation Affiliates, unveils program offerings

EDMONTON, AB (September 12, 2019) – The Alberta Machine Intelligence Institute (Amii) is pleased to announce the launch of Amii Innovates, a program which guides teams and businesses on the path to AI adoption. One of four program areas within Amii, Amii Innovates works closely with Alberta-based businesses to grow their internal machine intelligence capabilities.

Amii’s Innovation Affiliates were chosen through a highly selective application process based on their readiness for machine intelligence adoption and potential for commercial success. Amii has worked collaboratively with these 23 companies over the past year, four of which have already become alumni.

“We’re proud to work with organizations that understand the transformative potential of machine intelligence across every sector, and who are working to innovate within their industries,” says John Shillington, President and CEO of Amii. “We strongly believe that machine intelligence will be the primary driver of sustainable growth for Alberta’s economy, and that this program will help bring our province’s bright future into focus.”

“In keeping with the high standard of providing leading edge trading software, our company is pleased to have partnered with Amii to work towards expanding our internal AI capacity,” says Tim Gunn, President of Net Energy Exchange (NE2). “Working with Amii has substantially expanded our company’s knowledge in the area of Machine Learning. This knowledge has enabled our company to begin hiring and training our own AI support team, paving our way into the future.”

The first cohort of Innovation Affiliates includes:

  • 2S Water
  • AIMCo (alumnus)
  • Alberta Biodiversity Monitoring Institute (alumnus)
  • ARC Resources
  • The Climate Corporation (alumnus)
  • Cognitive Diagnosis
  • Dot Technology Corp.
  • Drugbank
  • EHS Analytics
  • FORCORP Solutions
  • Frettable
  • Hoot Research
  • Imperial Oil Limited
  • Integral Engineering
  • Medo.AI
  • Mikata Health Inc.
  • Net Energy Exchange (NE2)
  • OKAKI
  • SAM
  • Shell Scotford Refinery (alumnus)
  • Synauta Inc.
  • Testfire Labs
  • Willowglen Systems Inc.

To mark the occasion, Amii will bring together Innovation Affiliates and members of business and technology communities for Amii Innovates launch events in Edmonton and Calgary. These special events will spotlight the first cohort of Innovation Affiliates, feature other Amii partner businesses, and officially unveil the Amii Innovates program offerings.

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About Amii: One of Canada’s leading AI institutes, Amii drives advanced research in machine intelligence at the University of Alberta and other academic institutions and leverages scientific expertise to advance state-of-the-art industry research, enable businesses to build their internal machine learning capabilities and grow Alberta’s AI workforce. Visit amii.ca for more information, or view our fact sheet.

Editor’s note: In the initial release, we reported that we had been working with 24 companies; this number is actually 23. We apologize for the miscommunication.

DLRL Summer School students and faculty pose together on the final day of class
DLRL Summer School students and faculty on the final day of class
Wrapping up an exciting two weeks of AI excellence in Alberta: 2019 DLRL Summer School

The 2019 CIFAR Deep Learning & Reinforcement Learning Summer School has concluded. Hosted by Amii and CIFAR from July 24 to August 2, 2019, this amazing and inspiring two weeks brought together the world’s brightest graduate students, post-docs and professionals to cover the foundational research, new developments and real-world applications of deep learning and reinforcement learning.

Highlights of the event include:

  • Over 1200 applicants from 75 countries
  • 300 attendees from 36 countries
  • 113 women attendees
  • 128 participants from outside of Canada (including 28 from developing nations)
  • Over 25 speakers
  • More than 90 hours of educational sessions and social events
  • 40 participating organizations at the Career Fair
  • Over $300,000 in corporate sponsorship

Prior to DLRL Summer School, the inaugural Summer Institute on AI and Society was held from July 21 to 24. Co-convened by CIFAR, the AI PULSE program at UCLA School of Law, and Amii, Summer Institute brought together 40 interdisciplinary experts for engaging conversations and productive workshops on the impacts and effects of AI in society.

Check out some highlights from the event using the hashtag #DLRLSS or via Amii’s Twitter moments of Week One and Week Two!

This story was featured in the AICan Bulletin. Subscribe to the bi-monthly email publication to keep up to date on AI in Canada.  


Conclusion de deux semaines d’excellence en IA en Alberta : École d’été sur l’apprentissage profond et l’apprentissage par renforcement 2019 du CIFAR

L’École d’été sur l’apprentissage profond et l’apprentissage par renforcement 2019 du CIFAR, organisée par l’Amii et le CIFAR, a attiré 300 des plus brillants étudiants diplômés et postdoctorants de 36 pays qui ont pu découvrir les recherches de pointe menées par les plus grands chercheurs du Canada sur l’apprentissage profond et l’apprentissage par renforcement. 

Le tout premier Institut d’été sur l’IA et la société s’est tenu du 21 au 24 juillet, juste avant l’École d’été DLRL. Organisé conjointement par le CIFAR, le programme AI PULSE de l’École de droit de l’Université de la Californie à Los Angeles et l’Amii, l’Institut d’été a réuni 40 experts interdisciplinaires qui ont pris part à des conversations stimulantes et à des ateliers productifs sur les impacts et les effets de l’IA sur la société.

Jetez un coup d’œil à certains des faits saillants de l’événement à l’aide du mot-clic #DLRLSS ou par l’entremise des moments Twitter de l’Amii, Première semaine et Deuxième semaine!

Cet article a été publié dans le Bulletin IACan. Abonnez-vous à la publication électronique bimestrielle pour rester au fait des plus récentes nouvelles en IA au Canada.

Amii is pleased to announce the launch of two massive open online courses (MOOCs) on Coursera! Take top-tier AI courses taught by leaders in the field. Best of all? You can try before you buy with a 7-day free trial. Learn more about each course below:


Machine Learning: Algorithms in the Real World Specialization

Machine Learning: Algorithms in the Real World specialization is offered by Amii, and taught by our Senior Scientific Advisor, Anna Koop. This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.

After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning.


Reinforcement Learning Specialization

Reinforcement Learning Specialization is offered by the University of Alberta and Amii, and taught by Amii Fellows at UAlberta, Martha White and Adam White. This specialization explores the power of adaptive learning systems and artificial intelligence (AI). Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end.

After completing all four courses, learners will understand the foundations of much of modern probabilistic AI and be prepared to take more advanced courses, or to apply AI tools and ideas to real-world problems. This content will focus on “small-scale” problems in order to understand the foundations of RL, as taught by world-renowned experts at the University of Alberta.

The tools learned in this specialization can be applied to game development (AI), customer interaction (how a website interacts with customers), smart assistants, recommender systems, supply chain, industrial control, finance, oil & gas pipelines, industrial control systems and more.

The tools learned in this specialization can be applied to game development (AI), customer interaction (how a website interacts with customers), smart assistants, recommender systems, supply chain, industrial control, finance, oil & gas pipelines, industrial control systems and more.


The world’s top AI talent convene in Edmonton for the DLRL Summer School

EDMONTON, AB (July 24, 2019) – Classes are now in session at the CIFAR Deep Learning and Reinforcement Learning Summer School (DLRL Summer School). The Alberta Machine Intelligence Institute (Amii) and CIFAR are excited to welcome the brightest minds in artificial intelligence (AI) to learn at the University of Alberta in Edmonton from July 24 to August 2, 2019. The event brings together graduate students, post-docs and professionals to cover the foundational research, new developments and real-world applications of deep learning and reinforcement learning – two key areas of AI research.

“We are thrilled to kick off the 15th annual DLRL Summer School in partnership with Amii, Mila and the Vector Institute,” says Dr. Elissa Strome, AVP Research & Executive Director of the Pan-Canadian AI Strategy. “Every year, the DLRL Summer School attracts hundreds of the brightest students from around the world to learn from prominent leaders in AI. This supports the Pan-Canadian AI Strategy’s goals of increasing the number of AI researchers and skilled graduates in Canada.”

Over 1200 individuals from 75 countries applied to this year’s DLRL Summer School. Of this number, only 300 individuals were accepted, representing 36 countries; approximately 57% of attendees are Canadian, and 28 students are attending from developing countries.

“We are proud to be showcasing Alberta’s innovation community, including our accomplished researchers, brilliant students, and world-class AI-enabled startups and businesses,” says John Shillington, President and CEO of Amii. “Over the next ten days, we will show the global AI community how innovative and full of potential this province is.”

This year’s DLRL Summer School also features a crossover event with the Summer Institute on AI and Society on July 24. Co-convened by CIFAR, the AI PULSE program at UCLA School of Law, and Amii, Summer Institute brings together experts, grad students and researchers to explore the societal, governmental, and ethical implications of AI. Participants of multiple backgrounds are represented, including political science, humanities, computing science and social sciences. 

The Deep Learning and Reinforcement Learning Summer School 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 for more information.

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Please follow this link for full Media Release & Backgrounder.
Please follow this link for b-roll and high-res photos of the opening morning.

Primary Media Contact: Spencer Murray, Director of Communications & Public Relations, Amii
t: 587.415.6100 | c: 780.991.7136 | e: spencer.murray@amii.ca

Secondary Media Contact: Krista Davidson, AI Communications Lead, CIFAR
c: 647.383.7218 | e: krista.davidson@cifar.ca


Les meilleurs talents en IA du monde se réunissent à Edmonton à l’École d’été APAR

EDMONTON, AB (24 juillet 2019) – Les cours ont commencé à l’École d’été sur l’apprentissage profond et l’apprentissage par renforcement (EEAPAR) du CIFAR. L’Alberta Machine Intelligence Institute (Amii) et le CIFAR sont heureux d’accueillir les plus brillants cerveaux dans le domaine de l’intelligence artificielle (IA) à l’Université de l’Alberta, à Edmonton, du 24 juillet au 2 août 2019. Cet événement réunit des étudiants diplômés, des postdoctorants et des professionnels pour traiter de la recherche fondamentale, des percées et des applications pratiques de l’apprentissage profond et de l’apprentissage par renforcement, deux secteurs clés de la recherche en IA.

« Nous sommes ravis de donner le coup d’envoi de la 15e édition de l’EEAPAR en partenariat avec Amii, Mila et l’Institut Vecteur », déclare Dre Elissa Strome, vice-présidente adjointe à la recherche et directrice exécutive de la Stratégie pancanadienne en matière d’IA. « Chaque année, l’EEAPAR attire des centaines d’étudiants parmi les plus brillants du monde qui souhaitent apprendre des chefs de file en IA. Cela soutient la Stratégie pancanadienne en matière d’IA qui vise à augmenter le nombre de chercheurs et de diplômés qualifiés en IA au Canada. »

Cette année, plus de 1 200 personnes de 75 pays se sont inscrites à l’EEAPAR. De ce nombre, seulement 300 personnes de 36 pays ont été acceptées ; environ 57 % des participants sont canadiens et 28 étudiants viennent de pays en développement.

