[Music] Winning isn't complicated. You have to be ready to execute and you have to commit 110%. commit 110%. commit 110%. But winners also have to adapt constantly. The game is always changing and what work on a small scale doesn't necessarily work on the championship stage.To succeed at the highest level, you need a motivating team with the experience and the hunger to win. That's true in football and it's true in business.Today's new disruptive threat and opportunity is AI. I know which team has what it takes to help you to win. >> Over the last few years, generative AI has exploded onto the field, kicking off a race to AI adoption. Enterprises quickly understood that AI would completely disrupt their industries, and if they didn't fasttrack their AI adoption, they'd be left behind. Few organizations were prepared. Summit practiced testing AI initiatives on a small scale, but they realized that their data and infrastructure weren't ready. As enterprises scrambled to catch up, AI only grew in power, in complexity, and in importance. >> All right, that's fantastic. >> Thank you.>> made it look easy. Now, we're entering a new age of enterprise AI, and it's a whole new ball game. Enterprises need to unlock the full value of their data with AI by running a completely new set of plays. It's about fielding optimized trusted data infrastructure solutions that can mobilize all your enterprise data across onrem and cloud and reliably, efficiently power AI innovation. For that, there's only NetApp. We're tackling the biggest challenges in enterprise AI. For the latest on our innovation, let's check in with Sham Nyer. Sham >> George, huge news. Enterprise teams want to confidently seize their AI advantage. But to do that, they need efficiency, reliability, protection, integration, and intelligence. And that's just not available today from any of the other teams on the field. Let's talk data infrastructure first. None of the fancy new AI startups or the old and busted legacy players have a great lineup here. They're all missing key capabilities. The younger franchises just haven't been around long enough. They haven't built the enterprise track record and proven that they have what it takes to build mission critical systems over decades. The legacy players, they may have the track record, but most are stuck on older monolithic architectures or first generation distributed architectures and they certainly haven't built a AI data pipeline directly into their systems.Both of these teams have spotty records on full range of intelligent data services built in. And none of these teams have native integrations with all the major clouds. And none of them have built ransomware protection directly into their systems. Now what if I told you someone could give your AI team all those key capabilities? A modern disagregated architecture, enterprisegrade reliability, native integration with all major clouds,integrated ransomware protection. That's an unbeatable lineup and it's just what NetApp is delivering today. Introducing NetApp AFX higherformanceultra scalable disagregated storage that's purposebuilt for the AI powered enterprise. AFX delivers a massive global name space, unmatched data visibility and parallel file system performance without all the complexity. Granular linear scale of compute and capacity makes optimizations easy. AFX is powered by proven enterprisegrade ontap intelligent data management that ensures seamless data mobility across on premises and cloud. And with integrated realtime ransomware detection, AFX is the most secure storage on the planet. But wait, there's even more to this plate. To truly accelerate your AI outcomes, your data infrastructure needs to turbocharge your data pipeline. For simplicity and speed, you need to integrate those two things. And to really streamline your AI workflows, you need intelligent data services at your fingertips. This is the total package. Only NetApp delivers it. A typical AI data pipeline today involves more than a dozen disparate AI tools and requires repeated data movement all over the field. Data teams cobble together this kind of workflow and then have to manage all of its complexity. This is not how you hustle your competitors. To enable your AI advantage, we pair NetApp AFX with the new NetApp AI data engine. AI data engine radically streamlines enterprise AI workflows at scale by delivering data discovery, curation, guardrails, and realtime vectorization for Gen AI in one end toend AI data solution. Data teams can quickly discover and curate data sets across hybrid multicloud while ensuring AI data is relevant, secure, and compliant throughout its life cycle. NetApp AI data engine is perfectly integrated with NetApp AFX. Together they let NetApp deliver the enterprisegrade data platform for AI. George, this is how NetApp helps our customers win the AI race with a trusted unified data foundation that optimizes AI pipelines while speeding time to insight and value. >> Sham, I love it. AI is an inherently complex hybrid workflow. Yes, it requires high performance at scale. But the essential AI challenge in the enterprise is trust. Do you trust that your data is being used safely and responsibly?Do you trust that your data infrastructure is truly production