(gentle upbeat music) >> Hello, and welcome to theCUBE presentation of the AWS Startup Showcase Open Cloud Innovations. This is season two episode one of an ongoing series covering setting status from the AWS ecosystem. Talking about innovation, here it's open source for this theme. We do this every episode, we pick a theme and have a lot of fun talking to the leaders in the industry and the hottest startups. I'm your host John Furrier here with Lisa Martin in our Palo Alto studios. Lisa great series, great to see you again. >> Good to see you too. Great series, always such spirited conversations with very empowered and enlightened individuals. >> I love the episodic nature of these events, we get more stories out there than ever before. They're the hottest startups in the AWS ecosystem, which is dominating the cloud sector. And there's a lot of them really changing the game on cloud native and the enablement, the stories that are coming out here are pretty compelling, not just from startups they're actually penetrating the enterprise and the buyers are changing their architectures, and it's just really fun to catch the wave here. >> They are, and one of the things too about the open source community is these companies embracing that and how that's opening up their entry to your point into the enterprise. I was talking with several customers, companies who were talking about the 70% of their pipeline comes from the open source community. That's using the premium version of the technology. So, it's really been a very smart, strategic way into the enterprise. >> Yeah, and I love the format too. We get the keynote we're doing now, opening keynote, some great guests. We have Sir John on from AWS started program, he is the global startups lead. We got Swami coming on and then closing keynote with Deepak Singh. Who's really grown in the Amazon organization from containers now, compute services, which now span how modern applications are being built. And I think the big trend that we're seeing that these startups are riding on that big wave is cloud natives driving the modern architecture for software development, not just startups, but existing, large ISV and software companies are rearchitecting and the customers who buy their products and services in the cloud are rearchitecting too. So, it's a whole new growth wave coming in, the modern era of cloud some say, and it's exciting a small startup could be the next big name tomorrow. >> One of the things that kind of was a theme throughout the conversations that I had with these different guests was from a modern application security perspective is, security is key, but it's not just about shifting lab. It's about doing so empowering the developers. They don't have to be security experts. They need to have a developer brain and a security heart, and how those two organizations within companies can work better together, more collaboratively, but ultimately empowering those developers, which goes a long way. >> Well, for the folks who are watching this, the format is very simple. We have a keynote, editorial keynote speakers come in, and then we're going to have a bunch of companies who are going to present their story and their showcase. We've interviewed them, myself, you Dave Vallante and Dave Nicholson from theCUBE team. They're going to tell their stories and between the companies and the AWS heroes, 14 companies are represented and some of them new business models and Deepak Singh who leads the AWS team, he's going to have the closing keynote. He talks about the new changing business model in open source, not just the tech, which has a lot of tech, but how companies are being started around the new business models around open source. It's really, really amazing. >> I bet, and does he see any specific verticals that are taking off? >> Well, he's seeing the contribution from big companies like AWS and the Facebook's of the world and large companies, Netflix, Intuit, all contributing content to the open source and then startups forming around them. So Netflix does some great work. They donated to open source and next thing you know a small group of people get together entrepreneurs, they form a company and they create a platform around it with unification and scale. So, the cloud is enabling this new super application environment, superclouds as we call them, that's emerging and this new supercloud and super applications are scaling data-driven machine learning and AI that's the new formula for success. >> The new formula for success also has to have that velocity that developers expect, but also that the consumerization of tech has kind of driven all of us to expect things very quickly. >> Well, we're going to bring in Serge Shevchenko, AWS Global Startup program into the program. Serge is our partner. He is the leader at AWS who has been working on this program Serge, great to see you. Thanks for coming on. >> Yeah, likewise, John, thank you for having me very excited to be here. >> We've been working together on collaborating on this for over a year. Again, season two of this new innovative program, which is a combination of CUBE Media partnership, and AWS getting the stories out. And this has been a real success because there's a real hunger to discover content. And then in the marketplace, as these new solutions coming from startups are the next big thing coming. So, you're starting to see this going on. So I have to ask you, first and foremost, what's the AWS startup showcase about. Can you explain in your terms, your team's vision behind it, and why those startup focus? >> Yeah, absolutely. You know John, we curated the AWS Startup Showcase really to bring meaningful and oftentimes educational content to our customers and partners highlighting innovative solutions within these themes and ultimately to help customers find the best solutions for their use cases, which is a combination of AWS and our partners. And really from pre-seed to IPO, John, the world's most innovative startups build on AWS. From leadership downward, very intentional about cultivating vigorous AWS community and since 2019 at re:Invent at the launch of the AWS Global Startup program, we've helped hundreds of startups accelerate their growth through product development support, go to market and co-sell programs. >> So Serge question for you on the theme of today, John mentioned our showcases having themes. Today's theme is going to cover open source software. Talk to us about how Amazon thinks about opensource. >> Sure, absolutely. And I'll just touch on it briefly, but I'm very excited for the keynote at the end of today, that will be delivered by Deepak the VP of compute services at AWS. We here at Amazon believe in open source. In fact, Amazon contributes to open source in multiple ways, whether that's through directly contributing to third-party project, repos or significant code contributions to Kubernetes, Rust and other projects. And all the way down to leadership participation in organizations such as the CNCF. And supporting of dozens of ISV myself over the years, I've seen explosive growth when it comes to open source adoption. I mean, look at projects like Checkov, within 12 months of launching their open source project, they had about a million users. And another great example is Falco within, under a decade actually they've had about 37 million downloads and that's about 300% increase since it's become an incubating project in the CNCF. So, very exciting things that we're seeing here at AWS. >> So explosive growth, lot of content. What do you hope that our viewers and our guests are going to be able to get out of today? >> Yeah, great question, Lisa. I really hope that today's event will help customers understand why AWS is the best place for them to run open source, commercial and which partner solutions will help them along their journey. I think that today the lineup through the partner solutions and Deepak at the end with the ending keynote is going to present a very valuable narrative for customers and startups in selecting where and which projects to run on AWS. >> That's great stuff Serge would love to have you on and again, I want to just say really congratulate your team and we enjoy working with them. We think this showcase does a great service for the community. It's kind of open source in its own way if I can co contributing working on out there, but you're really getting the voices out at scale. We've got companies like Armory, Kubecost, Sysdig, Tidelift, Codefresh. I mean, these are some of the companies that are changing the game. We even had Patreon a customer and one of the partners sneak with security, all the big names in the startup scene. Plus AWS Deepak saying Swami is going to be on the AWS Heroes. I mean really at scale and this is really a great. So, thank you so much for participating and enabling all of this. >> No, thank you to theCUBE. You've been a great partner in this whole process, very excited for today. >> Thanks Serge really appreciate it. Lisa, what a great segment that was kicking off the event. We've got a great lineup coming up. We've got the keynote, final keynote fireside chat with Deepak Singh a big name at AWS, but Serge in the startup showcase really innovative. >> Very innovative and in a short time period, he talked about the launch of this at re:Invent 2019. They've helped hundreds of startups. We've had over 50 I think on the showcase in the last year or so John. So we really gotten to cover a lot of great customers, a lot of great stories, a lot of great content coming out of theCUBE. >> I love the openness of it. I love the scale, the storytelling. I love the collaboration, a great model, Lisa, great to work with you. We also Dave Vallante and Dave Nicholson interview. They're not here, but let's kick off the show. Let's get started with our next guest Swami. The leader at AWS Swami just got promoted to VP of the database, but also he ran machine learning and AI at AWS. He is a leader. He's the author of the original DynamoDB paper, which is celebrating its 10th year anniversary really impacted distributed computing and open source. Swami's introduced many opensource aspects of products within AWS and has been a leader in the engineering side for many, many years at AWS, from an intern to now an executive. Swami, great to see you. Thanks for coming on our AWS startup showcase. Thanks for spending the time with us. >> My pleasure, thanks again, John. Thanks for having me. >> I wanted to just, if you don't mind asking about the database market over the past 10 to 20 years cloud and application development as you see, has changed a lot. You've been involved in so many product launches over the years. Cloud and machine learning are the biggest waves happening to your point to what you're doing now. Software is under the covers it's powering it all infrastructure is code. Open source has been a big part of it and it continues to grow and change. Deepak Singh from AWS talks about the business model transformation of how like Netflix donates to the open source. Then a company starts around it and creates more growth. Machine learnings and all the open source conversations around automation as developers and builders, like software as cloud and machine learning become the key pistons in the engine. This is a big wave, what's your view on this? How how has cloud scale and data impacting the software market? >> I mean, that's a broad question. So I'm going to break it down to kind of give some of the back data. So now how we are thinking about it first, I'd say when it comes to the open source, I'll start off by saying first the longevity and by ability of open sources are very important to our customers and that is why we have been a significant contributor and supporter of these communities. I mean, there are several efforts in open source, even internally by actually open sourcing some of our key Amazon technologies like Firecracker or BottleRocket or our CDK to help advance the industry. For example, CDK itself provides some really powerful way to build and configure cloud services as well. And we also contribute to a lot of different open source projects that are existing ones, open telemetries and Linux, Java, Redis and Kubernetes, Grafana and Kafka and Robotics Operating System and Hadoop, Leucine and so forth. So, I think, I can go on and on, but even now I'd say the database and observability space say machine learning we have always started with embracing open source in a big material way. If you see, even in deep learning framework, we championed MX Linux and some of the core components and we open sourced our auto ML technology auto Glue on, and also be open sourced and collaborated with partners like Facebook Meta on Fighter showing some major components and there, and then we are open search Edge Compiler. So, I would say the number one thing is, I mean, we are actually are very, very excited to partner with broader community on problems that really mattered to the customers and actually ensure that they are able to get amazing benefit of this. >> And I see machine learning is a huge thing. If you look at how cloud group and when you had DynamoDB paper, when you wrote it, that that was the beginning of, I call the cloud surge. It was the beginning of not just being a resource versus building a data