Thank you all so much. Uh, thanks for joining me here. I'll apologize up front if I start to lose my voice. I picked up a little cold while in Vegas. Big surprise. Um, but I'm here to talk to you about a topic today that to myfriend's point over here, you've not heard about at all during this conference. Um, and that's Gen AI, right? It's every conference I go to, whether that's additional partner conferences, our own partner uh conferences, those types of things, Genai is the top of everybody's discussion point, right? We heard real uh life stories yesterday from Dr. Fay Lee um and from Thomas Currion around the NetApp partnership with artificial intelligence. You even got a great presentation um by Ake yesterday on the partnership between uh NetApp Cloud Volumes with Google's Vertex. Um Genai is a huge deal right uh to the point where it's all I am basically talking about seven days a week. And I'm not talking about just to clients. My 70-year-old mother is asking me how she can use generative AI and what does it mean and is it going to cause her any problems or is there any concerns about the world um utilizing Gen AI for nefarious practices? Um but what I want to kind of cover today is how you get from that Gen AI discussion, right? Um we all know it's important to creating business value in an organization, right? It's this amazing hype train. Um and for good reason. So, we'll just pop in here because I've only got 20 minutes. Um, but one thing I do want to cover with you is if you've been sleeping underneath a rock, you haven't heard about what I just talked about for two minutes there. Um, there is a lot of hype to the point where one of NetApp's biggest partnerships in the technology space. Um, agentleman who uh owns and runs a very green artificial intelligence focused company has called Genai the iPhone moment of artificial intelligence, right? Um, and there's a few reasons for that, but this is something that's not going away. I think you know through some of the demos you've seen over the last couple days, some of the sessions that you've been sitting in around the NetApp story with artificial intelligence, um this is in my opinion it's the next cloud, right? Uh I got into this industry in about 2006. Um right at the point where cloud was actually starting to make a little bit of an ingress into our business uh as an infrastructure sellingkind of guy. um I was a little bit worried about it, but as you've seen over the years, it's become a very useful and um wellutilized tool depending on what you're trying to do in the IT space to move your business initiatives forward and generative AI is no different, but it's not new really. Um artificial intelligence as a whole isn't new, right? We're talking about something that has been around since the 1950s when the term artificial intelligence was coined. Right? This has been going for I mean I'm not very good at math but let's say uh you know a good 60 70 years um at this point using artificial intelligence to garner value from data and machine learning is another term that you'll hear thrown out all the time. This isn't new either. my co back in the 90s was building machine learning models to do analytics and predictive analytics on whatever he was working on right whether that was math problems um you know with colleges like MIT and those types of things is it been a general progression over the years since the ' 50s to get to where we are today deep learning was the next thing to come up in 2017 you've all hearduh about the touring test and all of those things but generative AI is really important to our industry because what it's done is it's created this mentality of okay, we've been talking about machine learning and deep learning and AI for years from my perspective, but a lot of organizations weren't ready to take that leap. They didn't want to be the early adopters. They didn't want to be the first movers. They wanted to kind of see how it played out. This has actually democratized artificial intelligence to the masses to where they can't ignore it anymore. I talked to a lot of clients at Insight about our artificial uh intelligence, machine learning, deep learning, genai capabilities. What we're actually finding is there's only a portion of people that actually need to utilize and build generative AI models, right? In a lot of cases, they're confusing the terms. They're probably looking at something predictive more on the machine learning side of things or they need to solve a problem with a deep learning model, not necessarily generating images or text or, you know, audio or video or those types of things on their behalf to solve these challenges for their organization. So, it is really an evolution of the AI tools and there's a few reasons that it is in my opinion um going to change our industry over the next 5 to 10 years here. Part of the reason is because generative AI for the most part, you know, based on what we've seen with chat GPT and all of these models that are out there and what we're doing from an organizational standpoint throughout this entire room is it's bigger, right? It's trained on billions of parameters. It's able to trend uh to train on significant curated data that's been out there for years on the internet. So it is much bigger than what you would consider a data set for a traditional machine learning model or a deep learning