 Hello everyone and welcome to theCUBE's coverage of HPE Discover 2023. I'm your host, Lisa Martin. Today I'm joined by Shown Nandi, Director Technology Industries at AWS. Shown, great to have you on theCUBE. Really excited to talk to you today. Thank you, Lisa. Super excited to be here. Let's go ahead and start. Give the audience an understanding of your role, what you're doing, all that good stuff. Yeah, I work for Amazon Web Services. I've been here several years and I look after our field tech teams. These are the folks who help our largest customers build with AWS. And I'm especially focused on our industry's customers. So whether you're in financial services or travel or healthcare or automotive or manufacturing, we're thinking through the use cases and how you help your customers. And my team goes out there to work with your engineers and your product managers and all the folks in your company. Got it. We wanna talk about, start with the hottest topic, I think on the planet, not just in tech, generative AI or gen AI, super white hot topic. It's captured so much attention, even kids are talking about it. Talk a little bit about what AWS is doing with generative AI to help customers really maximize the value of AI and ML for their organizations. Yeah, you sort of have to start and realize that generative AI feels a bit like magic, but it's not. It's actually evolutionary. It's building on all the work that we and many others have been doing for a long time. Generative AI is powered by machine learning models. These are really large models that are pre-trained on tons of data and we call them foundation models. And what we're doing is trying to offer customers lots of choice. We're making the best foundation models available to customers to use in easier and simpler ways. We're also helping our builder customers go and design and build their own foundation models when they need to. And we're looking at building tooling. I'll tell you a bit about that if we have time that helps people put this right to work with minimal effort in different types of use cases. So there's a lot. There's a lot happening in the space. Absolutely. I love that you said generative AI is evolutionary. That's definitely something I think is quite intriguing. We know that Amazon and AWS have played a really big role in democratizing machine learning so that it's accessible to anyone who wants to use it. Talk about why that's important really to the ethos overall Amazon and AWS. Yeah, you know, we've been working on AI and ML in some fashion for almost 20 years it is part of our heritage. It's also part of our future. You know, it started inside Amazon where we thought about robotic picking rates and our fulfillment centers and supply chain and forecasting and computer vision. And of course, everyone knows about Alexa. When we think about AWS, you know, one of our key concepts, one of our leadership principles is cups room obsession. We want to help our customers succeed. And we think having these tools will help our customers build faster more effectively for their customers come to outcomes that they couldn't come to otherwise whether they do them more quickly, more inexpensively, more securely. And so it sort of plays right to the heart of what cloud was built to do. That's why I sort of call it evolutionary, right? It's just one more really, really big tool. I can't just call it another tool in the toolkit that will help customers get there. And I mean the level of passion is intense, right? Everyone, everyone is talking and asking about this like you said. I can only imagine and we've been covering AWS for so long and we know well on theCUBE, the customer obsession is real, but it's also shared in the ecosystem. We're going to be talking about that, but I also want you to kind of share, AWS has a very broad and deep portfolio of both AI and machine learning services at all three layers of the stack. Walk me through that so we really get the, the, the net and that depth and breadth. Yeah, probably what's exciting folks the most is our latest offering that's just entered preview, which is called Amazon Bedrock. And Bedrock is all about bringing capabilities in so that customers can access their foundation models with minimal effort. We support secure customization. It's a service that basically makes the best foundation models, some of the ones we've seen out there, both from Amazon, we're going to have a first party model and from some of the leading startups like AI 21 Labs, an anthropic and stability AI available by API. By making it available by API, that's part of the democracy you alluded to earlier so that all builders can just get to it and access it and fine tune it. We're also, also of course thinking about that layer cake offering all the infrastructure layer capabilities that customers might need. We've built a foundation model hub and SageMaker. We have of course our leading infrastructure offerings including our GPU backed instances, our custom AWS silicon influences like Inferentia. So we sort of go across the whole stack. And last but not least, we're starting to build some unique applications like AWS Code Whisper, which is a code assistant that helps builders build and gives them advice and counsel on how to go and write code in real time. That's one we might end up talking about more. I can't imagine how excited those builders are and the decision makers as well. So big, huge investments