center, certainly a great alternative. Every startup did it. That's history phase one inning and a half, first half inning. Then it became a large scale. Machine learning feels like the same way now. You feel like you're seeing a lot of people using it. A lot of people are playing around with it. It's evolving. It's been around as a science, but combined with cloud scale, this is a big thing. What should people who are in the enterprise think about how should they think about machine learning? How has some of your top customers thought about machine learning as they refactor their applications? What are some of the things that you can share from your experience and journey here? >> I mean, one of the key things I'd say just to set some context on scale and numbers. More than one and a half million customers use our database analytics or ML services end-to-end. Part of which machine learning services and capabilities are easily used by more than a hundred thousand customers at a really good scale. However, I still think in Amazon, we tend to use the phrase, "It's day one in the age of internet," even though it's an, or the phrase, "Now, but it's a golden one," but I would say in the world of machine learning, yes it's day one but I also think we just woke up and we haven't even had a cup of coffee yet. That's really that early, so. And, but when you it's interesting, you've compared it to where cloud was like 10, 12 years ago. That's early days when I used to talk to engineering leaders who are running their own data center and then we talked about cloud and various disruptive technologies. I still used to get a sense about like why cloud and basic and whatnot at that time, Whereas now with machine learning though almost every CIO, CEO, all of them never asked me why machine learning. Instead, the number one question, I get is, how do I get started with it? What are the best use cases? which is great, and this is where I always tell them one of the learnings that we actually learned in Amazon. So again, a few years ago, probably seven or eight years ago, and Amazon itself realized as a company, the impact of what machine learning could do in terms of changing how we actually run our business and what it means to provide better customer experience optimize our supply chain and so far we realized that the we need to help our builders learn machine learning and the help even our business leaders understand the power of machine learning. So we did two things. One, we actually, from a bottom-up level, we built what I call as machine learning university, which is run in my team. It's literally stocked with professors and teachers who offer curriculum to builders so that they get educated on machine learning. And now from a top-down level we also, in our yearly planning process, we call it the operational planning process where we write Amazon style narratives six pages and then answer FAQ's. We asked everyone to answer one question around, like how do you plan to leverage machine learning in your business? And typically when someone says, I really don't play into our, it does not apply. It's usually it doesn't go well. So we kind of politely encourage them to do better and come back with a better answer. This kind of dynamic on top-down and bottom-up, changed the conversation and we started seeing more and more measurable growth. And these are some of the things you're starting to see more and more among our customers too. They see the business benefit, but this is where to address the talent gap. We also made machine learning university curriculum actually now open source and freely available. And we launched SageMaker Studio Lab, which is a no cost, no set up SageMaker notebook service for educating learner profiles and all the students as well. And we are excited to also announce AIMLE scholarship for underrepresented students as well. So, so much more we can do well. >> Well, congratulations on the DynamoDB paper. That's the 10 year anniversary, which is a revolutionary product, changed the game that did change the world and that a huge impact. And now as machine learning goes to the next level, the next intern out there is at school with machine learning. They're going to be writing that next paper, your advice to them real quick. >> My biggest advice is, always, I encourage all the builders to always dream big, and don't be hesitant to speak your mind as long as you have the right conviction saying you're addressing a real customer problem. So when you feel like you have an amazing solution to address a customer problem, take the time to articulate your thoughts better, and then feel free to speak up and communicate to the folks you're working with. And I'm sure any company that nurtures good talent and knows how to hire and develop the best they will be willing to listen and then you will be able to have an amazing impact in the industry. >> Swami, great to know you're CUBE alumni love our conversations from intern on the paper of DynamoDB to the technical leader at AWS and database analyst machine learning, congratulations on all your success and continue innovating on behalf of the customers and the industry. Thanks for spending the time here on theCUBE and our program, appreciate it. >> Thanks again, John. Really appreciate it. >> Okay, now let's kick off our program. That ends the keynote track here on the AWS startup showcase. Season two, episode one, enjoy the program and don't miss the closing keynote with Deepak Singh. He goes into great detail on the changing business models, all the exciting open source innovation. (gentle bright music)

from London England it's the cube covering Koopa inspire 19 Mei brought to you by Koopa hey welcome to the cube Lisa Martin on the ground in London at Koopa inspire 19 very pleased to welcome to the cube for the first time we have Dean Henry the EVP of business financing and supplier management from American Express Dean welcome to the cube thank you happy to be here so let's talk about payments we those of us in our date lives as consumers the b2c transactions are so easy these days right you can transact from your phone from your watch it's we're doing everything we're paying bills we're buying things yet in the b2b space business payments haven't had as rapid as innovation as we seen on the on the consumer side talk to me a little bit about the business-to-business payments industry from MX's perspective before we get in to what you guys are doing with Cooper yeah well first comment on on the innovation you're absolutely right the innovation that's happening and retail payments hasn't made its way to b2b payments I think that's mostly a function of you know a consumer having the ease to try something new download an app and and change the way that they transact a bit at a store but with with whomever they're paying whereas a big business has a lot of processes that drive their their business spend and the way that they manage it and systems and you know as we're here talking with Koopa today you know the the processes that they automate and that they bring are critical to you know making payments happen and because because of that there's just barriers to entry that make make b2b payments harder to mirror the speed that you see in the retail side that said there's a lot of exciting things happening you know b2b payments is a hundred and twenty seven trillion dollar market globally it's a big profit pool that a lot of players are innovating in and when you look into the landscape and you consider who's playing out there you know there's traditional big banks that have been sort of the stalwarts of Global Payments there's obviously a large and grow and growing FinTech community with new companies every day that are in the media offering new capabilities to to clients and then there's players like American Express and I think we're actually uniquely positioned in that landscape with not too many exactly like us and when you look at you know the big banks and some of the challenges that they have when I talk to our customers about fees and and you know processes that take a while or money that moves with with relative uncertainty in terms of how much is actually going to show up and the beneficiaries account based on lifting fees as money moves between banks and then you look at the FinTech community that's new innovative solutions but you're not sure that they're always going to be around you know after the next funding cycle I think we're we're trying to play an in the middle where were a great alternative to the FinTech community we're a global platform for payments we're a global platform for lending so we can really do all the things that a FinTech can do all the things that a bank can do in many instances and and do that with the brand and the certainty that is a max and so we're excited about the space and we're investing a lot of time and energy and and partnering where we need to in order to make sure our customers can transact where they want us to to help them facilitate commerce right that point of enabling a customer to transact where they want what influences are you is the American Express seeing and being able to infuse into your partnerships from the consumer side from that consumer who buy something with a click or a swipe on Amazon and wants to be able to do something similar in their business day job tell me about the influence that American Express is seeing and what that position that you just subscribe is allowing you guys to say all right this is a direction that we're gonna go and because we know yeah I need to meet you mr. customer where you are right what look I think part of it is is demographics to be perfectly honest if you look at Gen Y and Gen Z they're they're more of the decision makers in today's management they will be even more tomorrow's management and so they to your point have that expectation that their business life shouldn't be that much more complex in their personal life so so what we're trying to do is find the partners that have the best user experience and make sure our solutions work seamlessly there that's step one that's that's what we're doing here with Koopa step two is we're also trying to make sure that our capabilities on on Amex a digital real-estate works just it just as easily as our retail side of our business and we're we're doing that you know with a with the unifying principles and American Express which is you know the trust and the service and the brand that that we offer to our clients but then also the the merchant rewards so there's a rich history of of American Express providing a differentiated value proposition with the credit card rewards that that exists and we take take that capability into our our business relationships and make sure that it's a value add to those customers that want it so let's talk about what American Express is doing with Kupa what was it just announced with Koopa pay so yeah Koopa pay you know I was impressed by the stats that Rob put up there they're they're growing quickly and we want to be part of it we're a candidly following the requests of our clients who want American Express as a payment option inside the Koopa pay we offer a tremendous value prop inside of Koopa pay the data that flows with a payment the data that we're able to collect that differentiates us from our competition helps our our clients reconcile their payments eliminate the paper realize the efficiencies that that Koopas clients are excited about and so we're they're simply enabling American Express to be a payment option and my hope and I think Koopas hope is that that's step one of a partnership and and will be able to do more together to serve our collective clients so this is enabling American Express of virtual cards be available as a payment option within Kupa pay yes and what is a virtual card so virtual card is is a virtual credit card number it can be a one-time use or a multi-use okay and you know our our clients use it for several different reasons you know buyers of of goods use a virtual card in order to make the payment of a supplier easier to get more data along with the transaction so that they can reconcile a payment to a purchase order and to associated invoices the suppliers get benefit as well and in that they to get enhanced data to reconcile payment that they receive on their end there's also working capital benefit in that if if a buyer chooses to pay early an invoice we can extend financing and pay the the supplier earlier so that they have more working capital to operate their business and so so it's a real balanced value prop where both parties are realizing value is this going to enable a buyer to have benefits like increased security with the way the virtual card works yeah what increased security and so far as a virtual card isn't is encrypted the fact that you know American Express stands behind all of our card payments with our brand and our promise that differentiates from you know a traditional bank payment you know ACH and other other low value clearings that don't have those guarantees along with it and so so that is a big differentiator but but I think candidly the the biggest benefit our clients see is the enhanced data and the working capital I think that's where we're trying to enrich both sides of the transaction give more data to enable the