Hello, and welcome to the Financial Analyst Meeting for 2024. Been a very exciting week. Attendance was definitely up, energy way up, way up. Now, there's a lot of thematics you'll see through the show, one of which is artificial intelligence. Now, using artificial intelligence, I pose the question: what slide would investors want to see most? And here's what it came up with. I know, I know, you love it. You love it, I know. Me too. Okay, kidding aside, I need to call out some important key points about our safe harbor, right? First, and obviously, we will be making some forward-looking statements today, and of course, the statements are subject to risks and uncertainties. Some of the factors that could affect our forward-looking statements, we detail those for you in our financial filings with the SEC, including forms 10-K and 10-Q. All the information we're sharing with you today is as of today. Now, lastly, we will not be undertaking any obligation to update the forward-looking statements we'll be making today in light of future information or, you know, any other market-moving events. We will not be obligated to update what you hear today. Second thing is, we will be making use of non-GAAP financial measures, so just keep that in mind. They'll be noted for you on the slides when we're using non-GAAP measures. And then, of course, especially with some of the product guys, you will hear some comments about some of our technologies, but just bear in mind, these are just for informational purposes. There's no commitments about any of this. Just keep that in mind. Okay, the agenda. We're gonna have a pretty good day. Busy. We'll start... Clay is gonna come on up first, talking about Oracle Cloud Infrastructure, and then after that, we're gonna have a couple panels, actually three. Two roundtables led by Lea Yumtobian. She'll be basically bringing up the first group, talking with you about database and analytics. Following that, we'll bring up our apps guys, including Mike Sicilia, running the industries business, and they'll talk about cloud applications, and then it's always good to hear the voice of the customers. Safra did a great job just the other day, bringing up tons of customers. Better that you hear it from them sometimes, and we'll have some of those folks coming up from Nomura Research Institute, MGM Resorts, and Vodafone. That'll take us to lunch. After lunch, Doug will come on up and provide you all with a financial update, and following that, Safra will come on up. She's excited about doing the Q&A. She wants to hear all the great questions you have. And then we'll do our usual annual Q&A with Larry, who will definitely be here. So with that, let's go ahead and get started. Please welcome Clay Magouyrk to the stage. That was less of a reception than I was expecting. Can we... I'm gonna walk over here again, and I'm gonna need- Okay. See, that's not even... That's not for me, that's for you. Look, let's be honest. I'm gonna get to be done here in about thirty minutes. You're gonna have to sit here, and the higher energy you can maintain, I don't know if any of you have a whoop on, your calories burned will be higher. Okay. So this is the slide that Ken mentioned, that he said I have to also tell you, and then I think this is the second slide that Ken mentioned that he says I also must tell you about. So those are the slides that Ken talked about. OCI is growing very quickly. Based on which key metric you want to look at, if you think about revenue growth, up more than 50% year over year. In terms of customer-facing regions, and the reason customer-facing regions is important, just so you're understanding, is we don't build regions unless people want them. I've tried asking Safra if she'll let me just build regions that don't have demand. You don't want to hear her response. But the fact that we are growing the region footprint this quickly is a very different way of looking at our business. The fact that data center capacity is growing at a much faster rate than revenue, we're not building data centers because we don't have demand either, so these are all indicators of the scale of demand that we're seeing across the industry. Another key metric that I think is important to grasp is that the number of customers that spend more than $5 million a year with us on OCI directly. This doesn't include the other parts of our business. It's not talking about database license revenue or support, but just on cloud infrastructure has grown 42% year over year. What is it that's driving this growth? And for those of you who've been here before, which is many of you, I really try to take our business and break it down into a few different pieces. We're gonna talk about our enterprise customers, which are the ones that everyone knows the most about here at Oracle. We've had for a long time. We'll talk about cloud native and AI customers, and then we'll talk about another critical part of our business, which is what we're doing with distributed cloud around Dedicated Region and Alloy. So when you look at what's driving enterprise growth, we can talk about many of the services, and I'll bring some of those up in a second. The general things that you'd expect from any public cloud provider: you launch more regions, you launch more features and functions, you scale your sales organization, you scale your ability through SIs. We're doing all of that. But the single biggest thing that we've done recently is that if you go back 13 months ago, there was one cloud where you could get Oracle Database services. There was one cloud that had its salespeople out selling Oracle Database services, and it was a great cloud. Look, I'm very proud of it, but it was only one cloud. As of today, we now have four clouds, and it's not just any four, it's the four. And I don't know how many of you have talked to different customers. I've had a lot of different conversations. There's something very different about some versus all, and when I have conversations with customers now, they are incredibly encouraged by the fact that it doesn't matter which cloud they choose, they can maintain their investment in the Oracle Database, they can move that into the cloud and still get all of our best and greatest services. This, along with all of the other investments we're making into our general purpose public cloud, is what's causing us to have such high growth, for example, and the number of customers spending more than $10 million in the enterprise space year over year. And I want people to also grasp, you know. I'll talk about the number of regions we're launching here in a minute. We have several thousand racks of capacity, and by capacity here, I don't mean we land the racks ahead of time. What I mean is that we have plans for this. This is the size of the market that we see in our conversations with ourselves and with our partners. If you take a look at this map, you can see a few things. One is that we need a bigger screen 'cause there's not enough place to put all the dots, but we have a lot that we've been doing, both across our commercial regions, our dedicated cloud regions, but when you add to it the huge investment we're making across our multi-cloud partnerships, you realize that the available locations in which you can procure our industry-leading, best-in-class, highly differentiated data platform services. You're just able to procure them in so many more places than you were yesterday. I'm gonna take a moment and try to get everyone here to understand one critical point, and this is something that if you get it, you're gonna feel like I'm spending three minutes on a topic that is obvious. But I've talked to enough customers now, who even after I've said this, and probably is feedback for me, I'll put it in my performance review, get better at explaining technology to people. But it's really important to understand the way in which our multi-cloud strategy is different than what anyone has done before. So if you go and you look at a traditional company, so I'm not gonna name names, but if you think about, companies that are doing analytics on Amazon and Microsoft and Google, or companies that are doing databases, the way in which they run is they have a service, and they run that thing on top of those clouds. You go to Amazon, and you procure some EC2 instances, and you procure some Elastic Block Store, and you procure some S3 storage, and you build your application, your service. And then when you wanna do Google, you have to go and redo that thing, and you have to use it on top of that cloud, and the same thing applies for Microsoft Azure. That's not what we've done with OCI. What we've done is we've created a first-in-class, kind of ever-done-before partnership, where we bring OCI, and we extend it into the other cloud provider. Okay, now, the reason that's important is that it's important for us, it's important for customers, and it's actually really important for our partners, and I'll explain why. First, the most important reason why this is so valuable to customers is that I don't know if anyone has paid attention to the things that Oracle's been doing over the past forty-seven years, and I know that in a few minutes, Lea's gonna be on stage, and we're gonna hear from Edward and Juan and TK about all the great innovation. Everything that we have available inside OCI is now going to be available in our partner clouds. So as we come up with a new hardware platform, the next generation of Exadata, the next generation of our highly optimized network, I don't have to go and try to bargain with these multi-cloud partners to allow me to use that technology. It's my technology, I put it in there, okay? The reason customers love that is that they get the same level of service and quality. It's not a matter of, "Well, it's great we rolled it out to OCI, but it's gonna take us eighteen months to get it into Google and..." No, it's the same service, so when I was having a conversation with customers yesterday, and they said: "Hey, Clay, so, like, you know, what are your references for this recently launched four regions with Google?" I go, "Fusion, NetSuite, Exelon, you know, FedEx." Every single customer that runs their database is in our cloud today, and they go: "Well, I don't understand." I go, "It's the same service. I don't mean it's like... It's not a, even a separate copy of the same service. It's literally the same service with the same functionality." Now, I know, again, it feels like if there was a horse, and it was no longer alive, and I was hitting it, I understand. But it's important everyone here understand the true value of that. The customers get all the best capabilities that we have instantly. We love it because it massively simplifies our management. We don't have to go in and have four copies of this service with extreme cost and overhead. It's the same thing. And our partners like it because what they know is that they actually get the same quality across all of them. I don't have this conversation with Microsoft or Google about when do I get... It's like, great, it's the same. They're happy because they get the same capabilities. So-... I'll stop beating that one, but it's really important everyone walk away understanding why that's so different. We also continue to launch more and more new services, right? Our new caching service, something, you know, I'm not sure if Juan will talk about, but the fact that we now have our globally distributed autonomous database, I think is truly incredible. We continue to innovate across the board, and all of these services end up, right, continuing to grow across our enterprise customer base. So moving on to our cloud-native and AI customers. 162% year-over-year growth in the number of customers in this category. You know, more than two and a half times capacity increase compared to where we were a year ago serving these customers, and more than $3 billion in TCV of wins in Q1. Why do these people pick us? It was funny. I'll tell you a anecdote. As part of the preparation for this, I was talking with Doug Kehring, who talks later, and he sent me a text. He's like: "Hey, what was the exact date, you know, when we launched OCI?" And so I type it into Google, and I found the blog post that was written in 2016. So I've been working on OCI from the very first day until now, and it was interesting to go back and to read the blog post. And I was like: Wow, either we were... either we're not good at changing our strategy, or the strategy was good. Because I can tell you that the blog post from eight years ago talks about the same things that I'm talking about today. Now, it's much easier to convince people it's a good strategy that we're successful. I can tell you, is that when you're talking about a strategy and you haven't been successful yet, it doesn't always go well. These customers are choosing us because of very fundamental things, like performance and availability, security, and support. That's what it is, and if you go back and you look at our very first launch, when we said, "Here's our first region," that's what we talk about, okay? You know, a couple of notable ones here. Over the past quarter, you know, Cloudflare, sorry, CrowdStrike and Palo Alto joined us. The reason for that is because they're becoming more and more aware of the economic advantages and the, and the security advantages that our cloud offers. Then, if you saw my keynote, you can see how a company like Skydance is now rendering entire films on top of us. But then we're working very closely with Greg and the team on actually completely revolutionizing their entire studio, where they don't wanna have any more workstations. They don't wanna have any more of their own data centers. Everything to be able to run an entire animation studio runs in the cloud. That's the, you know, breadth and depth of this segment of our customer base. So it's great that we've been talking about it for a long time, but why? Why does it work? I'm not gonna stand up here and talk about a whole bunch of very detailed technical pieces. I will talk about one that hopefully will resonate. So in the very beginning, we decided to do bare metal. We offered. In the beginning, actually, we only offered bare metal, and we did that because we believed it was the right security posture, such that if you have that clear separation between what you can give a customer and you can firmly believe you can take it back and securely wipe it, you build a more secure cloud over time. We also, in the beginning, invested very heavily because of the great work that Juan and Andy and their team did on Exadata to ensure that we built dedicated RDMA networks for clusters, right? If you were at any other company and you were building a cloud from scratch, I promise you that would not have been a priority for you, okay? And by the way, when we did that technology, we didn't just build it. We made sure it was just as secure, that it was entirely virtualizable in a different way than our front-end network, but it was multi-tenant, so we can carve it up and we can... So we did all of that. So suddenly, along comes AI, and what does AI need? AI needs clusters. They know they might be bigger, they might be smaller, they might look different, but they need highly secure, very performant clustering technology. If you actually go and look at the available clouds today, ourselves and our key competitors, and you actually go and understand why are people choosing us, it's because of these same investments. It's the fact that we built a completely virtualizable RDMA network, but it's integrated into our systems. So what other cloud providers will do is they'll say: "Oh, we have this," but it's basically bare metal hosting off to the side. That's not what we do. We have complete API control. You can provision, you can restart, you can securely wipe. Other people don't do that. Many other clouds don't even have a dedicated network. They said: "Hey, that's too complicated, it's too expensive, it's too hard. We don't wanna deal with all that complexity. Why don't we just sacrifice your performance and run it over the same front-end network?" Right? So when this workload came around, yes, we had work to do. I'm not saying that we didn't have to design larger scale networks, and there isn't different tuning, there's... But we can go into all of, you know, ECNs and how you do congestion control on a very large GFAB, and how does that compare to a couple of Exadata racks? But what I can tell you is the fact that at Oracle, we believed that performance matters, and we believe that security matters, and that you don't just tack it on at the end, that you make this a critical part of your functionality, enabled us when this opportunity came around, right, to provide just a better offering to our customers. And you see this in our numbers every day. I mean, I update this slide just so you know, I don't copy-paste the same slide year to year. I do actually have my team go out and make sure, because prices can change... You can come to OCI, and at list price, you don't have to talk to me, you can do it with a credit card. At Oracle, we're really good at taking different forms of payment. I don't know if you knew that. We try to never turn money down, as long as it's a valid, you know, accurate and legal way to do it, obviously. Or you can go to our competitors, and you can commit all up front for three years, and you're still at least 10% more expensive than if you just came to OCI. This is why these customers pick our cloud, and most of my time is not spent modifying our technology to make it work for them. Most of my time is spent with them going, "I don't believe you." And I go, "Okay, well, but you might wanna try it." And they go, "Well, still..." "Okay." And they try it, and they go, "Oh, this is actually really, really good." It's like, yeah, it's almost like that's the thing we've been saying, remember, for the whole time we've been here. Another area that we're investing very heavily is that. So I talked a bit about the networking side and why we're highly differentiated there. The fact that we can move very quickly, the fact that we can offer the latest and greatest of all of NVIDIA's GPUs, the fact that we're investing very heavily into our managed Lustre offering, the fact that we update our file storage service to be able to be used for scale-down customers, the fact that we offer AMD GPUs, and we have a huge amount of our energy dedicated to enabling these types of customers, right? In a who's who of logos on this slide, and there's many more that I can't show you publicly, right? These are the people pushing forward the frontier of what's going on in AI, right. Those people are... They're not uninformed technologists. They know their business. And I promise you, they're not coming to us because they haven't heard of our competitors, or they haven't heard of any other options. They try what we have, and they're extremely impressed. So hopefully, that segment of our business, it's clear why that's continuing to grow at an accelerating rate. So I wanna take a few minutes now to talk about distributed cloud and Alloy. So one of the other things that we built into OCI from the very beginning was a different belief about the way you should build clouds, the way you should build your regions, the way in which they should be operated, and the way in which, customers should be able to consume the cloud. Having worked at multiple cloud companies, I can promise you, and to be fair, it's nice having that late mover advantage sometime, it was... None of the other cloud providers designed in from the beginning the concept that someone might be able to run the cloud in their own data center. The idea was very simple: we'll build a relatively few, you know, on the order of ten, twenty, thirty, really large places, and all of the world's computing will happen in those thirty large places. We thought that was a bad idea. We thought that, well, actually, A, it's a concentration risk. You shouldn't put all of your computers in one space. We thought that there's this thing called countries, and they care about where their data lives. We found that there's these things called customers, and they care a lot about being able to bring the cloud to them. We've been on a journey for the entire time that we've been around, focused on how do we scale down as well as scale up? How do we offer customers choice about deployment? We started with Dedicated Region, which was. It's not a genius idea. It was, well, if we just make the cloud small enough, there are customers that would like one. And so we worked very hard to scale it down, and that required a bunch of work on the way in which we build and operate these clouds. I cannot tell you the amount of effort that we put in to be able to push a button, and then at the end of that button push, you have a cloud region. I know it's. You're gonna think, "Well, Clay, that's. Isn't that obvious? That's how you would do it." No. The way that most of these cloud providers build a cloud is it's the same way that, when a city gets an Olympic win, they build the Olympics. They go in, and they go, "Great, we have a construction project, and we're gonna build this thing," and there's project managers, and there's people manually deploying stuff, and at the end of it, you end up with a one-off cloud. That's the way our competitors build their clouds. That's not how we build our cloud. We have an installer that runs, and it runs, and at the end of it, it goes, "Oh, we've brought up the cloud. It works." That's the only way we can build this very large number of clouds. But it's really hard because this is not a packaged software product. You're not, you know, you're not building a copy of Windows, right? You're not building Firefox or Chrome. You're actually trying to build this massively sprawling set of functionality that spans across these very disparate hardware systems. So we scaled it down, and we worked on our software. But we continue to innovate in that area, right? If you saw me on stage yesterday, there were three racks. In some ways, three racks seems interesting, in some ways not. The racks themselves are not the interesting part. It's the fact that there's only three of them, you know? This is not launched yet. It'll be available very soon, right? Sometime next year. But we already have this version that runs in 12 racks today, and we're already bringing out the three-rack version. We had to redesign the network, we had to converge our hardware platform, but this enables a huge opportunity for us. 