ready? NetApp innovation has long been proven in the enterprise. Just ask the tens of thousands of customers who've stored more than 100 exabytes of data on our technology. Now, we're pushing the envelope once again. NetApp AFX and NetApp AI Data Engine enable enterprises to confidently unlock the power of data through AI. But we couldn't do this alone. And we've got an incredible ecosystem of partners. There's one partner in particular whose trust we're especially proud of, and that's Nvidia. For years, we've worked with Nvidia to deliver breakthrough AI solutions for more than 600 joint customers. Who better to talk about our partnership than the man himself. I recently sat down with Jensen Huang, CEO of Nvidia, to discuss our collaboration and why it is so critical to the AI ambitions of organizations across industries today. Let's take a look. Today is such a big day and this is a it's a huge day because we're announcing a revolutionary product at a revolutionary time. >> Exactly. You know, this is um we've been working together now for so long. DJX1 was the world's first AI supercomputer. >> That's exactly right. >> And it was connected to NetApp. >> That's right. >> And we use NetApp all over our company. I love the fact >> that you are multicloud and you're a hybrid cloud >> with one basic platform. You can manage your storage. You can manage all of your company's data from structure to object to files. Multimedia, multimodal data. Now that's right. Today today's world is complicated.>> That's exactly >> insanely complicated. >> And the vast majority ofour data is actually multimedia and multimodal. And so that's got to be 90% of NVIDIA's data is unstructured anduh and now with and with NetApp uh we can manage that coherently, you know, on across all of the clouds anduh and hybrid cloud. Uh and the thing that's reallyexciting is that uh today we're announcing a dream come true for both of us. What we're announcing today bringing our two companies technologies together is exactly that. How do you bring accelerated computing technologies and your software stack for AI data platform together with NetApp technologies? So we're really excited. It's groundbreaking. It allows us to bring our mission of helping our clients get knowledge from the vast amount of data that we store for them. Well, this is exciting because AFX and the AI data engine is a complete reinvention of data processing as we know it. AI is reinventing computing as we know it. And then today we're reinventing storage AI for the very first time. And this is such a big deal. I'mexcited that it's reinventing both of our companies. >> Thank you. >> And it'sas you know uh this is the biggest industrial revolution the world's ever seen. Uh this is complete reset of the computer industry and it's created a huge opportunity for me. Um I think it's going to create a huge opportunity for you and this partnership has been a great joy for me. >> Thank you so much. Thanks for having us. Our clients will be excited to see much more co-inovation from us going forward. >> Thanks Jensen. Congratulations on the launch.>> Thank you. >> Thank you very much. >> From partners to customers, there's all kinds of excitement around our new data infrastructure for AI. Take DreamWorks Animation.Data is the lifeblood of their business and NetApp is helping them unlock the full value of that data. Jamarian Monroe has more. Jamarian, >> thanks George. I'm here with Kate Swamorg from DreamWorks. Kate, thanks for joining us. You know, DreamWorks has long turned to NetApp to power and protect data. What role does data management play within your environment? >> Well, what a lot of people don't realize is that our CG feature animated films are actually crafted from the ground up by our artists inside computers. So, everything that you see on screen is actually digital. It's data. We're in the business of producing data. We need enterprisegrade solutions in order to simplify what would otherwise be a dauntingly complex amount of data to manage. We leverage a number of NetApp solutions that are fit for purpose. And it's like George said, we trust our data with NetApp. Even though AI has a significant potential to streamline business operations, it can still be daunting for enterprises to navigate the complexities of adoption and strategy. So, what's your reaction to NetApp's announcements today? Well, to put it simply, we're thrilled. I mean, NetApp is always on the cutting edge of solutions, and today's announcement is just the latest in your amazing innovations. Now, I want to be really clear. At DreamWorks Animation, we are not using AI to generate imagery. We have the best artists in the world for that. But what we are investigating is how AI can help us reduce complexity in our operations, help streamline our workflows and our pipelines. And this is where NetApp and your partnership are going to be side by side with us, putting us in control of our data and focusing on what we need to do to accelerate our business. >> I love that. Well, at NetApp, it is a privilege to have that level of trust, and it's really energizing to hear that your teams are expecting NetApp's AFX and AI data engine to be a gamecher. >> Thanks, Jamaran. >> And on that note, let's dig into the details