automation that's happening in the industry and extend credit so that businesses can operate more efficiently and and and by the things that they need to buy and hire the people they need to hire is this also something that will give suppliers and buyers more visibility you talked about enhanced data well they now have more visibility over buyers like different supplier options or suppliers with different ways that they can get paid so certainly enhance visibility on on when a suppliers getting paid and relative to the invoice date and what we're trying to do is work with Koopa and work with our partners around well how do we enhance the data so that so that as you know Koopa talks about the community of suppliers that their buyers utilize how can we be part of that how do we support the buyers and making decisions the suppliers and utilizing American Express as a as a source to be a verified business that has gone through all the legal legal checks that are required in commerce and bringing both of those capabilities to to do a transaction on the Koopa Network one of the stats that Rob mentioned this morning and love stats I really geeked out over them I don't know why you say there's five million plus suppliers on the Koopa platform is that an advantage that American Express sees to help extend the footprint of your virtual cards absolutely I what I'm candidly more excited about is the millions and millions of suppliers that are on the American Express network and that's an asset that I see personally as something that we can work with with Koopa and other partners to bring you know the businesses that are already verified that are on our network that we personally talk to every you know every year and bring those verified profiles to the commerce networks like Koopa so that it's easier to transact on Koopa if you have an American Express card got it and then last question for you is if we look at this partnership what was announced today this is launching in the UK and Australia first and then you'll roll it up more globally can you tell me a little bit about why those two regions yeah one that's going to be available for customers to use so so the honest answer is we wanted to be fast to market and quick and quick out to our customer base the UK and Australia are two very important geographies for us so we're launching first in those places by the end of the year and then looking at rolling out in the US and early 2020 and then from their expanding alongside excellent well Dean thank you for joining me on the cube this afternoon sharing what's new with Amex and Cooper we appreciate your time thank you so much really happy to be here excellent for Dean Henry I'm Lisa Martin you're watching the cube from Cooper inspire London 19 thanks for watching [Laughter]

>> Live from Las Vegas, it's theCUBE covering Dell Technologies World 2019 brought to you by Dell Technologies and its ecosystem partners. >> Welcome back to Las Vegas. Lisa Martin with Stu Miniman. We are on day one of theCUBE's coverage of Dell Technologies World 2019. We've got two sets, lots of great guests, lots of great conversations already. We're pleased to welcome to theCUBE for the first time Mike Apigian, Senior Director of Education Services at Dell Technologies. Mike, welcome to theCUBE. >> Thank you, thanks for having me. >> Our pleasure. So here we are talking about digital transformation. We've been talking about it for a long time. >> Yes. >> I love how last year's Dell Technologies World was make it real, it being digital transformation, IT, work force transformation, security. This year it's about real transformation. We talked a lot about the technologies. What are some of the other things though that companies need to be thinking about as enablers of this transformation? >> Sure, great question and obviously the technology is a huge part of it, right? But of course, myself being from Dell Technologies Education Services, a big focus on the people. So that is what we see as an additional critical focus because at the end of the day, digital transformation is big. It's really big and technology alone isn't going to suffice, right? It's not going to be just that. So focus on the people and you know we hear it time and again from our customers, from research in the market that you know, one of the top three actually barriers from customers and organizations driving adoption and that success in digital transformation comes down to having the right skillsets in place. >> Yeah so Mike, I'm glad we have you on. We just had your Chief Customer Officer Karen Quintos on. >> Yeah. >> And she was talking a little bit about the skills gap. So we know how many people we're going to need to have and you know, half of the programs we're going to need is going to require them retraining of you know, my work force there, so. >> Absolutely. >> We've talked to years with what used to be EMC and is now Dell Education Services. >> Sure. >> From storage certification to converge certification to cloud certification. So what's the latest and greatest? What is the kind of go-to skillset that people need and the ones that people are calling up and saying oh my gosh, if I could learn this, it's going to really catapult my career? >> Yeah so the Dell Technologies now, Dell Technologies proven professional program has been in place for years. A lot of industry-recognized certifications to your point, a lot focused on storage, data protection, product-related and over the past 12 months to 18 months, we've actually got a lot of expansion beyond that into more areas of transformation and those areas where we've expanded beyond just products have been tied back right to that skills gap that we're seeing in customers and what they're challenged with that they drive digital transformation. So some examples being more of a focus on converged infrastructure, hybrid cloud. We have some associate level certifications we recently brought to market there. Multicloud, that's a big focus for us. Obviously some of the discussion and announcements this morning focused around multicloud and they talked about cloud chaos, right? So we have some expert level certification in place focused on that. We also have a focus around security and specifically designing infrastructure with that security-first mindset and then finally the other most recent transformational type of certification is a master level. So think of a career pinnacle level certification that's focused on transformational architecture. >> Yeah Mike, just to follow up on that, one of the things I hear in multicloud is there's certain technologies that might allow us to move, but one of the biggest challenges is skillset because if I learn and I understand how to configure it and how to manage it and how to do it here and if I move somewhere else, even if it's 70% the same, oh my god, that's not awesome. Can you just, I wonder if you can step back and give us you know, what you see out there and what works today and where do we need to go as an industry as a whole to try to help users to live in this multicloud world that we're already in but struggling with? >> Yeah I mean there's a ton of proficiency in the silos, right, in managing specific infrastructure service storage network now also around converged infrastructure as well as cloud deployments, but to your point, in a multicloud environment, there are different providers, both private and public, different technologies, and it can get complex fairly quick, right? So having the skillsets to kind of take a step back and look at that holistically and understand about workload placements, you know, there's knowledge and skillsets that require to make some of those determinations. We obviously have a lot of services capabilities that help provide that, but there's a level of obviously proficiency that our customers want and need in house as well. So a lot of it is building that knowledge and understanding the decision points and the criteria for the different providers as well as workload placement and movement across that multicloud environment. >> Essentially-- >> Very different than skill sets in the past. >> Sorry about that, very excited. I'm curious about if we talk about talent and retention with respect to some of the guys and gals who've been around for a while, Michael mentioned on stage this morning that later this week is Dell's 35th anniversary in business and as we look at all the technology transformations and multicloud world that we live and Stu mentioned, what are some of the benefits for, I don't want to say an older population, but say the veterans of technology? Why, what are some of the things that Dell Technologies Education Services will deliver to say the more seasoned individual to stay relevant and be able to adapt as quickly as technology is so that they're competitive for jobs themselves? >> Yeah, yeah, great, great question and I mean it's the pace of change is so fast and it's impacting everyone, everyone from recent college graduates, right, getting right into the field that we're in in technology as well as to your point, seasoned veterans who've been around for a while and that's where a lot of the difficult transformation is taking place, right? 'cause it's the roles of the past and today, the skillsets of today, like those roles and skills that have gotten us to today are very different than what's needed to get us to tomorrow and that's where a lot of our technical training, our curricula as well as our industry certifications come into play and helping build that knowledge, the required and the skills and the certifications to validate those capabilities for the next generation workforce. So it's really for the right out of school and maybe new to the field as well as evolving throughout their career. >> All right so Mike, we know that your team's doing things throughout the year, talking to your customers, but you've got 15,000 people here at Dell Tech World. I've seen the hands-on lab, I know there's always certification. So give us from your team, you know, some of the big focus, some of the activities and some of the takeaways that you want people to have from your team. >> You know, the one big thing that I would give a plug for is our proved and professional center. So right downstairs in Casanova 501, we have 57 certifications available and we have hundreds and hundreds of customers and partners that will be taking certification exams and then achieving certification this week, all right? We have a promotional offer. So every attempt at, first attempt at every exam is free just for this week so I encourage everyone who's here to check it out. In addition to taking those certifications in preparation for that, we have 29 different preparation sessions that we're running. So right downstairs, two rooms next door where we're rotating through on topics that are specific to our latest and greatest product lines, PowerMax, PowerEdge MX, in addition to that cloud-focused data science certification prep sessions, multi-cloud expert. There's a whole array of prep sessions that are helping our customers and partners prepare for taking those certifications. >> AI machine learning? >> There are some intersections with that as well, certainly, as part of our data science curriculum and certification exams. >> And where are customers in terms of discussing with you, say maybe at last year's Dell technologies World, like these are some of the certifications and the trainings that we really need. Talk about that sort of bi-directional symbiosis where customers are, I'm assuming, help you the teams identify, develop and then deliver this spot-on training. >> Yeah that's a great question. So actually every year here at Dell Technologies World, we have a customer advisory council and that should last two years, came out loud and clear last year was more of a focus in some of the areas that they're challenged with from a transformation perspective. Security came into play in a big way, different aspects of cloud and multicloud, enterprise architecture, a lot of our focus related to Pivotal and a lot of the offerings there, application development. So all of that feedback and discussion that we have into customers actually feeds into our prioritization and road mapping and it has a big impact on the technical training and the certifications that we bring to market. So we're going to be our customers throughout today, also tomorrow and that'll be additional input to where we go in the future. >> All right, Mike, what other feedback are you hearing from customers? We hear in the keynotes some of these broad topics and you talk about AI and IoT and edge computing and how much of that funnel back and are they looking for help on that now or you know, how do they start getting themselves ready for some of these massive waves that are coming? >> Yeah that's definitely part of the themes that we hear and the feedback that we get from customers and what's really relevant to them and that ties into their skills transformation as well. As you said, IoT, AIML, data engineer. That's a more recent role that we're focusing on and you'll see a bunch coming out from Dell Technologies Ed Services on that in the not too distant future so a lot of that. Those themes are, we hear the exact same, same customer base and those are areas that