'Cause customers now suddenly can get the cloud, they can put it in their data center, and they don't have to sit here and figure out, "Well, how do I do this complicated move of everything over there?" They can just bring the full cloud functionality to themselves, and then we did other really interesting things. If you bring the security down to the rack level, such that now you can put the racks wherever you want, the cables, the way in which they're brought in, everything's encrypted when it leaves, and you actually, from the outside, you can't get in and plug things into the computers, and we have real-time telemetry on the racks themselves. It's suddenly very easy to take this cloud product, put it into your data center, wire it up, and boot the thing up. The same thing we've been working on across what we call Oracle Alloy. Alloy is our offering that allows customers to become cloud operators themselves, right? If you attended my keynote yesterday, you would see I had, Koga-san from Fujitsu on stage, talking about how excited he is that he now can offer all of his customers, not just in Japan, but globally, a cloud that gives them the control and data sovereignty that they need, but with the full features functions, right? In his conversation with me, he said, "I had two choices before that were bad. I could run it on my cloud, which was great. I had lots of control, very secure, but did not have the functionality. I could run it in other hyperscalers, but I could not solve for the unique regulatory and control needs. Alloy solves that problem, and this is only possible because we have Dedicated Region. If I go to Koga-san and say, "Hey, Koga-san, I'm gonna need you to buy, like, a thousand racks to start." He's like, "Man, this is a very hard business case to make. It's expensive, and I gotta buy lots of data center. It's hard." But you make it small, suddenly it's very easy to say, "Yeah, let's get into that business." It is not just Japan, right? You look at what we're doing with STC in Saudi Arabia, what we're doing with Team IM in New Zealand. This is something that we have massive demand for around the world. The other thing that I think, you know, I don't wanna crib too much of what Larry always says. I'll repeat it though anyway: it's the fact that Oracle's both infrastructure and applications. Because to be able to offer Alloy as a complete solution, it's not just cloud infrastructure. I'd like to tell you that, you know, we've built all the important software in the world. It's not. I have a... We have a very busy team, but we're not nearly that good. If you wanna be able to offer Alloy, you need an ERP system. You need CPQ. You need a way to bill your customers. You need a service cloud to be able to take support requests. Oh, here's the cool part: Oracle has that. So when we go with Alloy, we don't just sell cloud infrastructure. Included with that is Fusion and other pieces of our business, our other industry applications, that move together such that now a customer, like NRI, can use that technology to solve their customers' problems. The other thing. This is the last slide, and then I'll get off the stage, and we can go to Lea and the team. I've talked about these pieces of our business as if they're independent, and it's useful to talk about it that way, but there's also a lot of virtuous cycle between them. So as an example, the types of customers that are procuring our Dedicated Region are also our enterprise customers, and the fact that we have our enterprise customer base is what allows, for example, our distributed cloud operators like Alloy. They They then can move to that cloud. The same thing is true across our cloud native and AI customers. The fact that we've invested so very heavily into things like Exadata and high-performance computing for our enterprise customers is what enabled us to actually be extremely good at operating the cloud for them, and what's also interesting is that as these cloud native and AI customers show up, they start oftentimes buying a lot of compute and storage and networking, but they move up the stack. They start using Autonomous Database. They say, "Oh, I really would like to have Fusion," and all of these things come together. Yes, we have these individual segments of our business, and it's important because they're, they grow at different rates, and their needs are different. But between them, there's a magical virtuous cycle whereas we have more cloud native and AI customers, we get more scale. It lets us offer, you know, lower prices to our enterprise customers. The enterprise customers drive very complex demands. The... Our cloud business as a whole is very well diversified and growing in multiple different dimensions. And so with that, thank you very much. It's been fun being here, and, I'll hand it off to the next people. Thank you. Please welcome Lea Yumtobian, Edward Screven, Juan Loaiza, and TK Anand to the stage. Hi, everyone. It's great to be here. Before we get started, I think we have two slides from Ken that he shared with folks in this room before. Can we show those slides? Just a reminder, couple reminders. Okay, great. So we just heard from Clay on our business momentum and OCI and our key differentiators that are helping to accelerate our business. Now, I wanna turn to database and analytics. I wanna pick up on the threads from Clay. Edward, I'll start with you and our platform services that we've built on OCI. We've taken a different approach as compared to others. Others have approached their services by building on all clouds. Our approach has been an integrated strategy, where we build on OCI and deliver via multi-cloud. Why have we taken that different approach, and how is it helping our customers? Well, first of all, you know, it's very important that our platform services, like Database, be available to our customers, no matter which clouds they're choosing for the rest of their application stack. Now, as you point out, I mean, one way to do that would be, you know, we could just try to take Oracle Database and HeatWave and port it to every other cloud and try to make it run well there. But the problem is, we would try to make it run well there, you know? Because we're building on Oracle Cloud Infrastructure in our own cloud and in the cloud regions that we attach to the other clouds, we can take advantage of a combined engineering between that physical infrastructure and the virtualization software that's running on top of it, and the database software on top of it, whether it's Oracle Database or HeatWave. So at the end, our customers, you know, get a service which is faster and far more functional and far more secure. Great, and we offer flexibility across deployment options. We have six deployment options. It really enables us to be everywhere. Juan, I have a question for you, which is around our ubiquity. How is it not only enabling us to maintain our database customers, but also accelerating the adoption of our unique capabilities like Autonomous? Yeah, so that's pretty straightforward. You know, one of the main reasons our customers come to our cloud is because we're running Oracle Database, the full Oracle Database, including our Exadata platform, which is, you know, what 90% of the largest companies in the world are already running on-prem and what they rely on. So having that available in all these clouds, actually obviously makes it possible for our customers to adopt the cloud platform. So yeah, we also have it on dedicated regions. We can provide it in cloud customer. We can provide them an Exadata on-prem. So yeah, it's all there. It's back to our roots in Database. We're everywhere. So that was one of the original roots of Oracle. It's available everywhere everybody wants it. We're back to that. Very unique. This is a huge year for us in this respect. So yeah, so that's... It's very straightforward. You know what? The other thing that Clay mentioned is true, which is this is the premier platform that all the big financial institutions, telecoms, retailers, everything... Sorry, I've been talking all week, and my voice is starting to run out. But this is it, and we're putting that exact platform, everything, and everything we've built in the cloud for the last, you know, eight or so years, Autonomous Database, we put a huge engineering effort into building that. It was exclusively in OCI, now it's in all the major clouds, so it's a huge deal. So we're meeting our customers wherever they are. We're making it easier for them to move to the cloud and take advantage of the unique capabilities that the cloud offers. I wanna switch over to 23ai, which your team has been building, Juan. Can you talk about the unique value that we're delivering with 23ai, and why are we so confident that our customers are gonna upgrade to 23ai? Yeah, so that's another very good point. So this is a very big year for Database, and we talked about the first thing, which is we're everywhere now. We're in all the clouds. That's a huge deal. The second huge deal is, in May, we released our latest major version of Oracle Database that's called Database 23ai. So that's something where we've been working for several years, a lot of major architectural innovations in that release. Some of the stuff we've been working on for, like, six or seven years. It's been kind of baking, baking, baking, and it's finally come out. And there's three main focuses there. You know, number one, AI. AI. AI is huge. I don't have to explain that to everyone. AI is huge. The second was we put a huge effort into developers, a lot of innovative new development technology, and then, you know, our traditional mission-critical, a lot of new developments in mission-critical technology. So we've baked AI, you know, things like vector search, natural language query, natural language search into the Oracle Database. We've adapted the Oracle Database to make it friendly toward AI. So there's AI in the database, but we've also changed the structure of Oracle so that generative AI, it basically, it's easier for it to generate code for Oracle Database. So those are both very big things. In developers, we've unified some of the major data models that developers have been using, the document JSON relational model, the graph model, and the relational model. No one's ever done this before. This is, this is a big breakthrough in, in data management that no one else has. So that was a major effort that we've had going on for several years. And there's also many, many enhancements on the mission-critical side. You know, big one, we talked about Exadata. Exadata has really been for large customers, large enterprises. We have a new technology called Exascale, which is kind of a software reengineering of the way Exadata work, and it, it scales even higher, but more importantly, it scales down. So now, even a tiny little customer, the minimum size now for running Exadata is two cores. So even the tiniest customers now can get the benefits of, of Exadata, and the thing I say is, "You can get stock exchange-level performance, availability, security, even if you're the smallest customer." So again, that's very unique. We're bringing our super enterprise technology, downscaling it to mid-range, even low-end customers. We have our global distributed database. Clay mentioned that. It allows customers to distribute their data anywhere they want around the world. This is huge for data sovereignty. More and more countries are passing laws, saying data has to be local. I could go on, but I'm gonna stop right there. So much technology. So this is a huge year for those two reasons for Database. Why are we so confident our customers are gonna make the upgrade and that it's gonna continue to accelerate our business momentum? Yeah. So you know, because this, these technologies we've developed are really powerful technologies, and the one thing I would say is the AI technologies, you know, we're helped by the fact that, you know, there's so much AI, you know, stuff going on in the market, but our pre-release program for the AI technology is the biggest that we've ever had. We have more interest than that, and the reason people like it is they can say, "Hey, I wanna, I need to adopt AI. I know I gotta do this to stay competitive," and what we're allowing to do is to say, "Hey, you can take these AI technologies and just put 'em in your existing mission-critical databases." You don't have to change anything. It's just a new kind of query, a new kind of data type. Every feature, all the availability, security, scalability, all that stuff, because it's just a feature of Oracle Database, everything that we've built for the last 40 years, it works with the AI technology, so it's instantly mission critical, so you can deploy it for anything. That is really a big deal for customers, 'cause they wanna go quickly. They have directives from their CEO, from their board, "We gotta do AI." So how do you do AI for mission-critical systems? Well, if you can just drop it into your Oracle Database, that's the fastest, easiest, safest path to do AI. This is great. So we're meeting our customers wherever they are. We're enabling them to move to cloud faster. We're enabling them to adopt AI more quickly. Edward, I wanna come back to you and ask you, the Oracle Database is just one of the services that we offer. We also have MySQL HeatWave and other PaaS services. Can you talk about the unique value that those offer, and how does that translate into our business momentum accelerating? Yeah, I mean, of course, you know, a lot of, especially a lot of our cloud-native customers, they, you know, they've chosen to use MySQL as their transaction store. And MySQL HeatWave combines MySQL-based online transaction processing with extremely high performance, highly scalable in-memory analytics. And in a lot of ways, if you look at what we do in Oracle Database, what we do in HeatWave, we sort of have a build-it-in philosophy, right? I mean, we have an amazing range of capabilities that are part of 23AI, right? And in the same way, in HeatWave, we took that base, highly scalable in-memory analytics, and we put on top of it something we call AutoML, so automatic machine learning. We let customers who basically, you know, they don't have to know anything really about data science in order to build regression models, classification systems, you know, recommender systems, you know, anomaly detection. We added on top of that, something called Lakehouse, so we can perform these extremely high-performance in-memory analytic queries, right? Just pulling from files that are stored in Object Store, right? And then we also just released, GenAI capabilities. So now our customers can do very high-performance, vector database creation, right, integrated with the normal analytic queries. So I can do joins across structured data and similarity searches that are exact, right? I can combine that with results from AutoML for doing something like anomaly detection, and then I can feed all of that into large language models for generation. Just to make sure that our customers have it all built in, we actually have an LLM that's built right into HeatWave. We just try to make it as simple as possible for our customers to do extremely sophisticated data analytics, right, at extremely high speed across a wide range of scale. You know, everything from a single node all the way up to five hundred and twelve nodes. Before I turn to TK to dive more into data and analytics, I just wanna ask Juan, Edward, is there anything else that you think we should highlight for the audience here today, that's helping us to continue to deepen and expand our relationships, especially with our enterprise customers? Look, I think, I think, you know, enterprise customers like performance and low cost like everyone else, but I... But one thing I think that's especially critical is security, right? Security that you can achieve in a simple way, right? So we've always been very, very focused at Oracle, I mean, long before cloud, on making sure that we had powerful security features built into our products. When we built our cloud, number one priority was keep the data secure, right? And we've built, I think, a comprehensive framework of security features and security enforcement mechanisms that help our customers stay secure. Now, if you listened to Larry's keynote, he talked about something called ZPR. ZPR is the next stage of, you know, world-class security. So imagine being able to write relatively simple expressions, declarative rules, about, you know, what, who has to have access to what, who may have access to what. And the fundamental infrastructure of our cloud network enforces that security. It simply will not permit access to data unless you are supposed to get it. And that, you know, that ZPR security screen is enforced at the network level, but it's understood by Oracle Database, HeatWave, and other data stores. And I think that is very appealing to enterprise customers. I don't think there's a sophisticated enterprise customer out there who believes that they can do a good job of securing their own infrastructure. They just don't. They know they can't. The only parties who can do it are cloud vendors, and the cloud vendor who can do it best is definitely us. Thank you. Juan, anything before I turn to TK? I could go on, but actually, let me just add to the ZPR thing. ZPR's very cool technology, very unique. The thing I really like about it is it puts the security all the way through the stack, in the network, in the database, you know, all the way across the network. So you can say, "Hey, this is a," let's say, "a support analyst or something," and that knowledge goes all the way through the stack, through the application tier. So it knows you're a support analyst, what can you do, what can't you do? It goes into the database that says, "Hey, you don't have access to the credit card information 'cause you're a support analyst." So it's all the way through the stack, which is something that's been missing, 'cause we've had these isolated levels of security without the integration across all the stacks. So this is really kind of breakthrough technology, and it's gonna be very, very interesting to customers. Security comes up all the time. I mean, you see what happens when there's a breach in any enterprise. It's, you know, horrific, a kind of situation where... I mean, I've gotten, I think, five letters myself about data breaches, and you know, "Oh yeah, we lost all your data." So, you know, this is not good. Absolutely not good. I wanna turn now to data and analytics. Obviously, our customers are looking to maximize the power of their data, TK. So, can you explain how is Oracle uniquely positioned to help our customers unlock the power of their data, but really maximize the potential of it? Yeah, yeah. I mean, obviously, Oracle is the custodian of so much of our customers' valuable data in our databases, MySQL databases, Oracle applications in the cloud, on-premises. So it's just natural that they come look to Oracle to help them get value out of all of this data. And in OCI, I think we have an amazing comprehensive suite of data intelligence services that help them extract value from the data. First and foremost, with Autonomous Data Warehouse, which is one of the flavors of Autonomous Database, and HeatWave, we have two of the industry-leading analytical database engines. These are the engines that can help really analyze and go through all of your data and extract insights and all that. So we have a great foundation, a unique differentiator with that, right? And of course, now it's available in other clouds as well. Many customers want to also leverage open source technologies like Spark to be able to do data science and other workloads, so we have an intelligent data lake service that we're offering in OCI that helps bring those capabilities as well. And Oracle Analytics Cloud, which is our visual interactive analytics offering, is another capability that you know has been growing rapidly over the past few years. Recently at the Gartner Data Analytics Summit, we had this thing called the BI Bake-Off, where we had a large audience, and the three vendors. We were one of the three vendors alongside Microsoft and Tableau up on stage. There was a bake-off among the three of us, and the audience rated us the best. So we had that. That's another piece of the strategy. Then, of course, we have a growing suite of AI and data science services in OCI. We're integrating all of these together into a more cohesive experience for our customers. The world of data analytics is sort of converging. Customers want a simple, integrated experience across data lakes and data warehouses and visual analytics and AI, and that's kinda what we're doing in OCI. The nice thing about analytics is that the approach we've taken is it's also a multi-cloud approach. We recognize that our customers also have data in other clouds. We can reach data wherever it is. For example, our Oracle Analytics offerings can allow customers to go visualize and explore data in an Oracle database, also relate that with data, let's say, in Google BigQuery or Snowflake. We're open also in that nature. Yeah. So the concept of being open extends also to data and analytics? Absolutely. That's great. So now I wanna talk... Another unique feature of Oracle is our breadth and our depth, and the fact that we have an integrated product portfolio. So TK, can you explain how you're integrating our analytics directly into the applications our customers use day to day, whether it's for the front office activities, back office, industry? Can you talk about that a little bit? Yeah. Yeah, I mean, this is what actually gets me super excited because this is the unique differentiator that Oracle has that no other vendor has. I mean, you, I mean, you all know, and Larry often talks about the thing that makes Oracle Cloud unique is we have amazing cloud infrastructure and databases and so forth, and we have amazing suite of applications that leverage this infrastructure and makes the infrastructure better. Well, that same principle applies to analytics and data intelligence as well. So, you know, we have a rich suite of horizontal applications with Fusion and NetSuite. We've got industry vertical applications like healthcare, life sciences, financial services, et cetera. And we, Oracle, have deep understanding of all of the data within these applications. They're not just bits and bytes to us; they're actually entities, like customers, products, patients. And we understand what the data means. We also understand what sorts of insights that customers are looking to get out of this data. We also know what are the types of intelligent decisions and actions that they wanna take based on whether you know there's an adverse event that they wanna react to, and so forth. So what we've done is we've built a suite of data intelligence applications. We have something called Fusion Data Intelligence for our Fusion apps. We have something similar for NetSuite. We have Health Data Intelligence for our Oracle Health customers. We're also working on other industries. At CloudWorld, a couple of days back, we announced the Energy and Water Data Intelligence application for our utilities customers. We're gonna keep going, because as a data geek, like, I just love the fact that we have access to all this amazing data across horizontal and vertical domains. We're offering SaaS analytics. You know, the data, we massage it, we get it ready for analytics. We give customers pre-built analytics infused with AI, and best of all, we connect the insights back into the applications. Ultimately, that's what customers want. Customers are like: "Yeah, I can use all sorts of analytics and business intelligence tools to go look at data and analyze and explore it," and then it's left as an IQ test to the user to go figure out, "Okay, how do I go improve my business? Why don't you just help me do that? Exactly. That's kinda what we're doing. Actually, at Oracle, we, you know, we're obviously a customer of your technologies. One of the ways we use it is to help us ensure that we can drive the productivity of our sales reps. Can you explain some of the ways our customers are using the analytics day to day? Yeah, I mean, like, there are. I'll give you an example in the case of healthcare, right? Like, so our Health Data Intelligence offering is being used by healthcare customers that are a mix of Cerner as well as even Epic customers, right? They really appreciate the fact that we can bring all of the. I mean, healthcare is just a space that I find which is just so ripe for disruption through analytics. We're able to bring data from all of the different hospitals, healthcare providers, payers, and so forth, and we're able to bring a unified notion of a patient's health history, and we use that to offer healthcare providers to kind of manage their patient population as a whole, understand what are the sort of trends that are happening. More and more in the healthcare industry, they're moving to a value-based care model, so providers are being asked to measure themselves in terms of how they're improving the healthcare of the population as a whole, as opposed to just getting paid for services. So that's something that we're helping, and all that's possible because we have deep intelligence about all of this happening in the system. We also do things like point-of-care solutions, like a patient's walking right up to a doctor for an appointment, and we can give all this intelligence to a doctor about well, what is the history, the recent history with that patient? What are some of the preventive actions that can be taken? This is just one example. We have similar solutions for finance, HR, all sorts of other domains, and again, because we're the custodians of business data for our customers, we can provide these deep solutions. Right, and the key theme across all the use cases is that you're enabling whoever it is to be more productive, be more efficient, and drive the best outcomes. Absolutely. We're not just giving our customers a data platform, saying: "You can go put all of your data," and they run really super fast queries, and then it's up to you what you do with that data. We're actually turning it into a complete, finished solution, and that's something that only Oracle can do because we have the platform- Right ... thanks to our amazing database technology, but we also have our applications and the domain knowledge. Very unique. Juan, I wanna come back to you because we've talked a lot about how we're expanding our reach and deepening our relationships with enterprise customers, but you also mentioned developers. Can you expand on that a little bit more? How are we continuing to expand our reach in the development community? Yeah, so that's one of our main focuses for our next release, the current release, actually. I keep thinking about the next release. We released it back in May. It's production. So our Oracle Database 23, you know, I mentioned, I think the biggest thing is this model change. It's, you know, model changes don't happen very often in data management. This whole unifying the document, graph, and relational model is a huge deal. Another really big deal is our APEX development tool. We've been working on that for twenty years, and we're starting to build all our major apps on that. So this is what we can: you generate the app, okay? So instead of writing lots of code, you can get apps built, like, ten times faster because you're visually creating the app. And now we've put AI into that, so we can use generative AI to make it even better. So that's a big focus of us up the stack. So I think that there's a lot of other stuff. For example, we put JavaScript directly in the database, the world's most popular programming language. There's all sorts of other stuff that we've done, but I think those are two really, really big deals. We think we have the best platform for developing enterprise apps with APEX and this new data model in the Oracle database. Yeah, and actually, just to add one thing to that, Juan. I mean, APEX, Application Express, I mean, it lets you build the application very quickly, as Juan described. But when the application is running, there... Because it's being completely run inside the database, right? It's the database itself, the autonomous database which is managing the application. There's no separate tier of the application that you know, the customer then has to be responsible for or think about scaling or pay for separately in any way. It's all built in, and I think that's probably, honestly, in many ways, at least as appealing as the ease of development. Yeah, ease of building. I think so. And the other thing is that it's enterprise-ready. You can build the world's biggest, most complex app in it. It's not a toy, little development where I do this little thing on the side. This is, like, world's biggest, most complex application. Right. As you mentioned, we're using APEX to build our own applications. Yep, pretty much every new application is built, not only externally, but for ourselves internally, is built on Application Express. So before we close, are there any interesting customer examples that any of you want to share that would help demonstrate the unique value we're delivering? I think, you know, one customer of HeatWave which is very excited to see is there's a company called iFood. It's, you think of it as kind of like the Uber Eats of Latin America. I mean, they use HeatWave. ... and they use a combination of the automatic machine learning that's built into HeatWave, plus the gen AI to do the following. So when you go and you place your order, you know, or you're thinking about placing an order, they use AutoML to generate a recommender model, right? Which then, based on your past history, comes up with a list of recommendations. They feed that list of recommendations into gen AI to get to give you a natural language description of what they wanna suggest you'd order, right? And that, you know, if you look at their application, the total amount of code they'd