that AWS is making in AI and machine learning hugely impactful to customers. Talk about the impact on the partner ecosystem which I know is enormous. Yeah, look partners, they're benefiting in almost every possible way here. They have customers asking for help on visualizing the right use cases. Love talking about industry use cases. There are partners who are thinking of going and building up on top of the stack and even partners who are directly benefiting from the tooling already. So if I think about one big partner Accenture that Amazon Code Whisper offering, I mentioned that's the AI coding companion. They've discovered it is already helping reduce their development efforts by 30%. So their developers can focus more on security quality and performance as they build applications and products for their customers. So they are both benefiting from helping customers that opt in AI by using it themselves to accelerate their outcomes. Very symbiotic, I love that. And we know that that generative AI, like we said, it's such a hot topic. It's also already having impact, big impact across a lot of industries. I'd love to know, are there, you mentioned some in the beginning, any industries in particular where that are really early adopters where AWS is seeing the strongest traction? Yeah, look, it's super early. Every industry is excited and uncomfortable and nervous. And they're looking for some key elements, right? They're looking to understand intellectual property rights and security and regulatory oversight. And so we are thinking about that from the beginning. We're thinking about the elements to allow them to use their data-trained models. When you think about industries that are regulated like financial services and healthcare, they see potential to help their advisors get insights faster, move through approvals processes more quickly, providing personalized financial advice, but they have to make sure they get through the right regulatory steps. And a lot of that is understanding what data is being used to train these models. In healthcare, we know it's going to help researchers. We know it's going to help summarize data for them and give them quick insights back. And we've done a bunch of early work with healthcare companies on building, in some cases, chatbots that are really narrow and private using very curated data. But if you think about it over time, where we think this will go, is doctors and practitioners able to get advice? Right, it may not be advice they can run with without expertise, but it'll help summarize the thinking so they can put in sort of the challenges you're seeing and get ideas on what they might do next. And last but not least, media and entertainment. Wow, we saw publicly one of the large M&E companies did their first sort of background in an early production done by Generative AI back in February. We expect more of that. And media companies do refine the right balance between protecting their creators and using this capability to sort of accelerate their ability to build content. So there's lots, there's lots happening from an industry perspective. And I can't think of an industry that won't be able to use this technology in one way or another. I agree, you brought up some great use cases in healthcare and financial services, media and entertainment. I imagine education as well, but to your point, no industry will be left untouched and hopefully be able to tap into the potential. You mentioned some of the tools you mentioned, Code Whisperer and No SageMaker. Just give the audience an understanding of some of the tools that AWS has that customers can use for building Generative AI on AWS. Yeah, you know, I started with and I'll continue to talk about Bedrock, right? Bedrock is so exciting because one of the things that's changing so quickly is many of the leading startups are releasing and providing foundation models. I had mentioned those earlier that really help drive, that's what powers LLMs. And what we've done through Bedrock is make these LLMs available, these foundation models available via API. So a builder who's going to build a product who wants to get that interactive element in doesn't have to figure out how to go and get that foundation model on their infrastructure, figure out how to go and work with it and configure it. They can just go do that through Bedrock. So it's going to accelerate them. And in addition, we're going to be providing some of our own foundation models, which is also super exciting. So customers will have choice and we think choice is amazing power. It also means they'll be able to control where their data goes. What's unique for most enterprises and industry companies operating here is they have their data. Their data is probably the key to their success. So you can go and work with something like Bedrock to control where your data goes. You can customize these models and still keep your data private and secure. So that gives you the option to get curated answers to your questions, but not sort of lose that access and control to your data and not share it with others. So the guardrails are built in. Oh, the guardrails are a big part of our design model. That's one of the things we're working through and we understand that different customers will have different levels of concern. Some customers, by the way, are going to want to use publicly available data. Right, guardrails aren't going to be top of mind for