we're addressing in our roadmap and as we bring new technical training offerings to market. >> So listening to your customers is key. As Stu mentioned, we were talking to Karen Quintos a little bit earlier that that's essential for pretty much any role, but you're listening, you're taking that into account, you're designing it and delivering for that. A lot of benefits we can talk about for the individuals going through the training, right, in terms of upscaling and job retention, but from your customers' perspective, do you have a favorite example of a customer who's really been able to transform their company because they've made this investment and ensuring that their talent has the latest and greatest education? >> Yeah, and actually, we've seen, we've done a bunch of research in market and what we see time and again is a really really strong correlation between those organizations that are focusing on and investing in their people and the skills development, a correlation between that and the progress and success that they're having with their transformation initiatives, right, and one area where we've been engaging a lot deeper with customers as of just recent and beginning to do a lot more of is we call it an organizational learning program. So we obviously offer technical training and certifications, but this is more of a consultative engagement with our customers more at the organization level and very consultative and we work closely with them to understand their digital strategy, their plans, and as part of that, drive a very prescriptive assessment of what's going on in their environment from a people and skills perspective. So really understanding their current state and where they want to go, where they need to be, and based upon the findings of that assessment, we work closely with them to develop a defined documented strategy and plan. In this case, it's a learning plan. It's a continuous learning plan for that organization over a series of quarters to work against and drive and really capture, gain those skills and knowledge that's required to help move them forward. >> Yeah, Mike, I love that. It reminds me of the joke in your space is what if we give them new skills and they leave? And of course the alternative is what if we don't give them new skills and they stay? >> Exactly. >> So last thing I wanted to ask is talk a little bit about internal. There's a lot of change going on. You've been from the EMC to Dell for quite a few years. >> Oh yes. >> I won't say how many just to protect the innocent, but one of the things, I mean I spent 10 years at EMC and the training was something that helped me a lot in my career. Talk a little bit about, you know, what's changed and how you help the internal teams and all the different groups stay up on the latest and greatest areas. >> Absolutely so in Education Services to your point, we support our employees, technical employees, around the globe, our partners and customers. So huge focus on enabling those employees and if you think about it, right, they are, they're the front lines, they're the folks that are with our customers and they need to be as up to speed, if not more up to speed in these areas of technology. So we have a massive undertaking to enable our services audiences, pre-sale systems engineers, our consultants around the globe to ensure that they are up to speed and quite knowledgeable on the latest and greatest technologies and really how those come to life within our customer environments. >> It seems like maybe Education Services is a catalyst for this internal cultural transformation that we're seeing from Dell Technologies. >> It absolutely is. There's transformation everywhere. It's internal, it's external and at the end of the day, kind of back to where we started, right? It comes down to the people. It's our customers and us as a company, our most important asset and at the end of the day, you know, the people need the right skills to be successful and to go digital. >> Great stuff, Mike. Thank you so much for joining Stu and me on theCUBE this afternoon and sharing all that you're doing to help transform Dell Education Services for your internal folks and your customers alike. We appreciate your time. >> Thanks for having me. >> Our pleasure. For Stu Miniman, I'm Lisa Martin. You're watching us live from Las Vegas. Day one of theCUBE's coverage of Dell Technologies World 2019. Thanks for watching. (upbeat music)

(digital music) >> Live, from Orlando, Florida it's theCUBE. Covering Microsoft Ignite. Brought to you by Cohesity, and theCUBE's ecosystem partners. >> Welcome back everyone to theCUBE's live coverage of Microsoft Ignite here at the Orange County Civic Center in Orlando. I'm your host, Rebecca Knight along with my co-host Stu Miniman. We're joined by Bev Crair. She is the vice president data center group product development and quality at Lenovo. Thanks so much for coming on theCUBE. >> Thanks Rebecca, thanks Stu. >> So, Lenovo is a longstanding partner of Microsoft. Why don't you just sent the scene for our viewers, and talk a little bit about the history of the partnership and where you are today. >> So, Lenovo and Microsoft have had a partnership of about 25 years, which is a long time in this industry. And we work really closely together on both innovation, but also making sure that anything that Microsoft is building runs best on Lenovo. >> Great, and what about, here at this conference, what are you hearing, what are you seeing in terms of this partnership? >> We have actually six things that we're really talking about here at the conference, which is a lot if you think about it. But the first is the announcement of our ThinkAgile MX, which is that integrated WSSD system. It's pre-certified, you just buy it as itself. There's four or five different sizes of it, if you will. The second one is our Azure Stack, but also our Azure services. So we're now doing both on prem Azure Stack and Azure services, which is really about customer choice. Because a lot of data center customers are really struggling with how do I build a hybrid cloud infrastructure, and what do I do with that. The third thing that we're doing, oh my gosh, I'm not going to remember them all. The third thing that we're doing is our SQL Server performance. We continue to be the best in performance for all of our SQL Server efforts. Our two-socket systems are best performing. Our four-socket systems are best performing, and so are eight-socket systems are best performing. In addition to that, we have, when we're proud to work with Microsoft on the launch of Windows Server 2019. Again, that's part of that 25 year partnership. It's just something you got to do. And we're really proud of that. The other thing that we've announced here is what we're calling the buy back program. And a lot of companies have buy back programs where you can actually buy back equipment, and you buy back your competitors equipment in order to build your stuff up, but the one thing that's kind of different about what Lenovo's doing is something I call Zillow for systems. So, you actually can go online and put in the systems that you have or the equipment that you have and we give you an automatic, instant quote back. Nobody else is actually doing that. So, it's kind of a Zillowish system where you can see what's my stuff really worth. >> I want to click in a little bit. So, I know the partnership for a long time. I think about PCs, you think about servers, obviously. Lenovo has the gear, Microsoft has the OS and various pieces that go on there. When I look at solutions like WSSD and Azure Stack, Microsoft has a number of partners, maybe help us understand what that partnership means, how Lenovo differentiates from some of the other players out there. >> So, that is one of the things I forgot. One of the things that we've announced today, and that we showed today, and actually Jeff Wosley talked about it in his talk earlier today, is an integration of Microsoft's Windows Admin Center for WSSD, and Lenovo's Xclarity system management system. So, via a single pane of glass from your Windows Admin Center, you can actually not just look at Windows Admin in the Window's infrastructure, but you can actually dig down and really understand what's actually happening with the hardware itself that WSSD is running on. And that's part of that really close partnership and relationship that we have. >> Can you talk a little bit about the approach to the partnership just because we had a Microsoft Executive on here earlier today, and he said that "our partnerships, we have this, we're able to have "a collaborative and collegial partnership "with our competitors." So, it's sort of part of their DNA." How does Lenovo think about when it partners and how it partners with a competitor? >> Well, but Microsoft isn't actually a competitor of ours. Right? And this is the thing I think that Lenovo, as a company, really is focusing on offering to our customers is choice. Right? We have a co-located lab up in Seattle with Microsoft. We have had for years. We do innovation summits with them, we look at where the technology is going and what is it that we can do together in order to make that more effective for our shared customers and how they deliver in the long run. And so it really is a very strong collaboration. We don't build operating systems. We don't build all of the SQL Server. We don't build the Azure Stack, and the Cloud, and all the rest of that. So, the partnership with Lenovo, Microsoft gets to take advantage of all of our supply chain goodness, all of our services goodness, as well as all the platform stuff that we do as well. >> Now, if you look, HCI is one of the things that we've been talking a little bit more about here. Obviously, it makes sense for Lenovo to partner here, but Lenovo also has a number of other solutions. How do you look at it? What are you hearing from customers when it comes to that kind of solution and how Microsoft-- >> It really is about choice. Right, it really is about choice. Customers have different kinds of problems in their environments, and they're seeking partners to help them solve those problems in their environments. And that, and those choices are actually really critical for them. So, when you're working with somebody like Lenovo, where we also offer Vmware, we also offer some of the other solutions that are out there in the market, that, you work with a partner like Lenovo, where we have all of the services and the infrastructure to back that up, plus the long standing relationships that we have with our partners, enables us to offer that kind of choice that allows our end customers to solve their customer's problems. And that's really the core piece that we're looking at. >> Yeah, Microsoft, of course, partners with a lot of companies. I heard in some of the technical key notes, I heard that get mentioned quite a bit. Of course, Rebecca and I were with your team at Lenovo Transform in New York City recently. And maybe for our viewers that might not have caught that show, give us the update, what you're hearing from people about the big partnership -- >> So, we announced a partnership with network compliance, NetApp, at our Transform show last week, I guess it must have been. We've been working on it for awhile, so, just the fact that the announcement happened was really cool. And it's kind of a three-part partnership. The first part is that Lenovo will be branding NetApp's a couple of the sets of systems that NetApp has. And it allows us to fill out our storage infrastructure. Last year, when we launched our largest portfolio of servers, we launched eight all in a single day, and the rest of the Purley platforms followed from my team in the next quarter. This year, with NetApp, we actually launched the largest storage portfolio in the market. And so, this partnership actually allows us to do that very, very collaboratively. Then the second part of the relationship is joint venture that we're starting with NetApp in China. Given the depth of work that Lenovo does in China, it allows NetApp to actually build their market, and their infrastructure. And I think, some of the customers in China are actually really looking for the kinds of solutions that NetApp has available. And then the third is moving forward to build innovative solutions together. Taking the innovation and the 25 years worth of innovation that my team has done over the years, and all of the work we do in performance, all the number one on client satisfaction, all the number one on reliability for the fifth year in a row, and bringing that into our NetApp alliance. >> One of the themes at this conference, and also frankly at Lenovo Transform, is about company culture and about this idea of the importance of collaboration and creativity and teamwork, and inclusivity. Can you describe a little bit for us how you think the Lenovo culture is similar to the Microsoft one that Satya Nadella is a proponent of and also how it's different? >> How is is similar and how is it different? That's a really interesting question. The thing that I have found about the Lenovo culture that I think surprised me the most, one year in, is how committed Lenovo is to really understanding how people think and bringing that in to how we build effective solutions together. It is by far the most diverse organization that I've worked in. In lots of lots of ways, but if you look at the senior leadership level, right? You would expect it, given that the company is actually headquartered in Beijing and the United States, and we're on the Hong Kong stock exchange, you would expect it to be Chinese. But it's not. The leadership team is actually incredibly diverse. Way more diverse than I expected. But even on my team, and further down in the organization, a lot of our engineers have spent multiple years overseas. They've raised their kids overseas. They've gone to school overseas. And so the have a very inclusive perspective on how do we solve problems. And they also understand that the way in which we solve problems, isn't necessarily the best way. So, in our conversations with Microsoft and the culture that we create with them together, it becomes very collaborative. 