have to write to do that AutoML work, the recommender engine, and the gen AI, it's almost nothing, right? I mean, if you look at the code, the source code for these applications, it's very, very small. And I think, you know, that's something which, you know, they weren't ML experts, you know, in any way, right? They didn't know anything about recommender systems. They didn't know anything about gen AI, yet they're able to build this very powerful application because of what we've built into that, the data store. We're enabling our customers to do so much in a much easier way, even if they don't have the knowledge. Any other, Juan or TK, that you wanna highlight? I'll pick one from, again, from healthcare, and this is this one I love this example. It's Advocate Atrium Health, which is a pretty big healthcare network. They love the integrated end-to-end offering that we have with Health Data Intelligence, with the analytics and the closed-loop actions. But their entire... They run Epic pretty much exclusively for their EHR right now. We'd love for them to move to Cerner, but they love our analytics, so much so that, and because we operate just like we're multi-cloud, we're also interoperable with all sorts of healthcare systems, so we've integrated well with Epic Systems. So they, they're very happy to work with us, with Health Data Intelligence and analytics. That interoperates very well with Epic as their EHR. So that, I find that a pretty powerful statement. Great. Open is the theme. Yeah. Juan, should we close with you on another example? Yeah. So, you know, we released our latest release just in May, so actually, we had a number of customer presentations here at CloudWorld, and some of you saw some really big financial firms, retail firms, entertainment firms, that are already adopting the AI technology and Oracle Database. So we had a number of these customer panels, and I've never seen adoption this fast. I mean, this is an enterprise database, you know, and it's been, what, three months? I don't know, maybe three and a half months. And we already have customers here talking about how they're using this stuff, and the reason for that is it's so easy. We've baked it into the Oracle Database. So, like, a six-line SQL statement, you can combine all your business data and AI together and do amazing stuff that was never possible before. So this technology, super easy to adopt. And so that's why a lot of people are like: "Oh, I learned this in an hour." It used to be all this AI stuff, you basically had to go to school. You had to get a data science degree. Now, we have just regular Oracle database developers just cranking this stuff out. So it's very easy, and yeah, it's fantastic. We had a lot of customers showing what they were doing already here at CloudWorld. That's great. Thank you so much. So much easier, we're expanding our reach, we're open. Thank you. TK, Juan, Edward, I'm now gonna let you guys go, and we're gonna switch from database and analytics, and we're gonna switch over to talk about applications. I wanna invite up Steve Miranda, EVP of Oracle Applications Development, Evan Goldberg, EVP of Oracle NetSuite, and Mike Sicilia, EVP of Oracle Global Industries. Let's talk about our applications business momentum now. Hello. Thanks for joining me. Thank you. Steve, I'll actually start with you. Two of the many initiatives that you're working on, I wanted to pick on two to start with. One is the journey of Fusion Applications to OCI and to Autonomous. Mm-hmm. Then the second, of course, is gonna be AI. We have to talk about how you've been embedding AI for many, many years into the Fusion apps. But let's start with the journey to cloud. Where are we on the journey? What are some of the benefits we've achieved? And looking forward, what's left? How, you know, how are we gonna continue to move to Autonomous? Sure. Well, in some ways, we're done, in that 100% of the Fusion customers are on OCI, and they've already achieved performance improvements. They've seen reduction in terms of the time it takes to do an update. What they probably haven't seen or haven't noticed is increased security behind the scenes in many different dimensions that OCI brings us. So from that sense, it's complete. However, in another sense, it'll never be complete, and that's goodness for our cloud-based customers. So an on-premise customer or somebody who chooses our competition has a static cloud underneath them or, in fact, has it on-premise. So what happens then is you build up technical debt, whether that's hardware, whether that's infrastructure, whether that's database, whether that's operating system, middle tier, I can go on and on. We don't have that because we are built and designed directly on top of OCI. So everything that Clay and Juan and Edward and TK talked about before, our apps just inherit that. We update the database on a pretty continuous basis with the latest and greatest features. We update really every layer of the stack, both in speed, security, reliability. I'll save the AI part of the question later. The next big step on the database is obviously to move to Autonomous. Mm-hmm. As Larry announced in his keynote yesterday, we'll be moving all of Fusion over to Autonomous, starting in 2025, so we're well underway. Now, that'll give us another layer of performance security, and from our standpoint, it not only gets reliability and security, but also, because it's fully autonomous, reduces the cost of us operating our cloud. And that will happen over time, and there's many dimensions, not only the people aspect but also the scale up, scale down aspect that Autonomous gives us automatically, to help us manage the cloud cost. Right. It continues to enable us to achieve more with less. Absolutely. Now, the latest example then of what else do we get by sitting on top of OCI is AI. So again, our speed to react versus our other application customers is really because we sit on top of OCI. So as Clay has signed up essentially every LLM engine in the world, certainly the leading ones, we get direct access to it. And in fact, at one point, Larry asked me, "Well, which one are we using?" And I just said, "Larry, the answer's always the same. We use the API to OCI," which is to say we use the best LLM available on the market. We fully expect that's gonna change over time. To our application customers, it doesn't really matter. We're gonna have the best in class because that best in class is hosted on OCI. So what we announced last year was 50 AI use cases, things like using the LLM to generate job posts, using the LLM to generate item description, using it to summarize reports and financials, what we call narrative reporting. We announced 50, we ended up delivering over 100 over the last year, and we showed those. Those are to all of our customers, 'cause all of our SaaS customers get those quarterly updates. We way over-delivered there. And then at this conference, we've taken it the next step from, let's say, tactical uses of AI to more what we call AI agents. Mm-hmm. So these are more comprehensive use cases where you could have an agent respond to questions about benefits and give you clarifications there. And the important thing there is it's secure, so we never change any of our customer data to the LLM. It's contextual, so you don't have to tell the LLM who you are or where you are or what your tenure with your organization is because it's embedded in the applications. And it's also contextual because you're in a process that you're doing it. So it gives you a lot of efficiencies. We've added it to financials in a number of places, the general ledger being a notable agent, where you'll have... You know, most of what our financial analysts do are look for exceptions, ask questions, try to answer reports from executives. I think Juan talked about it earlier. Now, in the applications, they're using English to do that. "Give me the revenue trend of this account. Show me the expense for this region over the last six quarters. Put that into a bar chart graph so the executives can see it." You all can do it yourselves with ChatGPT today, and we've enabled the same in the application. So, leverage on top of AI, OCI, in some ways, 100% done. In other ways, to the benefit of our customers, it'll never be done because we're on it, everything Clay talks about, we push forward to the application customers. So let's dive into the AI piece. You already started to hit on it. Yeah. Can you give some of the specific examples of how you've been embedding AI into Fusion apps? And you talked about continuously releasing new features- Yeah. I think it's hundreds- Yeah ... every ninety days. Can you give us some examples? Yeah. So just as a refresher, because we have the SaaS application, these quarterly updates, every quarter, in every product area, so financial, supply chain, HCM, CX, we release on average 100 features to all of our customers. About 80% of those are driven from customer requests. So we have an online forum that customers and partners, these are system implementer partners, give us ideas. Those ideas are debated, frankly, amongst the customers and partners. They're debated with our product managers, and then they get delivered. And then, of course, there's ideas that we bring forth, which are usually combinations of technology and business, which is what AI has done. So this concept of agents are sort of full projects. We've gone from tactical AI to agent AI, which is kind of a full task that you can now embed with an AI. I briefly mentioned the benefits case. Let me explain to you how it works. Mm-hmm. So your company, Oracle, for example, we have a rather lengthy benefits document. It tells you what your healthcare rights are, and it does that per country, 'cause keep in mind, in the U.S., you'd pick Kaiser or UnitedHealth, but in the U.K., you have a public health option, and every country is slightly different. Sometimes there are regulatory rules around benefits, sometimes based on your tenure. Your vacation time varies, or your maternity leave or leave of absence rules vary. So these are very complicated documents. Our customers and apps will load that document into a secure 23ai AI database, that Juan talked about. We will index that, we'll use a vector search, and then we use the LLM on top of that. So in the context, when you're enrolling in benefits or you're asking anything in HR, you ask it these questions: "I'm about to go on maternity or paternity leave. I have vacation balance left. Can I extend that?" "I'm traveling in Europe. Do I have to do anything special to get a medical coverage?" Or, "I'm in Europe on travel. I need a prescription. Is that covered?" You know, things, things like that. Today at Oracle, we have people whose job it is to answer these questions. We took those sample questions, we applied it to the LLM in this index document. The answers were, I'll say, excellent, and that's probably underselling it. Let's say better than humans can do- Wow! 'Cause these are enormously complicated documents. Not only answers the question, but it cites you exactly in the document where it got it from to drill down on. And so that's an example of an AI agent. This is not just helping you write text. It's a full-on process, and we have fifty-plus of those coming over the next year. Wow! So enabling us to spend our time on the higher-value activities versus the more mundane tasks. Now those benefits people can spend their time negotiating to get us better benefits policies instead of answering questions like, "Hey, do I have to pay for my prescription? Right. Right. So we're obviously a customer. Yeah. I'm wondering if you can share some of the specific examples of how we're using AI in our Fusion Apps internally? Sure. Well, I mean, I'll just share the results, and we talk about this all the time, but I wanna make sure that people understand the importance of it. So we announced our earnings results, as you all know, on the ninth. ... with the holiday in between. Exactly. Stole my, stole my thunder. So that was our year-end close on, or quarter-end close on a Saturday. Day one technically was a Sunday, day two was a holiday in the U.S., then there was another weekend. So depending on how you wanna count weekends and holidays as working days, it was four or five, and that's not closing the books. That's filing to the SEC, that's having the fully audited, that's having the forecast ready and set up for you guys. Oh, by the way, we had this little event to prepare for along the way, for it, so now, in some ways, who cares that we announce it, well, what it cares is someone, a customer today, or this week, giving the analogy, it's sort of like driving in the fog. The fact that we can announce nine days after and have that done, it's not done because we gathered all the data, you know, the day after the close and did that really fast. It's done because throughout the quarter, we have visibility. So if you're not able to announce until 10, 20, in fact, some of our apps competitors announce as much as 30 days after the end of their close, they're essentially like driving in the fog. They can't see that far ahead 'cause they don't have those results. So what do we use AI for? We use AI for everything from a character recognition on all of our documents, it goes paperless. We use AI for audit and audit anomaly detection. We use AI for reporting to help, again, that narrative reporting part. Really, every step of the process, we use AI, and the results are visible on a nine-day announcement. But what you don't see is that because we have the nine-day announcement, we have better transparency of our data throughout the year. Right. And not only are others driving in the fog, but when you look at it across a year, it means we have an extra month or two that we're looking forward and they're still looking back. You have an extra month or two. Oh, by the way, you know, you spend less time auditing your results, meaning it's easier for the auditors. You spend less money that way, you spend less time with your people doing it. It's exactly what you said earlier. You can spend time doing value add to the business instead of sort of the logistics of the business. Now, before I turn over to Evan and to NetSuite, I just... We talked about two of the many initiatives. Is there anything else that you wanna highlight? The other big highlight is really, if you look at the move to SaaS, it's very clearly started in terms of service companies. But we've really seen the momentum in the last couple of years moving the product companies. In fact, we had Zebra Technologies and DHL on stage with us that are full, and not only financials, but supply chain. That really speaks to the fact that we've really completed the move in terms of the cloud capabilities, now far surpass anything we had in manufacturing in either E-Business Suite or JD Edwards. Then the big announcement we announced this year was something we call Smart Operations, which is really, I'll call it a modern MES application added to our manufacturing, which we never had before. And I call it modern because what we found from customers is that the days of, you know, what you classically think of, or I classically thought of an assembly line, you know, workers, and they've got big gloves and an MES system with four buttons on it, those are diminishing. Now, many, many, many assembly lines or manufacturing plants are part people, part robotics, and the people are dealing with fairly sophisticated instrumentation. So they have, you know, RF, or QR codes or RFID, and they scan that in their phones, and they get work instructions on a tablet, and that's what they're doing. And so our smart operations with operators workbench and work, and module workbench, one, it's a tremendous advantage for our existing customers to be able to modernize. Two, it's yet another step and incentive for those product on-premise manufacturing customers to move to the cloud, and we're getting great response. Great. Thanks, Steve. Thank you. Evan, I wanna move over to you, and I wanna start with a similar question as what I asked Steve. Because it's been a few years now since we acquired NetSuite, you've made a similar journey to OCI. You're now the largest ISV that runs on OCI. Can you explain some of the benefits we've seen as a result? Sure. Well, I'd actually just like to cut and paste Steve's answer. No, I mean, very similar, and, you know, for our customers who are smaller, fast-growing companies, it's even more dramatic for them to be able to run on the flagship Oracle hardware, the same hardware that Fusion run, is running on, Exadata, NetSuite is running on. They're moving to autonomous, we're moving to autonomous, and our customers massively benefit from autonomous because they don't have, you know, the resources to tune a database. Obviously, they'll call us in and say, "Something's not running fast enough," and we'll get a person on it, but now the idea that the sort of robots are doing it every night, to make their NetSuite instance run as optimally as possible is fantastic, and of course, the same thing as with Steve, they're getting world-class reliability, security, performance. And again, it should be sort of transparent to them, but we can measure it, and we can see the benefits that they're getting. So it's been a fantastic experience, and again exactly the same as Steve said, all those services inside of OCI, we're increasingly taking advantage of. We use the machine vision service for our bill capture, for example, and it works great, and it's fast and reliable, and we can have... I mean, we have 40,000 companies, so there's a lot, you know. We push the infrastructure pretty hard, and it does not even bend, much less break. So, I wanna ask you about AI as well, the AI you continue to embed in NetSuite. But first, something that we do that's unique, I think, compared to others across all of Oracle, not just in NetSuite, is we're not charging for the AI that we're embedding. We don't have a smart version and a dumb version of our apps. Can you explain why we've taken that differentiated approach, and how does that translate into benefits both for our customers and for Oracle? Yeah. I think the reason we've taken that approach is 'cause if you look at the very high level of what you want business applications to do, is you wanna be able to ask them a question, whoever you are in the organization, and you wanna be able to get an answer back that you understand. And then you wanna have, be able to have a conversation, to drill down on different pieces. Exactly how you would work if you had, like, a world-class financial analyst at your beck and call to help you run your business effectively. That's the vision for AI in business applications, and why would we offer so- anything else? and I think that, you know, the dramatic improvements in insights that we can give to business entrepreneurs and everybody in the business, the dramatic improvements in productivity that we can give to them. I use the analogy, you know, you wouldn't sell a car without wheels. I mean, you can't sell a business application without this stuff because it is absolutely central in what we're trying to do for the business user. Right. It's like the difference between buying the Garmin GPS versus the GPS that's just embedded in our phones. Exactly. I mean, that's the way the world is going. And, you know, we both, Steve and I have a very similar philosophy of having a suite where, you know, everything works together. It's running off of a single data model. It's the best data to run AI on because you have comprehensive data about your business. If you're looking at a customer, you have comprehensive data about the customer. That's the way you're gonna be able to sort of make the best inferences about, like, what's the best next step with this customer? If you're in a prospect situation, what's the best next step if you wanna upsell to the customer? That's one of the most exciting things we have going on. To me, the canonical use case for an entrepreneur is: how do I sell more? That's what they're thinking about all the time. So we've spent a lot of time, even before the LLM revolution, using traditional machine learning to help them sell more. But, you know, LLMs are allowing us to make the interface better so that any salesperson can use it really easily, and it's super exciting stuff. So let's talk about some of the specific examples. How have you been embedding the AI? What are some use cases? Yeah. So we did initially, I think, what a lot of applications did, was just provide very easy access within the application to large language models, but I think we did it in a pretty unique way. We pre-configured every place in NetSuite where you have to enter text to automatically know about all the related data in NetSuite that's relevant. So if you're in a sales description, you don't have to say, "Write me a sales description. Oh, and here, it includes the price, and it also includes, you know, some of the features of the product." I mean, we've pre-configured so that they just say, "Write me a really peppy sales description," and that's it, and it knows how to bring in all the right data automatically. This year, we've introduced the fact that each business can actually configure how that works for every area in NetSuite. So if you have a particular brand style, you can edit the prompt in something called Prompt Studio to make sure that it adheres to your brand style. You can say, there's some other custom information that we have that's really important. You can point it to that. You can choose, even because, you know, this is something Steve alluded to, that, you know, the OCI generative AI service has basically every large language model available. You, as a NetSuite customer, can, you know, basically test and try each one and see which one does best and configure it. And maybe in one area, one LLM works better, and in another area, it doesn't. So we're giving a lot of power to the users. And then from, you know... Again, this is something that customers won't necessarily perceive, but it's really, really important. Their data never leaves OCI. And, you know, Oracle makes a promise to secure everybody's data, and this is another way that we're doing that. So that's super exciting. And then I alluded to the sales upsell help. We call them intelligent item recommendations. Anywhere where you're dealing with a customer, whether you're in an opportunity, in a sales order, if you're just looking at the customer record, we're surfacing, you know, our assessment of what other things you might wanna sell that customer, and we're using all kinds of data. I mean, we have very rich data in NetSuite. We're using everything we know about that customer. What region are they in? What size are they? Anything we know to make these recommendations really intelligent, and we have metrics that show that it's working. In the last quarter, these recommendations had an 11% conversion rate. Customers used them to do an additional $5 million of sales, and we're just getting started. But, you know, again, entrepreneurs, they wanna sell. They wanna sell. We love that. Yes. Before I move over to Mike, is there anything else you wanna highlight that, and you wanna share with the audience around how you continue to expand NetSuite's reach and as well, deepen and expand the relationships with your customers? Yeah. So, you know, Steve and I actually, and our teams have been collaborating on the next generation business user experience powered by AI. I mean, AI has so much power just to make the experience better. You can recommend ways to use the system. Obviously, you can give this incredible next generation help that's tailored to how, you know, what you've learned about how that kind of learning level that user has. So AI is an important component, but also just making these interfaces to business applications, which have traditionally been horrid. You know, you come in on Monday morning, and it's like, Ugh... Ugh... I gotta log in to my business application. You know, with the team, you know, that is working on Fusion and NetSuite and the Redwood Design System, we really strive to have users fall in love with these business applications one interaction at a time. And that may sound unrealistic, but we're getting incredible feedback... that they're feeling like, "Wow, this is much more like the applications that I'm used to using and that I like using in my personal life, and I've never seen a business application that looks and feels like this." And so that's a really exciting area for us. Yeah, it's not just pleasant. You're actually guiding each employee to do their best work- Absolutely. -which I think is great. So Mike, I wanna turn it over to you. We just talked about horizontal applications. Your team is providing the mission-critical applications that our customers need across industries. Can you start by explaining how are you seeing customers leaning in now, maybe more than they were six months ago or a year ago, into the cloud, and what do you see for the future? Sure. Yep. The mission-critical applications, particularly in heavily regulated industries like banks and healthcare, telecommunications, utilities, you know, it's not unusual that if you look at the data centers, the customer data centers today, you'll find a lot of mainframes. You'll find a lot of AS/400s that are running these mission-critical systems, and there are cars that are now classic cars that are younger, you know, that are younger than the age of some of this infrastructure. Mm-hmm. I think what's really... There's a couple of things that has changed the mindset to think about: how do we move that mission-critical stuff to the cloud? The first is the success they've had with the back office, right? The success that they've had with it, you know, the quarterly updates, the security as a service, the innovation as a service. And there's now a comfort level to say, "Well, actually, we need to think about moving all of it. It's becoming very hard, very expensive to maintain this old code, and if we don't start to modernize it, we're, you know, we potentially have business impacts. We also potentially have major cybersecurity impacts as well." Because it's also very hard to secure that stuff because at some point, there's some internet-facing