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.
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.
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.