There are a multitude of aspects that come into play when you're going to evaluate. If you're going to, for instance, train one of these very large models, one that has access to data, there are currently certain issues around the copyright law that prevent companies from using text or images, whereas, in the U.S. or Japan, they can freely use them.
This has been pointed out in the past. This prevents anyone who's training these types of models from training them or operating them from Canada. What you're seeing is that Canadian companies are going to the U.S. and driving runs of hundreds of millions of dollars of training into the U.S.—not in Canada, because that prevents them from being able to innovate. I'm giving an example. My concern was that by having a blanket approach, there will be pockets of situations like that.
What I'm pointing out here is a small thing. It's just text for this particular situation, and then, boom, Canada is not playing in the large language model game. There will not be any large machine-learning data centres built in Canada, not a single one. These are multi-billion dollar investments.