gateway into that. Mm-hmm. So that's what I think is seeing in the heavy regulated industries, again, banks, utilities, healthcare, telcos. Another class of industries, like retail, hospitality, food and beverage. You heard, you know, in Safra's keynote yesterday, again, in my keynote, I had three customers, all of whom had talked about the benefit of cloud for omni-channel transformation. So, you know, it's really hard to do that by yourself. And you know, just with the changing nature of the business in retail and hospitality and food and beverage, and everything from third-party delivery aggregation to customer intelligence to upsell wheels, and you heard about that from MGM. You know, it's it'd be difficult to try to stitch that together, you know, on your own. I think that those drivers are really getting people to start to think about time to take the mission-critical applications to the cloud. I would say very good progress in mission-critical applications to the cloud in retail, hospitality, food and beverage, merchandising planning systems, order management systems, payment systems, and so on. And the bigger regulated industries, like banking. What you saw a couple of years ago was starting to surround their mission-critical applications with cloud services like financial crimes and compliance, anti-money laundering. Now, the conversations are about moving accounting foundation services to the cloud, together with ERP, right? Together with Fusion. In our public safety businesses, you know, moving mission-critical tactical response systems to the cloud together with NetSuite as well. It's really, I think, that push and pull. They've been very successful in the back office. They love the momentum. Regulation, hard to keep pace with regulations 'cause you've got to certify this old stuff- Yep. That it's actually compliant, and now it's time to move the back, you know, the heavy duty, in some cases, very heavy iron, to the cloud, and I think that I don't think that there's a category that I can think of, at least in the 10 vertical industries where we supply end-to-end automation, where somebody has said to me, "Cloud's a bad idea," or, "Cloud's off the table." That's three years ago, in certain verticals, that may have been a conversation. That's no longer happening. Definitely accelerating momentum. And you just hit on our industry cloud applications together with Fusion and NetSuite, but you're really bringing not just our horizontal and vertical applications together, but database and OCI. Can you talk about how you're delivering really holistic end-to-end solutions to each industry? Yeah. There's a couple things that I think that are important to highlight there. The first is, not only are we pre-integrating Fusion applications, let's say, with accounting foundations or and for banking, we're also creating vertical-specific functionality inside our back-office applications. So Steve's got specific functionality in HCM and supply chain management for healthcare. Not a custom version, not a customization, off-the-shelf, available features that are applicable to healthcare organizations. In NetSuite, we have a specific version for local government to deal with payroll management and things like that. Again, not a custom, not a custom extension. This is off-the-shelf software. So bringing these two things together from an integration perspective and then further tailoring them for the specific needs of the vertical industry, I think has been, you know, something that customers are very, very excited about. The other thing is, when you talk about end-to-end solutions, talk about front-office applications, back-office applications, analytics, and OCI- Mm-hmm. As the infrastructure, the conversation with customers is about outcomes. And I'll give you a couple examples. In healthcare, the conversation, and one of the buyers is the chief medical officer in healthcare organizations, and I can talk about the performance, scalability, and security of OCI. I can talk about our IoT aggregation network. I can talk about our ability to deliver private 5G networks in a hospital using our enterprise communications platform. I can talk about our ability to arbitrage low-orbiting satellite, terrestrial networks, and cellular networks so that you've got you know, you've got triplicate coverage in a mission-critical operation. A much better conversation is to say, "In your ICU, of the thirty-two beds, which patients are likely to progress to a septic situation within the next hour?" That's an outcome that's very difficult to talk about if you can't supply all of those things. Now, arguably, they could go to a bunch of different vendors and stitch that together on their own. But if we can supply that as a service, we can supply it as a HIPAA-compliant service, and we can supply that with a quarterly update and cyber defenses, you know, which is a huge struggle for healthcare today. It's a highly differentiated conversations, and that's exactly the conversations that we're having, right? Because it's all of that together that allows us to have instant telemetry into something like an ICU. You can extrapolate from there a bunch of different use cases in healthcare. In our public safety business, which we launched a couple years back, we had a big demo here today, this week at CloudWorld, with a Cybertruck in the center of the floor, lots of buzz, lots of activity about all the technology we put in there. The outcome-based discussion, because of the OCI computer vision, right, because of our APEX low-code generation activities, and because of the command suite that we put together in-vehicle, and in-vehicle on first responder and more things. The outcome discussion is about weapons detection and tactical, you know, tactical response generation. The reason we can have that conversation is because using OCI computer vision, we can process 30 frames per second, right? Wow. Nobody needs to know the technical detail, but what they need to know is that I can instantly identify and hopefully neutralize a threat, you know, far, you know, much further away from the perimeter of a facility that somebody's trying to breach, right? With fixed asset cameras, IoT networks, and, you know, integration. So I think that's just a... It's just something that's very unique to Oracle, right? It's that we're having that conversation based upon what are you-- what's the transformation that you're trying to achieve? And it's because we have all of it. It's not just unique value, but we're really delivering new value. Absolutely. I didn't ask you the question about your cloud applications moving to OCI, 'cause I think you'd give the same answer as we've already heard. But I will ask you about AI, because I think- Yeah ... you know, I can't let you leave the stage without doing that. How are you embedding AI into our industry cloud applications? Yeah. What are some use cases? I think in a few stages. You know, the first stage, which is now widely accepted, and we've gotten terrific feedback around, is what I'll say is at, because these industry applications are often at the edge, right? It's automating, you know, routine tasks that are very laborious, very manually intensive, and people get tired of doing them. In healthcare, for example, doctors, nurses, you know, there's a lot of paperwork generation, there's a lot of documentation, and this is the perfect vertical industry where AI essentially is the UI, right? So instead of having an electronic health record system, where you've got to click through 10, 12, 15 screens to process a patient interaction, and you've got to do that while you're trying to deal with the patient at the same time, if we do not... If you do nothing but, you know, let the autonomous system listen in the background, you know, semantically break down the conversation, automate the ordering of labs, automate the ordering of prescriptions, automate the documentation process, that's a pretty big win. That's generally available. We released that in June of this year to just, you know, terrific, terrific accolades from our, our, our customers. So, you know, that I think is the first example of applied AI. You can imagine in every vertical industry that there are these edge use cases where there are highly repetitive tasks that are, you know, don't have a whole value add when you're trying to transform patient experience or customer experience. The next generation of it is what I spoke about with, you know, as the example of continuous telemetry into a cardiac, you know, continuous cardiac monitor. Whereas, you know, you need machine learning, you need low-latency networks, you need to be able to figure out, look for patterns, to be able to make predictions about what may happen to a patient. Predictions about where a customer may, you know, choose to take their energy business in deregulated markets. Predictions about where customers may choose to shop, you know, in an omni-channel environment for retailers. And then, you know, the next frontier, if you will, right, is things like molecular discovery. You know, looking at our clinical trials business, and, you know, our pharma customers are saying: "Look, if we, if we can really access these GPU clusters at scale, and we can look at figuring out doing much of the simulation using computers for new medications and molecular discovery, we can not only save a lot of time and a lot of money, but potentially develop things that are far more safe and far more efficacious." I could go on and on and on about each vertical industry and give you a, you know, very deep answer on all of it, but hopefully that gives you a flavor of, I think, the layers of AI that consumers are clamoring to. Yeah. The theme of it is we're enabling our customers to automate their operations, not only so they can save money, but also so they can focus on their missions and advance those. Exactly. We're almost out of time. We've talked a lot about our business momentum and applications. Is there anything else that you wanted to close on for the audience here? Steve? Anybody? Yeah. Hopefully you got a chance to stay during the week, 'cause I would say that, you know, say what we will up here, but the excitement and the buzz and the crowd was, you know, very, very noticeable this year. I, you know, I felt it in all my customer meetings, I felt it in all the sessions that I attended. The excitement, more importantly than us saying it, the excitement from our customers to receive it and really looking for adoption was, you know, you could feel it in the buzz in the room, in every room that I've been in. I thought it was just great. That's great. Evan, how about you? Yeah, I mean, well, I think the thing to highlight is the collaboration that we have across Oracle. You know, between Fusion and NetSuite, we cover basically every size business, and we have all that amazing business data, and a lot of the things that, the problems that we need to Steve and I need to solve are similar, and we're increasingly collaborating on that. We're taking some of Steve's amazing products that were aimed at enterprise, and we're scaling them down for our fastest-growing NetSuite customers, and they are eating it up. So, you know, just whenever you do these sort of acquisitions, it takes a while to really get in your groove, and I think we are now and just working incredibly well together. Incredibly. And, Mike, how about you? Well, look, I always have a lot to say, but I think what's far more important is what our customers say. And, you know, what I continue to notice the trend is how many customers are not just talking about the technology, but they're talking about business transformation, clinical transformation. And, you know, I sat in my keynote yesterday and learned a lot, even in the keynote from our customers, just about how, you know, the impact of thinking about this from a one Oracle, from an end-to-end-to-end strategy. So to me, that's incredibly exciting. As Steve and Evan said, the buzz has been terrific, and I'm quite happy with what our customers and humbled by what our customers have been able to do with our technology. Right. Ultimately, our success is all about our customer success, so thank you for joining me. Thank you, everyone. I really appreciated the opportunity to talk about our business momentum, and with that, we'll move on to the next session. Thanks. Please welcome to the stage Oracle Executive Vice President, Jason Maynard. He is joined by Ish Chittimalla from MGM Resorts International, Hiro Hamada-san from Nomura Research Institute, and Pedro Sardo from Vodafone. All right. Hello! All right. You got that Clay energy flowing, I can tell, right before lunch. Well, we've got the most exciting panel. All right. I think before we get started, I've been instructed to alert you to my favorite slide. I miss this slide, I'm not gonna lie. The disclosure slide right behind me. All right. So thank you guys very much for coming, but really, I want to thank our three guests here. Like I said, I have the best job of the day, which is I get to share with you all some of our great customer stories, and you can learn a little bit about what they're doing with Oracle products. And what's really exciting to me is we brought customers from all around the world. So we've got customers here in Las Vegas, Tokyo, London, so you'll get a nice global flavor as well across the entire product portfolio. So first, let's kick it off a little bit. Pedro, why don't we start with you? Tell everyone a little bit about yourself and the work we're doing together? Hello, everybody, and thank you for inviting me. I work for Vodafone. For the ones that do not know Vodafone, we are a mobile operator that mainly covers Europe and Africa. Again, we provide all of the typical services that you'd expect from a telco: fixed, mobile, TV, IoT. And we have around 300 million customers. Within Vodafone, my responsibilities are I manage all of our operations and data centers, which include all of the infrastructure, and that's one of the reasons why we have a close relationship with Oracle. Because we have a very strong insourcing strategy, I also manage our technology centers that act a bit like an internal SI that work exclusively for Vodafone, where we have already a relatively good size of 15,000 people working across operations, delivery. And so a lot of the projects that we do together, again, instead of sometimes we go using SIs, we work together directly with companies like Oracle. Oh, that's great. Thank you. Hamada-san, maybe tell folks a little bit about yourself. Sure. My name is Hiro Hamada. Thank you for having me. I'm from NRI. NRI is a management consulting and IT services company headquartered in Japan, and NRI has a long, successful history of partnering with Oracle. As a matter of fact, NRI was the first in the world to adopt DLCC. So now NRI operates OCI in our data centers in Japan, and also we recently launched Alloy as well. Yeah. NRI, one of NRI's core business is its search solutions for financial institutions. They are widely used in Japan, accounting for about half the trading volume on the Tokyo Stock Exchange. There are multiple solutions covering both buy side and sell side, and we have migrated all these solutions to OCI, so they are absolutely mission-critical applications, and they are all running on OCI. Fantastic. Thank you. Ish, yourself? Thank you for including me here. At MGM, our mission is to entertain the human race, and Oracle is a key partner. We use number of core systems for hospitality, where we check in the guests, check out the guests using Opera. We use the financial systems where we close our books using Oracle Fusion Financials, and we use the supply chain systems to do our forecasting, inventory management, and how do we make sure our warehouses are managed. That's fantastic. Let's go back, and we'll dive in a little bit here 'cause we obviously have had a lot of news this week about not just multi-cloud, but obviously with the database. So Pedro, let's kick it off and talk a little bit about how you're one of the first multi-cloud customers with Oracle Database at Azure. Talk us through a little bit about what your thought process was in making that move and how you're thinking about this multi-cloud strategy. Look, maybe let me start a couple of years back because I don't think that at least even for us, multi-cloud was an obvious thing in the beginning. We started using cloud probably over 10 years ago, and then for several years, we tried to keep to one cloud. Okay? At that point in time, it was more or less obvious which one it was. We tried for multiple reasons to stay with one cloud. We want standardization, consolidation. Quite quickly, that was probably six or seven years ago, we got to the conclusion that that was the wrong strategy. Yeah. We actually decided to go multi-cloud over six or seven years ago. Probably our first big partnership that we did on that part was with GCP. Yep ... in terms of analytics. Because when we decided to go multi-cloud, we also needed to give a lot of guidance to our teams. Okay, so which clouds are we going to use for which workloads? And so the first one, big one, was then with GCP for all the analytics workloads. And then we have been expanding again. Then we did also a lot of work with Oracle. We started actually first with OCI, our first solution with OCI that managed our retail stores in the UK moved to OCI over five years ago. And then probably three years ago, we started discussing about DRCC. Okay. and the reason for that was that we were finding out that we're pretty good at migrating and creating all of our workloads on public cloud, especially when we are talking about new applications. But we were getting a bit behind when we were talking about our more core applications that were probably... Yeah, I don't like to use the terminology of legacy, because some of them, they are really critical and cover our core processes. We were not doing such a great job of modernizing those ones. So that's when, again, the partnership with Oracle came. Again, we created six DRCCs together with Oracle, and ever since then, we have been migrating applications and databases, and we have been modernizing a lot of our databases into DRCC. Then we also started discussions with Microsoft because there was a need for, to have some certain workloads in Azure, and we also signed a partnership with Microsoft. I strongly believe, because when we were discussing the partnership with Microsoft and how big that was going to be, that probably if the partnership between Oracle and Microsoft did not happen, maybe our partnership with Microsoft would not have been so big because the Oracle Database is a really key application for us. It's a really... Most of our core systems rely on the Oracle Database, and we plan to continue to rely on the Oracle Database. So if I try to summarize, the ability of us moving the workloads where we need to move to because of whatever reason it might be, and always have such a component, such a critical component of our architecture, which is a database that is Oracle, and have that available into all of them, I think for us it's a major surprise. That, to be fair, probably 12 months ago, we were not expecting to have that benefit. Yeah. No, it's great. It's interesting to hear you talk about the flexibility and the choice and the ability to- Yes ... to, you know, run in a heterogeneous environment. Yes. What are some of the benefits that you are seeing and expect to see as part of this move? I think that the key one is really the flexibility and the optionality. Let me give an example. Okay. When we started working with DRCC, one of the reasons why we put DRCC was to enable us to do modernization layer by layer. So I might be modernizing the database without having to modernize the application. Mm. And then later on, I modernize the application. DRCC being on-prem, being close to wherever the application is running, enables us to move different pieces of the application and modernize them at different pace. Yeah. That is optionality. Later on, if we want, we can then flip all of those applications when they are all modernized into public OCI. We expect the same about this, the benefit of having Oracle at Azure, at GCP, and now at AWS, enables us to... Gives us optionality. We can then choose what we want to do, which one of our applications. No, that's great. We just signed the... Again, we are in the beginning because we signed the agreement two weeks ago. Yeah. Although we have a long-standing relationship, this specific agreement, again, is pretty recent. Yeah, this is just getting rolling, but then we'll have you back next year, and we can talk a little bit more about it. Yes, that's okay. So that'll be great. Hamada-san, it was interesting. We're, you know, flexibility, optionality. Mm-hmm. You're building an AI platform on Alloy, which was really designed in many ways to enable, from a business model standpoint, that flexibility and optionality. What are you looking to achieve with that, and how are some of your customers going to take advantage of this AI platform that you're delivering? Yeah. So, let me give you some background. So, I think the financial industry has very high expectations on GenAI, and many POCs have been already completed. And the real value lies in how to integrate AI with the existing core systems. However, there are challenges. Much of the data that financial institutions handle include confidential information, such as PII. Yeah. So they need a secure and robust environment to fully leverage the power of AI. So in the right answer for this need is our financial AI platform. By fully leveraging the latest technology that OCI provides, we provide the secure and robust environment that our clients need. And I think, this platform will empower the financial institutions to transform their- ... existing core systems through the power of AI. No, that's great. I think everybody in this room, obviously working in the financial services industry, can appreciate security and privacy of data and the importance of that, so that's fantastic. We're gonna shift gears a little bit and talk about applications, right? And MGM Resorts, obviously a Fusion customer, as you mentioned, with ERP, EPM, supply chain, but you're also using our OPERA Hospitality platform. OPERA's moving to the cloud. You have a lot going on in terms of a modern transformation. Give us a little background and discussion of how you've thought through this evolution and really what you're looking to achieve from this transformation. Yeah. As we go through upgrade cycles for each of the core systems, one of the things we looked at was partnering with Oracle, understanding what does the cloud bring? What is the transformation that we can achieve through the cloud? And then purposefully made the decision to move to cloud for all of these systems. There are a few key advantages that stood out as we did that analysis. One was efficiency. As we go to the cloud, our team can be hyper-focused on the business needs and not have to worry about maintaining the infrastructure, the cycles of upgrades, and work through the maintenance cycle that typically drains out some of our focus. The second is security. Security is very, very paramount for us. We have confidential data in all of these systems. Moving to cloud gives us an advantage, taking of what Oracle brings to the cloud maintenance, but also the cloud systems are built more secure. They are more flexible, from access controls to data retention policies. That allows us to keep our systems more secure. The third advantage is employee experience. All of our employees use these tools day in, day out to support our guests. Yeah. As we go to the cloud, the modern UI, intuitive UI, allows the employees to be more efficient and get through their tasks very, very quickly. The fourth is around extensibility. Oracle team has done amazing job in redesigning the applications to be cloud native first. So there's a robust set of APIs. There's more open transport protocols used. That allows us to extend the systems very easily and build integrations. And the fifth is around future-proofing ourselves. Mm-hmm. As we go to cloud, we are on a faster cycle. We are able to release capabilities faster to the business, and we are also able to take advantage of additional modules that are in the cloud, get all of our data into one place, so we are able to run reports and decision-making processes faster in one system. I have to follow up on that one 'cause I think it's. it's. That's such an important and interesting point, which is you're taking the entire suite, consolidating data, and, you know, in every business we're in, it's the fragmentation of data that drives us crazy, right? Trying to get answers to questions. What are some of the things that you've seen as a result of being able to have that easy look across the business to make those decisions? Yeah, we are still working through all of those processes. Yeah ... so we're not at the end state yet, but some of the advantages we have seen is our reporting cycle are faster. Yeah. As you mentioned, consolidating the ERP data into an external data warehouse and then compiling the analytics data takes time. One big advantage is near real-time analytics and the data that comes out of it to help our operational leaders make the decisions faster. We have seen how our operations with hotel, finance, and revenue management are all able to take some advantages as we are just on that journey in making those decisions faster. No, it's great, and MGM has such a great reputation for customer service and care and bringing great offers and capabilities. It's so cool to hear about some of the work you guys are doing there, so... All right. Now, as you guys all know, if we're mandated at these points to talk about AI, right? There's, like, a quota on the AI conversations that we have to have, and these guys out here, they're all like: "Tell us about AI. What's going on with AI?" So we all know you guys are doing some stuff in AI, but I think maybe let's start, Pedro, let's go back to you. Give us a few minutes. Just talk about how you think about AI in the broad context of your business, and then maybe give a couple specific examples and ways that you're starting to get rolling with