Contributions to the Canadian AI Ecosystem:
Innovation, Talent Attraction & Economic Development
TMLS (Toronto Machine Learning Series) was created in 2016 as an educational/networking series to grow the Canadian Machine Learning community. With over 6,000 active members across several disciplines, today members include business leaders, scientists, researchers, investors and data practitioners.
The TMLS Community and Steering Committee works to explore technical, social and industrial opportunities that promote and encourage the adoption of successful machine learning initiatives within Canada. Our initiatives allow for the dissemination of key case studies, and the utilization of our rich academic resources shared among our diverse community.
2019 has seen the Canadian AI ecosystem continue to grow at an unprecedented rate. With over 650 AI start-ups recorded in 2018, this number continues to grow in 2019. As well, SME’s and enterprise companies are taking more serious steps to leverage their data, pilot and launch AI initiatives. Still, operational AI is still very nascent, with best practices for technical and structural implementation still being explored and understood within traditional industries.
To implement competitive AI strategies and go to market with successful global products, Canadian companies are looking to take advantage of the research in Academic hubs, learn from global use-cases, build long-term strategies, attract talent, and source experienced leadership.
Our Committee has found that many Canadian companies and executive teams are not fully aware of the opportunities around AI. The time requirements of a long-term data strategy, and the technical requirements of managing data across functioning teams is still being understood. Data Management, and Change Management are the most common hurdles observed by our Committee. These challenges are common struggles, hindering the ability to demonstrates ROI for stakeholders, or prioritize specific initiatives within larger organizations.
While Canada has produced the world’s leading AI researchers, engineers, and top academic talent, the number of Canadian technology companies (including AI start-ups) is significantly underrepresented in global markets.
As well, Canadian companies still look benefit from these resources and find competitive global opportunities, while an influx of international artificial intelligence research labs open in Toronto, Montreal and Waterloo.
In 2019, TMLS initiatives strive to;
Position Canada not only as a global hub for AI research, but a hub for innovation and commercialization.
Highlight world leading AI research, as well as key strategic opportunities for Canadian Industries.
Continue to thwart the talent “brain drain” by providing ample opportunities for researchers and practitioners to connect with local companies and find fulfilling jobs in AI.
Promoting the inclusion of diverse groups and interdisciplinary participants as a standard practice in the development and implementation of AI initiatives.
Increase entrepreneurship with the commercialization of intellectual property by linking academic research with relevant industry contexts and connections.
Helping Industry understand the importance and urgency of using their data critically and responsibly to successfully integrate roadmaps and effective AI strategies.
Helping Industry identify key opportunities, based on regional and international markets and trends.
TMLS hosts a series of events and community initiatives to that help facilitate high-quality networking, hiring and both technical and industry-specific content unique to Canadian Industries.
Our content is peer-reviewed by a Steering Committee from Industry and Academia, and delivered by local and international thought-leaders (over 300 to date), focusing on four key areas;
(1) Business Opportunities
(2) Advanced Research and Tech
(3) Use Cases of Operationalized ML
(4) Hands-on Workshops
26.8% Business Leaders, (Executives, Managers)
52.4% Data Practitioners; (Data Scientists, Machine Learning Engineers, Data Analytics Etc.)
20.8% Researchers, Students, Other
52% of currently working in Industry
800+ Job Seekers
33.7% Highly qualified practitioners