model. It's more generalized. Um they're trained for those pattern recognitions, right? And it can be trained on text and music and video and art and all of these things that we can create, right? My biggest use case that I see is from a marketing perspective or even just incorporating it into an organization so you can chat with your own data. That's really where we see the value from an insight perspective is starting to utilize it, finding those use cases, ideulating those use cases on where you can actually create organizational value, but until you dive in, you're not going to be able to get to the point where you can figure out where the use cases are. And you may not be able to do that either. I'll cover some of that a little bit further on where insight can help. Um, but the biggest thing around Genai that that's really kind of impressed me, again, I had mentioned my 70-year-old mother, it's accessible. Every single person in this room can use it. You can go out to OpenAI chat GPT. Uh, your organizations may have already launched this in an Azure instance, a GCP instance, a uh AWS instance internally to your organization. Now, there's a lot of challenges around doing that. Um, and that's where some of the strategy has to come into play to tr find that true business value while also keeping your data secure, right? Because when we're talking about something like an open AI chat GPT, we're talking about putting your data out there on the internet. Um, I don't know about you, but personally in a identifiable information, uh, health information, your own personal information, I personally don't want that getting out on the internet. And anytime you use something like that in a web-based type of format, you are basically giving your data out there to be trained against. So you got to be able to come up with strategy and ways and means to ensure that if you are going to use your data, your customer's data, your partners' data um that you do it in a very secure and uh succinct way. So as I had mentioned before, there's a few key use cases around generative AI. These are really more tuned on this slide. um sorry if I'm standing in front of that um around the natural language processing uh side of things with Genai. So what it's really good at um and what it's not good at. So finding and uh summarizing data, right? Taking care of that search. We all know about SEO and how much of a pain it is to go out and try to find something on Google uh in a lot of cases, right? Um, but being able to use generative AI is kind of that catalyst to get that information faster to you, right? I could go out and spend 20 minutes, half hour looking for some information around, let's just say, um, vector databases, right? Um, but Gen AI can return thoseresults a lot faster. It's really good at summarizing as well. So, if you like me are very wordy, um, I do write a lot of emails in my profession. Um, I tended to write real long emails or if I'm writing an article or if you know I want to put something out from a marketing perspective. Um, I tend to write a lot. Um, but Genai is really good at taking that kind of dissecting the meat and the potatoes out of it for lack of a better word. Um, and kind of giving you the result that you actually want out of your data, right? And that's what this is all about. And then on the other side, you saw thedemo yesterday where uh Ake was able to create this beautiful image of a man sitting in front of a cloud um for a blog around the marketing side of things. So really what Ake was showing you yesterday was exactly these three use cases, right? Finding the information about why NetApp Cloud Volumes um was great. Let me summarize why that's great. and then let me generate some images, not only the text, but the images around that to be able to and the code to be able to put that out quickly. In the past, that's something that could have taken marketing weeks, right? Because you got to work with multiple different teams. You've got to work with your content team on the um the you know the value side of things on cloud volume on tap. You've got to work on your content team or your imaging team on creating that image and then you've got to work with your development team to get that launched into a HTML or onto a website. So really the big key around generative AI is it's meant to make life easier. Uh Dr. Feay did say this as well. She considers AI, generative AI, all of these categories to be an augmentation of humans, right? Humans will always have a place in the loop. We have to make those decisions. We have to be responsible for it. Um so at this point, I mean it's you do get a lot of concerns from people saying, "Well, it's going to take my job. It's going to do this." My whole opinion on it is it's not. It's going to augment your role. you're going to have to learn new skill sets. And I would suggest personally starting to dive deep into prompt engineering and those types of topics just to get yourself ramped up on how to use generative AI um in your day-to-day job because I'll be honest, I use it personally in my day-to-day um and it's made a world of change in my life. Um allowing me to focus on more important things, right? things, right? things, right? from an u an enterprise perspective um some of the biggest use cases that we're seeing and they all kind of align with what I was just talking about um are