(gentle music) >> Hey, everyone. Welcome back to New York City. Lisa Martin and John Furrier here with theCUBE, covering AWS Summit NYC. This is a series of summits this year. There's about 15 of them globally. We are excited to be here with a couple of guests. We have an alumni back with us. Couple of guests from Caylent, Stephen Garden joins us, the Executive Chairman, and Valerie Henderson, Chief Revenue Officer. Guys, welcome to the program. >> Thank you. >> Thank you. Thank you for having us. >> Great to have you, welcome back. >> Appreciate it, from 2016. >> 2016, it's been a minute. >> Yep. >> But that was before Caylent. Talk to us about Caylent, what do you guys do? What do you deliver? How are you affiliated with AWS? >> Sure, so we were founded in 2015, initially as a container management product. So our roots are very deeply centered around Cloud native. We've since evolved and become a Cloud native consultancy. We're all in with AWS. We were actually just awarded AWS Premier Partner a couple of weeks ago, so we're pretty pumped about that, but we're about 250 people now, across North and South America. And our goal is really to work with customers that are looking to innovate and evolve and use AWS as a catalyst to build new products for their business. >> As a catalyst, I like that. Valerie, talk about the customer. Obviously so much tumbled in the last couple of years. Still going through it. >> Yeah, of course. >> How have customer conversations evolved and changed in the last couple of years, from your perspective? >> Yeah, I think from my perspective it is such a unique time and it's a time that is constantly changing. And I think change breeds opportunity, and I feel like customers see that, and they're leaning in. They want the opportunity to create new revenue streams, do more, more efficiently, and I think that's the key. And the questions are really asking, how can we take our data, and turn it into something that we can monetize? How can we be smarter with what we have? And I think it's an incredible time to be in the space that we're in. Every conversation I have is really forward thinking, and about the business. And I've been in this space for a while, and that was not always that case. And I think now people are shifting that IT shop to IP shop, and that's so key, from my perspective. >> Interesting, interesting shift there. Every company has to be a data company these days, to be competitive, the last couple of years it was, how did we survive? Pivot, pivot, pivot. But to be a data company, means you have to be able to extract the value and insights from that data and act on it, to your point, develop new products, new revenue streams, new opportunities. How do you enable companies, and maybe this is a question that you can both answer, to truly become data companies? >> The whole model from a service's perspective is not a do-for model, it is a do-with model. And any time we go into a customer, it's like, where are they on the curve? From monolith application, to microservices, where do they sit today? And I think when you dig in, you assess, you deeply understand where they are, you can get them to where they want to be, and build a plan. And the way our model works is, we're doing it with them, and what that means is we're enabling them, documentation, we're supporting them, that if we're not there, they're going to be able to carry it forward and continue to do more. So, that's so so important. I'd love Stephen's take on it. >> Yeah, I think the other trend that we're seeing in data more recently is that customers need to share their information with other partners, collaborate. And AWS is just the perfect platform to be able to do that, enable that sharing. And you're seeing even businesses like Snowflake build a data Cloud on top of AWS. So, I think that's a new angle that we're seeing which is really bringing together way more innovation- >> What about that data clean-room trend that's going on, Snowflake's doing a lot of that. But some of them have a little lock in spec there, versus being open, security, privacy, governance, what's the balance between open sharing and the requirements you need to be secure and compliant? >> Yeah, I think very simplistically, the information that you are using to deliver your product and service to customers generally safer, more public and available, the information that's confidential to your business behind the scenes, obviously, you use the right protocols to lock it out. But it is a very hot topic in today's world, especially with Web3 and people seeking to get their information back, so... >> So you mentioned you guys around since 2015, if you go back in time, it seems like yesterday, but Cloud time, it's like two generations ago. Why is data now more relevant? Is it because the technology's gotten better and easier, or more maturization of the client's understanding, or being full with data, having a data problem and hence an opportunity? Or is it open source has evolved? Or all three, what's your reaction to that? Why is it exploding now when it's been around for a while? >> It keeps exponentially growing, right? The more and more data. There was a stat four or five years ago about, hey, we're taking more photographs in a single year now than all of mankind, leading up to that date, but I think just the sheer quantities and the way people are managing it now, and being able to actually capture information points of everything across their entire business, just presents a much bigger opportunity to be able to take and form decisions of the back of that. >> So do you see the customers having more data full problems, that they're having more data? So that's... And in that one >> 100%. >> Of the consequences of not leveraging it? >> Yeah, it's what to do. Yeah, absolutely, and if you think about when you wake up in the morning if you ask Alexa what the weather is, and like, you're creating data, in every engagement with the world. So I think it's this