it. Okay, good. Let me also give a bit of background on that one- Yeah ... because I was mentioning that we, one of the first partnerships that we signed was actually with Google in terms of analytics, and that's when we decided that we are going to have a very simple strategy regarding to data, which is our data was only going to reside in two places: either on the operational system, where, of course, it's mandated so that the system can operate, and on our data ocean. Probably at that point in time, we did not foresee how important this, ensuring that all of our data is in one place was going to be so important for our AI initiatives. But look, fortunately, that started, and today we have over 20,000 terabytes, which we think is around 70% of all of the data in terms of analytics that we want to load into our data ocean already there. We have 10,000 pipelines moving those data. We have already 600 AI models running. So I think that is how we started. We also wanted... I'm not sure if everybody understands that, for instance, in Europe, GDPR is quite strong, and there are some variations according to countries. So we wanted our engineers to focus on how they develop those and explore those data and those AI models instead of being worried about anonymization of data, privacy, security, and so on. So we created a platform that enables all of the development and operations of all of our models, and that is completely transparent to the engineers and to the analysts that are doing the work. We call it AI Booster, but it's basically based on the Vertex product from Google, and that enables us to really. It's a massive accelerator on how we can use and how we can build models. When GenAI started to come, we were also very clear in terms of our strategy. Again, we are not going to build a new LLM, okay? But what we've built was an architecture that makes us independent from the different LLMs and enable each one of our analysts and to select which LLM applies better to their need. And all of this, again, just enables the people to focus on what on the use cases that they need to build. In terms of what we see, in terms of the use cases for AI, I would probably. We see AI at this point in time as probably, I would say, falling into two fields. One is augmentation of and I'll give a couple of examples, augmentation of the work that we all need to do. Mm-hmm. Or sometimes to enable things that would not ever be possible in any other way. When we talk augmentation, again, we all use Copilot 365, for instance, to help us to write an email in a better way. But again, Copilot can help our sales teams to better build a proposal, can help our call center operators to respond better to our customers, or can help, again, even our software engineers when they are developing code to accelerate and to be faster and more productive when doing code. That is one clear example. The second one, in terms of the things that probably would not be possible, one example that I think has been very successful for us is every day we take all of the calls that we receive in our call centers. We transcribe them to text, and then we ask a summarization of all of the calls that we had the day before, and that is extraordinary. That is giving us some insights, early insights sometimes into problems, where we can start seeing that some problems might be appearing, that in any other way it would be impossible to pick it up. So that is an example of something that is really probably not possible without the summarization capabilities that we get out of AI. Of course, then we have the chatbots, but again, I think that one- Yeah. I did not even mention that one because I think that that one is the one that everybody traditionally expects. Yeah. No, and I think that's what's so interesting right now, though, is that you're seeing all sorts of different ways that organizations are thinking about AI from routine business processes. I think what you're talking about here is so—it's gonna be a very interesting evolution in terms of bringing AI to your data, running your Oracle Database, and then actually even running that in multiple clouds. So this heterogeneous nature- Yes ... of what your existing IT environment's like, and then being able to put your Oracle data where it needs to be, is gonna open up a lot of opportunities. Yeah. So it's really- Even how we deploy network. Yeah. Even the way that we deploy network, where we decide to deploy capacity, we use a lot of AI models to help us and to help the engineers decide, "Okay, I'm getting much more profit if I deploy more capacity in this location versus this location. Yeah. Tomohiro-san, you're literally jumping right in with this AI platform. You're like, "I'm—we're going." Give us a little bit of the how and the why behind the scenes in terms of what motivated you and where you really saw the opportunity. Yeah. As you mentioned, data is really the key to successfully use AI. And I think for every company, existing application is a great source of data. So it doesn't have to be limited to existing applications, but it's a precious resource of data. And one thing we did recently is preparing for a demo application for this CrowdStrike to showcase. What we did was, we built a sales assistant chatbot designed for entry-level financial advisors. Mm. So, this application highlights how we can improve the effectiveness of the entry-level workforce while staying compliant. So I think, this application is a prime example of how AI can be seamlessly integrated into existing application. I can appreciate that use case. Lots of salespeople and trying to make them smarter and do better and take care of customers, that is exciting. That's great stuff. Thank you. Ish, you're using Fusion, which has embedded AI. Maybe, what are you thinking about the bigger picture with AI and some of the, some of the things that you're hoping to achieve? Yeah. I think AI is so interesting, and as Hiro said, it all boils down to data. What quality of data do we have? For MGM, the way we are thinking about AI is focusing on deeper understanding of the guest. How do we understand the preferences, insights through the guest journey? They have so many touch points that we implicitly, explicitly understand the guest. Yeah. How do we capture all of that to build a very deeper understanding of the guest and personalize their experiences? The second focus area is around operational efficiency, both in technology and on the business side. In technology, we use AI throughout the lifecycle, from engineering, as we already discussed, as well as our product QA and our operations, understanding where systems might likely to fail, where we have vulnerabilities, detecting those through AI-based tools. And on the business side, getting the data faster, something that we touched earlier on, and allowing the business the key insights. And one part that we are fully working with Oracle is understanding the Fusion Data Intelligence and use that to get the insights to the business and operations team faster. Yeah. And the third piece that we are looking at AI is the guest interactions. Mm-hmm. So we did, like I think most people have, we launched a chatbot as well for the guest interaction to allow self-service while during their stay, and we are now looking to expand that to their trip planning and post-trip engagement. That's great. No, it's exciting. I think the work that the teams are doing with Fusion and analytics and data, and bringing it together in data intelligence will be really exciting- It- For the back office. But the front office is really gonna be cool. That customer interaction piece will be exciting to do that. Let's stay with you for a second here. We've got a few minutes left. What's kinda next? What's on the horizon? What are you working on? What are some of the things you can talk about? Yeah, OPERA Cloud is the biggest, probably the project for us. It's a massive uplift rolling out to all of our 16 properties. Yeah. Each property has a unique brand, and one thing we really are aiming as a foundational is to standardize everything and allow the properties to express their unique brand within the configuration options and not customize the core platform. And that's a core mission as we migrate out of our on-prem to- Yeah ... OPERA Cloud, and that, that's one of our big project next year, next couple of years. And it's gonna be really exciting to see the work you guys do, because in 2027, we're gonna be moving CloudWorld to MGM. Yeah. And so we're all gonna get to benefit from this. So all of you in the crowd, you're gonna be like: "Yes, I heard it here first," and you're gonna have a great experience. We will check you in through Opera Cloud at that time. You'll check us in? It'll be amazing. I won't have a blow dryer in my room or anything like that. I'll have, I'll have the nice pillows. You're gonna customize the whole thing? Yeah. It's gonna be awesome. I can't wait. Absolutely. I can't wait. This is gonna be great. Tommaso, what's next? You've got a lot on your plate here with AI, but where are you gonna go? Yes. What's in the future? Definitely. So, it's gonna be twofold. So one is, we would like to leverage AI technology as much as possible to our system development work, so coding, testing. We would like to make it as efficient as possible. And the other part is, we would like to give our clients new value or additional value leveraging AI. So I think the next immediate step would be building something that we can showcase how our clients can leverage that generative technology. No, that's great. You're gonna be building more cool stuff and making things better for your- for everyone. That'll be great. Right. Pedro, we're gonna give you the last word here with a couple minutes left. You got a lot on your plate, I know. I know. So tell us what you got. Of course, AI. AI. There you go. No, no, but no, on a more serious note. Yeah, of course, in AI, we need we are kind of experimenting and trying to really understand what is the real benefits that we can get from all of the use cases that we are doing. And if I focus on a lot of the work that we are doing with Oracle, we have all of our cloud migrations that we want to execute. We want to modernize our infrastructure and our applications. We have a big initiative in terms of how do we take the good things that we see in some of our local markets, that have taken some of the Oracle applications and make it into a state-of-the-art stack that serves our core business, that has the agility, the time to market, that enables us to deliver faster time, faster products and service to the market. How we can take that to all of our markets, because, again, having that only in one of our markets is not enough. So now what we are looking is how do we take all of that experience of one market that gives us the agility? Because that's what our business is asking. We need to be faster in taking things to market, how we do that, and be able to leverage that across all of our markets. No, this is great. I love the themes up here: bring AI to data, run your Oracle database in any cloud, flexibility, choice, security, making sure we take care of that information, and then enabling these end-to-end transformations. Whether you're building applications, you're using Fusion across the board, it's great stuff you guys are doing. So I really do appreciate you taking your time, and we value our relationships with all of you, and it's just fantastic. So from myself and everyone at Oracle, we really do appreciate it. Thank you for coming to us today, and everybody, thank you for the time. We can share the stories. All right. Thank you all. We will now take a short break. Lunch is located in the hallway. Our program will resume promptly at 12:30 P.M. Please take your seats and silence all devices. We are about to begin. Please welcome Doug Kehring to the stage. ... Hey, everybody. It's great to be back again this year at the financial analyst meeting. I'm Doug Kehring. I run operations here at Oracle. Many of you may have seen me last year, but here I am again. This is one of the better weeks that we've ever had, given the fact that we had an excellent earnings announcement on Monday. We've got financial analyst meeting today, and in between it, we had all of our favorite customers and partners who joined us. So my goal today is to translate the product and customer discussions that we've had earlier in the morning into how it's impacting our financials. So as a result of this, you're gonna see me being very, very cognizant of my notes, because Safra said, "Don't screw this up." So, just to be very blunt, I'm gonna be careful about what happens up here. So as you've seen, we've got our safe harbor language. We also are gonna use non-GAAP measures in this presentation, so here's the requisite disclosure again. And then, finally, we've got the fact that there may be some future product direction discussions in here as well. So this is for informational purposes only. Okay, let's get started. So as we reported during earnings, RPO is now greater than $99 billion. It's up 52% year over year. This figure has grown rapidly and clearly shows the pent-up interest and demand in the Oracle Cloud, which is now almost three-quarters of the total RPO amount and is up 80% year over year. Actually, over 80%. This figure really sets the stage for our discussion today because it's all about satisfying this amazing demand by delivering profitable growth. Now, of course, RPO grows when the commitments our customers make to Oracle grow. This RPO figure, and its absolute size, points to the multidimensional interest from our customers. As we talked about earlier today with all of the great development leaders that were up here, it's across our entire portfolio, from applications to analytics, from database to infrastructure. But beyond that, it's across all geographies and across all industries, and it's not just across our traditional enterprise customer base, but it's across many different customer types that I'm going to highlight today. The demand is widespread, and it's been accelerating. Now, the historical RPO size is driving our ability to accelerate revenue growth. As we forecast last quarter, and we confirmed again on this week's earnings call, we expect to deliver at least 10% revenue growth this fiscal year. Using our previously committed FY 2026 revenue target of $65 billion, the implied growth rate for FY 2026 is 12%. Now, not only are we confident in our ability to meet this target, but we expect to exceed it. I've got even better news to report on this as it relates to our future, but I'm gonna save it for the end. So unfortunately, you're gonna have to put up with a few more minutes of me before you get to hear the good stuff. So there are really three drivers behind the confidence in our ability to deliver. The first, as we've been saying, is we believe we've built the best technologies for the cloud in the world. The second is our product differentiation is driving increasing wins and momentum. And the third is we are building the capacity in order to convert this momentum into accelerating revenue and profits. What I'm gonna do today is drill into each of one, each one of these areas. So let's start with our product and service differentiation. Unfortunately, I can't do justice to what the development guys were talking about today, but I'm gonna sort of wrap it in a little bow. First, our product portfolio has never been more comprehensive or more complete, and as you heard, it's completely AI-enabled, and as we know, AI is transforming everything, and Oracle is poised uniquely to help any organization with that transformation journey. Whether that's about transforming their data in order to use our end-to-end database features to ensure that they have the best and most up-to-date data to drive their automation, or it's about transforming their line of business functions, whether that's front office, back office, supply chain, HR. Whether you're a big business or a small business, we have it all to help our customers make their employees' jobs go even better, and we transform their business processes. So using AI and data, combined with our applications, allows us to help transform customer experiences, employee experiences, or any other experiences where our customers want to deliver better outcomes at a lower cost. And finally, we're transforming entire industries. This is really the Holy Grail. It's using the power of all of our technologies put together, where we can help our customers achieve just that. We don't think anyone else out there can do it. And I was about to go through a whole explanation of how that, what that means, but I just realized that when Mike Sicilia was up here, when he talked about healthcare, that really resonated with me. That was him discussing the power of all our technologies brought together. It's not just in healthcare, but many other industries where we're doing that with our customers. So now, beyond that, all of this is connected together in, Sorry, I apologize. That's part of the, healthcare thing. Let me get to the second area, which is we add to that portfolio the most flexibility, so customers can get the cloud delivered to them in the manner and at the price point that they want. Our data center or yours, the customer? Public or private? Sovereign or security air-gapped? Managed by us, managed by our customers, or managed by partners? On OCI, on Azure, on Google Cloud, or on AWS. We do it all with the same cloud capabilities and consistent pricing. One stack for all possibilities. And we can do it because we built OCI differently. Clay talked a little bit about that, well, a lot about it, but let me highlight one very interesting point, which is our cloud infrastructure can start with all of our services with just three racks. It's a fraction of the size of everyone else. In fact, we believe the minimum footprint of our competitors is over one hundred and forty times larger to get started compared to what Oracle offers. This differentiation and flexibility is exactly what customers want, and that's what we talked a lot about this week. It's why we're becoming so popular in the cloud, and then finally, we enhance our technologies by activating our customer success services organization for every customer. As Safra has repeatedly mentioned, customer success is now at the heart of everything we do. We've built the customer success journey to accompany the customer from the start of the buying decision through their ongoing usage, making sure that they get value from every dollar of investment that they make with Oracle. It starts with helping our customers as soon as they make a buying decision. We guide customers and train their users on how to be cloud-ready. We then work with our implementation partners to ensure that our customers get a smooth and successful go live, then, on an ongoing basis, we work with our customers to operate the cloud, from proactive issue resolution to helping them drive value realization, and finally, we assist them with evaluating and deploying new features and innovations, such as AI, as it becomes available. We're also in a unique position as a result of this, to help guide them to the next best Oracle product and service that they can purchase. We take the best technology, the most flexibility, and an obsession with customer success, and it's this combination that's driving our cloud momentum with customers. Let's move on to the second driver. It's how we're converting these product and service advantages that I just went through into customer wins and momentum. So let's go back to RPO, 'cause we really enjoy this number. This velocity has been accelerating. It's moved from a 12% CAGR a few years ago to now 46% over the last two years. It's obviously being driven by the cloud. As you can see, cloud now represents 72% of RPO, up from 46% four years ago. And with the close of Q1, we now have an RPO value that's greater than $99 billion. Now, this RPO velocity and the accompanying revenue acceleration didn't just happen overnight. It's been steadily building as we've been going. It's included the gradual and ongoing conversion of our installed base of on-premise customers to the cloud. That's number one. Number two, it's about winning net new customer opportunities using the technology advantages that not only I just described, but that you've heard throughout the day this morning. And then third is our embrace of multi-cloud, which is giving us significant new ways to provide customer choice and driving more revenue opportunities for Oracle. It's these three things working in concert that's behind our bullishness. So I'm gonna break down each of these three ideas into a little bit more detail for you today. Let's start with our installed base of support. We have approached or surpassed, in many areas, feature parity across our cloud applications compared to our on-premise applications. Steve Miranda pointed out many of those areas in which our cloud is actually outperforming many of our traditional applications. The move of these customers has been accelerating. In fact, it's doubled over the last four years. Yet, as you can see up here on the chart, there's still a big installed base of application customers yet to move. Same thing on infrastructure, but we're even earlier in that cycle. In that case, similarly, we've more than doubled in the last four years, the movement of our infrastructure support base to the cloud. Now, when our customers do move to the cloud, the amount of revenue we're generating is getting even better. So if we look at the last fiscal year, we experienced a 4X uplift in ARR in applications and a 5X uplift in infrastructure. That's even better than I talked about last year when we discussed these same multiples. Using these improved conversion rates results in a potential incremental revenue opportunity for Oracle of around $85 billion, just upgrading our installed base of customers. Now, let's turn to the expansion with net new customers, where we're gaining interesting new workloads that we never had before when we were an on-premise company. So as you can see, the rate at which we're adding new customers is increasing. So it went up from 10,000 net new customers in FY 2023 to 11,000 last year. We now have over 80,000 customers that have bought Oracle Cloud. In terms of who we are attracting, there are four interesting types of customers that are being added. The first is we're winning more application customers, whether that's moving on-premise customers from our competitors like SAP or Infor, or we're actually getting a lot of changes from existing cloud customers who wanna move away from what I'll call legacy cloud, like Workday. In addition, with the build-out of our mission-critical industry applications, we're just starting to see the uplift in the amount of growth we can see with landing customers in these areas, in the businesses that Mike has been focused on, like hospitality, construction and engineering, healthcare, industries of that type. We're very early in that adoption cycle. The second, of course, is AI. Two years ago, this category didn't even exist, and now it's exploded, as these companies are very well-funded and have money to spend, but they're seeking the very best infrastructure technology on which to run, and Oracle has proven to be an excellent fit. Third is via the cloud infrastructure options only Oracle can deliver. Clay talked a little bit about this in his presentation, but things like Alloy, where our partners can run their own OCI clouds in their data centers, nobody else has that. Sovereign clouds, via governments and country-specific data centers, where with our flexibility and size, we can go into many, many more countries than our competitors can do to provide this option. Finally, dedicated, where customers can take the same capabilities of our public cloud and put it into their personal data center and wall it off, and yet we can still manage it and provide them the economics of public cloud. Given our flexibility, this group of customers is highly unique to us in terms of our ability to land them and grow our revenue. Fourth is ISV and native cloud customers, where they want to participate in the bigger Oracle ecosystem, or where they have demanding needs, where they see the price-performance advantages of Oracle. Taken together, this whole group significantly expands the opportunity for Oracle to sell our cloud. Now, the final area of momentum is being driven by multi-cloud, where, of course, as you've now heard, we make our software available via the public clouds of our competitors, who are now our partners, driven principally by the Oracle Database. But before I get into the details of that, I just want to remind everyone how sticky the Oracle Database is. You know, it's not by chance that all three of the non-Oracle hyperscalers are now calling and are big partners with us. First off, the Oracle Database remains highly ubiquitous. It's in use by 94% of the Fortune 100. Second, the Oracle Database is sticky. If you look at over the last four years, our net dollar retention rate in our support base is 102%. It's not declining, it's growing. And finally, the move of the Oracle Database workloads to the clouds is just beginning. So not only are these database workloads ripe to move to the cloud, but customers are showing an increasing interest in doing so. So they need to be on later versions of the Oracle Database in order to take advantage of the cloud features that we have available, things like 23ai, which Juan talked about today. So we've seen a tremendous uptick, as you see in the slide, in the percentage of our database customers that are now on our latest releases. That's how we refer to customers in the database side as cloud-ready. The final thing that is helping with the move of these workloads to the cloud is customer choice. You know, as we've now heard from various sources, almost every customer uses multiple clouds. The panel of customers up here help amplify that opportunity, and our goal with this is to provide the ability to use Oracle on the cloud of the customer's choice, while we work with each partner to ensure a seamless experience in using our technologies, so customers choose where to run, and we give them access to the very best