across all the facets of an organization right from finding information for sales to summarizing that information through sales reports um product recommendations and sales forecasting these are just alist ofways that generative AI is actually adding value to organizations today um and somewhere that Insight is working specifically with clients, helping them to ideulate and strategize around where can I get the biggest bang for my buck, creating a generative AI minimally viable product, right? From everything in HR and IT and beyond, there are tons of use cases where generative AI um can make a difference in an organization. But you have to be very careful with that and you need some strategy around how to incorporate your own data because it's one thing using the internet's data. um your own data has a lot more uh things you need to worry about. So from an insight perspective, we do this through our generative AI engagement model, right? Um we start out with an executive briefing, right? I get calls from customers and from my sales reps and everybody that I talk to on a daily basis saying, "Look, my executive my client's executive team knows they need to get started with artificial intelligence. They've heard about this Gen AI buzz. How do I get them going in this? How can we explain to them where it can create that return on investment and value in an organization? So, we actually will take a two-hour workshop or a 1 to three day strategy workshop with our clients and help figure out those gaps, help figure out where the gaps are in their data, help figure out, you know, if their data is disperate, how do we coalate and get that together in adata lake that we can actually utilize, right? Because you don't want to utilize junk data in an AI model. Um, we can also help them accelerate. We've got this program called Insight uh Lens for Genai Accelerator. Now, we do this on Microsoft Azure at this point. Um also on prem in partnership with Nvidia uh Nvidia with their Nemo framework. Um if you've been in any of the AI sessions, uh you did hear about NVIE um on stage at the keynote yesterday. Um, but this is another framework and another uh software development side of things that can help you to do these things on prem if you don't want to put your data uh up in the cloud on an Azure or a GCP or an AWS and then from andthat's really all about getting you launched in a private and secure way where you and your team can actually utilize the models that are available to you. start to play with it, start to understand the use cases, start to see where you can maybe use some of your own data andutilize that in your organization. The other side of that coin after you get to that point um is creating co-pilots, right? We've got a use case. We want to incorporate your data. Let's help get you started in that in two weeks. That seems like a short period of time, and it actually is. I mean, if you have to start from scratch and you don't have a partnership to be able to help you with the strategy with building these things out, it can uh take quite a long time and you're looking at months oryears to get to the same point that partnering with somebody who has the expertise who actually has done this internally in our organization um utilizing GPT or you utilizing Genai from a chat perspective um with our own data um that can kind of get you to that point and then if you are one ofthose organizations that is the builder of AI, right? Where you're actually not looking to consume, but you're building new models to integrate into your products or your solutions or your applications or those types of things. One of the biggest uh termin terms in the industry right now that is obviously I'm hearing from NetApp, I'm hearing from Nvidia, I'm hearing from my own thought leadership on that side is creating that AI center of excellence. You need a strategy and we're not just talking about an AI strategy. We're not just talking about AI models. We're talking about an organizational change to ensure that when you start to produce an AI model, when your uh data science teams and your developers get together, that you're able to do it in a consistent and standardized way that will continually achieve success for you because a lot of data and AI models do fail, right? They either don't have the funding, they don't have the strategy around it, they may launch in the cloud and realize that it gets too expensive. But if you have a center of excellence built around that, you've got these people and these processes and these practices in place to ensure AI success through um through the entire journey, right? Because it is a journey. It's not a widget that I'm going to sell you. Ican't sell you Gen AI. I mean, technically, I guess I could, but I can't sell you Gen AI. It is a complete solution, and there's some organization around it. Um, like I said, we you saw thedemo from Ay um yesterday. We have a similar thing out on Azure um and we just launched this about I'd say 6 to 12 months ago um where we can actually get you launched in two weeks right up and chatting with uh with chat GPT orGenai um in a private and secure way where you have complete control over the security the roles and permissions um the costing around it and the analytics around that. So if you see somebody using a little bit more than they should, you can put in those um stop gaps tokind