explosion of it, but then it exists, and what do you do, and having a strategy. I still think one of the biggest gaps is people, and talent, and expertise to do the work, frankly. Which is, the hypothesis of Caylent existing. >> Yeah, I think a data concept and application, because what's the weather to Alexa, is an application of what's the weather, it's a request, but it's actually the data's built into the app. >> It's built in. >> So data as code is a new trend. >> Yes, yeah, yeah, and I think it's funny to answer the question. There's more data points surrounding how to leverage your data, and I'm like, it's crazy, I think you're really seeing that working- >> We have an old data warehouse, we can't get the weather data, although it's there somewhere. But that's the problem. Getting the data, in the applications, this is not... Wasn't around 10 years ago. No one was talking like that. Now it's more standard. That sounds like DevOps to me, a DevOps problem. >> Yeah, moving from the monolithic to the microservice is wild, and just the way that people are building applications today. The users, their customers are demanding more from the service, and AWS is able to deliver that. >> What are some of your customers doing with you guys, can you give some examples and scope the scale of your relationship with the customers, vis-a-vis AWS and the Cloud, how they're using you guys and the Cloud. >> Yeah, yeah, for sure, a customer of ours, Allergen, which is an incredible organization, really had a large effort to modernize. And they actually have a data lab within their company called Allergen Data Labs, and they leveraged us to truly just modernize this containerization effort. How they can do more with less, and that serverless experience. So, I think from my perspective what we're seeing is also a need to be thoughtful about DevOps retooling and tooling because talent wants to work with the best toolset, the hottest stuff on the street, and again, to keep talent is key, in any organization's success. >> Valerie, how does Caylent help with that from a talent perspective? Obviously there's talent shortage, we're also still in the great resignation. >> Oh my gosh. >> How do you help organizations bridge the gap so that they can glean insights from data and be competitive and win? >> Yeah, we actually just published a case study with Novus which was bought by SEI, which is a huge financial firm. Where they said, "Listen, it's human nature to say I have a gap, and I need to fill it, I'm going to hire somebody." That's human nature to say, okay, this is what we're going to do. But the reality is, I think companies are starting to see the advantage of using a partner and say, okay, I could hire one person or I could bring in a partner who's going to have a team of five, works incrementally for a period of time, does with, helps coach my team up, document all of that, and I think that they're seeing value from that. And ultimately, it's not that we don't want them to eventually hire. When they do hire, we want that person to come in and have the best experience. >> And sometimes the people aren't even available, right? >> Correct, yeah. >> So you have a combination of managed services, a plethora of managed services that are also involved with the customers. So, it's that integration, scale, and partnering and sharing. You mentioned sharing data earlier, how do you guys view that integration piece, 'cause if you have a modern architecture, you got to have that decomposed, decoupled but integrated approach. >> Yeah, we really believe that the whole world of project services and managed services is coming together as one. So we have a single delivery model which we're really passionate about. And we look at it as an embedded team within our customers, embedded DevOps to support them, basically on anything that could be from a modernizing a new application through to addressing a more traditional Cloud architecture framework that's in place. But yeah, the trick to it is, as Val said earlier is the do with approach, not just do for, right? I think customers need to learn about the Cloud. They need to understand the technology that they're using. They want to have that understanding. And we found a way of fitting in our services to help them accelerate that part. >> So Valerie, I got to ask you the question. So, in sports you talk about the modern era of baseball or whatever, we're in the modern era of Cloud, going next generation. We call it Super Cloud, a concept that Dave and I put out at re:Invent. If someone asks you, what does the modern era look like? As you look at your customer base and the data you guys have, how would you describe this modern era? What is it made up of? Is it outcomes versus solutions? Is it technology that's decentralized? How do you talk about it? What is the modern era, if you were- >> Not to oversimplify it, but I'm going to, the idea that somebody could come into work and all they have to think about is business outcomes and the data points that they need to achieve said business outcomes. I'm the biggest fan of measure what matters, I think it is an incredibly powerful methodology. And I think anybody who thinks about running business, they know that it's a scale. The amount of companies that are in that place is very small right now. So I think modern era is really that running an IT company to an IP company. >> So Stephen, if you unpack that, what's under the covers to make that happen? Automation, machines, what's your assessment of that outcome, which by the way was well said. Beautiful, beautiful comment. What makes that happen? >> I think it is around automation. It is around do once and then apply many times. That is key. Obviously it's a fundamental principle of the Cloud, is that consistency in that repeatability. So when you can simplify services down to a point, click, deploy, I think you're in a much better position to be able to move quickly and then not have to worry about anything under the