Q Um, without bad-mouthing your competitors, they, they, they are, um, a variety of, of, of companies, including the startups that have emerged around in this space, like Graphcore, and Sabanova, and all the things. Can you maybe help us contrast the approaches and, Are those doing different things for different people, or are you guys all going after the same opportunity? In that case, how different are you?
A Yeah, I certainly won't. There's plenty of space in the field, in the computer hardware field, for there to be multiple innovative plays. What we're doing is aiming towards the largest problems at data center scale, and fundamentally new research. If you have more data that you can train with right now, that would be where our machine comes in. And I, I think there are specialists who work only in low power inference, who want to have edge devices, who are, uh, trying to put intelligent processors in cars, um, and, and who are taking different cracks at the same thing, who, uh, who maybe wants the, the most compatible with the existing software ecosystem rather than fundamentally new innovation. So I, I think that there's plenty of room at this point while the field is advancing, and, and that's part of what makes it exciting is the, Um, the developments in, in data science and AI have made it possible for us to do this innovation.
AI assessment note: “What we're doing is aiming towards the largest problems at data center scale”