The Exchanges

Q people who are working in cloud or working to train models, are working to build their own chips. There's always a preface. We love working with NVIDIA and we're also building chips that compete with what they do. So how does that relationship work out? They don't get upset that you're trying to build the same. I mean, they have a supply issue, but how does it work with them?

A Oh, no, I have a great relationship with NVIDIA and Jensen and, um, uh, and, and this is a thing that we've done before. Um, we have a fantastic relationship with Intel and AMD, and we produce our own general purpose processors. And, and it's a big world out there, and there's a lot of market for, and then, uh, for lots of different use cases. That's not one is going to be the winner, right? There's going to be use cases where people are going to want to use GPUs, um, and there's going to be use cases where people are going to find training to be the best case. There are use cases where people find that, um, our Intel instances are the best choice for them. There are ones where they find that the AMD instances are the best choice for them. And there's increasingly a large set where they find Graviton, which is our purpose-built general purpose processor, is the right fit for them. And it doesn't mean that we don't have great relationships with Intel and NVIDIA, or Intel and AMD, and it means we'll continue to have a great relationship with NVIDIA, because for them and for us, it's incredibly important for NVIDIA processors and, and, uh, and then GPU-powered processors to perform great on AWS. And so we are doubling down our investment to make sure that NVIDIA performs outstanding in AWS. We want it to be the best place for people to run GPU based workloads. And, um, I expect it…

AI assessment note: “I have a great relationship with NVIDIA and Jensen and this is a thing that we've done before.”

Q said that the activity within AI right now, gen AI, is 50% training, 50% inference. Does that ratio still hold, and how are you going to put the chips out there to allow companies to be able to do cheaper inference? Because that's the issue with generative AI. It works well, but it's so expensive that companies take proof of concepts, and only one-fifth actually make them out into production.

A Yeah, it's absolutely the case, and I think we're You know, we're still probably seeing about that ratio of fifty-fifty. I think more and more it's more inference than training, and increasingly we'll see more and more of the workload shift that way. Um, it, cost is a super important factor that many of our customers are, are definitely worried about and thinking about on a, on a daily basis. And, you know, if you think about where a lot of people were, they went and did a bunch of these Gen.AI capability, or, um, tests, right, where they did proof of concepts and they launched hundreds of proof of concepts across the enterprise. Without really paying attention to, like, what was the value you're going to be or anything like that, and now they're looking at them and they're saying, well, my ROI is not really there, they're not really integrated into my correction environment, they're just kind of these POCs that I might get a lot of value out of, and they're expensive, as you mentioned. So two things that people are thinking about is, one, how do I lower the cost so that I make that, um, the cost much lower to run, and that's their point about cost of inference, and two, how do I actually get more value out of that so the ROI equation just completely shifts and makes more sense, and it turns out it's probably not all hundred of those. It's probably two or three or five of those…

AI assessment note: “we're still probably seeing about that ratio of fifty-fifty”

Q about in terms of anthropic, being able to help them scale the way that you are. And that would lead me to believe that Amazon would have its own cutting edge, state of the art model, one that would lead, you know, and be better than the open AIs and the anthropics. This is your core competency, and this is what makes these Models run. So why hasn't that happened?

A Our, our core competency is about delivering compute power for all of the people that need it. And, you know, for, for a long time, um, we've been very focused on how do we build the capabilities to let our customers build whatever they want. And sometimes, um, uh, there are areas that Amazon also builds and other times they're not areas that Amazon builds. And so you think about whether it's in the database world, or you think about in the storage world, or you think about the data analytics world, or you think about the ML world, We build this underlying compute platform that everybody can go build upon. And sometimes we build services that compete with others, uh, out there in the market. Think about a Redshift competing with a Snowflake, who's also a very important partner of ours and a big customer of ours, somebody that we do a lot of partnering together on. And then there's other times where there's applications that people build on top of AWS that Amazon doesn't go and build. And so we, we, uh, uh, operate across that whole swath of area and, um, and sometimes we'll build and sometimes we don't. But that's the, the kind of the beauty of AWS is that our goal is to build that infrastructure so that sometimes we can build those, sometimes we won't build them, but we want this platform that everybody can go build the broadest set of applications possible.