hood and just focus, like Val said, on the business outcomes. >> That's more creative. They're focusing on the problems, to not do the rock fetches and the heavy lifting that's not differentiated. >> I find that what gives people energy generates opportunity. And I think when people hit those roadblocks of, these things don't work together. There's all these interdependencies. It's really challenging. So I love what's happening. I think there's never been a better time to be in this business. >> Not a dull moment, That's for darn sure. >> Not a dull moment. >> Valerie, talk about outcomes. You mentioned a couple of customers that you're working with, some case studies. It is all about outcomes these days. That's the conversations that we have with the entire ecosystem is all about business outcomes. What are some of those key transformative business outcomes that Caylent is helping customers to achieve? >> Yeah, to me one thing that is key is, anytime I'm meeting with a customer, I want to understand who their customers are. I'm like, who is your customer? And how can we create a better experience for that customer. Whether it's their end users or their external customers. And I think that is a huge element. What we're seeing is that sassification of, how do I make it easier for my customers to procure and engage with my platform? And a lot of what we're doing right now is helping clients with that. And it's not a flip of a switch, it's not a click of a button, it's complicated. But that is what we are here to help, help simplify, help create that understanding of what's possible. >> How do you guys talk to your customers, take a minute to give a plug for the company. What are you looking for? What's the stats? How many employees you guys hiring, and what's the pitch to customers? >> Yeah, so I think every organization is on their journey to the Cloud now. It's gotten to that point where if you're not working with a public Cloud provider, you're part of a very, very small group. We like to say that we'll meet customers where they are, and help evolve them as a business, help evolve their teams. And that's what we mean when we say do with, so it's a pretty broad spectrum. We're big in healthcare. We're big in FinTech. We've worked with a lot of startup customers. We have about 250 customers today, 250 employees. And we're scaling rapidly. We've grown that from about 50 employees a year ago. >> Oh, wow. >> Yes, when I started, we were just around 60 people and we're at 260 today. >> And why are people working with you? What are you guys, solving a problem? Are you enabling them? What's the pitch? >> Without a doubt, I love that. Being in sales my whole career, somebody asking me for a pitch is my favorite. >> Okay, let's go. >> Yeah, yeah, the true value prop of what we do is all of the above. We enable, we help customers do more faster, but again, we do not want customers to walk away from an engagement with us saying, oh no, we don't know what to do. We want them to feel empowered. I still think the biggest gap from everything being in that IP business outcome is people. And for us, we're so passionate about that, and building a company that really truly believes that. And that's part of who we are as a company and our value system. >> And the digital transformation, ultimately what they're going through, you get them there faster. They get the outcomes and they're operational. >> Absolutely, and also to be clear, when a customer has a great experience working with you, they want to tell other people about the experience. And for us, like the referrals that we get, the partnership with Amazon is so key. >> What are some reactions after you go through an engagement? We've been riffing on this concept of Super Cloud where you're starting to see people build on top of, not the AWSs, but their partners that work with them. And so the customers are getting their own Cloud experience at scale. What are some of the comments you hear from your successful customers? What are some anecdotal feedback? >> Yeah, yeah. >> I'm so glad we did this because now I'm selling more, I'm doing this, what are some of the things that they're thinking? >> Yeah, yeah, I think ultimately the consistent theme that we get is, "I'm so glad that I didn't let fear hold me back from engaging a partner," because a lack of control scares a lot of customers. It does. And I think customers that are willing to say, "Okay, I'm going to have a little faith, trust in the process." They thank us. They do, and we've seen that across the board. I think that crossing that chasm is not to be underestimated without a doubt. >> Great story, congratulations. >> Oh, thank you. >> Well, there's nothing more powerful and potent than the voice of the customer. >> Without a doubt. And really you have to listen. >> Yes, yes, definitely. Stephen, Valerie, thank you so much for joining Dave and me on the program today, talking about Caylent, what you guys are doing for customers with AWS, empowering, enabling, collaboration. I love it, thank you. >> Yeah, thank you both. >> All right, our pleasure. For John Furrier, I'm Lisa Martin. You're watching theCUBE live in New York City, we are at AWSO in NYC, John and I will be right back with our next guest. (gentle music)