« Nous sommes fiers de mettre en valeur la communauté albertaine de l’innovation composée de chercheurs chevronnés, de brillants étudiants ainsi que d’entreprises et de jeunes pousses en IA de calibre mondial », indique John Shillington, président et chef de la direction d’Amii. « Au cours des 10 prochains jours, nous montrerons à la communauté mondiale de l’IA l’immense potentiel et le remarquable esprit d’innovation de notre province. »

L’EEAPAR présente également le 24 juillet l’Institut d’été sur l’IA et la société, un événement conjoint organisé par le CIFAR, le programme AI PULSE de la Faculté de droit de l’UCLA et Amii. À cette occasion, des experts, des étudiants diplômés et des chercheurs exploreront les incidences sociétales, gouvernementales et éthiques de l’IA. L’événement réunira des participants de divers horizons, notamment en sciences politiques, en sciences humaines, en informatique et en sciences sociales.

L’École d’été sur l’apprentissage profond et l’apprentissage par renforcement est organisée par l’Amii et le CIFAR, avec la participation et le soutien des autres pôles d’IA du Canada : l’Institut Vecteur de Toronto et Mila de Montréal. Visitez le site www.dlrlsummerschool.ca (en anglais) pour plus de renseignements.

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Personne-ressource principale pour les médias : Spencer Murray, directeur, Communications et relations publiques, Amii
Tél. : 587 415-6100 | Cell. : 780 991-7136 | Courriel : spencer.murray@amii.ca

Personne-ressource secondaire pour les médias : Krista Davidson, responsable, Communications en IA, CIFAR
Cell. : 647 383-7218 | Courriel : krista.davidson@cifar.ca

The Greiner Lab, within the Alberta Machine Intelligence Institute (Amii) at the University of Alberta, is seeking strong researchers to hire as Postdoctoral Fellows.

Postdoctoral Fellows will help the Greiner Lab (along with medical researchers and clinicians) address a number of interesting and important medical-informatics tasks (including learning models for managing, screening, diagnosis, and/or prognosis) related to:

using technologies that include:

  • Metabolic profiles
  • Microarray / NGS / SNP / CNV, etc.
  • Clinical data
  • Images, scans, etc.

as well as foundational topics such as:

See also Possible Projects.

The ideal candidate has:

  • A PhD in Computer Science or a closely related field
  • A research record related to Machine Learning / Artificial Intelligence (eg, first-author papers at ICML, NeurIPS, UAI, AAAI, IJCAI)
  • Experience working on medical projects (eg, papers in medical/biological journals)

To apply, please email the following to rgreiner@ualberta.ca and use ‘PDF Medical Informatics 2019‘ as the subject of your email:

  • A cover letter, specifying which projects most interest you and indicating why you feel that you qualify (optionally, summarize how you would work on each such project)
  • Your CV, including a description of any previous research or industrial jobs you have held
  • Names and email addresses of at least 2 references
DLRL Summer School brings global AI experts to Canada

EDMONTON, AB (July 18, 2019) – The Alberta Machine Intelligence Institute (Amii) and CIFAR are excited to welcome the brightest minds in artificial intelligence (AI) to Edmonton for the 15th annual CIFAR Deep Learning and Reinforcement Learning Summer School (DLRLSS). The event brings together graduate students, post-docs and professionals to cover the foundational research, new developments and real-world applications of deep learning and reinforcement learning.  While the Summer School will be taking place at the University of Alberta in Edmonton from July 24 to August 2, 2019, there will be a host of additional events and opportunities for media engagement.

The Summer Institute on AI and Society | July 21 – 24; B-roll & Interviews by Request Only

The inaugural Summer Institute on AI and Society, co-convened by CIFAR, the AI PULSE program at UCLA School of Law, and Amii, takes place prior to the DLRLSS. Experts, grad students and researchers from multiple backgrounds will examine the societal, governmental, and ethical implications of AI through a combination of lectures, panels, and participatory problem-solving.

First Day of Class | July 24 @ 8:30 – 9:30 a.m. 
PCL Lounge & 1-430, Centennial Centre for Interdisciplinary Science, University of Alberta

Join the world’s brightest minds in AI as they experience their first day of DLRLSS classes. 

Improbotics | July 30 @ 7 – 9:30 p.m.
Myer Horowitz Theatre (8900 114 Street)

This tech-infused improvised comedy show features A.L.Ex. (the Artificial Language Experiment), the first artificial improvisor which uses advanced natural language processing and machine learning. A.L.Ex. will perform alongside University of Alberta Ph.D. graduate Kory Mathewson (Computing Science 2019, Amii) and Rapid Fire Theatre’s top improvisers.

Career Mixer presented by Alberta Innovates | July 31 @  5:30 – 9 p.m.
Hall D at the Edmonton Convention Centre (9797 Jasper Avenue)

Representatives leading companies including LG, DeepMind, Imperial Oil and Volkswagen; local corporations such as Alberta Innovates, Servus and AltaML; as well as local startups such as Medo.ai, Testfire Labs, CoParenter and Drugbank, will highlight local career opportunities for the world’s top talent.

The Deep Learning and Reinforcement Learning Summer School 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 for more information.

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Primary Media Contact: Spencer Murray, Director of Communications & Public Relations, Amii .
t: 587.415.6100 | c: 780.991.7136 | e: spencer.murray@amii.ca

Secondary Media Contact: Krista Davidson, AI Communications Lead, CIFAR
c: 647.383.7218 | e: krista.davidson@cifar.ca 


L’école d’été APAR attire des experts mondiaux en IA au Canada

EDMONTON, AB (18 juillet 2019) – L’Alberta Machine Intelligence Institute (Amii) et le CIFAR sont heureux d’accueillir, à Edmonton, les plus brillants cerveaux dans le domaine de l’intelligence artificielle (IA) à l’occasion de la 11e édition de l’École d’été sur l’apprentissage profond et l’apprentissage par renforcement (EEAPAR) du CIFAR. Cet événement réunit des étudiants diplômés, des postdoctorants et des professionnels pour traiter de la recherche fondamentale, des percées et des applications pratiques de l’apprentissage profond et de l’apprentissage par renforcement. Même si l’École d’été se tiendra à l’Université de l’Alberta, à Edmonton, du 24 juillet au 2 août 2019, il y aura une foule d’autres événements et de possibilités de participation des médias.

L’Institut d’été sur l’IA et la société | 21 au 24 juillet ; Rouleau B et entrevues sur demande seulement

Le premier Institut d’été sur l’IA et la société, organisé conjointement par le CIFAR, le programme AI PULSE de la Faculté de droit d’UCLA et l’Amii, se tiendra avant l’EEAPAR. Des experts, des étudiants diplômés et des chercheurs de divers horizons discuteront et débattront des incidences sociétales, gouvernementales et éthiques de l’IA par l’entremise d’une série de conférences, de tables rondes et d’ateliers participatifs de résolution de problèmes.

Premier jour de classe | 24 juillet – 8 h 30 à 9 h 30
Salon PCL et 1-430, Centennial Centre for Interdisciplinary Science, Université de l’Alberta

Joignez-vous aux plus brillants cerveaux dans le domaine de l’IA alors qu’ils vivent leur première journée de cours à l’EEAPAR.

Improbotics | 30 juillet – 19 h à 21 h 30
Théâtre Myer Horowitz (8900, 114e rue)

Ce spectacle de comédie improvisée imprégnée de technologie met en vedette A.L.Ex. (Artificial Language Experiment), le premier improvisateur artificiel, qui mise sur un traitement avancé du langage naturel et sur l’apprentissage automatique. A.L.Ex. se produira aux côtés de Kory Mathewson, titulaire d’un doctorat de l’Université de l’Alberta (Science informatique 2019, Amii) et des meilleurs improvisateurs de la troupe de théâtre Rapid Fire.

Réseautage carrière, présenté par Alberta Innovates | 31 juillet – 17 h 30 à 21 h
Salle D du Edmonton Convention Centre (9797, av. Jasper)

Des représentants d’entreprises de premier plan, dont LG, DeepMind, Imperial Oil et Volkswagen, de sociétés locales comme Alberta Innovates, Servus et AltaML, ainsi que d’entreprises en démarrage locales comme Medo.ai, Testfire Labs, CoParenter et Drugbank feront part des perspectives de carrières locales pour les meilleurs talents du monde.

L’École d’été sur l’apprentissage profond et l’apprentissage par renforcement est organisée par l’Amii et le CIFAR, avec la participation et le soutien des autres pôles d’IA du Canada : l’Institut Vecteur de Toronto et Mila de Montréal. Visitez le site www.dlrlsummerschool.ca (en anglais) pour plus de renseignements.

###

Personne-ressource principale pour les médias : Spencer Murray, directeur, Communications et relations publiques, Amii
Tél. : 587 415-6100 | Cell. : 780 991-7136 | Courriel : spencer.murray@amii.ca

Personne-ressource secondaire pour les médias : Krista Davidson, Responsible de communications de l’IA, CIFAR
Cell. : 647 383-7218 | Courriel : krista.davidson@cifar.ca

Amii is proud to once again sponsor the Competition on Legal Information Extraction and Entailment (COLIEE). By building a community of practice regarding legal information processing and textual entailment, COLIEE has been able to steadily advance the understanding of the process of applying AI to legal reasoning. Now in its sixth year, COLIEE takes place on June 21, 2019 in Montreal, and is run in association with the International Conference on Artificial Intelligence and Law (ICAIL) 2019.

Origins of COLIEE

How many competitions have begun in response to a failed bar exam? At least one. COLIEE was founded by long-time colleagues Randy Goebel (Amii Fellow and Professor at the University of Alberta), and his colleague Ken Satoh (Professor at the National Institute for Informatics).

“Ken and I had always worked on all kinds of applications of AI to reasoning in any domain. Legal reasoning was an early target for AI […] because it’s a domain in which there’s an attempt to be precise about how you write things in natural language,” says Goebel. “And Ken was so keen on this, that nine years ago […] he got very frustrated with trying to take the next step in applying AI to legal reasoning, so he took a law degree.”

Satoh completed a law degree at the University of Tokyo, while at the same time maintaining his position as a full-time professor at one of the most prestigious computer science departments in Japan. Once completed, he took the Japanese bar exams and failed – five times.

“COLIEE was born out of his frustration at the way the bar exams were administered,” explains Goebel. “He and I decided we could stage a competition. We could use Japanese bar law exams as examples with statute law in Japan and mount a competition to see how people could use AI to answer bar law exam questions.”

Since the competition was first staged, Satoh has passed the Japanese bar exams. Meanwhile, Goebel has accomplished the same, albeit with AI; he led a team which designed a program that passed the exams in 2017. But COLIEE still happens every year, growing in challenge and ambition. This year, Goebel and Satoh are just two of six coordinators, and a total of 18 teams are competing from 13 different countries, from the US to Botswana; Argentina to Germany.

The Tasks at Hand

Since its inception, the challenges have steadily increased in complexity; now, the competition includes two categories classified by legal concepts in statute law and case law. Those two categories each have two tasks: an information retrieval task and an entailment task. Teams have the option of submitting for one task, all four tasks, or any number in between.

The information retrieval tasks challenge a program to take a given test case and retrieve the related statutes or cases. The entailment tasks take it a step further.

“Entailment is really just saying: if this is a statute and this is a question, does the statute entail the question or not? [Editor’s note: the Dictionary.com definition of entail is “to cause or involve by necessity or as a consequence: e.g. a loss entailing no regret”] It’s the legal reasoning required to say, if you are wearing an expensive kimono and a bystander pushes you out of the way of a car that’s about the hit you […] is he liable for damages to the kimono?” says Goebel. “So we want to build computer programs that […] retrieve the appropriate statutes, then they have to find a connection.”