'Cause we go back to what's the customer problem we're really trying to solve. How are we actually helping our customers in their intelligent transformation? How do we become their trusted partner? And how do we actually help solve humanity's greatest challenges? And that's a together statement, right? With Microsoft and just kind of peeling back the onion on what are the real problems that we need to get to to solve together. >> You mentioned how diverse a company Lenovo is, and that's actually at a time where the technology industry is not known for its diversity. In fact, it's really known for its bro culture. It's the dearth of female leaders. I'm wondering if you could just give me your thoughts on how technology, sort of the state of affairs today is it as bad as the newspaper headlines make it out to be? And (Rebecca and Bev laugh) what we need to do to move forward. >> So, I think in part, there's two answers to that. One of them is that the participants in technology are changing. So, if you look around the room and you watch who's here, what you're seeing is that there's a whole generation of new people coming in who've always had technology at their fingertips. And so they think differently and assume differently about what that technology is supposed to do for them. And so just age diversity starts to come into play. But also the people that buy our stuff, right? 65 to 75% of commercial electronics are bought by women. That's a stunning figure when you really think about it 'cause it's very different from the people that actually create or have in the past created that technology. So when you start to see who's buying and why they're buying, you actually have to start to understand that they're buying for very different reasons than perhaps you were creating the technology for. So, an example of this is the new Hub 500 or the Hub 700. Have you seen this? So, it's a link connected system that sits on the table and you push a button and you're automatically connected with everybody that's going to be in your Lync meeting or everybody that's going to be in your Skype meeting. And we had to do a fair amount of work to really understand how people were going to interact with the system or not interact with the system. And even colors like red and green, and the fact that they mean different things in different cultures, and how are we going to display those colors, right? But that's where the diversity of participation in solving a problem really comes into play. >> Great. Well Bev, it was a pleasure having you on the show. It was really fun talking to you. >> Thank you very much. I really appreciate it. >> I'm Rebecca Knight for Stu Miniman. We will have more from Microsoft Ignite in just a little bit. (upbeat digital music)

live from New York it's the cube covering AWS summit New York 2018 hot GUI Amazon Web Services and its ecosystem partners hello and welcome back here live cube coverage in New York City for AWS Amazon Web Services summit 2018 I'm John Fourier with Jeff Rick here at the cube our next guest is dr. Matt wood general manager of artificial intelligence with Amazon Web Services keep alumnae been so busy for the past year and been on the cubanía thanks for coming back appreciate you spending the time so promotions keep on going on you got now general manager of the AI group AI operations ai automation machine learning offices a lot of big category of new things developing and a you guys have really taken AI and machine learning to a whole new level it's one of the key value propositions that you guys now have for not just a large enterprise but down to startups and developers so you know congratulations and what's the update oh well the update is this morning in the keynote I was lucky enough to introduce some new capabilities across our platform when it comes to machine learning our mission is that we want to be able to take machine learning and make it available to all developers we joke internally that we just want to we want to make machine learning boring we wanted to make it vanilla it's just it's another tool in the tool chest of any developer and any any data data scientist and we've done that this idea of taking technology that is traditionally only within reached a very very small number of well-funded organizations and making it as broadly distributed as possible we've done that pretty successfully with compute storage and databases and analytics and data warehousing and we want to do the exact same thing for the machine learning and to do that we have to kind of build an entirely new stack and we think of that stack in in three different tiers the bottom tier really for academics and researchers and data scientists we provide a wide range of frameworks open source programming libraries the developers and data scientists use to build neural networks and intelligence they're things like tend to flow and Apache mx9 and by torch and they're really they're very technical you can build you know arbitrarily sophisticated says most she open source to write mostly open source that's right we contribute a lot of our work back to MX net but we also contribute to buy torch and to tend to flow and there's big healthy open source projects growing up around you know all these popular frameworks plus more like chaos and gluon and horror boredom so that's a very very it's a key area for for researchers and academics the next level up we have machine learning platforms this is for developers and data scientists who have data they see in the clout although they want to move to the cloud quickly but they want to be able to use for modeling they want to be able to use it to build custom machine learning models and so here we try and remove as much of the undifferentiated heavy lifting associated with doing that as possible and this is really where sage maker fits in Cersei's maker allows developers to quickly fill train optimize and host their machine learning models and then at the top tier we have a set of AI services which are for application developers that don't want to get into the weeds they just want to get up and running really really quickly and so today we announced four new services really across those their middle tier in that top tier so for Sage maker we're very pleased to introduce a new streaming data protocol which allows you to take data straight from s3 and pump it straight into your algorithm and straight onto the computer infrastructure and what that means is you no longer have to copy data from s3 onto your computer infrastructure in order to be able to start training you just take away that step and just stream it right on there and it's an approach that we use inside sage maker for a lot of our built-in algorithms and it significantly increases the the speed of the algorithm and significantly of course decreases the cost of running the training because you pay by the second so any second you can save off it's a coffin for the customer and they also it helps the machine learn more that's right yeah you can put more data through it absolutely so you're no longer constrained by the amount of disk space you're not even constrained by the amount of memory on the instance you can just pump terabyte after terabyte after terabyte and we actually had another thing like talked about in the keynote this morning a new customer of ours snap who are routinely training on over 100 terabytes of image data using sage maker so you know the ability to be able to pump in lots of data is one of the keys to building successful machine learning applications so we brought that capability to everybody that's using tensorflow now you can just have your tensor flow model bring it to Sage maker do a little bit of wiring click a button and you were just start streaming your data to your tents upload what's the impact of the developer time speed I think it is it is the ability to be able to pump more data it is the decrease in time it takes to start the training but most importantly it decreases the training time all up so you'll see between a 10 and 25 percent decrease in training time some ways you can train more models or you can train more models per in the same unit time or you can just decrease the cost so it's a completely different way of thinking about how to train over large amounts of data we were doing it internally and now we're making it available for everybody through tej matrix that's the first thing the second thing that we're adding is the ability to be able to batch process and stage make them so stage maker used to be great at real-time predictions but there's a lot of use cases where you don't want to just make a one-off prediction you want to predict hundreds or thousands or even millions of things all at once so let's say you've got all of your sales information at the end of the month you want to use that to make a forecast for the next month you don't need to do that in real-time you need to do it once and then place the order and so we added batch transforms to Sage maker so you can pull in all of that data large amounts of data batch process it within a fully automated environment and then spin down the infrastructure and you're done it's a very very simple API anyone that uses a lambda function it's can take advantage of this again just dramatically decreasing the overhead and making it so much easier for everybody to take advantage of machine load and then at the top layer we had new capabilities for our AI services so we announced 12 new language pairs for our translation service and we announced new transcription so capability which allows us to take multi-channel audio such as might be recorded here but more commonly on contact centers just like you have a left channel on the right channel for stereo context centers often record the agent and the customer on the same track and today you can now pass that through our transcribed service long-form speech will split it up into the channels or automatically transcribe it will analyze all the timestamps and create just a single script and from there you can see what was being talked about you can check the topics automatically using comprehend or you can check the compliance did the agents say the words that they have to say for compliance reasons at some point during the conversation that's a material new capability for what's the top surface is being used obviously comprehend transcribe and barri of others you guys have put a lot of stuff out there all kinds of stuff what's the top sellers top use usage as a proxy for uptake you know I think I think we see a ton of we see a ton of adoption across all of these areas but where a lot of the momentum is growing right now is sage maker so if you look at a formula one they just chose Formula One racing they just chose AWS and sage maker as their machine learning platform the National Football League Major League Baseball today announcer they're you know re offering their relationship and their strategic partnership with AWS cream machine learning so all of these groups are using the data which just streams out of these these races all these games yeah and that can be the video or it can be the telemetry of the cars or the telemetry of the players and they're pumping that through Sage maker to drive more engaging experiences for their viewers so guys ok streaming this data is key this is a stage maker quickly this can do video yeah just get it all in all of it well you know we'd love data I would love to follow up on that so the question is is that when will sage maker overtake Aurora as the fastest growing product in history of Amazon because I predicted that reinvent that sage maker would go on err is it looking good right now I mean I sorta still on paper you guys are seeing is growing but see no eager give us an indicator well I mean I don't women breakout revenue per service but even the same excitement I'll say this the same excitement that I see Perseids maker now and the same opportunity and the same momentum it really really reminds me of AWS ten years ago it's the same sort of transformative democratizing approach to which really engages builders and I see the same level of the excitement as levels are super super high as well no super high in general reader pipe out there but I see the same level of enthusiasm and movement and the middle are building with it basically absolutely so what's this toy you have here I know we don't have a lot of time but this isn't you've got a little