Diarmuid Gill: commitment

Transcript context

…And maybe just a last word on that. You have a team or a bunch of people working on what is called a trustworthy machine learning. And I think that it has never been as important as today because precisely the type of information, the volume of information that people are ready to share is like massive. And there's this question and that's That's not just a research question anymore. People are like, it's very practical. And we do look at how we can, so trustworthiness is fighting against hallucination, being sure that it's privacy safe, being sure that sometimes we're not. Or sometimes we do understand that the people we talk with have someone that we should recommend to. So that's something that we're looking at. Maybe we are a bit like more on the upstream side of things, but we know that at some point, yeah, something that is going to be very strong, either in terms of regulation, in terms of, I do not know, but we prefer to be on the same side, on the safe side, and we kind of prepare our weapons to be able to answer at the right time. And I think, yeah, I totally agree. And I think the fact that we kind of were based in Europe, right, where there's definitely with things like GDPR, there's a lot of sensitivity around those. We've always had that as a core principle as we build out these products. For advertising to be truly useful, it has to be trustworthy, right? So the user, we don't want to do anything that's creepy because if it's creepy, it won't work, right? It has to provide real utility when the user sees it, they go, okay, that's interesting, that's engaging. If that's the case, then they're more likely to click on it. They're more likely to click on it, then it means that we're a better value provider for the advertisers. Can you tell a little bit more about, I mean, I think probably a lot of people are surprised almost an hour into the conversation to hear the company has roots in Europe, is headquartered in Europe. You know, I tend to think of ad tech as a, you know, mostly American phenomenon. But how different is it really trying to operate in Europe versus the United States? Are there things that you actually do differently across jurisdictions based on restrictions that may exist in Europe? Or is it sort of the same approach globally? Like, I think people have a lot of sense that there's, you can't do AI in Europe is kind of what the, you know, I think the first order summary would be from a lot of people. So if you think that's wrong, disavuse us of that.…

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