of AFX and AI data engine with some of our resident experts. Phoebe, thanks, Jarian. All right, some electrifying news from NetApp. Let's unpack this announcement a bit. We're going to go deep on all the benefits that AFX and the AI data engine provide. Naomi, let's start more generally. What's driving enterprise AI adoption? Well, what it really comes down to is competition. Uh, in order to remain competitive, companies have to start moving their AI from proof of concept and into production. And in order to do that, they need to have access to all of their data. And that data needs to be accurate, appropriate, and current. And then on top of that, they need to comply with laws and regulations that are evolving around the same time. And most of the solutions on the market right now are falling short and really struggling to check all of those boxes. >> Yeah, that sounds like a real challenge with all those complex elements. Are there other things that happen, you know, as a result of all this complexity?>> Yeah. So, some companies are moving very slowly because they know that mistakes can be so costly. We're talking about moving from experimentation into enterprise AI with workloads that absolutely cannot go down. So solutions have to be reliable. They definitely have to be secure and they have to be built on data that's trustworthy. >> All right. And so tell me a little bit about how this announcement from NetApp with the NetApp AFX and the NetApp AI data engine are really changing the game when it comes to enterprise AI. >> So I talked about data access which is just one problem but NetApp is tackling three of the key IT concerns with this announcement. So for starters, NetApp AFX is disagregated storage, which gives enterprises the flexibility to scale for performance, but they can also optimize for efficiency and for cost savings. Uh second, both NetApp AFX and the AI data engine are powered by ONTAP. And so right out of the gate, that gives you theindustry standard for reliability, for security, and for governance. Third, NetApp is providing a unified data foundation. So no more getting tripped up with your data in silos. And we're talking about bringing enterprisegrade infrastructure right into your AI pipelines. No matter where your data is stored, you're able to access it whether it's on prim and all the hyperscalers, neocloud, and sovereign clouds. >> Yeah, those are three great reasons why you need an enterprisegrade data platform. Keith, tell me a little bit about how NetApp AFX and this disagregated architecture is really supporting this move of AI PC to production andbreaking those data silos. I'll tell you, Phoebe, we've been working on this product for a couple years andover that period of time, we've seen new large language models emerge, new GPUs, customers becoming way more aggressive around their AI timelines. And what we've taken away from that is you need to be able to adapt and be able to be flexible. And that's what AFX is all about. The ability to scale either performance or capacity as needed in a cost-effective way. That's really the key element ofAFX. and it's still ONTAP, so it has all of the availability, data security, and performance you'd expect out of an enterprise product. >> And we know that NetApp delivers the most secure storage on the planet. So that's really,exciting. But for a moment, tell me about parallel file systems. It's a way that we've previously scaled these large data sets. We've seen it in use for HPC and now AI. What's going on with those? So parallel file systems often come up primarily for the performance. But if you've talked to a customer that's managed a parallel file system, there's some challenges, right? They're difficult to manage. There's security concerns and often times in order to get that performance, it requires client software that's difficult to patch and often has more security concerns as well. AFX is not a parallel file system. It delivers the uh scalability and performance of a parallel file system, but with all of the security, availability, and robustness of an enterprise product. Tell me about how ONAP supports these AI workloads as well.>> Yeah, ONTAP has beenfantastic for AI already, right? Existing platforms already do uhalready support customers looking to do AI, but what we've added withAFX is taking that capability of ONAP and added in the ability to be adaptive. >> That's incredible. And we're seeing it in four times the performance for the same amount of capacity. Up to a terabyte scale throughput and of course real-time ransomware detection with 99% accuracy. This really makes AFX a powerful anchor for the NetApp data platform. There's even more. Right. There is absolutely on top of all of that we've built a metadata engine andwhat that means is the ability for ONAP to build a catalog about the data that sits on top of the cluster that gives administrators a fantastic insight of what's actually consuming the storage and helps data scientists find the data that's relevant to the business problem they're trying to solve. >> Well, we're going over to Darian on the field. She's down there with a partner worldwide technology. Thanks, Phoebe. I'm here with Brad Adams of Worldwide Technology. Great to have you here, Brad. >> Germaine, it's