features, while also making it very easy to purchase and manage together, so now, beyond running on Oracle OCI, we can we have the partnerships with the rest of the large hyperscalers, Azure, Google, and now AWS. Our work started with Google, with sorry, apologies, with Microsoft, and they really leaned into this early, a year ago. And then, of course, this summer, we announced our partnership with Google Cloud, and it's amazing how much faster they are also ramping up their interest and the number of regions that are coming on quickly together. And then, of course, the trifecta was Amazon AWS, which we announced this month. Across each of these, we have very strong pipelines. They're growing very significantly, and we expect it to be a more and more meaningful impact to our financials as we move forward. And in fact, we have over 450 joint customers with Microsoft Azure. You may have seen some of these stories. Obviously, you heard them from the panel. If you walked around the show floor, you would have gotten many more of these stories. A lot of these customers have big ambitions, and I can tell you that all of us as a management team are very pleased with what we've been seeing so far. Our final driver is how we're building this capacity to meet this customer demand and turn all this momentum into accelerating revenue and profits. We've been on a tear the last eight years. As Clay mentioned, we really launched Gen Two OCI in 2016. It was a very small footprint with very few services. And yet, over the course of the next four years, from 2016 to 2020, we grew the number of megawatts under management by 20X. And then between 2020 and 2024, we grew the number of megawatts another 4X. The demand keeps coming, and as you've all heard and continue to see, it's oftentimes faster than our ability to build out our capacity. It's a great problem to have, and we focus a lot of energy from an operational standpoint on getting that back into balance. Not only have we caught up with our major hyperscaler customer partners, sorry, our competitor partners, in terms of the number of features and services that we have on OCI, but we actually believe we're in more places than any of them on a comparison basis. In fact, as everyone probably is aware now, Gartner now ranks Oracle as one of the leaders in the Magic Quadrant for hyperscalers. We've come a long way. Now, the great differentiator for us, which I'll highlight again, is that flexibility of deployment. The flexibility of deployment allows us to do interesting things because we can, as a result of being in a smaller footprint, tie up less of our capital in land and buildings and more of our capital in compute and storage. But to keep up with that demand, we've got to fulfill the backlog by building out the capacity that's required. So as you've now heard, we're going to double CapEx this fiscal year. That increase in CapEx spend is the precursor to accelerating revenue. So as you see, over the last five years, with more capacity coming online, the percentage of our software revenue that's coming from cloud compared to license and support is now double, and it's about 45%. We expect that percentage will continue to go up, given license and support is a slowly declining business compared to the hypergrowth that we're seeing from the cloud. Now, the kicker for us is the trade-off is actually very attractive from a total profit standpoint. When you look at the gross profit contribution standpoint, we are adding many more dollars to our bottom line compared to the decline from lost dollars to license and support. So while the cloud has more inherent costs in order to deliver the service, the additional profit dollars more than makes up, given our growth rates. In fact, what we've been seeing is we get about $5 of added gross profit in cloud, compared to an average of $1 lost to the decline in license and support. So the bottom line is, as we move to the cloud, we are able to accelerate the growth of both our top line, total revenue, as well as our bottom line, total income dollars, as we make the transition to the cloud and cloud becomes a bigger and bigger percentage of our overall business. So let me just recap, I think, what you heard today. Our confidence in accelerating our revenue growth has only gotten stronger. First, it's because we think we have the best technology portfolio out there for what the market is seeking. Second, these product advantages are driving lots of customer momentum and interest that's ultimately driving bookings. And third, we're building the capacity to meet this demand. But what we are gaining is both more revenue and more profit dollars as we invest and grow our business in the cloud. Now, what does this all mean for our financial outlook? What we've all been waiting for. Based on the strong backlog that we've discussed today, we are now even more confident in our ability to achieve our FY 2026 revenue targets that we've previously issued. In fact, we are raising our revenue target from $65 billion to at least $66 billion for FY 2026, while at the same time, we are focused on the bottom line and remain committed to growing EPS at least 10% in FY 2026. However, given the strong demand that we've talked about and you've seen from Oracle, we've decided to defer an even higher EPS growth rate near term in order to grow our revenue faster over the next five years. So as the saying goes, just one more thing. As a result of what we've just discussed, we are sharing with you today our expectations for FY 2029, to give you a sense of where this is all going. We expect that revenue in fiscal year 2029 will exceed $104 billion. This implies an average revenue growth rate of 16% between FY 2026 and FY 2029. While at the same time, we plan to accelerate profitability with the plan to reach the 45% operating margin and to grow EPS greater than 20% in FY 2029. Thank you. Please welcome Larry Ellison to the stage. Did he say a hundred and four billion? That's gonna be so easy. It is kinda crazy. Yes. This guy. Hey, thanks very much, Larry. Brad Zelnick, Deutsche Bank. Great to see you. Larry, you've been in the software industry for, I think, over 50 years. You've seen many paradigm shifts. You've figured out how to succeed, how to win across every single one. What is it today- I'm actually having a very hard time hearing. I know... I hope I'm not going deaf. It's probably how you- I hope it's the sound system. I'm gonna have to move... relocate. Can you hear me now? I can hear you now. Cool. Perfect. You've been in the software industry for over fifty years. You've thrived through multiple paradigm shifts. Ahead of us, we've got a major opportunity that Oracle and many others are racing fast and investing very much in. What is it that supports your confidence that this is good for the industry of software, and there may not be a redistribution of value, I don't know, maybe to semiconductors or elsewhere along the tech stack? Actually, I'm gonna sit down again now. I'll just stand up for questions. The really interesting thing about AI, and again, I used to give this speech a long time ago when I was a kid. If you really want to understand the computer industry, you really have to study the industry that it's most like, which is the women's fashion industry. And you need to start reading W Magazine because they tell you what's hot and what's not. And the focus on AI, we're very good at the AI stuff, but, you know, you really can't train AI systems without data. A lot of companies are very excited about going ahead and exploiting artificial intelligence, and an awful lot of those models are being built at Oracle because we happen to have really interesting networking technology in our data center that allows you to build huge clusters. By the way, that we first built for our database a long time ago, and then when we brought our database to the cloud, we built very unusual cloud data centers with these very fast RDMA networks, and that's what made it relatively straightforward for us to build very fast GPU clusters using NVIDIA chips, where we can go to thirty-two thousand... Huge, huge clusters, give you terrific performance because the problem is not just processing the data and training, it's also moving the data into the cluster, and we're good at that. But I wanna go back to this idea of, yes, we're really good at AI and training AI systems, but we have this franchise where most of the world's important data is in an Oracle database. And I think the market... For a long time, I've kind of chatted with you guys, and sometimes you have confidence in things that we're doing, and sometimes less confidence in things that we're doing. And I think maybe go back three years ago, something like that, and I think you guys were pretty confident that we were doing well in SaaS. We'd kind of proven ourselves with Fusion and then the acquisition of NetSuite. We were a solid SaaS player, and we were going to be a solid SaaS player. I think the jury was out. Just say the jury was out for OCI, for us becoming a cloud competitor. But what we had made our name on, the technology that we had pioneered, relational database technology, I think most people thought we were going to lose that franchise. The only thing that kept us from losing, because we had Oracle only at OCI. We didn't have it at Google and Amazon and AWS. We had a huge amount on-premise. A lot of our customers didn't move those applications to the cloud. But I think there was a lot of skepticism whether we'd move all of that information to the cloud. And in fact, no one else invested in database during that period of time. What is the real... Is it Snowflake? Is it Mongo? What is it? Well, I think people... Well, you know, database isn't really very interesting. If you check W Magazine, AI is hot, database is not, which is really interesting because it... I mean, I think it's still called the information age. And unless you have your data properly organized, you can't use AI. It becomes utterly useless. It's this enormously powerful tool, and it has, doesn't have access, really coherent access to your data, so you can't exploit it. So if you want to take advantage of AI, you have to do two things. You have to really do a good job of organizing your existing data and making it accessible, and then you have to have the appropriate AI tools, whether they're large language models or other, other sorts of neural networks, depending whether you're doing some of the things we're doing. Two things we're doing in healthcare, one is which we're... creating automatically using large language models to create doctor's notes. Doc, we listen to a consultation between a doctor and a patient. We create the notes. We use a large language model to do that. We look at a biopsy slide, a very different neural net. We use a very different neural network to look at a biopsy slide and say, "Well, do we think there's cancer there?" So those are very different. But you have to have the training data for all the biopsy slides. You have to have all the medical records accessible. The hospital does, the clinics do, the payers do, the insurance companies do, the National Health Service in UK does. They have to organize all of that data, all that health data coherently. So it's really a two-pronged problem. When you're you say, "I really want to use AI, I want to take full advantage of AI," well, you can't do it unless you get your data in order for both training and inferencing. And there is no alternative to the Oracle Database that I know of. I would love. I think Microsoft SQL Server is not a bad product. Maybe it's the second-best relational database out there since IBM got out of the relational. IBM kind of got out of the business. Amazon, who's a valued and I think they're an incredible company. AWS is an incredible service, but they really don't build databases. They take open source products, and they put them in their cloud. They don't do a lot of database R&D. They do almost none. Google has BigQuery, but it's really not a database. So why am I confident the thing that the future is bright? I'm gonna slightly rephrase your question. You're saying, how, why am I, why am I not worried that AI will suddenly go out of fashion, and something, the next hot thing will come up, and then we're kind of, you know, well, we're solely dependent on, on AI, and we've got nothing else supporting our hopefully very attractive, you know, very big stock price, right? And that's supporting our growth, our EPS growth, our revenue growth, and making our business better. I think we have multiple ways to take advantage of the information age, take advantage of AI. Part of it is, you know, doing a really good job with that database business, holding onto that franchise. And if you think about us holding onto that franchise, what's that worth in the era of cloud? It was worth quite a bit back when everything was on-premise, everyone built their own data centers. But in the AI world, where data is an essential enabler, we have the best database, and it becomes more popular than ever. I think that's an important pillar to our future, and it's an important part of the value that we provide to customers. Our databases don't get hacked. They don't get hacked. Lots of really famous companies get hacked. Our data, we don't. It's highly secure. Our stuff is highly secure. We pay a lot of attention to security. We think we have huge differentiation on security and reliability. Our database, one of the unique things about Oracle is I can walk up with, you know, I shouldn't, well, you know, walk up with a gun and just start shooting our servers, but everything would keep running. We're the only database that can take multiple computers and high-speed network them together and create the illusion it's really one computer. We run one workload on 64, if you will, 64 servers with this high-speed RDMA network interconnecting them, and I can just start shooting 20 of them, and the system will keep running. No one else has anything like that. No one else has that kind of scale out. It's called RAC. It's called Real Application Clusters. We've had it for a long time. You know who else has got it now, a decade or so later, two decades later? You know who else has it now? Nobody. We're the only ones that could provide that kind of reliability. We're the only ones who provide that we can scale. I put up, you know, with another thing in security. We're you know, we're doing getting rid of passwords, and we talked about what a wonderful thing you know, biometric authentication, and Google Pay, Apple Pay, which is kind of the beginning of biometric authentication for credit. But we can spread it to all, any, any card, Mastercard, Visa, you, American Express. We can make it work with a biometric database all over the world. You need to be able to do twenty-two thousand transactions per second to validate those transactions. Not a problem. Not even close to a problem. But nobody else can do it. And it has to run twenty-four hours a day, seven days a week, never not get hacked, never, you know, never. Not a problem. Who else can say that? It's interesting. So, we have highly differentiated technologies. Our networks are very different than our competitors'. The RDMA networks that we build are essential for training, you know, large neural networks, but they're also essential for building this extremely advanced, extremely reliable, highly scalable, these global databases that we can build. And it means we can build systems that don't have to come down. We patch our database while it's running. So if you're a phone company, and you're expected to provide a service that never goes down. Well, Vodafone bought six of our data centers, and I think that's just the beginning. Because our database is also faster, which is. You say, "Well, yeah, it's great. You go really fast. That's really nice." Okay, let me translate that to a slightly different synonym in the cloud in much cheaper. It's much cheaper, and that's why we have an advantage in training AI models. Because, yeah, our networks are faster, which means training happens faster, and it costs you less 'cause you charge by the hour. And if we charge half, you know, you know, if we're twice as fast, we charge half as much. So I think... I think database is an unbelievable franchise, and sustaining it into the cloud era is bigger than our business is now. Everything we do now. More important than everything we do now. I think the other thing, you know, when it's fully grown, when that business is fully grown. I think AI is also an astonishing business. Last night, I had dinner with a friend of mine and my son at Nobu in Malibu, and we were talking about the future of robotics. And he's building a bunch of them in Palo Alto, so. It's unbelievable what's going on. We'll be training these humanoid robots... I was just discussing with Safra, you know, 'cause Safra and I would constantly say it, every tenth sentence, I feel like I'm living in a science fiction movie. And then we kinda get over it and go back and talk a little more about business. But we'll be training robots to be nurses. We'll be training robots to do a variety of things in hospital, but also, you know, nurses at home. These robots were originally designed to work in factories. They're humanoid robots because they'll be doing jobs that were formerly done by human beings, so you need a robot that's got two arms and two legs and kind of fits into the same spaces and can do the same manipulations that human beings can do. So they can work in restaurants. They can work in hospitals, and we're very involved in automating hospitals. And there are a whole bunch of things, you know, we're gonna do in terms of rolling out robotics in hospitals. We're connecting. We're working with a big German engineering company that makes medical devices, whose name I'm not sure I'm allowed to say, but it's a really big, important German company. Begins with S, but I can't tell you any more than that. We think all of their diagnostic devices, their two-tube scanners, their everything, their x-ray machines, their sonogram machine, ultrasound machines, all of MRIs, obviously. All of that data, all of those machines have to be connected to the internet, and they're all part of our big, our IoT framework. And we're working with these companies, whether it's bioMérieux in France or the S company in Germany or the, you know... To connect all of these devices to the internet. We're better at IoT than anybody because... And a really interesting reason why we're so good at IoT. By the way, this is the only question I'm gonna answer over the next hour. Realizing I'm going on and on here, maybe I should... Because we build applications that make demands on the underlying infrastructure, and we eventually get it through our heads exactly what we need to do because we're really doing the applied IoT. We actually have to hook up the medical devices in the hospital. We've got, you know, we're using RF, RFID to track inventory in the hospital. We know a lot where, how many RFID antennas we, you know, and where they go, and how much they cost, and we value engineer it 'cause we actually deliver it. We don't. I mean, I used to be a programmer. An anecdote, real quick. I was a programmer working my way through college, and one time, one summer, I got a summer job. Anyway, they had. I built an application program. Actually, it was automating an ice cream factory. I don't know why they gave me that job, but they gave me the job. I wrote the application. I thought I'd done it perfectly, turned it over to them kind of my last day, went back to college, and they said they threw the application away because it didn't work. I said, "Well, I don't think so. You know, you guys make ice cream. I'm a really good programmer. I'm sure it works." So I went in and said, "What went wrong?" They were making chocolate ice cream, but they had run out of chocolate. I said, "You know, there was no way to run, make chocolate. Well, you don't have chocolate ice cream. Chocolate, you can't make chocolate ice cream. By the way, you couldn't have made chocolate chip ice cream either here, 'cause you only had half as many chocolate chips as you needed to make chocolate chip ice cream. So you say you made this stuff, but I know my system shows it's impossible to make. So, you know, you're wrong, I'm not wrong. And they said: "No, Larry, if we run out of chocolate, we just use cocoa. And if we're missing half the chocolate chips, we just put in half as many." What? Why would you ever hire a college student to write that program? You know, I had no idea. I didn't know. But now, because we actually do it, we know. We built the IoT framework. We got a bunch of things, but they were, the kind way to say it, suboptimal. But as we built one application after another, after another on top of that IoT framework, it got really good. It handled one use case, and another use case, and another use case. And there are lots of it. So we had this unusual structure as a company, that we are both a supplier of this foundational technology you guys call infrastructure, and then we, we're a user of that foundational technology as we build a variety of applications. Automate, build school safety systems, police automation systems, military systems, all sorts of, all sorts of applications on top of it. And we're able then, we learn, we're on that learning curve, we're able to learn and constantly improve the database, constantly improve our IoT frameworks, constantly improve our network performance and reliability, et cetera. And it's that tight loop, I think, that gives us... is one of our, our secret advantages versus our competitors, that we're doing both. I'm sorry, I'll my next answer will definitely be shorter. Over, over here. Thanks. Hey, Larry, Jackson Ader at KeyBank Capital Markets. If I think about 2029, what about artificial intelligence has to go right for those targets to be hit? And how right does it have to go for those targets to be hit? Thank you. Okay, I think on the AI, I mean, how dependent our dependency on AI. By 2029, I can guarantee you, AI is not gonna be the problem. Because the simple phrase, the race goes on. And, I mean, this is like Formula One. What do I mean by that? It's really not one winner. I mean, you got three people on the podium, but it's really kind of one winner. Someone's gonna be better than this than anybody else, and multiple people are trying, and there is a race. If you listen to Jensen Huang, and I'm sure you do. I know, I know you do, because I've seen his stock price, and I know. I went to dinner with Elon Musk in Nobu, Palo Alto. I went to dinner with Elon Musk, Jensen Huang, and I went to dinner, and I would describe the dinner as Oracle and me and Elon begging Jensen for GPUs. "Please take our money. Please take our money." I, by the way, I got dinner. "Please take our money. Take... No, no, take more of it. You're not, you're not taking enough of it. We need you to take more of our money, please." It went okay. It worked. I mean, we got it. Yeah, I mean, the demand for GPUs, the desire to be first, the desire to build the most capable neural network in the world, getting there first is a big deal. Whether it's getting there first in self-driving or getting there first in reading cancer biopsy slides, getting there first in synthesizing video and making movies. Or, I mean, but, but there's a... I mean, this impacts so many, doing protein design, build design. You know, I mean, we're very involved in designing both small molecules and protein, lot, much larger molecules, peptides, proteins, for cancer therapeutics, designing cancer therapeutics. I mean, being first is very important. And the guys who are in this race are very smart, and they understand they need to be, they need to be best at something. They'd like to be first. So you, they're spending a lot of time and a lot of money begging Jensen, you know, building. We're building data centers. I mean, my God, we're building nuclear reactors. Are you kidding me? That sounds completely made up, but it's not. You need a lot of power to, you know, power acres of these GPU clusters. I mean, it's acres of these GPU clusters. I'm not sure, has anything like this ever happened before? You know what basic stakes is? You know what it costs to build a frontier model? Anyone know, over the next three years? Yeah. How much will be spent if you wanna? You're one of the companies that wanna build a frontier model, you know, how much, how much will you spend? Anybody? Anyone want to guess? $10 billion? Anyone? $100 billion? Yeah, $100 billion. Let's kind of get you in the game. Put down your $100 billion. You ever see Molly's Game? You know, you come in, and you say, "you know, here's my money." Okay, it's not Molly's Game. It's a bigger game. Put in your $100 billion, and you, and you, and you're in the race. Not a lot of people, not a lot of companies, not a lot of countries, you know, will participate. I'm going to go over there. So that's good, by the way, good for us. It's pretty good for us. We're good, we're good to 29. We're okay. Thanks, Larry. Derrick Wood at TD Cowen. I think a lot of us view Amazon to be a bit of a foe to Oracle, at least in the database business. But they decided to partner with you. Can you just shed some thought on, you know, why they want to partner with you? And then even stepping back from that, as you go into this multi-cloud capability, how do you feel about how that helps your ability to gain market share in the database space? Yeah, well, I think, again, we've been a supplier to Amazon. Let's go back to the days before it was AWS. Amazon ran on the Oracle database for a very, very, very long time, right? And I think, yeah, I got kind of cute commenting about, you know, Amazon uses Oracle, doesn't use AWS, blah, blah, you know. And that hurt some people's feelings. I probably shouldn't have said it, you know. But Amazon. We have a lot of the same customers. I think they're partnering with us because our customers have huge investments in Oracle databases, huge investments in the applications built on those Oracle databases. And they but they also like Amazon. So some of those customers want to move some of those applications to Amazon, or some of them want to move them to Google. Some of them want to move them to