In other words, an entailment task requires a program to perform information retrieval, then create a yes/no argument for the test case based on the returned statutes or cases. In the example above, a program would be required to retrieve statutes related to property damage and liability, then determine whether or not the bystander would be liable for the damaged kimono.

The structure of the competition has accelerated research in this area in a unique way. COLIEE has built a community of people who are tackling similar challenges, and as a result, its participants have naturally developed a vocabulary that has quickened the process of exchanging information and ideas.

“It’s almost to that point at the COLIEE competition workshops […] people talk without even specifying. They say, ‘and here’s our approach to task one’. They don’t describe task one anymore.”

Explaining explainability

Explainability – the ability to determine how a model arrived at an answer – plays a large role in the entailment portion of the competition. Goebel’s lab, the Explainable AI (XAI) Lab out of the University of Alberta, is dedicated to this exact concept. Goebel’s lab is competing in COLIEE, and in this aspect, he has an advantage.

“Our lab has been tackling these two areas of medical reasoning and legal reasoning; we want to drive the science of AI forward. So we have an advantage to all of the people on the planet who, in an ad hoc way, apply learning of any kind to these domains, because we’ve been doing them for longer, and our focus is on making them explainable.”

Many machine learning models are challenged by the inability to explain how they arrive at decisions. For example, a model can take points of data and group them together based on a similarity it noticed, but it will not be able to articulate the similarity. Many refer to this issue in metaphor, calling them “black box” models.

Black box machine learning models can perform brilliant tasks – but in application, they can have serious consequences. If a model is assisting a doctor to recommend treatment, a judge to recommend sentencing, or a hiring manager to choose resumes, it is important to be able to determine why it is arriving at decisions.

“Explainability is as simple as saying: when I tell you something, please explain,” says Goebel. “The background that I have comes from formal philosophy and building systems to create hypotheses about data. That’s what scientists do. In there lies all of the mechanisms you need to do explanation.”


The 6th Competition on Legal Information Extraction and Entailment (COLIEE) takes place on June 21, 2019, and is run in association with ICAIL in Montreal, Quebec. Visit https://sites.ualberta.ca/~rabelo/COLIEE2019/ for more information.
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.

Community & Events

Catch us at Inventure$

Inventure$ has arrived! This “unconference,” held from June 5-7 at the Telus Convention Centre in Calgary, joins together entrepreneurs, innovators, investors, researchers and thought leaders to discover and share the latest in innovation. We couldn’t be more excited to be part of what is quickly becoming Alberta’s premier business and technology event.

If you are also in Calgary this week, here is where you can catch the Amii team:

Oil Sands Innovation Summit Panel

When: June 4, 3:20 – 4:20 p.m.
Where: Hyatt Regency (700 Centre St SE)
Can Alberta be a global leader in Oil & Gas AI? What is the implication for our businesses? Find out at this panel featuring Geoff Kliza, Director of Amii Innovates. The Oil Sands Innovation Summit takes place June 3 – 4 in partnership with Inventure$. The event is sold-out.

Calgary AI Meetup

When: June 4, 5:30 – 7:30 p.m.
Where: Room EN C70, Engineering Complex, University of Calgary (2500 University Dr NW)
RSVP Here!
Anna Koop from Amii’s science team will be sharing the latest reinforcement learning research happening at Amii, and she’ll be joined by other members of the Amii team to answer your burning questions about machine learning in this latest edition of the Calgary AI Meetup.

Inventure$ Showcase

Where: June 5, 9 a.m. – 4 p.m.
Where: Calgary Telus Convention Centre (120 9 Ave SE)
Purchase Tickets Here!
Find Amii on the conference floor – we’ll be in our booth answering questions, sharing information and demoing research from our Amii Fellows and Innovation Affiliates:

Bento Arm: Developed at the BLINC Lab under the supervision of Amii’s Patrick Pilarski, the Bento Arm is a platform for training and research applications of AI-enabled prosthetic arms. The Bento Arm will be on display from 9 a.m. – 4 p.m.

DeepStack: Developed by a research team led by Amii’s Michael Bowling, DeepStack is the first AI capable of beating professional poker players at heads-up no-limit Texas hold’em poker. DeepStack will be on display from 9 a.m. – 4 p.m.

SAMDesk: SAMDesk monitors social media to determine when important events are taking place around the world. Visit our booth to see the tool work in real time. SAMDesk will be on site from 9:30 – 11:30 a.m.

Mikata Health: Mikata Health uses AI to help doctors and staff connect assist patients more effectively through chat technology. Mikata Health will be joining us from 11:40 a.m. – 1:40 p.m.

Medo.ai: Medo.ai aims to simplify the use of ultrasound for common and critical conditions. Visit the booth to see how they use AI-augmented ultrasound imaging to support diagnosis. Catch Medo.ai at the Amii booth from 1:50 – 3:50 p.m.

ATB Tech on Tap – Machine Learning Mishaps

When: June 5, 5 – 7 p.m.
Where: ATB Financial (102 8 Ave SW)
RSVP Here!
ATB is hosting a very special Inventure$ edition of Tech on Tap happy hour! Drink free beer and listen to Tara and Anna from the Amii science and education teams as they share some memorable Machine Learning fails and mishaps.


Can’t make it to these events? Join us at Hello, Amii in Edmonton on June 19 or Hello, Amii in Calgary on June 24!

Community & Events

Event Round-Up | June 2019

Amii Events

Meet members of the Amii team, connect with like-minded people, and learn the latest about what’s happening in Machine Intelligence at Amii events! Here’s where we’ll be this month:

Hello Amii! Info Session

Hello Amii! is your introduction to the Amii Innovates program and the Alberta Machine Intelligence Institute. Learn how our experts can guide your teams and processes to help build your machine intelligence capabilities and propel your business to the next level. We want to help you go beyond small-scale AI projects and jumpstart your in-house ability to develop your own plans around artificial intelligence and machine learning and drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors and Applied Scientists can help your organization gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

June 19 – Edmonton
Register today!
12 – 1 p.m.
Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1

June 24 – Calgary
Register today!
12 – 1 p.m.
Location TBD

Machine Learning 101

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all?

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

June 26 – Edmonton
Register today!
12 – 1 p.m.
Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1


In the Community

Members of the Amii team are proud to support Alberta’s innovation community. You can find us at the following events:

Inventure$

Amii will be present at Inventure$ and surrounding events during June 4-6! Learn more in our blog post: Catch Us at Inventure$.

Avenue Magazine: The Innovation Event

Discover Edmonton’s BIG, BOLD and BRIGHT future at Avenue‘s inaugural Innovation Event presented by Innovate Edmonton. Hear from an expert panel in the fields of Artificial Intelligence, Big Data, Sustainability and Health, as well as a keynote from Innovate Edmonton’s Cheryll Watson, as they discuss Edmonton’s future as an innovation hub.

June 18 – Edmonton
Buy your ticket today!
3 – 6 p.m.
NAIT’s Productivity and Innovation Centre
10210 Princess Elizabeth Avenue
Edmonton, AB T5G 0Y2

Demystifying Machine Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) are intersecting with business applications and processes on a daily basis. Having a foundational understanding of AI and Machine Learning is critical in every workplace. Whether you are a business owner, an engineer, technical manager or business manager, having an understanding of what machine learning does, how it impacts business and the fundamentals of implementing machine learning projects into business, requires the ability to understand data, inputs and outputs, planning, execution, and control, to deliver solutions your business is seeking. In this session, you will gain an introductory understanding of supervised, unsupervised and reinforcement learning, the widely used methods of machine learning and how they can be applied in a business setting.

June 25 – Calgary
Register today!
8:30 – 11 a.m.
Platform Beta @ Hillier Block
429 8 Ave SE, Main Floor
Calgary, AB T2G 0L7


Educational Opportunities

Amii Educates aims to boost machine intelligence skills and literacy. Here are the programs currently being offered:

Amii & UAlberta Faculty of Extension: Machine Learning Foundations

This is a must-have course for professionals who are seeking foundational, conceptual, and technical knowledge in machine learning. Learn how to analyze the credibility of artificial intelligence/machine learning and its applications in business. Gain an understanding of unsupervised, supervised, and reinforcement learning, the three widely accepted categorizations of machine learning.

Jun 19 – 21 – Edmonton
Register today!
8:30 a.m. – 5 p.m.
10230 Jasper Ave
University of Alberta Extension
Edmonton, AB T5J 4P6

Aug 21 – 23 – Calgary
Register today!
8:30 a.m. – 5 p.m.
Room 423, Social Sciences Building
618 Campus Place
Calgary, AB T2N 4V8


AI Seminars

Keep up to date on research coming out of the University of Alberta and beyond! The Artificial Intelligence Seminar is a weekly meeting where researchers interested in AI can share their research. Organized by and hosted at the University of Alberta, each AI Seminar happens (unless otherwise specified) at 12 – 1 pm in the Computing Science Center, CSC B-10 (floorplan). Plus, pizza is provided for all attendees!

Keep up to date with the AI Seminars by subscribing to the AI Seminar Speakers Google Calendar.


The Tea Time Talks

The Tea Time Talks are a series of talks primarily given by the students and faculty studying Artificial Intelligence at the University of Alberta, but everyone is welcome to attend! Organized by and hosted at the University of Alberta, the talks are held each Monday, Wednesday, and Thursday from 4:15 pm to 4:45 pm in the Computing Science Center, CSC 3-33 (floorplan), starting in late May and running until late August. Tea and cookies are served at 4:00 pm.

Keep up to date with The Tea Time Talks by subscribing to the The Tea Time Talks Google Calendar.


Amii Recommends…

Looking for other events to attend in June? Check out:

Community & Events

Event Round-Up | May 2019

Amii Events

Meet members of the Amii team, connect with like-minded people, and learn the latest about what’s happening in Machine Intelligence at Amii events! Here’s where we’ll be this month:

Hello Amii! Info Session

Hello Amii! is your introduction to the Amii Innovates program and the Alberta Machine Intelligence Institute. Learn how our experts can guide your teams and processes to help build your machine intelligence capabilities and propel your business to the next level. We want to help you go beyond small-scale AI projects and jumpstart your in-house ability to develop your own plans around artificial intelligence and machine learning and drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors and Applied Scientists can help your organization gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Dates:

May 21 – Calgary
Register today!
5:30 – 6:30 p.m.
The Inc. at Platform Calgary (formerly Calgary Technologies Inc.)
3553 31 St NW
Calgary, AB T2L 2K7

May 30 – Edmonton
Register today!
12 – 1 p.m.
Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1

Machine Learning 101

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all?

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

May 28 – Edmonton
Register today!
12 – 1 p.m.
Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1


AI Seminars

Keep up to date on research coming out of the University of Alberta and beyond! The Artificial Intelligence Seminar is a weekly meeting where researchers interested in AI can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics related in any way to Artificial Intelligence can be presented, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

Organized by and hosted at the University of Alberta, each AI Seminar happens (unless otherwise specified) at 12 – 1 pm in the Computing Science Center, CSC B-10 (floorplan). Plus, pizza is provided for all attendees!

