I'm glad you're putting your finger on that. Ivan could probably talk about this a lot more eloquently than I can. I know that he's given it a lot of thought.
What I will say is that I do think there's an immense opportunity to open this up, and that whatever is today's technology may not be the technology we need in a few years. For a lot of today's technology, the race is really on the acquisition of the GPUs, these graphical processor units that are the building blocks for training the models, with Nvidia being one of the few giants and MD being another one that has the ability to produce this, but it doesn't mean that's going to be the solution that is dominating the market.
There's a lot of AI that is now moving towards being deployed on site. We're going to need hardware to deploy that AI in various devices, vehicles and others throughout the manufacturing industry, where really the GPU may not be the right form factor. To give you an example on that trajectory, a lot of the work we do at Cohere is actually in training much more efficient models. Where others are running models that need several dozen GPUs to run, we have models that run on just two GPUs, and maybe in a few years these models will be running on much smaller chips. The form factor may change.
I am fully supportive of exploring in what way we can build on the innovation and the research capacity we have in Canada—photonics and others—to really accelerate that field as well. We shouldn't think too short-term, especially when it comes to some of the more research bets that we support.