problem this is the world's first deep learning in April were on wireless video camera we thought it D blends we announced it and launched it at reinvent 2017 and actually hold that but they can hold it up to the camera it's a cute little device we modeled it after wall-e the Pixar movie and it is a HD video camera on the front here and in the base here we have a incredibly powerful custom piece of machine learning hardware so this can process over a billion machine learning operations per second you can take the video in real time you send it to the GPU on board and we'll just start processing the stream in real time so that's kind of interesting but the real value of this and why we designed it was we wanted to try and find a way for developers to get literally hands-on with machine learning so the way that build is a lifelong learners right they they love to learn they have an insatiable appetite for new information and new technologies and the way that they learn that is they experiment they start working and they kind of spin this flywheel where you try something out it works you fiddle with it it stops working you learn a little bit more and you want to go around around around that's been tried and tested for developers for four decades the challenge with machine learning is doing that is still very very difficult you need a label data you need to understand the algorithms it's just it's hard to do but with deep lens you can get up and running in ten minutes so it's connected back to the cloud it's good at about two stage makeup you can deploy a pre-built model down onto the device in ten minutes to do object detection we do some wacky visual effects with neural style transfer we do hot dog and no hot dog detection of course but the real value comes in that you can take any of those models tear them apart so sage maker start fiddling around with them and then immediately deploy them back down onto the camera and every developer on their desk has things that they can detect there are pens and cups and people whatever it is so they can very very quickly spin this flywheel where they're experimenting changing succeeding failing and just going round around a row that's for developers your target audience yes right okay and what are some of the things that have come out of it have you seen any cool yes evolutionary it has been incredibly gratifying and really humbling to see developers that have no machine learning experience take this out of the box and build some really wonderful projects one in really good example is exercise detection so you know when you're doing a workout they build a model which detects the exerciser there and then detects the reps of the weights that you're lifting now we saw skeletal mapping so you could map a person in 3d space using a simple camera we saw security features where you could put this on your door and then it would send you a text message if it didn't recognize who was in front of the door we saw one which was amazing which would read books aloud to kids so you would hold up the book and they would detect the text extract the text send the text to paly and then speak aloud for the kids so there's games as educational tools as little security gizmos one group even trained a dog detection model which detected individual species plug this into an enormous power pack and took it to the local dog park so they could test it out so it's all of this from from a cold start with know machine learning experience you having fun yes absolutely one of the great things about machine learning is you don't just get to work in one area you get to work in you get to work in Formula One and sports and you get to work in healthcare and you get to work in retail and and develop a tool in CTO is gonna love this chief toy officers chief toy officers I love it so I got to ask you so what's new in your world GM of AI audition intelligence what does that mean just quickly explain it for our our audience is that all the software I mean what specifically are you overseeing what's your purview within the realm of AWS yeah that's that's a totally fair question so my purview is I run the products for deep learning machine learning and artificial intelligence really across the AWS machine learning team so I get I have a lot of fingers in a lot of pies I get involved in the new products we're gonna go build out I get involved in helping grow usage of existing products I get it to do a lot of invention it spent a ton of time with customers but overall work with the rest of the team on setting the technical and pronto strategy for machine learning at AWS when what's your top priorities this year adoption uptake new product introductions and you guys don't stop it well we do sync we don't need to keep on introducing more and more things any high ground that you want to take what's what's the vision I didn't the vision is to is genuinely to continue to make it as easy as possible for developers to use Ruggiero my icon overstate the importance or the challenge so we're not at the point where you can just pull down some Python code and figure it out we're not even we don't have a JVM for machine learning where there's no there's no developer tools or debuggers there's very few visualizers so it's still very hard if you kind of think of it in computing terms we're still working in assembly language and you're seen learning so there's this wealth of opportunity ahead of us and the responsibility that I feel very strongly is to be able to continually in crew on the staff to continually bring new capabilities to mortar but well cloud has been disrupting IT operations AI ops with a calling in Silicon Valley and the venture circuit Auto ml as a term has been kicked around Auto automatic machine learning you got to train the machines with something data seems to be it strikes me about this compared to storage or compared to compute or compared to some of the core Amazon foundational products those are just better ways to do something they already existed this is not a better way to do something that are exists this is a way to get the democratization at the start of the process of the application of machine learning and artificial intelligence to a plethora of applications in these cases that is fundamentally yeah different in it just a step up in terms of totally agree the power to the hands of the people it's something which is very far as an area which is very fast moving and very fast growing but what's funny is it totally builds on top of the cloud and you really can't do machine learning in any meaningful production way unless you have a way that is cheap and easy to collect large amounts of data in a way which allows you to pull down high-performance computation at any scale that you need it and so through the cloud we've actually laid the foundations for machine learning going forwards and other things too coming oh yes that's a search as you guys announced the cloud highlights the power yet that it brings to these new capabilities solutely yeah and we get to build on them at AWS and at Amazon just like our customers do so osage make the runs on ec2 we wouldn't we won't be able to do sage maker without ec2 and you know in the fullness of time we see that you know the usage of machine learning could be as big if not bigger than the whole of the rest of AWS combined that's our aspiration dr. Matt would I wish we had more time to Chad loved shopping with you I'd love to do a whole nother segment on what you're doing with customers I know you guys are great customer focus as Andy always mentions when on the cube you guys listen to customers want to hear that maybe a reinvent will circle back sounds good congratulations on your success great to see you he showed it thanks off dr. Matt would here in the cube was dreaming all this data out to the Amazon Cloud is whether they be hosts all of our stuff of course it's the cube bringing you live action here in New York City for cube coverage of AWS summit 2018 in Manhattan we'll be back with more after this short break

(upbeat music) >> Announcer: Live, from Las Vegas, it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> Welcome back to theCUBE, day three in Las Vegas at Dell Technologies World. I am Lisa Martin with John Troyer. We have been here for three days, there's over 14,000 people here, 30,000 plus more engaging with video content livestream on demand. We're excited to welcome back to theCUBE, not just back to theCUBE, but back today for a second appearance, he's so in demand, Ravi Pendekanti, Senior Vice President, Servers and Systems Product Management and Marketing at Dell EMC, welcome back! >> Thank you, Lisa, great to be here. >> So, you have so much energy for day three, but so much excitement, lots of announcements. >> Ravi: Yes. >> The theme of this event, "Make It Real," is provocative. We've heard a lot of >> Yes it is. >> Lisa: Interpretations about what that means for different customers and different industries who are looking to take advantage of emerging technologies: AI, machine learning, deep learning, IoT, to make digital transformation real. What's going on in the world of AI and machine learning? >> Lisa, a lot. Now, having said that, I don't think there's a single industry in the, in any part of the world today that we talk to that's not interested in AI, machine learning, for that matter, deep learning. Why is that so? Just think about the fact that each one of us today is probably creating and generating two and a half times more data than a year ago. It's huge. I mean, when I started out, people used to think megabytes is huge, then it went to terabytes, petabytes, exabytes, and now I think very soon we're going to talk about zettabytes, right? I'll leave it to you guys to talk about the number of zeros, but setting that aside, data by itself again, the second they went, so of much of data is being created, data in my view has absolutely no value until you create information out of it. >> Lisa: Absolutely. >> And that's where I think companies are becoming more aware of the fact that you need to start getting some information out of it, wherein starts the whole engine, first of all about going about collecting all of the data. And we have all kinds of data. We have got structured data, unstructured data, and now it's important that we actually get all of the disparate data into a format that can now be executed upon. So that's first and foremost what customers are trying to figure out. And then from there comes all the elements that the data analytics part, and then you can go into the machine learning and deep learning. So that's the way people are looking at it, and you made an interesting comment, Lisa, which is making it real. This is where people are looking at things beyond the buzzwords, right? It's sufficed to say AI is not a new term. I recall as a kid, we used to talk about AI. But now is when businesses are depending on it to ensure they have the competitive edge. >> So, Ravi, you know the pendulum swings, right, and ten years ago, >> It does. >> John: Software is eating the world and the cloud is coming, and at one point it looked like a future of undifferentiated x86 compute somewhere. It turns out, hardware actually matters, and as our application and data needs have grown, the hardware matters. >> It does. >> John: And so, part of your portfolio is the PowerEdge set of PowerEdge servers. I mean, how are you approaching that of making the needs of this new generation of software, this massive data parallelism and throughput real? >> Great question, John. It's interesting, yes, the pendulum keeps swinging, right? And the beauty is, as... It's my only hope that, as the pendulum swings, we're actually learning, too, and we're not making the same thing, the same mistakes. Thankfully, we are not. Now, when people talk about cloud, guess what? To your point, it has to run on something, software has to run on something. So, obviously the hardware. Now, to keep up with the changing tide and the needs, some of the recent things we have done, as an example, with our R840 launch yesterday, you know, NVMe is the talk of the town, too, talking about some of the new technologies. And customers want us to go out and provide a better way and a faster way for them to get access to the data in a much more faster way closer to the compute, so that's where the NVMe drives come in. We have got 24 NVMe drives on R840 today, which is two times more than the closest competitor. More into the R940xa; xa stands for extreme acceleration. Again, we have never had an xa product, this is the first of its kind that we are bringing out, and the beauty of this is, we wanted to makes sure there is a one to one relationship between the GPU and the CPU. So, for every CPU you have a GPU. It's a one to one relationship. If you look at the R940 we introduced earlier, it had, just to give the context to your question, John, it had, it could support four CPUs but only two GPUs. So if we are, think of it this way, if we are doubling the number of GPUs, and that's not it, we are actually enabling our customers to add up to eight FPGAs if they want. Nobody else does it, and this goes back to, I think Lisa, I think when we start to talk about FPGAs, too, and therein comes the issue, wherein customers don't have the flexibility in most of