Microsoft. Some of them want to move them to Oracle. I mean, you got all of the above. The only way you can do that, or the best way, I should say, the very best way to do that is get access to the very latest and greatest Oracle tech, cloud technology. And we talked about this with Microsoft initially, and they said, "Yeah, no, that's great. It's what customers are asking for." I've had Amazon customers, a very big bank in New York, and a very close, a good friend of mine. I mean, he didn't yell at me, but he said, he pretty much, "Larry, would you please make sure Oracle RAC and Oracle Autonomous runs at Amazon? Because we've got a big commitment to Amazon, and we're going to move a lot of our apps. Not all of our apps, not everything." But I don't think anyone's going to move every, you know, a giant money center bank is going to use, move everything to one cloud. I don't think that's going to happen, but I don't think so. They're going to use multiple clouds, and, "But we'd like to use Amazon." And I said, "Great. Makes sense to me." So we decided, but it's an interesting problem. Just to do it was not easy. To actually, I mean, Autonomous only ran in the cloud. There was never a software license you can get for the Autonomous Database. It was always a cloud service. It was born as a cloud service. So how do we take a cloud service out of Oracle and move it into Amazon, and Microsoft, and Google? It's not a matter of simply shipping them some software and saying, "Okay, run it on your computers." That's not possible. So it turned out the only, really the only way we could do it was to embed OCI into Amazon, Google, and Microsoft. A miniature version of our cloud that could run all these different databases. In fact, run all of our services, 'cause all of our clouds are the same. All of our clouds. This is another huge difference between us and everybody else. All of our clouds are software identical. All of our clouds have all of our services, period. In that way, we have one automation system that runs all of our clouds. If we make all the clouds slightly different, we can't automate them. But anyway, that was step one. So step one was we got to. Now we've got to shrink our data centers down small enough that we can 'cause we can't build 50 huge data centers inside of Amazon on day one. We, because they need them in several different locations. They need them in several different countries. So we've got to have some way to embed an Oracle data center in Amazon, Google, and Microsoft. Embed many of them in many different locations, and do it in an economic way. And our data centers are scalable, meaning you can have a starter data center today, which is about 150 kilowatts, and then you just keep adding more and more racks as you get more and more customers. But you can get the full Oracle Cloud data center at 150 kilowatts. I mean, this is. I don't think any of our competitors are 20. That's 5% of. And I'm sure 5% is a conservative number, meaning I don't think they can do it. They're 20 times larger. Their data centers are twenty times larger than our smallest data center that we can put in. So we were able to actually start with a bunch of small data centers in Microsoft, and as they have and as they add database customers, and they add Oracle services customers, we can make those data centers bigger and bigger and bigger. And we developed that strategy a long time ago because we want to put Oracle data centers in every major city in the world, in every pretty much every country in the world. Including, we want to put Oracle data centers, complete clouds. By data center I mean a complete cloud, on a submarine or an aircraft carrier, no problem. Submarine's a little trickier. So that's another thing, problem we had to solve to meet the customer requirement: I want to run Oracle Autonomous Database inside of Microsoft Azure. Well, then we have to embed the Oracle Cloud inside of Microsoft Azure. Then the next question is, where is Microsoft Azure? Let me give you a map. In these 60 locations. Oh, so you need 60 data centers embedded, Oracle data centers embedded in Microsoft Azure. In fact, the real numbers we're building about 30. But who knows? We might be, might go to 60. So we had to solve that problem. But we did. And we solved it in a way that not only allows us to embed these data centers in Microsoft Azure and Google and a submarine and do things like that, but we did it with a high degree. It allowed us to get a high degree of automation. And automation means you're much more reliable because if there's no human labor, there's no human error. It means you're a lot more secure because if there's no human labor, there's no human mischief or no mistakes that expose security vulnerabilities. And if there's no human labor, what is the cost per hour of no human labor? So our data centers are faster, more secure, more reliable, but you gotta be willing to pay less. It sounds impossible, but in fact, it was essential to solve. If we're gonna solve the security problem, we have to have an autonomous database. In fact, we have to have autonomous data operating systems. We have to have autonomous data centers. They've got to be robotic. Robots drive cars way better than human beings. They fly airplanes way better than human beings, maybe more consistently, maybe way more reliably, and the cost way less. Gives us a huge competitive advantage. So I think that's another interesting differentiator between us and the competition. We do applications and infrastructure. Well, you could say, "Well, that's-- Larry, you're not focused. You're not concentrated on infrastructure like your competitors." Actually, we think building applications has dramatically improved our infrastructure. We think the customer is demanding that we run in all the different clouds. Turned out to be very good for us, and by the way, and for Amazon. So Amazon now can satisfy their customers who want to move their Oracle applications to Amazon. Customer's happy, Amazon's happy. Our database, they keep using the Oracle Database, which is good for us, so we're happy. I think it increases the size of the market for us dramatically. And, and our customers who have viewed this. It's been very interesting because, you know, we, we debated this a lot inside. Okay, what's gonna happen when we partner with Microsoft and Amazon and Google? We debate back and forth. Is this gonna hurt our business? Maybe it'll help the database business, but hurt OCI, you know, and, and how is this all gonna play out? I think our experience, and please ask Safra, 'cause Safra and I are the ones that we spend a lot with Clay. We've spent a lot of time talking about this, and we're, of course, we're trying to predict the future, which is dangerous, and complex. But I think the customer reaction has been so positive that Oracle is doing this, that customers are very open to saying: "Okay, yeah, I'm using AWS, but I'd also like to use OCI. I think you guys are really good at this, and I'm gonna have two cloud providers, and the one's gonna be Amazon, one's gonna be OCI." So I think our OCI business has actually been strengthened. And you can make an argu-- you could make the other argument, that it would hurt the OCI business. But I think as it turned out, the customer dynamics were such that it's actually helped our OCI business, and it's growing our database business, and our OCI business is growing faster than other otherwise would have. Over in the back there. Gentleman? Yep. Hi, Larry. Karl Keirstead at UBS. I've got a similar question, but rather about Microsoft. It's been extraordinary watching the warming of this relationship between Oracle and Microsoft over the last year. That's, that's interesting enough to me that I'd love to get your perspective. I don't think anybody is shocked that Microsoft would want to host Oracle databases in Azure. You can see how they would benefit from that. What I think is extraordinary is that they'd be buying so much OCI capacity. That is wild. Can you give us some context? Yeah, I think, we're very good at this. I mean, we're really good at this, and Microsoft is making a major play in AI. And I think it's more important. If I'm running Microsoft, which I'm not, but what is more, I want to train. I'd like to see ChatGPT. I've got an investment in ChatGPT, OpenAI, or ChatGPT. I have some of my own AI services that I want to provide. If Oracle's cloud can help me speed up the training of ChatGPT, it's good for me. It's good for Oracle, but it's also good for Microsoft. I mean, there's really, in a way, no magic here, other than you at that point, you have to say, "Well, Oracle must be pretty good at this OCI AI training," that Microsoft would actually go ahead and buy it. I think that's true. I think we are very good at it. Microsoft is looking, I think, long-term and broadly, that they want to make their OCI, their AI, excuse me, OCI, not OCI. AI as capable and as competitive as they can. If by using Oracle Cloud Services helps them achieve that goal, so be it. Maybe they would've said, "Oh, I wish we could have done it ourselves. We didn't need Oracle, but if they can help us, let's not lose sight of the goal. The goal is for us to be a leader in AI. If they can help us be a leader in AI, let's go work with them." I think, you know, we're training the... I had dinner with Elon last night and my son, and we're training Grok, and, you know, Grok Two, and it's doing well. Yeah, I think same thing. I mean, Elon does a lot, does that, but I think when he made the decision on get started quickly, start training, you know, start training Grok, we were the best choice, and he chose to work, you know, work with us. And we're very proud of that, and we think that's a testimony to the quality of our offering at OCI, our AI offerings at OCI. And I think the same thing, so if Elon picks us and Satya Nadella wants working with us, those are all good signs that you know, we have technology that's valuable and differentiated. Okay. Right here. Hi, Larry. It's John DiFucci from Guggenheim. So- Thank you, John. You wrote some very nice things. Thank you. Well, thank you, because you, you drove that, you and your team. Listen, I, I really think a lot of us here really appreciated some of your comments on the call around AI. We hear a lot of people talking about it and how they're going to charge extra, and you, I think, used the word, bewildering, which I, I think was, accurate. Listen, I think we understand what you were talking about, and it makes sense that AI is just going to be part of everything. But there will be some things, there already have been, that have benefited from some areas of technology, whether it's OCI and the other hyperscalers or whether it's Jensen and GPUs. If you take a step back from Oracle for a second, what other areas do you think are likely to be beneficiaries, and what other areas maybe could see some harm or at least struggles because if they don't embrace it? Like some of the applications, it's easy to say, well, if you're an application vendor and you don't embrace it and include it in your technologies, you're going to fall behind. But can you comment on that? Yeah, well, the... It's really interesting. Yeah, we're-- we bought Cerner. This is another pillar for growth. I think, you haven't quite seen it yet, but we bought Cerner, and then we're in the process of rewriting all of Cerner. Now, how can we possibly rewrite all of Cerner in eighteen months? We, you know, maybe it will take us twenty-four months to fully rewrite everything they did, but I think that's about how long it will take because we're not really rewriting it, we're generating it using our code generator. We're using code generators. And, and so what am I getting at? But the user interface for this new medical system is very different, and I don't think I can charge separately for the user interface. For example, when you want to look at the latest X-rays. I took my son into at Stanford. He had a broken leg, and they took some X-rays, and the orthopedic surgeon couldn't find the X-rays at Stanford. They're using Epic. And then my orthopedic surgeon is a computer programmer, in addition to being an orthopedic surgeon. And he calls in an expert from radiology who's also a doc, and she comes in, and she's also a computer programmer, and she can't find the X-rays. Now, they took these X-rays about an hour ago. She can't find the X-rays with Epic. I mean, it's. And then they finally bring in the Epic expert at Stanford, and she found the X-rays. Took three doctors to find me, my son's X-rays. This is how you find the. First, they had to log in and do all these other things, and then find the right, you know, go to the radiology department, find diagnostic device, devices. It was stored on one of the, you know, on one of the databases in one of the buildings at blah, blah, blah. They had to find all that stuff. This is how you do it with Oracle Health. "Oracle, show me Zeke Ellison's latest X-rays." That's it. Automatically logs in, looks at you, automatically logs in, finds, you know, finds the radiology, finds the radiology database, brings, knows you're a doctor who can actually look at Zeke Ellison's. You're authorized to look at Zeke Ellison's, he's your patient. You, so you're authorized to actually look at that data, and up pops the data a second later. That's the difference. That's all, and it's all AI. We have voice interfaces for all of this stuff. Another example. So how do I charge extra for that? I mean, that's... No, I just think we'll sell more Cerner when we're competing with Epic, is what I think will happen. Another thing we do, and I probably have told this story too many times, but you know, a doctor's meeting with a patient. One thing we do that's very interesting, when a doctor schedules their day, we mix in-person meetings with telemedicine meetings. We make no distinction for telemedicine. So telemedicine is just built into the system. So it could be a remote kind of, we use our own Zoom-like telemedicine, HIPAA-compliant telemedicine secure conferencing. But before you meet with the patient, either in person or via telemedicine, we prepare a summary. We use a large language model to prepare a summary. It goes in and looks at your latest laboratory results, it looks at the latest entries in your electronic health records, it looks at what, you know, what medicines you're currently on, and prepares a summary for the doctor that they can read very, very quickly before they see the patient. The patient comes in, and the doctor consults with the patient. We listen to the consultation. This is all AI. We listen to the consultation. We then prepare, because we're not board-certified MDs, we can't actually update the electronic health record directly. We have to prepare a draft for the doctor of the updates to the electronic health record, to the new prescriptions, to the orders discharging the patient from the hospital, doubling the dosage of lisinopril from two and a half milligrams to five milligrams. So we collect all the send the prescriptions to the pharmacy, we send the orders to the nurse's station, we automatically update the electronic health records the moment the doctor reads the summary and okays it. And all of that is AI. We don't charge separately for any of it. It's just how the application works. The application just works much better. The doctor is spending, not spending any time in front of a keyboard. It makes the doctor much more efficient, and it has more value, and people are more likely to buy that than something where they just takes three docs in a room to find some X-rays. All these- And I think you'll see that throughout the system, our system. We use the autonomous database, we use AI to build the autonomous database. AI is the autonomous database, which is built on AI, it's completely self-driving database, robot DBAs. Again, there's nothing like this. Just like there's nothing like the rack thing, you know, where we connect a lot of different computers together and create the illusion it's one computer. No one's done that. No one's done an autonomous database with no DBA. There's no configuration. There's none of... That's all done. That's all AI. We don't charge more for the autonomous database because it's autonomous. We think it's okay, it's more secure, you use less labor, it's more reliable, all of those things, but it's just a better database. Go ahead, John, you have a follow-up. So it makes sense. It's gonna be part of everything, and everything's gonna be better. But there are some incremental things like NVIDIA and OCI- Yeah. Well, we are- Are there any other, like, areas- We'll sell more applications. We think because if our applications take advantage of AI, and our database takes advantage of AI, we'll sell more of it. Yep. Okay, and any other infrastructure? The separation, the separation is completely arbitrary. Okay. But no, but I can imagine, no, but we. I I mean, we could have a credit card fraud detection or expense report fraud detection program that we say, "Okay, if Fusion accounting will bill you extra for credit, you know, for our expense reporting system, the fraud detection module is a separately charged new AI module." We could do that, but in a way, I think it kind of misses the point. Yeah, we could always take features- Right ... separate features of any kind, whether they're AI or not, and we think that they're of particular value, or another way, very few people want them. Not everyone. If everyone doesn't want them, you can't raise the price of the product, or you don't really need to. We're not trying to raise prices. We're trying to increase the volume of sales. Got it. And I think that's a better strategy. That's more our strategies than kind of looking at AI. Now, I'm investing a lot of money in AI, how do I get a return on that investment? Well, we wanna sell more Fusion, you know, writ large. We wanna sell more autonomous database writ large. We want to sell more people to come to OCI. And I think it would be an exception for us to say, "Oh, that new particular AI feature, we wanna charge separately for." Yes, sir. All right, right in front of me. Finally! ... Larry, thank you very much for taking the question. You've been great at setting long-term visions and then delivering on it. Oracle's taken a different approach to security in the cloud, delivering security out of the box versus everyone else, IT has to turn it on and now, rather than decide what to turn on or not. Now, you're embedding more security with ZPR. You're You're building almost a, a security platform. Yeah. I'm not sure exactly what you'd even define it as at this point, a security layer. Do you see this as something that adds value to just the Oracle products, or do you see this as something new and innovative that becomes almost a platform or a product or a technology all unto itself? Because security is such a problem, and it's not being solved very well. By the way, I could not agree with you more, but I think this is the perfect, so a long time ago, Oracle had two versions of its database. Because our first customer was the Central Intelligence Agency, Oracle's very first database was high, we had a lot of security features in it, and we had these two versions of the Oracle database. We had one with, and then we helped to write this thing called the Orange Book. Now, there's probably not a person left in the room that even knows what that is anymore, but I'm old enough that unfortunately, I know. We helped to write the security book, and we had these two versions. I remember being in a meeting, and it turns out it costs us money to have two versions of anything. You know, we have to pay, we have to build the secure version, and then we have to build a slightly different version without the advanced security features. And I remember being in a meeting and said, "Okay, who wants the database that's not secure? Who want-" It's a little bit like, you ever heard the joke, you know, the smartass comes into the restaurant. Three people come in a restaurant, and they, you know, "What are you, what are you going to drink?" "I have water, water, water." And one guy says, "Yeah, I want it in a clean glass." And the waitress or waiter comes back and says, giving, putting the water, "Who had the clean glass? Who asked for the clean glass? What the hell? Who wants the not secure version of the database? What are you, nuts? I mean, it's costing us extra money to build a not secure version of the database. Are we out of our minds? So, I mean, I'm not quite answering your question, but I'm coming close, and I'll. I will get there. Actually, I had this argument with our head of database, his name is Juan Loaiza, who I love, and he's a brilliant guy. And this is a long time ago, and I said: "Okay, Juan, from now on, everything, all our backups are encrypted. There, you get no choice. Everything is encrypted. You cannot-" "But Larry, encryptions cost, it takes time. You know, it costs more money to encrypt it. We got to use a computer to encrypt it, to decrypt it, blah, blah, blah." I said, "I don't care. I don't want to be the guy that loses your data. No, you don't get a choice." Eventually, it took me a while, but I won that argument. So right now, you don't turn on, "Oh, I'm going to encrypt this in an Oracle Database." I don't think so. No, everything's encrypted. Everything. You don't get a choice. In transit, in storage, it's always encrypted. We're very careful about all of this stuff. When you do recovery, we don't let you do recovery. You just say, "Recover to this point in time." We pretty much say, "Recover to this point in time," and then hands off. We don't let you do that. We don't let people fly these things. What if you make a mistake in recovery and lose your data? Oh my God, you're going to blame me. I know I'm going to get the call. No, I don't want that call. So we've taken away a lot of the choices. That's kind of why we can't charge. It's It's kind of related to what John was saying. We can't charge separately for security. A lot of people do. They'll say, "Oh, that's a real great, it's a great revenue opportunity. You can have the unsecure version, but the guys with a little bit more money, they get the secure version." Or someone who just forgets to buy the secure version. They didn't even know the secure version was available, I mean, 'cause a lot of this stuff is so complicated. We decided that security, I don't want to read an article about us getting hacked, losing data, ransom, one of our customers being ransom, hospitals being ransomwared. No, I, no, I don't, I don't want, I don't want to take that phone call. I don't think Safra wants to take that phone call. So we are just making our system more and more secure as we have customers, not our systems that are failing. We have customers that certainly have been hacked and ransomwared and, you know, a big part of the reimbursement system for US medicine, you know, was down for a while. You know, I'm not going to start naming names, but thank God it was not us, and we were able to help a lot of the customers recover. But we think security is another example. It's always on, it's a part of the system, it's not an option. If we can make it more secure, we're going to make it more secure. We're going to make it absolutely reliable. You can't make a mistake. You can't, "Oh, I want..." No, you ask for a level of the reliability. You can say, "I want, if this data center is hit by a meteor and is destroyed, I want to make sure I can immediately fail over to another data center." Yeah, and then we have to. If you want to do it instantaneously, rather than just recovering, let's say, in a minute, you want to recover in a sixtieth of a second, in an electrical cycle, we can do that, but then that actually costs more because you have to have a full running system in another location. So you may have to pay, in that sense, for the redundancy for the reliability. But we don't think it should be. We don't think those are revenue opportunities. Maybe we're foolish, but we don't think those are good ways to make more money. We think we provide security, high degrees of reliability, and then just sell more of it to get more customers. In the back. Marshall Bush, Melius Research. Thanks for doing this. This is always one of the most fun hours of the year. So if you think that AI is gonna drive share shift at the application layer- Yep. Does that mean that the ultimate value capture will be at the infrastructure layer because AI-driven applications will inherently be more chatty with the database and the middleware? Yeah, really interesting question. I think it's... I think the applications that really do a good job of exploiting AI are gonna do very well. And I think the race to build the best training systems, the race to build the best large language models, the race to build the best robotic models. You know, the robotic models are very different. You know, the LLM is interesting. LLM is very different than... 