About

About the CIFAR Deep Learning + Reinforcement Learning School

Since 2005, when CIFAR’s Learning in Machines & Brains program hosted its first Deep Learning + Reinforcement Learning (DLRL) Summer School in Toronto, a thriving community of DLRL Summer School graduates has grown year-over-year, with our alumni now leading some of the world’s top tech firms and university labs.

Today DLRL is a keystone next-generation offering of the CIFAR Learning in Machines & Brains program and the CIFAR Pan-Canadian AI Strategy, hosted each year in partnership with Canada’s three national AI institutes, who take turns hosting each year: Amii in Edmonton, Mila in Montreal and the Vector Institute in Toronto.

Now celebrating its 20th year, DLRL truly is where the world comes to learn AI.

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Deep learning + reinforcement learning = machine learning to drive discovery and opportunity

Deep Learning (DL)

Deep neural networks are a powerful method for automatically learning distributed representations at multiple levels of abstraction. Over the past decade, they have dramatically pushed forward the state-of-the-art in domains as diverse as vision, language understanding, game playing, graphics, health care, materials discovery, and genomics. The DL curriculum offered in this year’s Summer School will cover both the foundations and applications of deep neural networks, from fundamental concepts to leading-edge research results.

Reinforcement Learning (RL)

Reinforcement Learning is a family of approaches for developing systems that learn optimal behaviour through interaction with an environment. In recent years, reinforcement learning has seen success as an essential component of Deep Reinforcement Learning, which has helped AI researchers achieve previously unheard of results in games like Go, robotics, and in the development of autonomous vehicles. The RL curriculum offered in this year’s Summer School will cover the basics of reinforcement learning and show its most recent research trends and discoveries, as well as present an opportunity to interact with graduate students and senior researchers in the field.

Generative AI

At the heart of generative AI are the breakthroughs in reinforcement learning and deep learning that will be explored at this year’s DLRL. From theory underpinning generative AI such as neural networks and deep reinforcement learning, to interactive sessions, prompt engineering and AI-generated music, participants will have the opportunity to deepen their practical and theoretical knowledge of generative AI.

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“The #DLRL Summer School is a place of learning at the highest scientific level in world-changing research areas but also an opportunity for networking, creating connections which can stay for life and fuel future collaborations.”

Yoshua Bengio

Canada CIFAR AI Chair, Mila | Co-Director, CIFAR Learning in Machines & Brains Program |
Scientific Director, IVADO | Scientific Director, Mila | Professor, Université de Montréal
Kimberly Nestor

“Attending DLRL 2023 was such an enriching summer school experience! I had a great time academically and it allowed me to expand my knowledge about the field. I made lifelong friends and connections, while learning about potential internships and postdoctoral opportunities.”

Kimberly Nestor

Kyunghyun Cho

“I attended DLRL early in my career. The lectures were amazing and provided an opportunity to have close interaction among the participants, and it was at that point that I decided I wanted to continue to do research full time in the area of deep learning.”

Kyunghyun Cho

Associate Professor, New York University; Fellow in the CIFAR
Learning in Machines & Brains program, CIFAR Azrieli Global Scholar 2017-2019
D'jeff Kanda Nkashama

“What struck me the most was the commitment of the DLRL summer school organizers to foster inclusive AI. As a member of a minority visible group, I was fortunate to receive the CIFAR Inclusive AI scholarship that enabled me to participate fully in this enriching program. Throughout the summer school, I delved into various aspects of machine learning, spanning optimization, computer vision, natural language processing, as well as ethical AI and AI safety. The breadth and depth of knowledge covered were truly impressive.”

D'jeff Kanda Nkashama

Alona Fyshe

“[The #DLRL] is a wonderful opportunity to bring the AI leaders of tomorrow together for a fun and immersive learning experience. It’s also a great way to showcase the depth of AI knowledge and expertise that exists in Canada.”

Alona Fyshe

CIFAR Learning in Machines & Brains;
Canada CIFAR AI Chair, Amii, University of Alberta
CIFAR Azrieli Global Scholar 2016-2018
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