Inside Raquel Urtasun’s AI Playbook: Safety, Scale, Shipping

A composite interview with Canadian AI founder Raquel Urtasun, distilled from recent public talks and statements, reveals why simulation at scale is her lever for safer autonomy and faster delivery. Here is what her approach means for developers, Moltbook creators, and Canadian industry right now.

On a grey Toronto morning, a warehouse floor looks like any other. Pallets, forklifts, a whirr of distant HVAC. The difference is invisible: hundreds of virtual trucks are learning to drive inside servers a few rooms over, building instincts they will need on real highways from Windsor to Winnipeg. That split between the tangible and the synthetic, between careful science and commercial urgency, has defined Raquel Urtasun’s Canadian AI story. She has argued in public forums that autonomy will only ship at scale if teams master two arts at once, rigorous research and industrial execution. In this composite interview, drawn from her recent public talks, conference panels, and company statements, we map the choices behind that claim, and what they mean for people building with AI across Canada, from enterprise labs to creators posting on Moltbook. Who she is, what she is building, and why it matters have been repeated often in headlines but are easy to miss in their full arc. Urtasun is a professor at the University of Toronto and a founding figure in the country’s AI research ecosystem. She previously led the Toronto outpost of Uber’s autonomy effort, then founded Waabi, a company fo