from science systems work right when people AI this workload, whether it's agents or whether it's training, is unlike anything else, right? These are data parallel, synchronous workloads where you optimize everything from the network to the storage to the accelerator and memory access into reviews of fantastic systems work that is extremely tons of things. Work that is extremely tough to fit for delivering this AI tokens for you both when you run free trading runs, already doing eight runs, and so that's, I think, one of the biggest use cases of innovation. The second of course, is right next to your AI stack for training or inventory. You have your data stack because ultimately, your AI is basically taking all the data and using it to train and or using it to ground your image. And so we have to obtain all the data to have nexus with your new AI compute. Now that means you want to bring everything from Oracle database or one end to snowflake or other end to support everything in Azure. But one of the most exciting areas of innovation for us is building a new AI stack for operational stores, whether it's cosmos or SQL or Postgres or new vector DBS and Azure Search. What we're building in AI first analytic stack with fabric so the rich data layer, coupled with the innovation the AI infrastructure are the core building blocks for anyone trying to build AI applications now we then have the best tool chain, right? So you have your AI infrastructure, you have your data. So the next thing as a consideration for anybody building an AI application is about having a fantastic tool chain. It starts with the app services, right? Where you need an app platform. In fact, AI doesn't stand alone, right? You need application services that you always used in the cloud to be right there with you when you're thinking about AI. So we have App Services, we have logic apps, we have Azure functions, we have AKs, which is the container service. So that's the first grid. And next to this is a new AI platform that's getting created, which is all about Azure. Ai. You want to be able to use new evaluation services across all models. You want to be able to ground these models using hybrid search. So all of those capabilities come by default in Azure AI. And of course, you have the model catalog and models as a service. And talking about models, Azure has the broadest set of models available. Of course, they are all the unique open AI models, right? This whole one model that's just come up is pretty exciting with its reasoning capability. But we also have all open source models, whether it's from llama or misfrom or even other closed source models from this electro here. So you have a full five selection of models that you can then use to build your applications. And then, outside of history, is the tool chip. Right by the clock from 1975 to 2024 is focused on one thing is building the best tool chip. And for us, the combination of VS code and GitHub. And now get out with GitHub co pilot has been absolutely changed. So we are very, very excited to bring the best tool chain to everybody building these AI applications right now, right here in Brazil, we are close to 5 million GitHub developers, and it's fantastic. It's the second largest, or soon to be second largest community of developers, and it's fantastic to see the progress you can get out right if I get on copilot now has this new feature that we are enabling to even o1 where you can code optimize. So for example, if you have some kind of an encoding algorithm, you can use Omar to go in and say, optimize that algorithm, right? So it's no longer just continuation, but it's even optimization. So it's very, very good to see the progress these products are making, and the five plus million developers here using all these products, and we have many customers already here, partners already using these products, I had this morning a chance to meet with folks from Alban Einstein hospital. They've been working with us for many years, but it's great to see them now take advantage of even all the AI work on top of all the data work they did, because one of the foundational contributions they're making is to make sure that Brazilian health data is really represented well so that global health, you know, and all the drug regimes and drug discoveries grounded in the data that represents all of the Brazilian health records. I also had a chance to meet with professor who built a complete new agent of theirs, which is powering operations, everything from customer service to their internal employee operations. In fact, I met the governor of the central bank here who's just unwilling to visionary when it comes to thinking about the financial stack, everything from the payments to finance or programmable finance to, in fact, what they're doing with cdbc and digital currencies. It's just exciting to see the vision that he has to ensure that Brazil has the most advanced system when it comes to even reusing the transaction costs for every everything that happens in the economy. And then I had a chance to meet three women entrepreneurs who started this company radar faith, which is exciting to see three women start a company in one of the most important sectors, which is about health and wellness and the progress they're making. Let's roll the video and give