May 10: Nathan Stutervant

More info to come

May 17: Bradley Hauer

Speaker: Bradley Hauer

Title: Theoretical and Empirical Advancements in Computational Lexical Semantics

Abstract: This presentation will summarize two recent studies investigating important problems in computational lexical semantics: most frequent sense detection, and homonymy classification. In the first part, Bradley discusses the use of two sources of semantic information: the most frequently co-occurring words (companions), and the most frequent translation. He presents two novel methods that incorporates these concepts and advances the state of the art. In the second part, he proposes four hypotheses that characterize the unique behavior of homonyms in the context of translations, discourses, collocations, and sense clusters. The results of the experiments using a new annotated homonym resource provide strong empirical evidence for the hypotheses. This study represents a step towards a computational method for distinguishing between homonymy and polysemy, and constructing a definitive inventory of coarse-grained senses.

Bio: Bradley Hauer is a doctoral student at the University of Alberta Department of Computing Science, working with Greg Kondrak. He has published papers on a wide variety of topics, including generating phonetic spellings of words, identifying translations of words from unstructured text, and analyzing a centuries-old manuscript written in an unknown script. His current research is focused on foundational issues of lexical semantics. His most recent paper was nominated for the IEEE ICSC 2019 Best Paper Award.

May 24: Ilbin Lee

More info to come

Keep up to date with the AI Seminars by subscribing to the AI Seminar Speakers Google Calendar.


In the Community

Members of the Amii team are proud to support Alberta’s innovation community. You can find us at the following events:

Edmonton – Women in Machine Learning & Data Science: Large Scale Data Remediation in Finance

WiMLDS’s mission is to support and promote women and gender minorities who are practicing, studying or are interested in the fields of machine learning and data science. This month’s event features Rhys Chouinard, Data Scientist at ATB Financial (Large Scale Data Remediation in Finance – A Full Stack OCR Journey) and Tara Petrie, Machine Learning Educator at Amii (Math in Machine Learning: Some Fundamentals).

May 14
Reserve Your Spot!
6 p.m. – 8 p.m.
Startup Edmonton
#301, 10359 104 St NW
Edmonton, AB T5J 1B9

Edmonton – Telus World of Science Dark Matters: Game On!

Dark Matters is an 18+ event, where the science is served on the rocks & the adults come out to play. This month marks the return of a Dark Matters fan favourite: GAME ON! Guests will battle it out for first place, test their strategy and hone skills. Not to mention, we’ll be exploring the math, technology, and physics behind everyone’s favourite games. Become a game-master, you know you wanna! Some highlights include:
– Board Game Café hosted by Table Top Café
– Video games in the IMAX Theatre
– Improv games hosted by Amii’s Kory Mathewson

May 16
Buy tickets!
6:30 p.m. – 10 p.m.
11211 142 St NW
Edmonton, AB T5M 4A1

Calgary – TECTERRA Industry Panel: Constructing a Business Development Strategy

Business Development combines sales, partnerships, brand development and even media engagement. But how do new business owners develop a comprehensive business development strategy, while also thinking of financials and operations? During this luncheon session, hear from individuals with a variety of backgrounds on what techniques have worked for their business model, and how you can apply them to your development plan. Lunch will be provided to attendees. Panelists Include:
– Moderator: Richard Gorecki, Director of Portfolio Development, TECTERRA
– Tammy Peterson, VP, Marketing & Communications, Solv3D
– Spencer Murray, Director, Communications & Public Relations, Amii
– Desiree Bombenon, CEO & Cheif Innovation Officer, SureCall

May 28
Register today!
11:30 a.m. – 1:30 p.m.
The Nucleus, Calgary
100 6 Ave SW, Calgary, AB T2G 2C4

Community & Events

Event Round-Up | April 2019

Amii Events

Meet members of the Amii team, connect with like-minded people, and learn the latest about what’s happening in Machine Intelligence at Amii events! Here’s where we’ll be this month:

Hello Amii! Info Session

Hello Amii! is your introduction to the Amii Innovates program and the Alberta Machine Intelligence Institute. Learn how our experts can guide your teams and processes to help build your machine intelligence capabilities and propel your business to the next level. We want to help you go beyond small-scale AI projects and jumpstart your in-house ability to develop your own plans around artificial intelligence and machine learning and drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors and Applied Scientists can help your organization gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Dates:

April 25 – Edmonton
Register today!
12 – 1 p.m.
Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1

April 30 – Calgary
Register today!
5:30 – 6:30 p.m.
Global Business Centre, Terrace View Room
5th Floor – 120 8 Ave SE
Calgary, AB T2G 0K6

Amii’s AI Meetup

Amii’s monthly meetup brings together the brightest minds in Edmonton’s AI community. Discuss the latest topics in AI and machine learning, learn about the latest tools and techniques in machine learning, discover how companies are using AI to drive value, and network with thought leaders from Amii, local AI companies, service providers, and corporate labs. Join us for Amii’s monthly AI Meetup and be a part of building Edmonton’s growing AI community!

April 29
Register today!
5:15 – 7:15 p.m.
Startup Edmonton
#301, 10359 104 Street Northwest
Edmonton, AB T5J 1B9


April AI Seminars

Keep up to date on research coming out of the University of Alberta and beyond! The Artificial Intelligence Seminar is a weekly meeting where researchers interested in AI can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics related in any way to Artificial Intelligence can be presented, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

Organized by and hosted at the University of Alberta, each AI Seminar happens (unless otherwise specified) at 12 – 1 pm in the Computing Science Center, CSC B-10 (floorplan). Plus, pizza is provided for all attendees!

April 26: Dr. Mo Chen

Speaker: Dr. Mo Chen

Title: Reachability-Based Robotic Safety and Reinforcement Learning

Abstract: Autonomous systems are becoming pervasive in everyday life, and many of these systems are safety-critical and complex. To provide safety guarantees, formal verification methods such as reachability analysis are needed. However, verification is computationally intractable for complex systems. During this seminar, Dr. Chen presents recent techniques that leverage system structure to make reachability analysis tractable, and discusses recent advances in effectively incorporating prior knowledge about robotic systems to greatly improve sample complexity.

Speaker Bio: Mo Chen is an Assistant Professor in the School of Computing Science at Simon Fraser University, BC, where he directs the Multi-Agent Robotic Systems Lab. He completed his PhD in the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley with Claire Tomlin in 2017, and received his BASc in Engineering Physics from the University of British Columbia in 2011. From 2017 to 2018, Mo was a postdoctoral researcher in the Aeronautics and Astronautics Department in Stanford University with Marco Pavone. His research interests include multi-agent systems, safety-critical systems, reinforcement learning, and human-robot interactions.

Keep up to date with the AI Seminars by subscribing to the AI Seminar Speakers Google Calendar.

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.

Personal assistants. Automation. Smart homes. Hailed by many as the fourth industrial revolution, machine intelligence is bringing remarkable changes everywhere – Canada included. We are fortunate to have places like Edmonton, Montreal and Toronto leading the way as Canada’s major centres for artificial intelligence. Notably, they are also home to some of Canada’s most exciting AI events.

If you want to learn how to harness the technologies that are shaping our future, here are three Canadian AI events you should consider checking out in the coming months:

World Summit AI Americas (americas.worldsummit.ai)
April 10 – 11, 2019 | Montreal, QC
World Summit AI has made it across the pond! The series with the world’s largest and most active AI community (over 40,000 members from the global AI ecosystem) is hosting the first World Summit AI Americas in Montreal this April. This event promises two full days of mind-boggling innovation, animated discussions on AI4good, applied solutions for enterprise, hands-on workshops and the development of plans for advancing the application of AI in the coming year. To learn more and purchase a ticket, visit the World Summit AI Americas page; use promo “AMII15” for 15% off your ticket.

SingularityU Canada Summit (sucanada.org/summit2019)
April 23 – 24, 2019 | Edmonton, AB
After a smashing Toronto debut in 2017, SingularityU Canada Summit lands in Edmonton this April. A mixture of keynote discussions, panel presentations, product demos, workshops, and breakout sessions, this conference shares the best of Canadian and international technology. Learn about the transformative impact that technologies like artificial intelligence, nanotechnology, and digital medicine will have on our lives and our world. To learn more and purchase a ticket, visit the Singularity U Canada Summit page; use promo “AmiiSUDIS20” for 20% off your ticket.

Big Data & AI Toronto
July 22-24, 2019 | Toronto, ON
Big Data and AI Toronto aims to address the greatest business challenges technology leaders are facing today. Industry sessions, keynote discussions and panel presentations explore the future of work in multiple industries. Visit the Big Data & AI Toronto registration page to purchase your ticket.

Whether you are a curious beginner or a seasoned pro, there’s lots of (machine) learning to be had this year!

Bonus Event:
The Summer Institute (dlrlsummerschool.ca/the-summer-institute/)
July 21-24, 2019 | Edmonton, AB
If you are passionate about understanding and shaping the relationship between AI and society, consider applying to attend the Summer Institute on AI and Society. A combination of lectures, panels, and participatory problem-solving, this intimate interdisciplinary event aims to build understanding and action around the most important issues facing AI. Visit the Summer Institute page for more information.

CIFAR, the AI PULSE program at UCLA School of Law, and Amii are thrilled to host the inaugural Summer Institute on AI and Society in Edmonton this July 21 – 24, 2019.

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

Summer Institute takes place right before Deep Learning and Reinforcement Learning Summer School and will include a combined event on July 24th for both Summer Institute and Summer School participants.

We spoke with one of the co-organizers of Summer Institute, UCLA School of Law professor Edward Parson, to talk about the origins of the event, what themes and topics might be covered, and why you should apply now. Check out what he had to say below:

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

Tell us about how you became interested in AI and its societal impact.

My main professional background has been in environment, energy and related policy areas. But because of my partial scientific and technical training, I’ve always had a central interest in technology and those areas – what it does, what forces determine how it changes, how, if at all, societies can get the benefits and limit the harms, and how that works. That was the bridge to thinking about AI.

How did you get involved in the Summer Institute?

Last year when I was on a sabbatical year at the University of Victoria, I became aware of CIFAR’s program supporting AI and related initiatives. And in particular, CIFAR’s interest in broadening its support from technical issues of AI out to societal impacts, regulatory, and governance issues. After speaking with them and then consulting with a couple of Canadian colleagues who are more on the technical side of AI – Alona Fyshe and Dan Lizotte – we submitted a proposal, it was approved, and we’re going forward with the three of us co-directing the institute, with joint support from CIFAR and from my project here at UCLA.

Can you tell us more about this project at UCLA?

It’s an outgrowth of a longer-standing activity at UCLA Law School that’s been on Science Technology in Law, called the AI PULSE Program. We’re looking at ways to think through potential impacts that are sort of intermediate in scale and time horizon. We’re looking for ways to get reasonably disciplined hooks on what the impacts might be five, 10, 20 years out, and how to anticipate, assess, and forestall the most disruptive and harmful aspects of those.

This also characterizes my main interest for the Summer Institute. But I’m one of three co-organizers. My two co-organizers’ interests come mainly from the side of technical aspects of AI. They’re more concerned with developing useful ethical guidelines that students and practitioners of AI and machine learning might observe in their current practice. So we expect to be covering a range of issues.

