Description
Toronto Machine Learning Society (TMLS) started in 2016 and describes itself as the largest Canadian in-person community for machine learning researchers, practitioners and executives. Its flagship TMLS Summit has run for ten years, drawing 60+ speakers and 400+ attendees to a multi-day program of keynotes, technical sessions and a dedicated workshop day, reviewed by a volunteer committee.
Read More
In 2026, TMLS is also presenting MLOps North, a Toronto summit on November 5 and 6 at RBC WaterPark Place, themed "Building with Agents." The two-day event covers 10+ tracks and 35+ sessions split across two threads: the agent stack itself (frameworks, memory, evals, orchestration) and what teams ship on top of it (products, workflows and agents in regulated industries). Seven curated tracks include Evals and Benchmarks, led by Kathryn Hume of the Vector Institute; AI Sovereignty, led by TMLS founder David Scharbach; Agent Memory Architectures, led by Suhas Pai of Hudson Labs; and Cost Management and ROI, led by Denys Linkov of Wisedocs.
TMLS is guided by conference co-chairs, including Scharbach (Executive Director), Pai, Linkov and Graham Toppin of Peerlabs, supported by a large committee of practitioners and researchers from banks, tech companies and universities who help shape each year's program. Beyond the summit, TMLS runs community initiatives around education and career development, business and partnership opportunities, hiring and talent connections, and diversity and inclusion, along with events like an agentic hackathon.
The society publishes recaps and articles on its site and archives past summit sessions and speaker talks for later viewing. Recent posts have covered topics like the TMLS Agentic Hackathon and how model capabilities are becoming commoditized, reflecting the community's shift toward practical, applied AI rather than research for its own sake.
TMLS is built for people already working in or adjacent to machine learning and AI, from researchers and engineers to the executives and teams adopting AI across Canadian industry, rather than for AI beginners. Attending the summit, in particular, means buying a ticket rather than joining for free, though the community's workshops, roundtables and online articles are open more broadly to anyone following the Canadian AI ecosystem.
- CategoryOther AI Tools
- Pricing ModelPaid
Highlights
Annual TMLS Summit with keynotes and technical tracks, now in its 10th year
MLOps North Toronto Summit (Nov 5-6, 2026) focused on building and shipping AI agents
Seven curated tracks led by named practitioners from the Vector Institute, Hudson Labs and Wisedocs
Year-round community programming: workshops, roundtables and an agentic hackathon
Volunteer committee of researchers, engineers and executives who help shape each program
Session and speaker archive published online after each summit
Education and career-development initiatives for the Canadian AI community
Hiring, talent-connection and business/partnership programming
Who Should Attend
- Attend the annual summit
- Learn agentic AI patterns
- Network with Canadian AI teams
- Find or recruit AI talent