great to be here. >> Now, WWT and NetApp have partnered for many years to enable it modernization with NetApp's data platform and working with enterprises now seeking to leverage AI. What do you see that's holding them back? >> Yeah, Jarian, great question. We work with literally hundreds and hundreds of enterprises to help them modernize their IT enterprise. As you can imagine, AI is among their most important priorities right now. >> But there's a lot of caution out there. >> Is it caution about responsible AI? Whether infrastructure can keep up data pipeline complexity, >> all the above really. No organization wants to be the one to misuse data or lose control of it in pursuit of AI. No one wants to move an AI application from Po to production and have the workload fail. Then there's the overall complexity of AI which can be veryintimidating.>> All those issues are slowing AI adoption.>> So in that light, how do you see your customers reaction to the addition of AFX and the AI data engine to the NetApp platform?Yeah, customers are looking to seize an AI advantage, but they do need to be reassured about their investments. >> That's where we're so excited to see AFX and the data engine raise the bar for the NetApp data platform. First, NetApp already has an unrivaled reputation for enterprisegrade performance, reliability, and protection, which helps resolve much of that caution that I did mention earlier. Now with AFX and AI data engine, NetApp provides enterprises with a streamlined on-ramp to their multicloud operations. >> And that means that it can answer all those urgent requests from data engineers and data scientists. >> Exactly. Building a robust AI data pipeline, which means all the latest AI technologies both in the cloud and from NetApp's incredible partner network. just became so much easier for our customers. That's a real competitive advantage. I can predict right now customer interest is going to be off the charts.>> Brilliant. I love to hear that customer confidence is a competitive advantage built into the NetApp platform. Back to you VB. Thanks Jarian. There is so much excitement around enterprise AI. So Arun, over to you. Let's talk about that. You're a data scientist. you're NetApp's chief data scientist. So, how does the AI vision and the AI strategy for NetApp support all of these workloads?>> Thanks for the intro, Phoebe. Uh, I've been doing data science for over two decades now. But one thing that's always been constant is the data. And by data, I mean data discoverability and uh data understanding, some of which Keith spoke about. But in addition, data scientists also need access to well-governed highquality data. >> That's really key that it's all about data. Tell me about the NetApp AI data engine. What is it doing here to support the AI the data scientists and the AI workloads they're trying to you know they're working on. >> Absolutely. Before answering this question, I would like to set some context. A lot of data in an enterprise is unstructured. We need to impose structure on top of unstructured data. And what this means is converting all this unstructured data into a vector of numbers. And this process of conversion is called vectorization. And the converted numbers are called embeddings. AI data engine provides this vectorzation and embeddings out of the box so that data persona such as myself can quickly build AI applications on top of that. >> That's great. When you mentioned the vectorization and the embeddings, it sounds like that's also generating some data. Is there a way that AI data engine you know works with that supports those workflows andmanages them better? >> That's a great question. In fact, all these embeddings add to a substantial amount of storage. In fact, we call this as data bloat. And the process of vectorization causes almost a 10 to 20x data bloat. For a real world enterprise, converting the data set to embeddings essentially results in a massive increase in storage capacity. We at NetApp understand storage the best and we have built-in technology to completely eliminate this data bloat. So not only do customers get AI ready data, they get a highly efficient form of AI ready data. >> There's one other thing um that I think is really important when it comes to AI which is security. Tell me a little bit about how security looks for AI applications today. So for example, think of a agentic AI or an LLM that is leaking sensitive data. Not only is this a big privacy risk, but it's also a glaring compliance hole because this directly violates many major regulations such as GDPR, HIPPA, etc. This can result in very steep legal fines and also cause severe reputational damage for the organization. You remember I was telling you about how aid provides uh AI ready data out of the box. During this process when the AI ready data is being uh created, we also scan the customer's data estate. We look at all the data sets and we extract the sensitive data and we categorize the sensitive data and we build guard rails on top of it. Essentially, we try to close all the privacy and compliance risks so that customers can deploy their uh AI agents and LLMs with confidence. >> That's awesome and it's great to hear it's part of NetApp strategy. In Bingo, as our