the cases in a lot of products out there. We have decided that flexibility has to be given to our customers because the changing, workload's changing, technologies, and even most customers today, they go in thinking that that's all they need, but sooner or later they realize that they need more than what they planned for. So our goal is to ensure that there is enough of scalability and headroom to enable that to happen. So that's how we, as PowerEdge Team, are building servers today, which actually enables us to provide our customers with an ability to have a headroom and at the same time give them the flexibility to change, whether it is NVMe drives or any kind of SSD drive, GPUs, FPGAs, so there's all the flexibility built into it along with ease of management. >> A couple things that you mention that I think are really important is that data doesn't have any value unless you're able to extract insights from it. >> Ravi: Yeah. >> Companies that are transforming digitally well are able to combine and recombine the same data using it as catalysts across many different applications within a business, that agility is key, that speed is key. >> Ravi: Yes. >> How are you, what are some of the things that you're hearing from the 14,000 plus people that I'm sure are all lined up to want to talk to you this week about what, for example, PowerEdge is going to enable them to do? You talked about flexibility, you talked about speed, what are some of the real applications that you're hearing feedback-wise from some of these new features that you've announced? >> Oh, great, so I think, again, an excellent question in terms of how the customers are reacting to and what are we doing. So now, talking about AI machine learning, think of it this way, right, the permutations and combinations are way too many. And the reason I say that is, keeping the hardware aside, when you talk about frameworks that are available today for most of the AI or machine learnings applications, people talk about TensorFlow, people talk about Caffe2, people talk about CNTK, I mean, there's a whole plethora of frameworks. And then there are different neural network methodologies, right? You hear of DNN, deep neural network, right? And then you hear of things called RNN, there is something called CNN, my point is, there is so many permutations and combinations in the mix that what our customers have come back and told us, going back to where we were earlier, talking about the flexibility in the architecture that we are providing, where we provide seamless scalability on any of the vectors, that they actually love that we are giving them the flexibility because when there are so many software options with frameworks and every other methodology, we wanted to make sure that we also provided the flexibility and the scalability. And our scalability comes in, whether it is the I/O connectability, we talked about PowerEdge MX that's going to be coming up soon that was a preview, but that's where we talked about something called the kinetic infrastructure, which essentially enables our customers to go out and run multiple workloads on the same modular infrastructure. Never happened before, right? Or, you know, the seamless way we do it now is a lot better than anything else. Likewise, to go back into the R940xa. We have the ability to go out and support hard drives, SSDs, FPGAs, GPUs, so the feedback has been that our customers are really excited about the fact that we're giving them the flexibility and agility to go out and match to the needs of their different workloads and the different options they have. So, they love it. >> Ravi, I was talking to some of your team yesterday and I was really impressed as they talked about the product development cycle. They said that we start with the customers and we start with applications. >> Ravi: Yes. >> And then we figure out what technologies are now appropriate to build in what combinations. They don't just start from let's throw the newest thing in because we can. As you talk to CIOs and enterprise architects, it used to be if you just do a server refresh and just check the box and push the button, now you've got to look at cloud readiness and what I keep on prim and what I keep off prim and what's going to fit my applications. What are you hearing from customers and how are you trying to educate them on how to approach their next refresh, well, I think even refresh is probably a bad frame, their next set of applications that they're going to have to build in this digital transformation? >> You know, John, this is actually no different, I mean let's step aside from the compute world for a minute, let's pick up an automobile industry, right? If you get into the automobile industry, a family might say they need a sedan, or a family of five or six with young kids might say they want a minivan, right? And maybe now the kids are grown up or you're still in your 20s or 30s and some of the folks would love to have a sports car, like the McLaren that up >> I'll take that one! >> Ravi: On the stage with Jeff; I know, I would love that too, right? (Lisa laughing) So my point is, when people are trying to decide on what is it they really want to buy, they actually know what they're looking for, right? A family of four doesn't go in and say, "I need a two-seat car," for example. It's a similar thing here, as people start looking at the workload first, they come in and start looking at mapping, "Hey, this is the kind of workload we have now," now let's start looking at what infrastructure can we provide behind it? You know, even if you look at our, something that we have announced in the past, but the 740xd. So, we have a 740 version and 740xd version; xd there stands for extreme density. So, if customers want a 2-CPU box, a 2-U box, a server, but they want more storage, then they have xd version. But they decide that storage is not really crucial, they just need the compute, then we provide the 740 on its own, the R740. So my point being that, accentuating the point you raised, is it's always nice to look at the application, look at what its needs are, whether it's memory, whether it's storage, whether it's the GPUs, the CPUs, and then look at how it transposes itself over the next few years because you really don't want to acquire something and then really decide later that you've run out of room. It's like buying a home and then you know you're going to have your kids or you're going to raise a family, you don't probably want to start off with a single bedroom and you know you're going to have a family in a couple of years. My point again being that, that is where the planning becomes absolutely important. So we are planning, and the planning phase is crucial because once you have that right, you now can rest at ease for the next few years and as we do that, one of the other fundamental design principles of PowerEdge is that we want to really support the platforms for multiple generations. Case in point, when we came out with our PowerEdge m1000e, we said that we will guarantee support for three generations of processors. We actually are up to the fifth generation as we speak right now. And our customers love it, because nobody really wants to go ahead and buy more servers every few years if they can go back with their investment they have made and ensure that there is room to grow. So, to your point, absolutely the right spot to start is start looking at the workload, start looking, once you have pegged it, then start looking at really at growing and what your needs could be. And then start connecting the dots and I think you would be coming out with the better outcome for the long run. >> We had the opportunity to talk, John and I just an hour or two ago, with the CIO, with Bask Iyer, and one of the things that was interesting is we talked to him about how the role of the CIO is changing to be really part of corporate strategy, >> Ravi: Yeah. >> And business strategy; as you talk with customers about building this infrastructure, to set them up for the flexibility and the agility that they need, allowing them to make the right decisions for what they need but also scale it over time, how much are you seeing the boots on the street that you're talking to have to sell this up the stack as this is fundamental to transforming IT, which is fundamental to transforming our business into a digital business? >> Very, very true. By the way, Bask is a great friend and a collaborator, we certainly look to, as the saying goes, "Eat your own dog food." So we work with Bask and team very closely because, as a CIO for a large corporation himself, we learn a lot; there's nothing better than trying to walk in the shoes of our customers so, going back to the comment you made, Lisa, is most of the, by the way, most of the customers today, the CIOs, who are now becoming not cost centers, they're becoming profit centers >> Profit centers, >> Lisa: That's what Michael Dell said on Monday. >> Absolutely, and he's absolutely right, Michael is absolutely right because most of the organizations we speak to today on an average, I would think that the number of CIOs we talk to has probably been dialed up, because we see the kind of questions that they're being asked of, right, to the point that we're making earlier, they're not looking at making point purchases for something that will satisfy them for the next 12 months or 18 months. They're looking at the next horizon, they're looking at a long-term strategy, and then they're looking back at the ROI. So what is it I'm able to go back in and provide to my customers internally, whether it is in terms of the number of users or the performance, whatever the SLAs, the Service Level Agreements may be internally, that's what they're looking for. So, towards that end, the whole concept of ROI and TCO, the total cost of ownership and the return of investment nowadays is probably a much bigger talking point that we need to support with the right factoids. I think that's becoming crucial, and the CIOs are getting more engaged in the discussions than ever in the past, and so it's just not about feeds and speeds, which I guess anyone can look at spec sheets, not as exciting, but at things beyond that that I think are getting more crucial. >> Well, Bask said, "Drinking your own champagne, eating your own dog food." I like champagne and dogs, although I'll go with both. >> I, why not. I just... >> We've got the therapy dogs next door. >> Therapy dogs, exactly. >> Lisa: Isn't that fantastic? >> They're great, they're great. >> So, last question in the last 30 seconds or so, biggest event, 14,000 as I said, expected live over the last three days, and tens of thousands more engaging, any one thing really stand out to you at this inaugural Dell Technologies World? >> The most important thing that has stuck for me is that human progress is indeed possible through technology. And this is the best showcase possible, and when you can enable human progress, which cuts across boundaries of nationality, and boundaries of any other kind, I think we are in the winning streak. >> Well said. Ravi, thanks so much for coming back today, couple times in hanging out with us on theCUBE and sharing some of the insights that you're seeing and that you're enabling your customers to achieve. >> Thank you, Lisa; thank you, John, it's been awesome. It's always wonderful being with you guys, so thank you. >> We want to thank you for watching theCUBE again. Lisa Martin with John Troyer live, day three of Dell Technologies World. Stick around, we'll be right back after a short break. (upbeat music)

