Given the volume, the complexity of attacks these days, if companies are not thinking about that, they are going to have a really, really difficult few months in the current strategy. And certainly, there's a lot of governments who are thinking about that with respect to their own infrastructure and making sure that they have the right access to the technology. But I would encourage every organization, whether it's a company, whether it's a nonprofit, to think about how to secure their own systems.
And we are back. We are live with Joelle Pineau, who is the chief AI officer at Cohere, which just announced the initial close of a huge Series E targeting up to 7 billion Canadian dollars, 5 billion USD, at a $35.7 billion Canadian valuation. So congratulations, and Joelle, welcome to MTS.
Thank you. Thank you. Great to be here.
Absolutely. So tell us about the raise. What will this allow you to do?
Yeah, I mean, you know, Cohere, for those who might not be as familiar with who we are, you know, model building company headquartered in Toronto, really focused on building frontier technology, but focused on the enterprise side, enterprise, governments, and so on. So we build our own models, we build harnesses that are suitable for those kinds of deployments. And we do a lot of cases where folks want solutions for AI that are deployed on premise, air gapped, with really high guarantees of security and privacy. Obviously, you know, a lot of the raise is going towards training the next generation of models. It's big numbers, and at the same time, you know, the competition to build frontier technology is ferocious. And between the data centers, the data itself, the talent, and so on, it takes a lot to really maintain our capabilities and make sure that we're building the right technology for the enterprise space, which in some cases is actually quite a bit different from what we're seeing on the consumer side.
Totally. Well, yesterday we had on someone from Mistral, and I asked them this question. I'd love to ask Cohere the same question, which is: Cohere is, you know, an incredible company when it comes to enterprise fine-tune, enterprise deployments, but it is not a, you know, super bleeding-edge frontier lab in the way that OpenAI or Anthropic are. So do you think that it would have been possible to become so when Cohere was founded, and do you think that it would be possible to do so today?
I mean, that's an interesting question, right? Like, Cohere was founded in 2019. If you know, you look at any of these companies in 2019, I think the trajectory of all of them is really quite unpredictable. There's a lot of things that happen along the way that we didn't expect. At that time, what it was founded on, though, is that conviction that the technology was going to be really transformational. Aidan, our CEO, one of the authors on the Transformer paper, and did some of that foundational work while he was at Google. You know, like a strong conviction from the co-founders, from the initial investors, that this was going to be a major technology shift. They also, you know, made some choices of focusing on enterprise versus consumer, which maybe gives the work less visibility than others. And headquartered in Canada, which maybe has some impact in terms of the early funding trajectory. I would say right now, I think we're in a really good position to continue where we are. Specifically with respect to the competitiveness of frontier models, you know, and we watch all the same indexes as others in terms of monitoring that. What we really aim for is to be in the ballpark of having frontier models. Whether you fine-tune such that you're really suited to the latest results or not, it becomes less important. And we saw some shuffle recently, for example, when some of the Artificial Analysis index sort of shuffled the way that we're doing these indexes, and then suddenly like the ranking changed and so on. We try not to over-optimize on that and to produce models that are really high value for money and yet are within that margin of the frontier. A lot of our customers actually don't want to run frontier models. They're way too expensive. They're not necessary for the workloads that they have. And so we offer like a mix. We're model-agnostic in our platform. So we offer a mix of different solutions depending on the needs and try to get the best trade-off they have from like a security point of view, cost effectiveness, and then capabilities. Not all models are good. If you're doing coding, obviously like some models are much better than others. If you're really into chit-chat and conversation, other models might be better. And so we try to pick our lanes where we really bring value and keep growing the company.
Right. So about a month ago, Prime Minister Carney, who for our audience who may not know, Mark Carney is prime minister of Canada, he said that there are four countries on the forefront of AI development: the US, China, France, and Canada. So how important do you see AI sovereignty for Canada in particular? How much should Canada lean into, you know, championing domestic companies like Cohere instead of relying on American AI companies?
I mean, obviously, you know, Canada, the government of Canada under Mark's leadership is coming in as an investor in this round. So they have a pretty strong conviction that it is important to certainly to support the mission of Cohere, which is to build sovereign AI. We're hearing the same from lots of other countries. We've, you know, also announced a partnership with Aleph Alpha, German champion, and an intention to build much more of our European operations, Berlin, and other locations. We've announced recently a partnership with Isle, a cyber security company based in Prague. So we're seeing a lot of different companies and governments who really want to have access to technology that is frontier, but also have optionality. And really, this is what sovereignty comes down to. It's having the ability to control your access to the technology, to control your cost, control where it's running. So for the government of Canada, obviously, you know, having the ability to run models that are running in Canadian data centers that are built by Canadian companies is definitely an asset in terms of their strategy.
