Canada hosts first WAIC 2026 Global AI Insights Dialogue

CAI and the Harvard Frontier Techne Club Initiative brought together researchers, entrepreneurs and ecosystem leaders in Toronto on July 25 to expand cross-border AI collaboration. The forum highlighted trusted AI, AI agents, embodied intelligence, AI for science and governance as Canada and Asia look to deepen ties.

Why it matters: - The Toronto forum aimed to strengthen trusted AI collaboration between Canada, Asia and other global innovation hubs. - The event brought academia, industry, investors and innovation communities into one conversation on AI deployment and governance. - The dialogue added a Canada-focused bridge to WAIC 2026 discussions already shaping global AI priorities.

What happened: - CAI, the Canada–Asia Council for AI and Digital Innovation, and the Harvard Frontier Techne Club Initiative hosted Canada’s first WAIC 2026 Global AI Insights Dialogue on July 25, 2026, in Toronto. - The forum connected AI researchers, entrepreneurs and ecosystem leaders across Canada, Asia and beyond. - Organizers said 61 global participants from more than 50 organizations took part. - The event focused on AI Agents, Embodied Intelligence, AI for Science and AI Governance.

The details: - Confirmed participants included the Canadian Academy of Engineering, the Alberta Machine Intelligence Institute, CIFAR, Harvard, Agent Arena, Cohere, Draper and the National University of Singapore. - Other participating organizations included the University of Toronto, Vector Institute, University of Pennsylvania, Tsinghua University, Fudan University, Harvard Kennedy School, Meta, ByteDance, Rogers, Bell Canada, Airwallex, BMO and Osler. - The forum was designed to surface opportunities and challenges in AI Agents, AI for Science, Embodied Intelligence, AI Governance and global innovation partnerships. - The agenda aimed to deepen ties among researchers, builders, investors and ecosystem leaders across Canada, Asia and the global AI community. - The forum was supported by Quakers Venture Club at Penn, the Cyberport x Draper Dragon Joint-Accelerator Program, Agent Arena, AllScale and Siyuan AI Box.

Between the lines: - The event built on WAIC 2026, where Canadian AI work was represented by Richard S. Sutton, Yoshua Bengio and Gilles Brassard. - Huijuan Mu, deputy secretary-general of CAISTC, used opening remarks to stress trust and practical international cooperation. - Hugh H.T. Liu of the University of Toronto Institute for Aerospace Studies and the Canadian Academy of Engineering linked Canadian research strengths with Asia’s manufacturing, engineering and deployment capabilities. - In a recorded presentation, A. Rupam Mahmood of the University of Alberta, a CIFAR AI Chair and Amii Fellow, said most models stop changing after training, while continual learning requires adaptation after deployment. - Mahmood said hyperparameter sensitivity and run-to-run variation remain barriers to reliable continual learning, and his related research on loss of plasticity appeared in Nature. - Panel 1 focused on real-world learning, multi-agent orchestration, validation gaps in bio screening and contract responsibility for AI outputs. - Panel 2 focused on trust in market entry, problem-led co-development, localization, partner matching, product-market fit and data protection. - Stanley Diao, founder of CAI Global, said AI’s future will be built through collaboration across research, industry, investment and entrepreneurship.

What's next: - The forum’s cross-sector network now has a template for future collaboration across Canada, Asia and other AI ecosystems. - Organizers and participants are positioned to keep working on AI agents, embodied intelligence, AI for science and governance after the Toronto dialogue. - The discussion around trusted AI and deployment challenges suggests more follow-on work on how models move from research to real-world use.

The bottom line: - Canada’s first WAIC 2026 Global AI Insights Dialogue framed AI collaboration as an international, multi-sector effort rather than a country-by-country race.