of uh alleviate that. Um but what this really iskind of a bridge to that custom enterprise integration, right? It gets you in and playing in a secure way. We can incorporate your data if you'd like us to do that or if you just want to use the internet data that's fine as well. Um, but it's kind of the starting point to get off in a inexpensive uh method to see if it's going to make sense for your organization. Um, but we take care of everything from setting up youryou know, your Azure uh instance to ensuring that you've got all the access that you need. So, this is a twoe engagement. Um, make sure to stop by our booth and ask any more questions about it if you'd like to learn more about that. But definitely something that we're seeing in the market isadding value and we'regetting calls on a daily basis um from our clients asking tokind of take them through this process to show them where Gen AI can truly uh provide an improvement for them. So now I got to tie it back to NetApp. Uh I am a NetApp SE by trade. Uh was for years, but data is the lifeblood of AI. Uh there's nothing more that I can say there. George said it on stage uh yesterday as well, right? you need a an AI ready data solution. Um, and that's where NetApp is really coming into play for us from a solutions perspective with the data fabric with all of the ability to move your data between the cloud on prem near in a collocation um with firstparty cloud services and beyond. So unlocking the power of AI uh two little points I want to make right democratic discoverability of sharing and sharing of data is huge like I'd said before you want to have curated data cataloges you want that collated with common vocabulary so you're not just putting it into one line of business um that's one of the biggest challenges that we have in the AI space right now is disperate siloed data that the business can't actually take advantage of and you've got people out there from data science teams and beyond um running their own models on separate data when they've got it all there. So you've got to ensure that that'sthere. Um obviously orchestration, replication andworkflows in a real-time environment are very important. Um obviously NetApp technology has some of those automation and orchestration tools around uh AI and generative AI in general. Um flexible compute, right? Like I said, I work really closely with one of NetApp's biggest partners, Nvidia. um you'll hear a lot more coming from them over the next couple years around the compute side of things, but the main point here for me is smart scalable storage. My battery is running low. Um sorry, you don't see that. Um so basically theability of NetApp to allow you to do your deployment wherever you want it. put your infrastructure in the cloud, put your infrastructure on prem, put your infrastructure on um near your cloud is really important to ensuring that you have an accelerated data pipeline to train and to inference on that data. And then of course seamless security and governance. Um I think that's most people's concerns these days, right? Security is one of the biggest concerns. We are currently sitting in a hotel that had some security concerns of theirelves uh a few weeks ago. So, it's something that you've got to consider when you're going down this path. And having a partner that can help you kind of overcome those challenges, understand those gaps, and get you to the right place is uh is imperative.>> Um I am dead. >> Uh oh. >> Yeah. >> Yeah. >> Yeah. >> Let me see if I can help you. Your battery is running low. Apparently lower than low. >> Lower than low. Well, I can get to the next slide at least. So, least. So, least. So, >> yeah, we're good. All right. So, um as you can see, like I'd mentioned, right, NetApp has the platform, the solution, the data management, um through ONTAP that allows you to kind of take your AI journey wherever you need it, right? From the edge to the core to the cloud with the performance that you expect from something like a NetApp and ONAP um and with the accolades that come with being an amazing AI partner, um like they are with Insight. So my takeaways um amidst all the hype around Genai, there is business value to be had. Um discovering how you can utilize that is paramount. Um sometimes you'll need a partner. Sometimes you are able to do it yourself. But when you don't have the capabilities to do that, look to somebody like an insight to help you kind of go down that journey. Um it is the newest IT factor and I like to use that it factor. They used it at conversion using it again. Um it is a culmination of every other technology out there. you may be looking at Gen AI use cases not realizing that we're not talking specifically about Gen AI here. So just keep that in mind um from finding information summarizing it beyond Gen AI isgreat uh solving math problems not so great. So if you need something generated, that's when you want to kind of focus on Gen AI. And last thing, you're not alone in it. There are partners out here like insight that can help you to align on the strategy creating those AI centers of excellence, finding valuable uses for Gen AI in your organization and our technology partnerships with those like that we have with NetApp on the data management side is making uh making our ability to help our clients with generative and regular AI um all that much more simple.