$NVDA CEO Jensen Huang says AI agents use roughly 15 to 100 times more compute than a human using the same tools, depending on the problem. Their broader business beyond hyperscale cloud, including sovereign AI, NeoClouds, AI startups, and enterprises, represents about half of their business and is growing 100% a year, which he expects to eventually be larger than what they currently see in cloud. Despite demand being much greater than 70%, supply allows them to confidently deliver 70% growth, which they are guiding to for the first time in order to give customers, shareholders, and the supply chain a consistent view. "As you probably are aware, AI has become useful and the AI agents that are being adopted everywhere use an enormous amount of compute. First of all, the large language models are larger than ever because they're smarter than ever. And these agents go through reasoning and planning multiple, multiple turns of tool use. The amount of compute necessary for an agent versus a human using it is probably 15 to 100 times depending on the type of problem you're trying to solve. And so the amount of compute necessary is just extraordinary. That's a factor that almost everybody sees. The part that people don't see about our growth because we're practically singular, because the nature of how we deliver products, we're the only company in the world that creates and builds, offers an entire AI factory platform, a full-stack system and customers can still mix and match. However, most companies just don't have the skills to do that or desire to do that. And so there's an entire part of the market that we experience growth. There's sovereign AI, the original IaaS, there's NeoClouds there's AI startups, there's enterprises where we're seeing, which represents about half of our business and that's growing 100% a year, that part of the world's computing is likely to be larger over time than even what we're currently experiencing in the cloud. I think the demand that we see is driven by all of those factors. It is also the case that you can no longer procure technology per se and stand up this infrastructure. You've got to go secure the land, power and shell, which oftentimes is a couple, two, three years out. All of the rest of the supply chain necessary to align the construction, the power, the cooling, all of the labor that's necessary. AI infrastructure is creating so many jobs all over the United States and all around the world, it just takes a lot more planning. And so we're involved in securing infrastructure now further down the pipeline. Just as a long time ago people asked me why it is that we're working with memory suppliers when we're a chip company? And today people understand it's really quite genius that we were working on our supply chain so far. Upstream we work with power generator companies, downstream we work with land, power and shell companies all around the world. And that helps prepare all of this computing that's going to be built that will ultimately deploy for our ecosystem and our customers. And so we just have a lot greater visibility now upstream/downstream It is the case that we've never forecasted or never guided to a year in advance. And, even though our demand is much greater than 70%, our supply allows us to confidently deliver 70% and we're going to continue to work with our supply chain to increase on that. But what we wanted to do is to be consistent with everybody from our customers, our shareholders, our supply chain. Everybody sees the same view. And the reason why that's important is because, everybody's putting a lot of resources at play. And so we wanted to make sure that everybody has the same set of information. And we've got a huge year coming up next year and it's going to be pretty extraordinary."