Toronto Machine Learning Summit (TMLS) 2026
📅 Tuesday, 16 June 2026 → Friday, 19 June 2026
Toronto Machine Learning Summit (TMLS) 2026 — Canada's flagship applied-AI conference, now in its 10th year — runs 16–19 June at CIBC Square, Toronto: a virtual day, two in-person days of keynotes and vetted industry case studies, and a workshop day for a 10,000-strong ML community.
Toronto Machine Learning Summit (TMLS) 2026 is Canada's leading conference for applied artificial intelligence, marking its 10th annual edition. It runs 16–19 June 2026 at CIBC Square in downtown Toronto, structured as a four-day experience: a virtual day, two in-person days of keynotes and technical sessions, and a dedicated workshop day. The summit draws 400+ attendees and 60+ speakers, with CIBC as platinum partner.
On the programme
TMLS deliberately positions itself around AI in production rather than pure research novelty. Its programme mixes cutting-edge research, hands-on workshops and vetted industry case studies — all reviewed by a programme committee — and emphasises community, learning and accessibility over vendor spectacle. Speakers are drawn from both research and industry, sharing practical lessons from deploying machine learning in real Canadian organisations across finance, healthcare, retail and the public sector. The four-day format lets practitioners attend the virtual day remotely, gather in person for the keynote and case-study core, and go deep in hands-on workshops, with the committee-review process intended to keep the signal high and the sales pitches out.
Who runs it
The summit is organised by the Toronto Machine Learning Society, a community of more than 10,000 ML researchers, professionals and entrepreneurs that exists to unite and support the Canadian AI ecosystem. That community-first orientation — rather than a pure conference-business model — is central to TMLS's identity and to the trust it has built over a decade.
Where it fits in today's AI
Toronto and the wider Canadian corridor occupy a singular place in modern AI history: this is the region where deep learning was substantially incubated, home to the Vector Institute, the Geoffrey Hinton lineage, and a dense cluster of research labs and startups. Yet much of the public AI narrative now flows through US tech giants, and the practical question for most Canadian organisations is not who trains the largest model but how to put AI to work responsibly and profitably. TMLS speaks directly to that gap. Now in its tenth year, it functions as the annual checkpoint for Canada's applied-AI community — where the people actually shipping models compare notes on what works in production: evaluation, reliability, cost, MLOps, and increasingly the deployment of LLMs and agents inside regulated industries. For researchers, practitioners, founders and AI leaders in Canada (and visitors who want a clear read on one of the field's foundational ecosystems), it is the country's most important applied-AI gathering. Tickets are sold via the official TMLS site, and a call for speakers runs ahead of each edition.
The CIBC Square venue and downtown-Toronto setting put the summit in the heart of one of North America's denser AI corridors, and the four-day shape — with an opening virtual day — means practitioners anywhere in Canada can take part even if they can only travel for the core in-person days. For a tenth-anniversary edition, the emphasis remains pointedly practical: vetted case studies, hands-on workshops and committee-reviewed talks aimed at the engineers, data scientists, ML leads and founders who have to make AI deliver value inside real Canadian businesses, supported by a platinum partnership with CIBC.