What do you believe the benefit is of the Summer Institute for attendees?

To be involved in conversations on these fascinating topics that don’t have a lot of place for consideration in the normal curriculum. Networking among a bunch of people with similar interests on issues that are likely to be really important and recurrent over time. And I expect it’ll be really interesting and fun.

What important ethics and societal implications should AI practitioners pay attention to?

AI is the weirdest technology in the world. I’ve spent decades studying social impacts of technology in all kinds of domains. AI is unlike any other technology that I’ve thought about before because nobody knows what it is. It is so diffused, so fuzzy in its boundaries, so diverse in the different strains of capability that contribute to what’s going on presently. And so limitless in the things it might be used for.

What might AI do? It might enable things that are not presently possible. It might enable an extraordinary advance in environmental protection management. It might displace human ingenuity, or augment human ingenuity, in dozens of fields of scientific and technological research. Some weeks ago, a new machine learning program out of DeepMind in London won the annual world competition for protein folding projections. It’s sort of like what happened to the Go masters just happened to the protein scientists.

On the other hand, things that become possible through technological advance often get done even if we disapprove. One of my colleagues who thinks about this stuff, Allen Dafoe at Oxford, has thrown out the slogan that “one of the social risks of AI is robust totalitarianism.” Comprehensive surveillance with perfect facial and human individual recognition and omnipresent information about everything you think, do, and say. In the hands of a tyrannical regime.

AI is big stuff. It is big, historical stuff. The possibility of capabilities that really fundamentally disrupt employment and livelihood and labour markets, that fundamentally disrupt the functioning of the state, that fundamentally disrupt the functioning of the economy, and every sub-sector thereof for good and ill.

The potential benefits are enormous, but even they will come with enormous disruption. So if we all get to move to a Jetsons world where we’re at leisure all day and the machines do the work, that might be really nice. But it will explode a bunch of foundations of social order. These are all the things we need to talk about at Summer Institute.

What aspects of its implications do you think are not being paid enough attention?

It’s the medium term – what happens five steps down the line, and how we can get any handle on thinking about that beforehand. To make an environment that makes it likely that people get the benefits and don’t get the worst harms from those rapid changes.

What are you most looking forward to about Summer Institute?

Talking about all this fabulous stuff with a bunch of really interesting and engaged people from all over the place spatially, and from all over the place in terms of intellectual background and how they think.

Interested in attending? Applications for the Summer Institute are open until midnight on May 15!

Visit dlrlsummerschool.ca/the-summer-institute for more information and to apply today.
Your Introduction to Amii

Hello Amii! is your introduction to the Alberta Machine Intelligence Institute and our Applied Machine Learning team.

Learn how our experts can guide your teams and processes to help propel your business to the next level using machine intelligence. We want to take you beyond small-scale AI projects that will have a local impact in your company and jumpstart your thinking around the ways artificial intelligence and machine learning can help drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors can help you gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Event Information

Register today!

Wednesday, March 27, 2019

5:30 – 6:30 p.m.

Amii HQ

#1101, 10065 Jasper Avenue NW

Edmonton, AB T5J 3B1

Community & Events

Amii’s AI Meetup – March 26

Meet the Brightest Minds in Edmonton’s AI Community

Amii’s monthly meetup brings together the brightest minds in Edmonton’s AI community.

Discuss the latest topics in AI and machine learning (ML), learn about the latest tools and techniques in ML, discover how companies are using AI to drive value, and network with thought leaders from Amii, local AI companies, service providers, and corporate labs.

Don’t miss out on the opportunity to hear from Brad Wrobleski and Greg Burlet this AI Meetup. Brad, a researcher and developer at the University of Calgary, will be discussing his research with Generative Adversarial Networks (GANs) and practical applications of reinforcement learning (RL) for communicating information and photography. Greg will demo the company he founded, Frettable, and speak about how to deploy and scale ML to service worldwide market.

Join us for Amii’s monthly AI Meetup and be a part of building Edmonton’s growing AI community!

Event Information

Register today!

Tuesday, March 26, 2019

5:15 p.m. – 7:15 p.m.

Startup Edmonton

#301, 10359 104 Street Northwest

Edmonton, AB T5J 1B9

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.

We are incredibly excited to announce three new courses on artificial intelligence and machine learning, co-developed by Amii and the University of Alberta Faculty of Extension!

Produced in collaboration between UAlberta’s Faculty of Extension and Amii, this three-course series is ideal for technically-inclined participants who wish to build foundational knowledge in machine intelligence, develop an applied understanding for approaching machine learning projects, and gain an introduction to intermediate and advanced techniques.

Participants can expect to gain a working knowledge around important machine learning areas such as supervised learning, unsupervised learning, neural networks and reinforcement learning.

Prior knowledge of basic programming, linear algebra and statistics is expected. Experience with mathematics, statistics and analytics is strongly recommended. Participants will be expected to have the ability to read and code trace existing code; be comfortable with conditionals, loops, variables, lists, dictionaries and arrays; and should be able to produce “hello world.”

Once all three courses have been successfully completed, an official University of Alberta Notice of Completion will be issued. The courses can also be used towards the Amii Machine Learning Technician Certification program, beginning in September 2019. Students completing the Faculty of Extension series will be grandfathered into the Machine Learning Technician program with a prorated tuition.

Learn more about the individual courses below:

Introduction to Machine Learning and Artificial Intelligence

EXCPE4784

(21 hours)
April 24 – 26, 2019
8:30 a.m.− 5 p.m.
Enterprise Square, Edmonton
$1695

Students will gain an overview of machine learning and artificial intelligence, beginning with discussing supervised learning applied to a classification problem. Students will develop a working knowledge of this type of application, and how it might look in a project from start to finish. Prior knowledge of basic programming, linear algebra and statistics is expected.


Applied Machine Learning

EXCPE4785

(21 hours)
May 22 – 24, 2019
8:30 a.m.− 5 p.m.
Enterprise Square, Edmonton
$1695

This course will begin the discussion of problem definition in machine learning projects, and other issues with data acquisition, cleaning and exploratory data analysis. Students will also discuss unsupervised learning in the context of developing data for successful machine learning modelling. Prior knowledge of basic programming, linear algebra and statistics is expected.


Intermediate Machine Learning Techniques

EXCPE4786

(21 hours)
June 19 – 21, 2019
8:30 a.m.− 5 p.m.
Enterprise Square, Edmonton
$1695

This course continues from the previous, discussing more advanced techniques of machine learning, such as neural networks and support vector machines. Students will also get a brief introduction to reinforcement learning. Prior knowledge of basic programming, linear algebra and statistics is expected.


For more information, please visit the UAlberta Faculty of Extension – AI & ML Courses page: https://www.ualberta.ca/extension/continuing-education/programs/technology/ai

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.
Your Introduction to Amii

Hello Amii! is your introduction to the Alberta Machine Intelligence Institute and our Applied Machine Learning team.

Learn how our experts can guide your teams and processes to help propel your business to the next level using machine intelligence. We want to take you beyond small-scale AI projects that will have a local impact in your company and jumpstart your thinking around the ways artificial intelligence and machine learning can help drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors can help you gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Event Information

Register today!

Thursday, March 14, 2019

12 – 1 p.m.

Amii HQ

#1101, 10065 Jasper Avenue NW

Edmonton, AB T5J 3B1

Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Event Information

Register today!

Tuesday, March 12, 2019

12 – 1 p.m.

Startup Edmonton

#301, 10359 104 Street Northwest

Edmonton, AB T5J 1B9

Community & Events

YEG Tech Night – March 8

Join your friends in Edmonton’s tech community

Join your friends in Edmonton’s tech community for an evening of entertainment and fun!

Work Nicer has generously agreed to host us for Drink Nicer, and afterwards, we’ll check out Rapid Fire Theatre’s Theatresports at the Citadel!

Theatresports, which pits two teams of Rapid Fire Theatre’s best improvisers against each other for the love of the audience, is Edmonton’s longest-running improv show – now in its 38th season!

Please feel free to bring your significant others, colleagues and anyone in Edmonton’s tech community!

The details:

Purchase tickets for $5!

Friday, March 8, 2019

Anytime after 4pm – Drinks at Work Nicer (Beaver House: 10160 103 St NW)

7pm SHARP – Arrive at the Citadel (9828 101A Ave NW)

7:30pm to 9:15pm – Theatresports

As a courtesy to Rapid Fire, we ask everyone to be at the Citadel no later than 7pm so that our group can be seated in an organized fashion before the show begins.

Sponsors:
Air Trail Logo
Drivewyze Logo
dealcloser logo
worknicer logo
Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Event Information

Register today!

Tuesday, February 26, 2019

12 – 1 p.m.

Startup Edmonton

#301, 10359 104 Street Northwest

Edmonton, AB T5J 1B9

Meet the Brightest Minds in Edmonton’s AI Community

Amii’s monthly meetup brings together the brightest minds in Edmonton’s AI community.

Discuss the latest topics in AI and machine learning, learn about the latest tools and techniques in machine learning, discover how companies are using AI to drive value, and network with thought leaders from Amii, local AI companies, service providers, and corporate labs.

This month’s talk features Johannes Günther presenting a modular, ML-based control approach to industrial laser welding using deep learning and reinforcement learning techniques, and Dornoosh Zonoobi from MEDO.ai, who will explore how ML & AI can radically simplify the way ultrasound scans are performed and interpreted, enabling any caregiver to make an accurate & confident diagnosis.

Join us for Amii’s monthly AI Meetup and be a part of building Edmonton’s growing AI community!

Event Information

Register today!

Monday, February 25, 2019

5:15 p.m. – 6:30 p.m.

Startup Edmonton

#301, 10359 104 Street Northwest

Edmonton, AB T5J 1B9

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.

Your Introduction to Amii

Hello Amii! is your introduction to the Alberta Machine Intelligence Institute and our Applied Machine Learning team.

Learn how our experts can guide your teams and processes to help propel your business to the next level using machine intelligence. We want to take you beyond small-scale AI projects that will have a local impact in your company and jumpstart your thinking around the ways artificial intelligence and machine learning can help drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors can help you gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Event Information

Register today!

Monday, March 4, 2019

5 – 6 p.m.

Nucleus Calgary

100 6 Avenue Southwest

Calgary, AB T2G 2C4

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.

Your Introduction to Amii

Hello Amii! is your introduction to the Alberta Machine Intelligence Institute and our Applied Machine Learning team.

Learn how our experts can guide your teams and processes to help propel your business to the next level using machine intelligence. We want to take you beyond small-scale AI projects that will have a local impact in your company and jumpstart your thinking around the ways artificial intelligence and machine learning can help drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors can help you gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Event Information

Register today!

Thursday, February 21, 2019

12 – 1 p.m.

Amii HQ

#1101, 10065 Jasper Avenue NW

Edmonton, AB T5J 3B1

Lunch is provided!

Community & Events

AI Seminars – February 2019

Keep up to date on research coming out of the University of Alberta and beyond!

The Artificial Intelligence Seminar is a weekly meeting where researchers interested in AI can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics related in any way to Artificial Intelligence can be presented, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.