>> Announcer: Live from Las Vegas it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> And welcome back. We are live here in Las Vegas. We're in the Sands right now of day two of Dell Technologies World 2018. I'm John Walls along with Stu Miniman, and it's a pleasure now to welcome Ashley Gorakhpurwalla, who is the President and GM of Server and Infrastructure Systems at Dell EMC. Ashley, good afternoon to you. >> Thank you, great pronunciation of my last name. >> Well, thank you very much, I've worked-- >> Not an easy thing to do. >> I worked on that, how about that? Stu and I were just talking briefly with you. What a cool exhibit floor, right? >> It really is. >> There's just a lot of-- What have you seen out there that's kind of caught your eye so far? >> Well, we brought in a lot of customers this time to show their outcomes. So I'm a car guy, so you know I went straight for the McLaren. >> How 'about that McLaren out there, right? Yeah. >> My son would love the F1 setup with the gaming, virtual reality. Top Golf is a great VxRail customer. We have GoalControl. Try to beat the AI and see if you can score a goal. I mean, there's some very cool demos back there. >> And then overall, just I'm curious about your thoughts about the show then because that's a part of it. >> That's a part of it. >> A lot of client relations you're doing here, business relations. >> Sure. We're only about half way through, but so far very, very positive energy I get. I don't know if you caught or already talked to Michael after the keynote, but certainly. >> Stu did today. Certainly, Michael was on fire at the keynote, and I really, really enjoyed the discussion with Dr. Chip Plater about, and Jeffrey Wright about, how technology connects to helping people. A lot of times engineers, stuck in a lab, looking at R&D, trying to figure out a problem, lose sight of what they're doing. Great opportunity for the team to see that and kind of expand and understand where their technology is going, what it's doing for the world, what the impact is that they're having. >> So, Ashley, your team's been real busy leading up to this, seeing some of the new products in the announcement. Before we get into this though, your role expanded a little bit since the last time we talked about, talked to Tom Burns yesterday as there was the group formerly known as VCE that turned into CPSG, It was split into some pieces, and HCI is now under your domain. >> That's right. So in addition to our server businesses, which are kind of the mainstream PowerEdge business, our Extreme Scale business, our OEM business. We had a reorganization to really kind of unlock the potential that we have in a great product set, a product set before my organization was already number one. It's a position of strength. What we're trying to do is accelerate from that. So if you think about the HCI marketplace, I think you have to be in the server business to win in the HCI business. I don't envy anyone trying to do this from a position of weakness or trying to adopt other people's technology. Our supply chain, our reach, our global services and support, and then the underlying ability to invest in the server technology and beyond and differentiate, innovate on top of that is what it's going to take to win, and maybe not tomorrow, but in the future as HCI takes off. We wanted to really accelerate that by shortening the decision-making loop, making it one mission for the team, and so that came in. In addition, maybe a quick call-out to the storage and data protection platform engineering team who also came into my group to, again, really put our best hardware and platform of systems engineers together from servers and data protection storage and kind of create a powerhouse of R&D. >> Yeah, Ashley, it's actually, it's not surprising to us, From our research side at Wikibon, we actually called it server SAN because it was really taking the functionality and what customers wanted as a business outcome from the SAN and was pulling it closer to the server. But at its core, it's really about software. One of the things that has struck me in the last few years, comparing this to EMC worlds in the past and now Dell, is what I used to see at Dell World, which was Dell is a platform that lots of things live on. So there's lots of storage partners that live on side of Dell. There's HCI partners. Of course, you've got a broad portfolio all from the Dell families, and then OEMs and other partners that fit there. 'Cause you're a team, it makes sense that HCI comes in there because you've got that platform at the server, >> Right. >> and it grows from there. >> If you circle back to just the Dell Legacy world perhaps, much more platform oriented, infrastructure at our heart, bringing that value with prop to our customers. And I've said it before, I think if you give any segment or capability time, I think a standard kind of open infrastructure hardware platform wins. It may not be a server, but it's going to look something like a server going forward. And the specialization and the value move into the IP stack and into the software. So you better be a company that can do the scale of a standards-based platform. You better have the IP, the specialized stacks, as we do in our VM-ware stacks, in our IP stacks or in data protection, storage, networking. You can see where Michael's kind of putting those two together. It's not a tomorrow thing but five, 10 years from now. We've seen it in the carrier space. We've seen it in storage. Everywhere you go, the commoditization curve takes us to standards, infrastructure, and IP in the software. >> You made an interesting point there, saying it might not necessarily be a server. Give us kind of, if you could step back for a second, the state of compute. >> Sure. >> There's compute in the cloud, there's compute at the edge, there's (chuckles) compute all over the place. A few years ago, it was like, ah, it's all going white box and undifferentiated. And in the public cloud, I say, there's probably more skews and compute in the public cloud than if I went to Dell and picked that up there. Whether that's a good or bad thing, you could probably have some insight on. But give us your view on kind of the state of compute in the industry today. >> Sure. So if I think back 10 years when we started our business with the hyper-scale, building those infrastructures as a service, multi-tenant public clouds, there really wasn't any other choice. You either did it in a legacy mode with your IT, maybe slightly modernizing, but you're still probably siloed. You probably had storage admins and networking admins, compute admins, or you went cloud. And it was such a different experience. Since then, what customers have said consistently is, why am I having to make that choice? I either go to this rent version, which is very expensive as I scale up, or I own it or I have to own it and it's different. So multi-cloud, hybrid cloud, private cloud, however you want to instantiate it. And something like hyper converged infrastructure just didn't exist. They didn't have a choice. Now, with a pushing of a few buttons, you can scale up your infrastructure, perhaps on prem or in a hosted environment. That is fairly seamless with that, and now you have that portability. >> Yeah, and I'm sorry, Ashley. I wasn't trying to poke at the cloud piece. Compute at edge use cases is a little bit different than traditional-- >> Yep, absolutely. >> Servers, what's happening with the Blade market. Definitely need to, I know we need to talk about the new PowerEdges. But there's the MX we're going to cover, too, but was just kind of, if there are form factors of servers. >> You bring up a good point. It's maybe emerging, so there's probably a little bit more hype than there is reality behind it. But there are going to be billions of sensors, trillions of sensors or things that create data outside of data center environments. That's where all the data's going to be produced, and that's where decisions are going to be made. Today, the theory is, it has to go back somewhere, although I don't think any of us are getting in an autonomous car if it has to talk back to a data center and decide what to do. >> Right. >> So there's already examples of what I would call edge compute. But what if your data center has to live at a base of a cell tower at the end of a 30 mile dirt road where someone only visits 45 days apart, and they're not an IT individual? How do you extend that infrastructure, that management domain, that security domain? How do you bring it all the way out there? How do you ruggedize it? Well, you're probably going to start with a company that's been doing fresh air cooling with 13, 14 billion server hours now, operating in fresh air environments. We understand how to bring that environment the way we've been working on that remote management, lights out management style, our security. I'll give you another emerging trend that's going to come out of that. Just at the time where we're going to extend our environments out of the safety of the data center, we're also going to go back to a stateful compute. With persistent memory, nonvolatile memory, storage class memories, and security paradigms are already shifting. We're getting ahead of that with our customers of what if it wasn't just the hard drive you had to protect but almost everything in that edge device. So the form factors will change, the connectivity will change, but what we know is, you'll likely gather as much data as you can. You'll throw some of it away 'cause it won't be useful. Right now, there's a sensor telling this building that these lights are on. Until they go off, it's not useful data. But in a car, it's very useful data. Some of that data will go back, it'll get trained because humans won't be able to take in all this data. You'll need a machine. You can't write the algorithm ahead of time. You have to learn something. Back goes that IP into the edge, and then decisions will be made at that stage. >> Before we head off, we've talked about some new products. You've alluded a little bit. So you've had a launch this week. Just run through that, if you would, real quick. >> Ashley: Sure, sure, we had a few things. >> It's nice to have a new baby to talk about. >> Sure, it's pretty exciting. And it really does stem from what we just talked about. So if I start on the PowerEdge side, if you have a strategy that is to help your customers with that digital transformation from cloud to data center and core all the way to edge, you can start to see why we're launching certain products and why they have certain technologies in them and innovations. So starting with the 940 XA, extreme acceleration, might have to rename it if you watched the keynote. Jeff called it extreme performance. He is the boss, so I think it's XP now. (Stu and John laughing) No, we'll keep it at extreme acceleration for now. That really is about large datasets training very quickly in database environments. So you want host to GPGPU to be a one-to-one ratio. You want large datasets to be local, so you need massive storage, 32 drives for instance. And you need the capability to, again, make sure it brings the tenets of security, manageability, the ecosystem with it. So, very excited about that one. I think there's some use cases we're just not even ready for. We've already have the technology today to put eight FPGAs in that system, direct connect. And there's very few workloads or even talent in the customer set to be able to enable that, but you got to get there first with the technology to allow that innovation to happen. And we want to stoke that. Then on the R840, this really was about, once you get the data in, you're going to have to make decisions. You need, still, that processing power. Maybe you don't need 20,000 cores in the box like a 940 XA. Maybe you need a little bit less, but you do need a massive storage localized in VME direct connect. That's more direct connect that any server, I think, period in the industry. And it's really about streaming those analytics, making those realtime choices. So it really fits into the strategy that we're undertaking. >> All right, Ashley, last thing I wanted to cover. It's a bit of preview that you showed at the show. The PowerEdge MX. >> Yep. >> Modular infrastructure, no midplane, should be able to upgrade it a lot more. So are we beyond where Blade Servers have gone? Do you consider this to fit into, some call it composable infrastructure. How would you position this kind of-- >> Well, I don't have some positioning yet. It's just a sneak peek. But let me tell you how we thing about it. Is it a Blade Server or not? I'm not sure the question is something we've considered yet. It's a form factor that we think for the future is really necessary, which is, we want to get to a stage, and we're putting our research into a stage of a journey where we want to get to the point where you can utilize the resources that you bring into your environment, whether they be your environment or someone else's. Today, so much is stranded connected to a CPU, and it's just the architecture that we have today. Whether it's memory, source class memory, persistent memory, GPGPUs, heterogeneous compute FPGAs, ASICs, memory semantics, IO semantics, have to leave the box. Then we can get you things like pooled up resources that can be utilized unbound, put together, then composed, if you want to use your word, or really just aligned around a workload then retired and put back in. APIs and software, we're starting to build that out. It's starting to emerge from certain management orchestration layers we have today. But we're going to need that fabric. And so, as you know, we're showing actually here today a Gen-Z demo where we're starting to build that fabric that has the latency, almost a memory-like latencies from load to store and usage, all the way out to it has the memory semantics that go all the way through from CPU all the way out to memory so that, all sudden, the node no longer traps and stands the resources. How do you do that? You better have an architecture that treats everything in the box, not just the compute part, as a first class citizen for power, for thermals, for management. Second thing, if you have a midplane, you have a point of failure, but you also are not upgradeable to these fabrics that are coming and these capabilities that are on the horizon, some of which are not even in Silicon or in a lab just yet. So when you build infrastructure, let me call it infrastructure for a second, people want it as an investment. That's the part we've talked about. There's a lot more to come, so the team's excited to get it out there. I tried to hold them back a little bit, but we cheated a little bit a showed it. >> A little demo goes a long way. Ashley, thanks for being with us. Thanks for telling your story, we appreciate the time. Look forward to seeing you down the road. >> Appreciate it, thanks, guys. >> You bet. Back with more. We are live here in Las Vegas at Dell Technologies World 2018. (electronic musical flourish)