them, but that's some minority in the enterprise. Most enterprises, they're pretty worried about their data. I agree. You must have, with all this excitement around Gen AI and all that AWS is doing, you talked a lot about Bedrock and the capabilities foundationally that that will deliver. You must have a favorite customer story that you think really shines a light on the value that AWS is going to enable customers to unlock with Gen AI. Share an example with me. It's all about moving fast. And I probably already spoiled my first and favorite example, the Accenture, getting that massive time savings for their engineers using Code Whisper. We've also seen customers like Finch Computing who reduce costs by 80% using Inferentia who are developing foundation models. So right now it's very early in this race, many of the startups are trying to build these foundation models. I think the best ones, the most exciting examples are the ones we're still building, working with some of those healthcare companies who are out building these drug discovery chatbots and engagement with researchers and some of the summarization. So lots more to come in this space, but every week you're in here about somebody new doing something really great. I bet there's never going to be a dull moment with this at all. Let's pivot a little bit on the ecosystem. In our last few minutes here, and AWS and HPE in particular have been partners for a long time. Talk to me about the partnership. What are some of the great things that you guys are doing together? You know, the partnerships really awesome. And I think one of the areas of focus for us is how can we make sure that HPE is what they build for their customers and the customers who are then also operating AWS. How do we simplify that engagement? How do we bridge what they're running with HPE and what they're working on with AWS? The first is trying to make HPE's products available in our marketplace. That's been incredible. That's been awesome. It becomes a one-stop shop for customers. The second, HPE GreenLake, private cloud enterprise, it's tied to Amazon EKS anywhere. So if you haven't heard about EKS anywhere, EKS anywhere is based on Amazon's Elastic Kubernetes Service, EKS. We use Kubernetes to orchestrate containers and workloads in the cloud. And what EKS anywhere enables is for you to do that on-premise with your existing infrastructure. And so HPE GreenLake ties all that together. It uses EKS anywhere. It lets you orchestrate and simplify your Kubernetes deployments across bare metal hosts, VMware, cloud stack. And the good thing for our joint customers, it uses the same Kubernetes distribution that we use for EKS in the cloud. So you have the same versioning, you have the same dependencies, you have sort of consistent software update processes and security patches. So it's really bringing it all together to become between HPE and AWS, a one-stop shop for customers. So then this might be a silly question, but if I'm a big AWS shop from a builder or am I a decision maker, what's in it for me in terms of the power and the breadth and the depth of what AWS and HPE are doing for me as a customer? Well, it means that for that piece of compute that you still have sitting in your data center, HPE now has an offering that'll knit the two together so that you're not operating in siloed fashion, so they're not separated. So you're bringing it together using EKS anywhere, running as part of GreenLake in this case, GreenLake PCE. And you just have a single, you have a single sort of approach. It's not bifurcated anymore like it used to be. And that's really great. That really simplifies their lives and of course it applies their security model. Absolutely, when the security model is so important. Any final thoughts, Shown, you talked to us about the ethos of Amazon and AWS, where gen AI fits in that, gen AI is an evolutionary model, which I love. Anything that you wanna leave our audience with any final thoughts? Look, I started by saying it's evolutionary. What I really meant by that is it feels like magic, right? You see these questions being answered amazingly by the latest consumer offerings. And the reason I say it's evolutionary is for those who've been working in this space a long time, we knew the potential was here, but all the pieces of cloud, having infrastructure operating its scale, bringing together our managed services, now makes it doable quickly. And that's all that AI ML work over the last 20 years sort of coming together, and starting to drive this value. I think that's exciting. I think it's gonna let our customers build so much faster, build so many better things and go impact the world. That's important to us. And I'll tell you, if you wanna hear more, tune in for the keynote, you're gonna see Dr. Madd Wood from AWS on a panel talking more about this. That's gonna be great. Awesome, huge impact to come dot, dot, dot. We'd be waiting to see what they talk about on the keynote. Shown, thank you so much for joining me on theCUBE today, giving us a great overview of what you guys are doing with gen AI and the huge impact and potential that you're gonna be able to enable every industry. We appreciate your time. Thank you for having me. I appreciate it, have a great day. You too. We wanna thank you for watching theCUBE's coverage of HPE Discover 2023. For much more content on HPE Discover, keep it right here on theCUBE, the leader in tech event coverage.