Each AI Seminar happens (unless otherwise specified) at 12 – 1 pm at the University of Alberta Computing Science Center, CSC B-10 (click here for a floorplan). Plus, pizza is provided for all attendees!

Here are the AI Seminars happening in February 2019:

February 8: Ilbin and Bo

Speaker 1: Ilbin Lee

Title: Introducing some Machine Learning Research Projects in Wildfire and Healthcare Applications

Abstract:
In this talk, Ilbin Lee will briefly introduce machine learning projects in wildfire and hospital operations. These two projects involve the use of machine intelligence models to predict risk and therefore increase the likelihood of successful intervention.

Bio: Ilbin Lee is an assistant professor in operations management at the University of Alberta School of Business. He was a postdoctoral fellow in the School of Industrial and Systems Engineering at Georgia Institute of Technology. He obtained his PhD in Industrial and Operations Engineering at the University of Michigan in 2015. His research interests include sequential decision-making based on data and prediction, computational optimization, and wildfire and healthcare applications.

Speaker 2: Bo Cao

Title: Machine Learning Applied to Psychiatric Disorders Understanding

Abstract: Bo Cao will talk about several studies using machine learning and brain imaging to understand psychiatric disorders, identify patients with these disorders and predict the treatment outcomes.

Bio: Bo Cao is trained in mathematics (BSc), psychology (MSc), computational neuroscience (PhD), neuroimaging and psychiatry (postdoc), and has a strong passion for understanding the fundamental mechanisms of how the brain works and how to cure the brain when the mechanisms are disturbed. He currently is an Assistant Professor of the Department of Psychiatry at the University of Alberta.

February 15

More details to come

February 22: Hengshuai Yao

Title: ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search

Abstract: In this seminar, Hengshuai Yao presents a paper which he co-authored with Shangtong Zhang and Hao Chen, regarding propose actor ensemble algorithm, named ACE, for continuous control with a deterministic policy in reinforcement learning. This paper was accepted by the AAAI 2019 Conference on Artificial Intelligence.

Bio: Hengshuai studied reinforcement learning at Reinforcement Learning and Artificial Intelligence (RLAI) lab from 2008 to 2015 in a PhD program at Department of Computing Science (supervised by Csaba Szepesvári), University of Alberta. His thesis is on model-based reinforcement learning with linear function approximation. He joined NCSoft game studio in San Francisco in 2016 working on reinforcement learning in games. He moved back to Canada in 2017 and joined Huawei Noah’s Ark Lab. Right now he is working on reinforcement learning and robotics.

BONUS Seminar
February 22, 2 – 3 pm: Marc Bellemare

Location: CSC 3-33

Title: A geometric perspective on optimal representations in reinforcement learning

Abstract: In reinforcement learning, an important component of an agent is its representation of state: how it encodes raw state inputs into features that are useful to the process of decision-making. This talk presents some recent work on what constitutes a good representation, especially in the context of deep reinforcement learning, where the representation itself can be adapted to minimize prediction error.

Bio: Marc G. Bellemare is a research scientist at Google Brain in Montreal, Canada; CIFAR Learning in Machines & Brain Fellow; adjunct professor at McGill University; and was recently awarded a Canada CIFAR AI chair, held at the Montreal Institute for Learning Algorithms (Mila). He received his Ph.D. from the University of Alberta where he studied the concept of domain-independent agents and developed the highly-successful Arcade Learning Environment, the platform for AI research on Atari 2600 games. From 2013 to 2017 he was a research scientist at DeepMind where he made major contributions to the field of deep reinforcement learning.


Are you interested in presenting at an AI Seminar? If so, please contact the current organizer, Juliano Rabelo, at rabelo@ualberta.ca.

Creating AI Strategy for Innovation Affiliates

Come find out Amii’s approach to creating AI strategy for our Innovation Affiliates.

We’ll discuss the data maturity you need to begin an AI initiative, how to develop your internal capacity to tackle disruptive industry questions, and finally, how sound change management concepts will tie all of your efforts together.

Please note that a basic knowledge of machine intelligence is required to understand this session.

Event Information

Register today!

Friday, February 22, 2019

12 – 1 p.m.

Amii HQ

#1101, 10065 Jasper Avenue NW

Edmonton, AB T5J 3B1

School’s in for summer: Students talk Deep Learning & Reinforcement Learning Summer School 2018

Amii and CIFAR are thrilled to host the Deep Learning & Reinforcement Learning Summer School in Edmonton this July 24 – August 2.

The Summer School brings together graduate students, post-doctoral fellows and industry professionals to explore the latest AI techniques and advancements, build their research networks and open new opportunities for collaboration. Participants learn directly from world-renowned AI researchers including Richard Sutton, Yoshua Bengio and Martha White. Other programming includes an AI Career Fair and social events around town.

DLRL Summer School 2018 - Rear view of classroom
DLRL Summer School 2018 in Toronto
Photo credit: Vector Institute and CIFAR

To give this year’s attendees an idea of what to expect for this year’s Summer School, we asked three of last year’s attendees to tell us about their experiences and what they found valuable. Check out what they had to say below:

1. Why did you decide to apply for the 2018 Deep Learning & Reinforcement Learning Summer School?

Katya: The [Summer School] is an incredible opportunity to meet distinguished researchers in the field face-to-face, get the latest cutting-edge research and, no less important, to connect and meet fellow students, find out what they are working on and discuss potential collaborative projects. This past year we had people from the University of Toronto, Université de Montréal, McGill, University of Alberta, CMU, MIT, Stanford, Google, Duke.

Matthew: When the application went up, I was actually informed by several of my lab mates that the Summer School was something that would be extremely valuable in my future research. There was also quite a big push to apply in the RLAI [editor’s note: Reinforcement Learning & Artificial Intelligence] Lab here at University of Alberta. I joined in and was even more excited once I saw the list of speakers.

Raksha: I was aware of various summer schools, but I’d never gotten a chance to attend one. So in late winter of 2018, when I heard about the [Summer School] happening in Toronto, it seemed like the perfect opportunity. The list of speakers for the school were distinguished researchers in the area, plus the RL school component, the positive reviews from peers who had been to the 2017 version, and encouragement to attend by professors in the department, made it very exciting – and I decided to apply to it!

2. What did you enjoy most about the event?

Katya: People. The brain power and diversity of research backgrounds in the room were fascinating. It was also valuable that the timetable had plenty of time for networking, i.e. over lunch.

Matthew: I was struck by the amazing talent of all the participants and how many were from fields outside machine learning and reinforcement learning. Some of my favorite conversations were with physicists who were looking to apply deep learning or reinforcement learning to model the dynamics of particular physical systems. There was also a lot of opportunity to connect with people from around the world. Learning about the many avenues of research explored is awe-inspiring and a reminder that my own interests are a minuscule part of the picture.

Raksha: As the focus is both on deep learning and reinforcement learning, it was a great opportunity for me, a person who works in reinforcement learning, to get insight into state-of-the-art research in deep learning and hear different perspectives about reinforcement learning. Additionally, it was really nice to meet and interact with the extended peer/research community in a more school-like setting!

3. Did the Summer School affect your career and/or research trajectory? If so, how?

Katya: Terrific impact. During one of the breaks, we sat down with Rich Sutton and discussed a new project. As a result of that discussion, four months later, I am visiting the RLAI group at the University of Alberta and working with Rich on this project, which becomes an intersection of the NLP and RL. This is a great example where a conversation turned into a mind-blowing experience – and not because of the winter in Alberta (I am from Siberia!) – but by being in the “mecca of RL” and having an opportunity to learn from Rich and the group.

Matthew: I would say it emboldened my research trajectory. My interests are still the same — i.e using reinforcement learning to make predictions of the world through interactions — but I am more excited about this topic and how it relates to the wider AI community. The scope of my research has also widened. While before I was very narrow in what I thought was the way forward, I am now looking towards many communities I had not considered (or was even aware of!).

Raksha: [The] chance to discuss my research with some leading researchers, listen to their experiences and thoughts about what’s to come and where we are headed, meet and interact with peers who are pursuing interesting problems in their research, etc., has been very inspiring!

4. What was the most valuable thing you learned or experienced at the event?

Katya: Being able to connect with people and learn from them … [S]uch as having an opportunity to ask Graham Neubig hundreds of questions and get most practical answers, learning about RLAI Lab from the people in that group and connecting with people there, being deeply inspired by Martha White and Jamie Kiros.

Matthew: I found the most value in how my view on the field was expanded. The exposure of ideas and topics that I hadn’t yet seen sparked many ideas that I want to explore in my future research. It gave me perspective on the massive amount of work that is still left, but with that the many interesting topics still unexplored.

Raksha: I have always heard about the general [Deep Learning/Reinforcement Learning] community being large and diverse, but this was my first hands-on experience of it. It was invaluable to meet and interact with peers from various countries! The Summer School was filled with energy from day one — and we got a sneak-peak into the breadth of research in the community, in a classroom-like setting, which was really valuable!

Visit dlrlsummerschool.ca for more information.

L’École d’été est de retour : des étudiants se rappellent leur stage à l’École d’été sur l’apprentissage profond et l’apprentissage par renforcement 2018

L’Amii et le CIFAR sont heureux d’accueillir l’École d’été sur l’apprentissage profond et l’apprentissage par renforcement à Edmonton du 24 juillet au 2 août 2019.

L’École d’été permet à des étudiants diplômés, à des boursiers postdoctoraux et à des professionnels de l’industrie d’explorer les plus récentes technologies et avancées de l’IA, de développer leurs réseaux de recherche et de multiplier les occasions de collaboration. Les participants apprennent de chercheurs en IA de renommée mondiale, dont Richard Sutton, Yoshua Bengio et Martha White. Le programme comprend aussi un salon de l’emploi en IA et des activités sociales en ville.

DLRL Summer School 2018 - Rear view of classroom
École d’été 2018 à Toronto
Photo : Institut Vecteur et CIFAR

À quoi doivent s’attendre les participants de l’École d’été 2019 ? Pour leur donner un aperçu, nous avons demandé à trois stagiaires de l’année dernière de nous parler de leur expérience et de ce qu’ils en ont retiré. Voici ce qu’ils avaient à dire.

1. Pourquoi as-tu participé à l’École d’été sur l’apprentissage profond et l’apprentissage par renforcement 2018 ?

Katya : [L’École d’été] est une occasion incroyable de rencontrer en personne d’éminents chercheurs dans le domaine, de connaître les plus récentes recherches de pointe et, tout aussi important, de rencontrer d’autres étudiants, de savoir sur quoi ils travaillent et de discuter de projets de collaboration éventuels. L’année dernière, il y avait des gens de l’Université de Toronto, de l’Université de Montréal, de l’Université McGill, de l’Université de l’Alberta, de l’Université Carnegie Mellon, du MIT, de l’Université de Stanford, de Google et de l’Université Duke.

Matthew : Au début de la période d’inscription, plusieurs de mes partenaires de laboratoire m’ont dit que l’École d’été pouvait s’avérer extrêmement utile pour mes futures recherches. Il y avait aussi beaucoup de pression pour s’inscrire au Laboratoire sur l’apprentissage par renforcement et l’intelligence artificielle (RLAI) de l’Université de l’Alberta. Je me suis inscrit et j’étais encore plus excité lorsque j’ai vu la liste des conférenciers.