AI assessment note: “Our core competency is about delivering compute power for all of the people that need it”

Q Motto. Um, what does it look like right now? Is the economy back or are people still in efficiency mode?

A Yeah, I'd say, and by the way, it wasn't even just deals. We, we went and proactively jumped in with our customers and helped them figure out how they could reduce their bills. And, uh, we looked about Where they could consolidate resources, where they could move to cheaper offerings, where they could maybe do more with less. Um, and we, we were really proactive about helping customers reduce those costs because we thought, um, from our view, um, one is important for them as they thought about how they got their economics in the right place, and it was the right thing to do for them and, and built that long-term trust. Now, customers, I think, um, number one, a lot of them have been optimized, right? And there's only so much you can kind of squeeze into an Optimize place and customers are still looking for optimizations, but a lot of that work has been done and they're using some of that optimization to help fund some of the new development that they want to do. A lot of that is in the area of AI. Much of that is in the area of migration and modernization where they're moving from on-prem into a cloud world. And so some of those optimizations they did are helping them fund some of that work that's moving more of their workloads to the cloud that's moving and letting them go and build new AI experiences. Um, in AWS. And so that is where we've seen our growth, uh, start to come b…

AI assessment note: “customers are still looking for optimizations, but a lot of that work has been done”

Q it exactly as he said it, uh, he says, um, there have been pre-meetings, uh, for, for pre-meetings, for the decision meetings, a longer line of managers feeling like they need to review a topic before it moves forward, owners of initiatives feeling less like they should make recommendations because the decision will be made Elsewhere. Was that going on within AWS, and what is the process to change that?

A Uh, yeah, I think it's across, uh, across Amazon. So it wasn't specific to, to the rest of Amazon. It was definitely inside of AWS too. Uh, and you know, I think it's, uh, it's kind of a natural, um, evolution. Like we have these leadership principles inside of Amazon. And I think one of those ones that's important for us, a couple of, a couple that are, are things like being customer obsessed and really understanding the customer. And in order to really understand the customer, you've got to be close to the customer. And so a flatter organization, the more layers you have, the more removed you are from customers. And so We just kind of fundamentally, as we were growing, and then we went through an area of explosive growth of just the number of people and the size of the company and the size of the business. And so throughout that, we just didn't always have the organizational structure exactly right. And so it's, you know, we, we, we believe that a flatter organizational structure is better. The closer you are to the customers, the better decisions you're going to make, the faster decisions are you going to make. And you really want ownership to be pushed down to the people who really are making some of those decisions. And, and when you have a, a very kind of Um, hierarchical organization, um, where people don't feel like they have that ownership to make decisions, you go slo…

AI assessment note: “It was definitely inside of AWS too. Uh, and you know, I think it's”

Q their data in the cloud. They're going to build with Uh, their data they have within AWS using bedrock picking models. But you also are limited in the fact that OpenAI is not there. I don't think Google's there. So wouldn't it make sense in parallel to the bring your own model strategy to also use this capacity that you have to scale infrastructure to get in the game yourself?

A Look, what I will say is I'll never say never, right? I think that there's a, it's an interesting idea and then we'll, we never close any doors. I think we're always open to, frankly, a whole host of things. We're always open to To having OpenAI be available in AWS someday, or having Gemini models be available in AWS someday, and maybe someday we will spend more time focused on our own models, for sure. I think, you know, I think all of that is open, and part of what I think makes AWS special is we're always open to, you know, take our announcement earlier this year about partnering deeply with Oracle, about making Oracle databases available in AWS. Lots of people would said, oh, that's never going to happen, and it's against your strategy. Our strategy is to embrace all technologies, because we want Anything that customers can use, we want them to be available and to be able to use it inside of AWS. And look, sometimes it happens today. Sometimes it happens tomorrow. Sometimes it happens weeks from now, months from now, years from now. Um, but, but that is our goal is to make all of those technologies available for our customers.

AI assessment note: “maybe someday we will spend more time focused on our own models, for sure.”