'Cause it, it's-- Every-- ChatGPT obviously began this revolution in the sense that, oh, my God, it talks. You know, baby talks. And it was completely unexpected, but it's not real time. In other words, once you prompt it, you have to prompt it, sometimes in a conversation. Think about how different it is when you're a robot. Let's talk about a four-wheel drive robot called Tesla's self-driving car, and you see something in the environment, and you have to react in a tiny fraction of a second. It is real time. It's a real-time neural network. It's got to be. You see a ball roll out in front of your car, coming off the curb, and you see that. What do you do? You have to make a decision instantly as to what to do. That's very different than carrying on a conversation. It's very different than looking at a cancer biopsy slide and trying to detect cancer in the biopsy slide. Those are all somewhat different problems. They're gonna be solved. They're gonna need specifically trained models that are somewhat different, and they're gonna need the appropriate applications that are quite different, one from another. So I think there's in a way, I don't know how to answer the question. I think there's opportunity, significant opportunity at the infrastructure, at the AI infrastructure level, and there's significant opportunity at the application level. I think this is a really big, big deal, and it's every place. Over here. Hey, Brent Thill with Jefferies. With the success of OCI, do you think the applications growth rate will meaningfully accelerate? I know you mentioned the backlog is driven by OCI today but- Right ... is apps gonna catch up and be the next leg here? Yeah. Well, I think Cerner, now called Oracle Health, it's the biggest industry in the world, a multi-trillion-dollar industry, that hasn't been served by the IT industry at all. The two giants were Epic and Cerner. We're used to competing with Microsoft, Amazon, Google. Epic and Cerner don't have those kind of resources. They don't have, they don't have that level of talent. So I think our medical system. And by the way, we're trying to automate the entire medical ecosystem. What Cerner and Epic did is they automated acute care hospitals. And what Epic specializes in is in the United States, Epic is the number one company for automating academic research hospitals. That's what they are. They hardly exist outside the United States. Like, we're number one in Germany. We're, I mean, we're almost the entire national health service in the U.K., Epic, Oracle Health now, or Cerner is. So that's it. I mean, yeah, there's Allscripts and a couple little things, but there's. How could the medical industry be completely underserved in terms of application software? It's stunning how awful those systems are. And actually, the purchase of Cerner has had an incredible impact on Oracle, in terms of fundamental cultural change. I remember I made the statement, "If Oracle's actually able to fix this problem, actually do a good job of automating healthcare around the world, if we can do it, we must do it." You know, we have a moral obligation to do it. I can't believe that this industry that is so important and touches all of us and all of our families doesn't have the very best technology support by our industry. But it's been largely ignored, and people have dabbled in it and tried. And to really change the medical industry, you have to, have to look at the entire ecosystem, not just acute care hospitals. You have to look at ambulatory clinics. You have to look at community hospitals. You have to look at medical laboratories and diagnostic laboratories. You have to look at payers, insurance and whether they're insurance companies or national governments. You have to automate because you know, the pre-authorization. If you go into a hospital and you're having a hip replacement, the hospital can't do the hip replacement without talking to the payer, whether that's the National Health Service in the U.K. or it's an insurance company in the U.S., and get pre-authorized, "Yes, if you do the hip replacement, you'll get paid for it." There are these human beings on the phone discussing this, and "Are you eligible?" This is all crazy. This all needs to be automated. The pre-authorization needs to be automated. We need to. In the NHS in the U.K., there are these waiting lists. You need to see a doctor, and you can't see a doctor for six weeks for something. Well, you're calling one clinic. What if there's a doctor available in another clinic eight miles away, further away, that we can send you to, that has an opening, that can see you tomorrow or the next day? They have no idea. They can't do that. They can't manage the load on the request load, you know, standard proper queuing theory, we would call it. And they can't. They don't have the systems to do that. And we're managing everything from, you know, people on smartphones, that's how you make an appointment. So that's how we give you the option. We'll, you can see your regular, you go to your regular clinic. If we can get you in on time, we'll then give you the option. If you don't wanna, your regular clinic can see you in four days, but we can get you in tomorrow at a clinic that's a little bit further away. Do you want that? So you have to have a patient engagement system on your smartphone to make the appointments. If the doctor's running late, we don't want you to come sit around in the waiting room for a couple of hours. We'll let you know in advance that, you know, "Okay, we're running towards late. Please come a little bit later." All of this stuff to make things more efficient. The doctors shouldn't be typing in on keyboards, you know, that all should be done with AI. Redoing all of that, how big is that? Well, that alone is much bigger than our apps businesses now. This, we're talking about all the hospitals in Germany, all the hospitals in France, all the hospitals in Australia, all the clinics in Germany, all the clinics in France, all the community hospitals, all the pharmacies, all of the diagnostic laboratories, plus the governments, who are usually the payers, need systems to do all of that. Plus, we have need. COVID made it very clear we need a system for national public health. We have no system for national public health. We had no idea. We sent a ship to New York City, well-intentioned, because we thought New York City was running out of hospital beds during COVID. No, they weren't! Almost no one went on that ship, but we did, just didn't know. We didn't know sending people back to the nursing homes was killing people. We took a long time. We didn't know COVID had spread months before, you know, from Wuhan to Milan, and then to New York. We caught it months after we should have known. And it's very easy to know when an epidemic or a pandemic is beginning. You can go back and open-source satellite pictures, open-source satellite pictures, and look at the parking lots in Wuhan and see they're filled at 4:00 A.M. in acute care clinics. Something's going on. We have no early warning systems. We have no global systems for pathology systems that look at that actually gene sequence a new coronavirus and say, "Well, that's a little bit different than I've ever seen before." We've done that. We, with the University of Oxford, we built a global pathogen system. We've attached gene sequencers to the Internet of Things, so any hospital can quickly sequence a suspicious new pathogen if you think it is something you haven't seen before. Yeah, I mean, of course, everyone does PCR and all these other things. All the PCR devices are also attached. The new PCR devices are also attached. We're doing all of that. We're not doing what Cerner did. We're doing what Cerner did, plus a lot of other things to completely reform and automate and digitize the healthcare infrastructure for the world. We have to do it in a way that it's pretty economical, that we can do that, that we can do community hospitals. How do you even communicate with community hospitals in Rwanda, or that's East Africa? You know, community hospitals in places in Central America or New Guinea. There was a gentleman who asked me a question a couple of days ago from New Guinea: "How do we get the latest, greatest digital technology in our country? We're not rich like some of the other people here." Well, we can communicate with all the community hospitals using Starlink. You know, we can use modern satellite technology to communicate with any school, any hospital, collect all of this data, so we have a true early warning system for pandemics. The buyers and the providers, you know, I mean, I should say the payers, the governments and insurance companies, and their providers have a very easy way to get prior authorization that's highly automated, doesn't take human doctors getting on the phone, try, you know, begging for the latest cancer drug. We can use AI to read your insurance policy. We can use AI to help you understand your legislation and to see whether that's covered or not, in most cases. We can look at the patient and the condition of the patient and tell you right away whether that should be covered. We can do all of that, and that's what we're doing, and that's one example. I'll give you a couple of other ones real quickly. Securing schools, we think we can absolutely lock down schools so that we dramatically reduce the case of anyone being on campus that doesn't belong on campus, and immediately alert the second someone pulls out a gun, immediately alert. Recognize. Use AI cameras to immediately recognize that. But A, we keep everyone off campus that doesn't belong on campus. The police, another thing, body cameras. We completely redesigned body cameras. Our body cameras cost $70. Normal body camera costs, I don't know, $7,000. Our body cameras are simply lenses, two lenses attached to your vest, attached to the smartphone that you're wearing. And we actually take the video that the police officer is re-- By the way, the camera's always on. You don't turn it on and off. And by the way, the way you turn it on and on, you can't turn it on. "I'm going to the bathroom. Oracle, I need two minutes to take a bathroom break," and we'll turn it off. The truth is, we don't really turn it off. What we do is, we record it so no one can see it, but no one can get into that recording without a court order. So you get the privacy you requested, but a court order, if you get a court order, we will... You know, judge, you know, can order, "I wanna look at that, this so-called bathroom break." If there's something comes up. And plus, "I'm going to lunch with my friends. Oracle, I need an hour for privacy with lunch with my friends." God bless. We won't listen in, unless there's a court order. But it's interesting. And but we transmit the video back to headquarters. So headquarters and AI is constantly monitoring the video. Remember this terrible case in Memphis, where the five police officers basically beat to death another a citizen in Memphis? Well, that can't happen because it would be on TV at headquarters. It'd be on TV at headquarters. Everyone would see it. Your body cams will be transmitting that. The police will be on their best behavior because we're constantly recording, watching and recording everything that's going on. Citizens will be on their best behavior because we're constantly recording and reporting everything that's going on. It's unimpeachable. The cars have cameras, you know, on them. All right, we have. I think we have a squad car here someplace. But those kind of applications using AI, if we can use AI, and we're using AI to monitor the video, so if that altercation that occurred in Memphis, the chief of police would be immediately notified. It's not people that are looking at those cameras, it's AI that's looking at the camera. "No, no, no, you can't do this." It would be like a shooting. That's gonna be immediately. That's gonna be an event that's immediately reported. An alarm's gonna go off. It's gonna be. We're gonna have supervision. In other words, every police officer is gonna be supervised at all times. And the supervision will, and if there's a problem, AI will report the problem and report it to the appropriate authority, whether it's the sheriff or the chief or whomever we need to take control of the situation. You know, same thing with. We have drones. We just. If there's something going on in a shopping center, and I'll stop. A drone goes out there, it'll get there way faster than a police car. There's no reason for, by the way, high-speed chases. You shouldn't have high-speed chases between cars. You just have a drone follow the car. I mean, it's very, very simple, and the new generation of autonomous drones spotting forest fires. A heat bloom drone spots the forest fire, and the drone then drops down and looks around to see if there's a human being near that heat bloom, and someone else either had an unattended campfire that caught fire or it's arson. We can detect all of that. That's all done autonomously with AI. All of these are AI applications. And so you think about the application business, and I'm just getting started. I mean, I'm sure you have other things to do in your life than just listen to me. But there are so many opportunities to exploit AI. One... This will be the last one. We use satellite images to look. We can find all the farms in Kenya, all the farms in Rwanda, all the farms in Morocco. And we can look from the satellite, we can tell what they're growing. They're growing maize. We can report back if the northern part of the field needs more nitrogen, more fertilizer, the southern part of the field needs more water. We can predict the. Using AI, we can predict not only identify what the crop that's being grown, we can forecast the output, the agricultural output of that country, based on what we're looking at now. We can actually survey and forecast if there's gonna be a shortfall, if there's a drought that's gonna reduce the output. We can provide early warning to the people in the agricultural department of that nation state. We provide all that information. These are the kind of systems we can... the next-generation systems we can build using AI. When I say, back to the previous question, yeah, I mean, it's going to enable so much innovation in so many different areas, that the opportunities. The world is gonna be a better place as we exploit these opportunities and take advantage of this great technology. Safra, am I out of time? Yep. Okay. Thank you, all. Please welcome Safra Catz to the stage. Thank you. Thank you. Thank you, all. Thanks, Larry. Okay, I don't know if you have any questions left, and I know a lot of you have flights, so we'll make this quick. Who's got a question? Brad, you wanna go? Okay. Sure. Hey. Hey, Safra. Yeah. Thank you so much for a great week. Lot of excitement. It's palpable walking the show floor, talking to customers and partners. It seems like it hasn't been this exciting to be at Oracle for some time. I wanted to ask you about the fantastic guidance that you've provided today and that Doug went over with us. Mm-hmm. Can you maybe just talk a little bit about... Obviously, you're not gonna box yourself into a corner and give, you know, tell us line by line exactly how you get there. There are many ways I'm sure that you can win. But as we think about the leverage in the business, both, you know, gross margin and OpEx efficiency on the way to 29, can you just talk a little bit more about the multiple ways to win here? Thank you. Yeah. So we have a number of ways to get there, and the reality is, first of all, you can see already in our remaining performance obligations, we have enormous enormous amount of business coming our way, and this is only the beginning. So, so there's the OCI layer, the GPU business is part of it. The other part of it, of course, is the database business. And what's wonderful about the database business, especially in our multi-cloud approach, is that that is a high-margin business because it's an extremely high-value business. And if you've been listening to my calls, and poor you, you have been, you know that we talked about three legs to the stool: Fusion, NetSuite, and our vertical applications. It's already a big number. Larry just told you, Cerner, as you know, as I was breaking down, over our first two years, Cerner is actually a drag currently. It's gonna turn around and be like a neutral because... and then it's going to be truly additive. And when I say neutral, I only mean that it won't be shrinking, but it may not be growing as fast, at least the first year, as Fusion and NetSuite. And then, and then all of our other industry, applications, they are only now coming online into the cloud. So those numbers are gonna be very helpful. So there's OCI and the GPU business, which, the GPU business is only a subset of, of OCI generally, and then the, the applications, and now the database. And sort of everything is hitting, and the database has just started, even though, like for other people, it would be a complete company, but for us, compared to everything else, it is just moving to the cloud. You know, we've given ourselves a couple of years, and basically everything is happening, and there are a bunch of other things that I'm not gonna share with you now, that we are just starting, that are just now you'll start to see little hints of it over this next year. The lines of businesses that you might have heard us talk about, transactions and things like that, other capabilities that we've not even hinted at, all of those are going to start showing up over the next few years. And of course, we're not gonna leave our historic discipline. You know, we treat this money like it's our money, not, not necessarily your money. We treat it like it's actually our money, and so we're always extremely careful about matching up what we do without giving up profitability. And, you know, the thing that's most interesting is not even the over a hundred billion number, but the 20% EPS growth. You know, I remember last time we talked about that, and we delivered it, and then we did our transition. Every single thing we said would happen over these years has happened. And do not think that we do not remember those of you who've been with us this whole time, who have had an understanding and faith in our ability to ultimately execute this. The success has been absolutely a result of some of the things that Larry shared in his original keynote, that he shared here, that the technical teams shared. We have extremely differentiated products. We're not a me-too operation, you know, like: "Oh, they're doing this? Us too." No, that's not our way. Always do the higher value things, do it faster, cheaper, and more securely. Those numbers should not be a problem at all. You pick. Yep. Thanks, Safra. How, as part of this new framework, how do I have to think about CapEx spending? And, you know, one of the things that could be interesting is, like, if you sit in Azure, if you sit in GCP and AWS, they won't spend a lot of money for you in a way. But, like, how do we have to think more broader, from a broader picture perspective about the supporting numbers on cash and CapEx? Thank you. I worry about CapEx, okay, and I figure out how to maximize the power of every CapEx dollar, so we are very, very careful to try to leverage every dollar and to also ride the coattails of richer companies who want to give us floor space and power. That's zero CapEx for me, okay, and all I do is put in my computers, and when they've got floor space and power, you know, my contribution CapEx-wise is very, very small. Additionally, there are all sorts of other clever ways to leverage other people's spending on your behalf and to make sure that we've got, you know, exactly a nicely aligned spending model. We will be spending more, there's no question, but we're always looking at clever ways to make our cash go further. And, you know, sometimes, as I've told you, on different earnings calls, sometimes, you know, the difference between it in one quarter and another, you should not break your heads on that. You need to kinda look at it in a backwards twelve months or a forward twelve months, because within any one quarter... And I think I gave an example even on the earnings call, though I feel like I've been talking so long, I can't tell where I said it. But sometimes the components come to us, and when we buy them, they are capital spent. But sometimes they actually don't come to us. They go to one of our manufacturers, and I don't buy it until another quarter, you know, three weeks later, in a computer. And you'd be like: "Oh, wow! Look at that, $400 million. You know, why didn't you spend it this quarter?" 'Cause I'm spending it there, you know, ten days from now. So don't worry about that. I've told you we're gonna double our CapEx. Believe me. And of course, you'll see the revenue. The revenue's right there. And so double this year, not giving guidance on next year yet, but, you know, we'll get there soon enough. Here. Hi, Safra. This is Siti Panigrahi from Mizuho. The topic this week is all about multi-cloud, and it's very impressive to see these three partnerships in just one year. So we know that that's going to unlock a lot of value for your legacy customer, database customer. So how should we think about the contribution of that, these partnerships, going forward? Once they get really rolling, it's gonna be—I think, quite significant, if you wanna know the truth. And it's gonna be very, very profitable for us. I wanna make one other point, though. You should understand that in this kind of multi-cloud world, it's not only them, it's NRI, that I think was on stage here just a little while ago. It's Saudi Telecom. All of these Alloy partners also have our cloud completely embedded on their floor space, fully plugged in. But you know where else it is? At, you know, at a bank. They have the full cloud. When they have what we call a dedicated region cloud customer, they have. It is literally a region. It just sits on their floor, or whatever floor they told us to go to, and it's just theirs. So you need to understand that as much, you know, Amazon's gonna be wide open, Azure is already in action, Google went live during this show. It, this is a big part of it. But you also, if you're hearing me on the calls, you hear me talk about consumption revenues going way up. Well, remember, we have planted, you know, on that big map, but we've also planted at customer sites, and as those fill up, that's money we spent a while ago. The JWCC, for example, many of you don't know what that is. Remember there was this supposedly JEDI project for the Department of Defense? Remember it was canceled? It was a single source to one of these guys. It was canceled. Instead, it was the JWCC. We're the ones that got the single largest task order about a week and a half ago. Remember, you have to understand, that data center is fully built out to federal standards, accredited, certified, and everything. It's been ready for a while. We got the single largest task order, okay? So this is just happening. There's a lot out there. There's a lot going on, honestly. It is. Everywhere we go, I want you to remember one thing: everything, everywhere. So at Azure, it's all our services. They're available. They may not have been turned on. They look exactly the same, and if customers want them turned on, you know, at Azure, at Google, and ultimately at AWS, the folks at Microsoft have been rolling out services on OCI this whole time. They've, they're actually all fabulous. Okay, we'll take one last question, as I know people have planes to make, and we're wanting to keep on time here. Hi, Safra. It's John DiFucci from Guggenheim. I want to come back to the database migration to the cloud, because this is something I've been writing about for years, and it's been hard because it just makes total sense, but the timing's been tough, and it makes sense. Larry talked about these being mission-critical workloads. They're really important, so it makes sense that they're the sort of the last things to move- Mm-hmm ... to the cloud, or when you're confident about the cloud. I've never lost faith in this, unlike, you know, Brad and Raimo and Karl. But what gives you the confidence today that now it's about to happen? Is it... Do you actually see it in- Yeah ... CRPO and RPO? Are those, are they contracted for now as part of that? Yeah. Like, you see that momentum in addition to... If you can just talk a little bit about- Sure ... why now? And I actually had it on stage with me, that even though my customers, they all did different things, when you're BNP Paribas, and you take all your data, you know, your Oracle databases, and you put them in our cloud, it's starting. German banks, more and more, it is just the... It's scary. It's the, it's your company's heart, and you're thinking to yourself: "Oh, my gosh, you know, is this what... Am I really ready to put it in the cloud?" Now it's happening. In fact, it's interesting because our multi-cloud strategy, which is not only being in the other hyperscalers, but allowing these customers to have their own region where they don't have to share with anybody, it feels to them like the safety of on-premise with all modern capabilities. They can go downstairs, four levels down into their basement, and be like: "It's here." And yet it is in the cloud, and they have all the services they want. They are completely up to date. By the way, one of you asked a question of Larry about... You did, I think. Who are the guys that aren't going to survive this? I'll tell you who. Folks who say they're cloud but are actually just hosted, okay? Applications where you get a new update every three years instead of every ninety days, those folks, the game... It's like game on now in applications. All these new modules, all these new agents, if you're pretending to be cloud by just putting yourself in one of these hyperscalers' buildings, that's not actually cloud. Cloud is new capabilities, exactly the same code everywhere, and new abilities and capabilities every ninety days. And so this is gonna be a very, very exciting time for us at Oracle. You can tell. I must say, the funniest thing I heard, and it kind of goes against our whole messaging, was one of our customers stood up at an event, like, in this room, and she said or he said, "We're not multi-cloud. We're only OCI, and we're thrilled." You know, so... And we embrace that, but we also embrace all the choice, and this is a really exciting time to be with us. I have to say, one of my customers in our public sector, in a public sector meeting, stood up. It's the city of Atlanta. They went big bang, Oracle Fusion. Big bang, Oracle Fusion, all the applications, and they just couldn't wait to talk about it. So with all our other customers, I hope that you all have gotten to see and hear from our customers. You shouldn't have to believe us. Of course, please believe our financial statements, not only announced on day nine, but the Q was filed overnight. I wanna thank you all. We do really appreciate your support. We've been working hard on this. I can tell you what Larry and I are talking about. We're talking about how exciting the next ten years are gonna be at Oracle. So, you should keep an eye on this. We're having a lot of fun. Thank you very much. Go back. There you go. There you go. Okay, I certainly can understand if you all feel that it was all a little anticlimactic after the safe harbor slide, so... But I do appreciate y'all sticking around for this. Covered a lot of ground. As always, thank you very much for coming out. Safe travels home. Good night. We'll call it a wrap.