Raksha : Je connaissais différentes écoles d’été, mais je n’avais jamais eu la chance d’en fréquenter une. À la fin de l’hiver 2018, quand j’ai entendu dire que l’École d’été aurait lieu à Toronto, j’ai pris cela comme un signe du ciel. Les conférenciers au programme étaient tous des chercheurs renommés dans le domaine. De plus, la composante en apprentissage par renforcement, les commentaires positifs de ceux qui avaient participé à l’édition 2017 et les encouragements des professeurs du département pour qu’on y participe rendaient cela vraiment intéressant. J’ai donc décidé de poser ma candidature !

2. Qu’as-tu aimé le plus ?

Katya : Les gens. Le calibre intellectuel et la diversité des recherches des participants étaient fascinants. J’ai aussi bien aimé que l’horaire laisse beaucoup de temps au réseautage, notamment durant le dîner.

Matthew : J’ai été frappé par les aptitudes incroyables des participants et par le nombre de personnes issues d’autres domaines que l’apprentissage automatique et l’apprentissage par renforcement. J’ai eu certaines de mes meilleures conversations avec des physiciens qui souhaitaient appliquer l’apprentissage profond ou l’apprentissage par renforcement à la modélisation de systèmes physiques particuliers. L’École nous a aussi fourni de nombreuses occasions d’établir des relations avec des gens du monde entier. En apprendre plus sur les nombreuses avenues de recherche explorées est une grande source d’inspiration et un rappel que nos propres intérêts ne sont qu’une infime partie du tableau.

Raksha : Comme l’École met l’accent à la fois sur l’apprentissage profond et l’apprentissage par renforcement, j’ai trouvé que c’était une excellente occasion pour moi, qui travaille en apprentissage par renforcement, d’avoir un aperçu de l’état actuel de la recherche en apprentissage profond et de découvrir d’autres perspectives de l’apprentissage par renforcement. De plus, c’était vraiment agréable de rencontrer des pairs et des chercheurs, et d’interagir avec cette communauté élargie dans un cadre plus scolaire !

3. L’École d’été a-t-elle eu des répercussions sur ta carrière ou ta trajectoire de recherche ? Si oui, comment ?

Katya : Des répercussions incroyables ! Pendant une des pauses, nous discutions avec Rich Sutton d’un nouveau projet. Quatre mois après cette discussion, je visitais le  Laboratoire RLAI à l’Université de l’Alberta et travaillais avec Rich sur ce projet, au croisement du traitement automatique des langues et de l’apprentissage par renforcement. C’est un bon exemple d’une conversation qui se transforme en expérience marquante – pas seulement en raison de l’hiver albertain (je viens de Sibérie !) –, mais parce que je me suis retrouvée dans la mecque de l’apprentissage par renforcement et que j’ai eu la chance d’apprendre de Rich et du groupe.

Matthew : Je dirais que cela a consolidé ma trajectoire de recherche. Mes intérêts sont toujours les mêmes – l’utilisation de l’apprentissage par renforcement pour faire des prédictions sur le monde au moyen d’interactions –, mais ce sujet et ses relations avec l’univers de l’IA dans son ensemble m’allument davantage. Le champ de mes recherches s’est également élargi. Alors qu’auparavant, je pensais que je devais suivre une voie étroite pour aller de l’avant, je me tourne maintenant vers de nombreuses communautés que je n’avais pas envisagées (ou que je ne connaissais même pas !).

Raksha : [La] chance de discuter de mes recherches avec les plus grands chercheurs, de les écouter parler de leurs expériences et de leurs idées à propos de ce qui s’en vient et de l’endroit où nous nous dirigeons, de rencontrer des gens et d’interagir avec des pairs qui rencontrent des problèmes intéressants dans le cadre de leurs recherches… Tout cela a été très inspirant !

4. Quelle est la chose la plus utile que tu as apprise ou expérimentée ?

Katya : Être capable d’entrer en relation avec les gens et d’apprendre d’eux… comme avoir la chance de poser des centaines de questions à Graham Neubig et d’obtenir les réponses les plus pratiques, en apprendre plus sur le laboratoire RLAI des membres mêmes du groupe et interagir avec eux, être profondément inspirée par Martha White et Jamie Kiros.

Matthew : Ce que j’ai trouvé de plus bénéfique, c’est que ma vision du domaine s’est élargie. En étant exposé à des concepts et à des sujets que je ne connaissais pas, j’ai eu accès à de nombreuses idées que je veux explorer dans mes futures recherches. Cela m’a donné un aperçu de l’énorme quantité de travail qu’il reste à faire, mais aussi des nombreux sujets intéressants encore inexplorés.

Raksha : J’ai toujours entendu dire que la communauté [de l’apprentissage profond et de l’apprentissage par renforcement] était vaste et diversifiée, mais c’était la première fois que j’en faisais vraiment l’expérience. Les rencontres et les interactions avec des pairs de divers pays étaient inestimables ! L’École d’été a débordé d’énergie dès le premier jour, et nous avons eu un aperçu de l’étendue des recherches dans la communauté dans un cadre scolaire, ce qui a été extrêmement intéressant !

Pour plus d’info, visitez dlrlsummerschool.ca.

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Your Introduction to Amii

Hello Amii! is your introduction to the Alberta Machine Intelligence Institute and our Applied Machine Learning team.

Learn how our experts can guide your teams and processes to help propel your business to the next level using machine intelligence. We want to take you beyond small-scale AI projects that will have a local impact in your company and jumpstart your thinking around the ways artificial intelligence and machine learning can help drive the next stage of growth for your business.

Join us at Hello Amii! and discover how our team of expert Machine Learning Advisors can help you gain the knowledge, skills and abilities you need to create a transformational shift in the way your teams think about data and decision making.

Event Information

Register today!

Thursday, February 7, 2019
5:30 – 6:30 p.m.

Amii HQ
#1101, 10065 Jasper Avenue NW
Edmonton, AB T5J 3B1

Meet the Brightest Minds in Edmonton’s AI Community

Amii’s monthly meetup brings together the brightest minds in Edmonton’s AI community.

Discuss the latest topics in AI and machine learning, learn about the latest tools and techniques in machine learning, discover how companies are using AI to drive value, and network with thought leaders from Amii, local AI companies, service providers, and corporate labs.

Don’t miss out on the opportunity to hear from Nadia Ady and Sean Feehanat this AI Meetup. Nadia (from Amii) is an expert on curiosity and Sean is leading the team at Drivewyze as they integrate AI into their fast-growth SaaS business.

Join us for Amii’s monthly AI Meetup and be a part of building Edmonton’s growing AI community!

Event Information

Register today!

Tuesday, January 22, 2019
5:15 p.m. – 6:30 p.m.

Startup Edmonton
#301, 10359 104 Street Northwest
Edmonton, AB T5J 1B9

Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Event Information

Register today!

Tuesday, January 29, 2019
12 – 1 p.m.

Startup Edmonton
#301, 10359 104 Street Northwest
Edmonton, AB T5J 1B9

About DLRL Summer School

Deep Learning and Reinforcement Learning Summer School brings together graduate students, post-docs and professionals to cover the foundational research, new developments, and real-world applications of deep learning and reinforcement learning. Participants learn directly from world-renowned researchers and lecturers. Related extracurricular activities will include an AI Career Fair, industry and partner-sponsored events, as well as tourism events.

The event is aimed at graduate students, postdocs, and industry professionals who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning and reinforcement learning) and wish to learn more about this rapidly growing field of research. Participants should have advanced prior training in computer science and mathematics.

The 2019 DLRLSS is hosted by the Canadian Institute For Advanced Research (CIFAR) and the Alberta Machine Intelligence Institute (Amii), with participation and support from the Vector Institute and the Institut québécois d’intelligence artificielle (Mila).

Event Information

Applications are now open! Please visit https://dlrlsummerschool.ca to apply.

July 24 – August 2, 2019
Edmonton, Alberta, Canada

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.

Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Event Information

Register today!

Wednesday, December 5, 2018
5:15 p.m. – 6:30 p.m.

The Global Business Centre
136 8th Ave SE
Terrace View Room (5th floor)
Calgary, AB

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.

Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Event Information

Register today!

Monday, December 17, 2018
12 p.m. – 1 p.m.

Startup Edmonton
#301, 10359 104 Street Northwest
Edmonton, Alberta

Make Sense of Machine Learning

Heralded by many as the fourth industrial revolution, artificial intelligence has inspired countless news articles, novels, and films. With this deluge of information comes hopes and aspirations, fears and misconceptions – some justified and others not.

How can we make sense of it all? 

Join Amii as we pull back the curtain on AI and lay a pragmatic foundation for what AI is, what it isn’t, and how you can begin to think about the place of AI in your business.

Register today!

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.

Research

Adaptive Prosthetics Program

Principal Investigators
Patrick M. Pilarski, Richard S. Sutton

Intelligent Artificial Limbs & Biomedical Devices

The Adaptive Prosthetics Program, a collaboration between Amii and the BLINC Lab, is an interdisciplinary initiative focused on real-time machine learning methods for assistive rehabilitation and intelligent artificial limbs. Through the development of fundamental algorithms and the translation of methodology into clinical benefit, the program seeks to increase patients’ ability to customize and control assistive biomedical devices.

The Adaptive Prosthetics Program explores fundamental and applied methods for real-time prediction, adaptive control and direct human-machine interaction. Technologies developed through the program include the Bento Arm and the HANDi Hand, both of which have open-sourced hardware and software through the BLINCdev community.

See Also

Development of the Bento Arm: an Improved Robotic Arm for Myoelectric Training and Research” published at MEC ’14: Myoelectric Controls Symposium

Development of the HANDi Hand: an Inexpensive, Multi-Articulating, Sensorized Hand for Machine Learning Research in Myoelectric Control” published at MEC ’17: Myoelectric Controls Symposium

Research

Arcade Learning Environment

Principal Investigator
Michael Bowling

Atari 2600 Platform for General Artificial Intelligence Development

The Arcade Learning Environment (ALE) is a software framework designed to facilitate the development and testing of general AI agents. ALE was created as both a challenge problem for AI researchers and a method for developing and evaluating innovations and technologies.

Historically, many AI advancements have been developed and tested through games (e.g. CheckersChessPoker and, most recently, Go), which offer controlled, well-understood environments with easily defined measures for success. Games also give researchers a concrete and relatable way to demonstrate artificial intelligence to a broad audience.

The Arcade Learning Environment, powered by the Stella Atari Emulator, provides an interface to hundreds of Atari 2600 games. These diverse game environments are complex enough to be challenging for an AI agent to solve yet simple enough to enable progress.

ALE is available to researchers and hobbyists alike with Atari now being used by groups like Google DeepMind to develop and test their deep reinforcement learning methodologies.

See Also

The Arcade Learning Environment: An Evaluation Platform for General Agents” published in the Journal of Artificial Intelligence Research

Research

Meerkat

Principal Investigators
Randy Goebel, Osmar Zaïane

Social Network Analysis & Visualization

Meerkat is an automated Social Network Analysis (SNA) tool used to analyze, visualize and interpret large or complex networks of information, allowing users to examine patterns and investigate relational dynamics.