resident AI solutions expert, tell me about this landscape. What does the AI ecosystem look like? >> Yeah, the ecosystem is an absolutely critical part for customers that are rolling out enterprise AI in production. They need to make sure that everything that they're putting together works, that it's tested, it's supported, and they know what kind of performance to get and what kind of results to get. And so there are really three elements to the ecosystem. Number one is the partners that go uh in front of the customer and actually deploy the systems, advise on the system, deploy the systems, support the systems. Number two, the ISV partners. ISV partners are absolutely critical to our customer success in the space of enterprise AI. And number three, cloud, right? So if you think about AI is actually one of those workloads where typically customers start in the cloud and then they might roll certain workloads on premises, others may remain in the cloud and then one cloud provider comes out with a new AI tool, then the other one comes out with a new AI tool. So you really want to be able to not only have tight integration with these tools whether they are on premises or in the cloud but also be able to have access to all of your data regardless of whether it's sitting in a public cloud, a hyperscaler, a sovereign cloud, a neo cloud or on premises. >> Talk to me about how you know NetApp and their history and their knowledge of how to manage data and how to mobilize data is supporting enterprise AI workloads. >> Yeah, absolutely. Okay. So what's unique about NetUP or one of the many things that are unique about NetUP is that for a very long time we had this tight integration strategy with the key public clouds. So this way you have the netup technology fully integrated natively in the clouds and on premises which really creates this unified data space where customers can find their data and point their applications to their data without creating this messy copy sprawl type environment where you have copies all over the place. You have security risks. You have redundancies. You spend too much money. You don't even know what's the current copy because do you have 120 copies? Which one is current? Nobody knows.>> So you talked about unified and NetApp has been known for unified storage which I think has meant a couple of things over the years. How does unified evolve with AI? >> Yeah, absolutely. It's interesting how unified has really started to evolve from block and file protocols and structured and unstructured data to now really thinking about okay what are the different data types like Arun earlier spoke about there all these different data types and we're trying to un understand them and structure them differently and then data is stored all over the world on premises and in the cloud. So, how can you unify all of that and bring it together into a unified data architecture is an incredibly challenging project if you don't know how to do that and well, we do know how to do that. >> Yeah, you've drawn a really great picture here of cloud, of hybrid cloud, of enterprise AI for our customers. So, it's really exciting to see how this announcement today is really changing the way that we can look at enterprise AI and accelerate those outcomes. And now, let's go to George and Jerry for some final words. The competition in business, just like on the field, is fierce. And just like the highest performing teams in the world, organizations must constantly be on the lookout for how they can gain their next competitive advantage. You're absolutely right, Jerry. And right now, in this moment, that competitive edge is AI. those organizations that are able to adopt it rapidly and successfully are going to have that edge, that critical competitive advantage over those that don't.>> But just like players on the biggest field at the biggest competition in the world, they can't do it on their own. They need a team. A team that is battle tested, that has shown up to the big moments before and has won, that has a proven track record. >> Absolutely. I believe NetApp is that team because of our unique blend of three key things. First, data. First, data. First, data. We are the data management experts with 30 years of leadership. Second, technology. Second, technology. Second, technology. We're leading the industry with our innovations and are embracing AI ourselves to give our customers the best, the most proven solutions. And finally, culture. We have a set of values and standards that make our employees as well as our partners and customers successful. You know, that sounds like a championship team. >> Jay, take one. All right. >> You know that sounds like a championship team. Okay. Roll it from the top right quick. Come on. Take it. Take quick. Come on. Take it. Take it there right now. Let's go. >> Delivering today. Introducing >> Mark. >> Mark. >> Mark. >> This going to be our best one. Okay. All right.>> Cuz you doing your part. Igot to my game. >> All right. >> Hey, I got you. I'm gonna make you look good. All right. >> Yes.>> Okay.>> Say it again. Just like that. >> I know which team is going to help you to win. >> Thank you. >> All right. Okay. Yeah. I know. Hey.That got to be a spiral. You got there. Now there you go.