The application uses information about the interactions between a set of objects (or nodes) within a network and lets the user employ different algorithms to automatically identify meaningful connections or highlight the most influential or central nodes in different ways.

Network analysis features include:

  • Automated community detection and analysis
  • Interactive visualization using general, community and metric-based layouts
  • Filtration and extraction of useful data
  • Dynamic analysis of network changes over time

Meerkat also provides tools for text mining, including polarity and emotion analysis, which give users the ability to examine text for positive and negative sentiments and a range of basic emotions. Meerkat ED, a version of the program that has been tailored specifically for educational environments, allows instructors to evaluate student activities in online discussion forums.

Research

DeepStack

Principal Investigator
Michael Bowling

Problem we’re trying to solve

For several years, AI researchers have had a number of different techniques for predicting and planning optimal actions in situations of perfect information (where all actors have the same, full knowledge of the world). Techniques have been lacking for dealing with imperfect information situations (where actors do not have access to certain information or have access to information the other doesn’t). DeepStack seeks to successfully apply, for the first time, theoretical techniques for perfect information games into situations with imperfect information.

How will this help someone / an industry?

For computing scientists and AI researchers, DeepStack represents a foundational step forward in dealing with issues around predicting optimal actions in the face of ambiguity and uncertainty. The theoretical advancements demonstrated in DeepStack will open new avenues of research for scientists interested in building, and planning with, models of unknown, complex dynamic systems.

Type of MI used

Reinforcement learning, Deep learning

(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.

Part of the Alberta Machine Intelligence Institute, Marlos C. Machado is a 4th year Ph.D. student in the University of Alberta’s Department of Computing Science, supervised by Amii’s Michael Bowling.

Marlos’ research interests lie broadly in artificial intelligence with a particular focus on machine learning and reinforcement learning. Marlos is also a member of the Reinforcement Learning & Artificial Intelligence research group, led by Amii’s Richard S. Sutton.

In 2013, Amii researchers proposed the Arcade Learning Environment (ALE), a framework that poses the problem of general competency in AI. The ALE allows researchers and hobbyists to evaluate artificial intelligence (AI) agents in a variety of Atari games, encouraging agents to succeed without game-specific information. While this may not seem like a difficult feat, up to now, intelligent agents have excelled at performing a single task at a time, such as checkers, chess and backgammon – all incredible achievements!

The ALE, instead, asks the AI to perform well at many different tasks: repelling aliens, catching fish and racing cars, among others. Around 2011, Amii’s Michael Bowling began advocating in the AI research community for an Atari-based testbed and challenge problem. The community has since recognized the importance of arcade environments, shown by the release of other, similar platforms such as the GVG-AI, the OpenAI Gym & Universe,  as well as the Retro Learning Environment.

Atari 2600 games
1. Atari 2600 games: Space Invaders, Bowling, Fishing Derby and Enduro

The ALE owes some of its success to a Google DeepMind algorithm called Deep Q-Networks (DQN), which recently drew world-wide attention to the learning environment and to reinforcement learning (RL) in general. DQN was the first algorithm to achieve human-level control in the ALE.

In this post, adapted from our paper, “State of the Art Control of Atari Games Using Shallow Reinforcement Learning,” published earlier this year, we examine the principles underlying DQN’s impressive performance by introducing a fixed linear representation that achieves DQN-level performance in the ALE.

The steps we took while developing this representation illuminate the importance of biases being encoded in neural networks’ architectures, which improved our understanding of deep reinforcement learning methods. Our representation also frees agents from necessarily having to learn representations every time an AI is evaluated in the ALE. Researchers can now use a good fixed representation while exploring other questions, which allows for better evaluation of the impact of their algorithms because the interaction with representation learning solutions can be put aside.

Impact of Deep Q-Networks

In reinforcement learning, agents must estimate how “good” a situation is based on current observations. Traditionally, we humans have had to define in advance how an agent processes the input stream based on the features we think are informative. These features can include anything from the position and velocity of an autonomous vehicle to the pixel values the agent sees in the ALE.

Before DQN, pixel values were frequently used to train AI in the ALE. Agents learned crude bits of knowledge like “when a yellow pixel appears on the bottom of the screen, going right is good.”  While useful, knowledge represented in this way cannot encode certain pieces of information such as in-game objects.

Because the goal of the ALE is to avoid extracting information particular to a single game, researchers faced the challenge of determining how an AI can succeed in multiple games without providing it game-specific information. To meet this challenge, the agent should not only learn how to act but also learn useful representations of the world.

DQN was one of the first RL algorithms capable of doing so with deep neural networks.

For our discussion, the important aspect of DQN is that its performance is due to the neural network’s estimation of how “good” each screen is, in other words how likely it is that a particular screen will result in a favourable outcome.

Importantly, the neural network has several convolutional layers with the ability to learn powerful internal representations. The layers are built around simple architectural biases such as position/translation invariance and the size of the filters used. We asked ourselves how much of DQN’s performance results from the internal representations learned and how much from the algorithm’s network architecture. We implemented, in a fixed linear representation, the biases encoded in DQN’s architecture and analyzed the gap between our bias-encoded performance and DQN’s performance.

To our surprise, our fixed linear representation performed nearly as well as DQN!

Basic & Blob-Prost Features

To create our representation, we first needed to define its building blocks. We used the method mentioned earlier of representing screens as “there is a yellow pixel at the bottom of the screen.”

As Figure 2 (inspired by the original article on the ALE) indicates, screens were previously defined in terms of the existence of colours in specific patches of the image. Researchers would divide the image in 14×16 patches and, for each patch, encode the colours available in that tile.

Screenshot and basic features of the game Space Invaders
2. Left: Screenshot of the game Space Invaders; Centre: Tiling used in all games; Right: Representation of Basic Features

In this example, two colours are present in the tile in the top left corner of the screen: black and green. Thus, the agent sees the whole tile as black and green with the “amount” of each colour being unimportant. This representation, called Basic, was introduced in the original paper on the ALE. However, Basic features don’t encode the relation between tiles, that is, “a green pixel is above a yellow pixel.” BASS features, which are not discussed in this post, can be used as a fix but with less than satisfactory results.

When DQN was proposed, it outperformed the state-of-the-art in the vast majority of games. But the question still remained: why?

One of our first insights was that convolutional networks apply the same filter in all different patches of the image, meaning observations aren’t necessarily encoded for a specific patch. In other words, instead of knowing “there is a green pixel in tile 6 and an orange pixel in tile 8,” the network knows “there is a green pixel one tile away from an orange pixel somewhere on the screen.”

This knowledge is useful as we no longer need to observe events at specific locations and can generalize them at the moment they occur. That is, the agent doesn’t need to be hit by an alien projectile in every possible pixel space to learn it’s bad. The AI quickly learns “a pixel above the green pixel (the player’s ship) is bad”, no matter the screen position. We modified Basic features to also encode such information, calling the new representation B-PROS.

Representation of B-PROS features
3. Representation of B-PROS features

B-PROS is limited in that it doesn’t encode objects movement. If there is a projectile on the screen, is it moving upwards from the agent’s ship or downwards from an alien’s?

We can easily answer the question by using two consecutive screens to infer an object’s direction, which is what DQN does. Instead of only using offsets from the same screen, we also looked at the offsets between different screens, encoding things like: “there was a yellow pixel two blocks above where the green pixel is now.” We call this representation B-PROST.

Representation of B-PROST features
4. Representation of B-PROST features

Finally, as is the case with DQN, we needed a way to identify objects. The filter sizes in the convolutional network had the typical size of objects in Atari games built into the system, so we made a simple change to our algorithm: instead of dividing the screen into tiles, we divided it into objects to examine the offsets between objects. But how to find the objects?

We did the simplest thing possible: call all segments with the same coloured pixels an object. If one colour was surrounding another, up to a certain threshold, we assumed the whole object had the surrounding colour and ignored the colour inside. By taking the offsets in space and time of these objects, we obtained a new feature set called Blob-PROST. Figure 5 is a simplification of what we ended up with.

Representation of objects identified for the Blob-PROST feature set
5. Representation of objects identified for the Blob-PROST feature set

So how good are Blob-PROST features? Well, they score better than DQN in 21 out of 49 games (43 per cent of the games) with the score of three of the remaining games having no statistically significant difference from that of DQN. Even when an algorithm is compared against itself, we would expect it to win 50 per cent of the time, making our 43 per cent a comparable result.

Conclusion

We started by asking how much of DQN’s original performance resulted from the representations it learns versus the biases already encoded in the neural network: position/translation invariance, movement information and object detection. To our surprise, the biases explain a big part of DQN’s performance. By simply encoding the biases without learning any representation, we were able to achieve similar performance to DQN.

The ability to learn representations is essential for intelligent agents: fixed representations, while useful, are an intermediate step on the path to artificial general intelligence. Although DQN’s performance may be explained by the convolutional network’s biases, the algorithm is a major milestone, and subsequent work has shown the importance of the principles introduced by the research team. The state-of-the-art is now derived from DQN, achieving even higher scores in Atari games and suggesting that better representations are now being learned.

For a more detailed discussion of each of the evaluated biases, as well as of DQN’s performance as compared to Blob-PROST, read our paper: “State of the Art Control of Atari Games Using Shallow Reinforcement Learning.”

What is Machine Intelligence?

Existing at the intersection of machine learning and artificial intelligence, machine intelligence is advanced computing that enables a machine to interact with its environment in an intelligent way.

Amii specializes in the research and development of machine learning technologies, including their application in artificial intelligence.

What is Artificial Intelligence?

Artificial intelligence (AI) is a set of algorithms, processes and methodologies that allow a computer system to perform tasks that would normally require human-level intelligence. AI can appear as a component in a larger system or in the form of a computer application, digital agent or autonomous machine.

What is Machine Learning?

Machine learning is a field of computing science focused around developing algorithms that enable a computer system to independently learn from, and continuously adapt to, data without being explicitly programmed for that data. Machine learning is a crucial component in many artificial intelligence systems.

Where is Machine Learning Used?
  • Recommender systems (e.g. Netflix or Amazon)
  • Contextual web searches (e.g. Google)
  • Intelligent digital assistants (e.g. Cortana or Siri)
  • Game-playing AI (e.g. AlphaGo or Cepheus)
  • Autonomous vehicles
  • Email spam filters
Why is Machine Intelligence Important?

Recently, machine intelligence technologies have experienced a global resurgence due to growing volumes and varieties of data, the utility of this data in training smart systems and an increased awareness of the value of data in providing a competitive edge in business.

Machine intelligence is expected to form the basis for most technological and business advancements for years to come. According to a report issued by McKinsey & Company, technologies that employ machine intelligence will have created over $50 trillion in economic impact by the year 2025.

How Can Machine Intelligence Enhance My Business?

Machine intelligence allows organizations to operate more efficiently and effectively, using data to predict the future and manage the present.

Computer systems with machine intelligence can perform a variety of tasks:

  • Optimize and automate processes
  • Extract and classify data
  • Detect, analyze and predict trends/patterns
  • Enhance interaction with humans/the environment

Want to bring machine intelligence to your business? Visit our Innovation Affiliates program.

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.