>>we'll go back to the cubes. Coverage of the age of US Executive Summit at Davis. Reinvent made possible by Accenture My name is Dave Volunteer. We're gonna talk about the arm nation advantage, embraced the future of productivity, improve speed quality and customer experience through artificial intelligence. And we herewith Bhaskar goes, Who's the chief strategy Officer X censure in Rajendra RP Prasad is the senior managing director in Global Automation. The Accenture guys walk into the Cube. Get to seal. >>Thank you. >>Hey, congratulations on the new book. I know it's like giving birth, but it's a mini version. If the well, the automation advantage embraced a future of productivity, improve speed, quality and customer experience to artificial intelligence. What inspired you to write this book? Can you tell us a little bit more about it and how businesses are going to be able to take advantage of the information that's in there? Maybe you could start, >>so I think you know, if we say that what inspired as primarily the two things really style, you know, over inspired have to start this project in first of all is the technology change step change in the technology. Second is the mile maturity of the buyer maturity of the market when it's a little more, you know, when I talk about the technology change, automation is nothing new in the industry. In the starting from the Industrial Revolution, always, industry adopted the automation. But last few years would happen. That there is a significant change in the technology in terms of not of new technologies are coming together like cloud data, artificial intelligence, machine learning and they are gearing match you, and that created a huge opportunity in the industry. So that is number one second if fighting the maturity of the buyer. So buyers are always buying automation, adopting the automation. So when I talked to this different by a different industrial wire, suddenly we realise they're not asking about workings automation, how that will help. But primarily they're talking about how they can scaling. They have all have done the pilot, the prototype, how they can take the full advantage in their enterprise through scheme and talking to few client few of our clients, and he realised that it's best to write this boat and film all our clients to take advantage of this new technologies to skill up their business. If I give a little more than inside that one, exactly we are trying to do in this boat primarily, we dealt with three things. One is the individual automation which deals with the human efficiency. Second is the industrial automation who visited a group efficiency. And third is the intelligent automation. We deal city business, official efficiency while business value. So we believe that this is what will really change their business and help our client help the automation. It users to really make clear an impact in their business. >>Yeah, And so you talked about that? The maturity of the customer. And and I like the way you should describe that spectrum ending with intelligent automation. So the point is you not just paving the cow path, if you will, automating processes that maybe were invented decades ago. You're really trying to rethink the best approach. And that's where you going to get the most business value, our peace In thinking about the maturity, I think the a pre pandemic people were maybe a little reluctant s Bhaskar was saying maybe needed some education. But But how? If things change me, obviously the penned Emmick has had a huge impact. It's accelerated things, but but what's changed in the business environment? In terms of the need to implement automation? R. P >>thank you Well, that is an excellent question. As even through the pandemic, most of the enterprises accelerated what I call as the digital transformation, technology transformation and the war all time that it takes to do. The transformation is compressed in our most land prices. Now do compress transformation. The core of it is innovation and innovation, led technology and technology based solutions. To drive this transformation automation. Artificial intelligence becomes hot of what we do while we are implementing this accelerators. Innovation enablers within the enterprises, most of the enterprises prior to the pandemic we're looking automation and I as a solution for cost efficiency. Saving cost in DePina deriving capacity efficiency does if they do the transformation when we press the fast forward but draw the transformation journey liberating automation. What happens is most of the enterprises which the focus from cost efficiency to speed to market application availability and system resiliency at the core. When I speaking to most of the sea woes Corrine Wall in the tech transformation they have now embrace automation and air as a Conan able to bribe this journeys towards, you know, growth, innovation, lead application, availability and transformation and sustainability of the applications through the are A book addresses all of these aspects, including the most important element of which is compute storeys and the enablement that it can accomplish through cloud transformation, cloud computing services and how I I and Michelle learning take log technologies can in a benefit from transformation to the block. In addition, we also heard person talk about automation in the cloud zero automation taking journey towards the cloud on automation Once you're in the clouds, water the philosophy and principles he should be following to drive the motivation. We also provide holy holistic approach to dry automation by focusing process technology that includes talent and change management and also addressing automation culture for the organisations in the way they work as they go forward. >>You mentioned a couple things computing, storage and when we look at our surveys, guys is it is interesting to see em, especially since the pandemic, four items have popped up where all the spending momentum is cloud province reasons scale and in resource and, you know, be able the report to remotely containers because a lot of people have work loads on Prem that they just can automatically move in the company, want to do development in the cloud and maybe connect to some of those on from work clothes. R P A. Which is underscores automation in, of course, and R. P. You mentioned a computing storage and, of course, the other pieces. Data's We have always data, but so my question is, how has the cloud and eight of us specifically influenced changes in automation? In a >>brilliant question and brilliant point, I say no winner. I talked to my clients. One of the things that I always says, Yeah, I I is nothing but y for the data that is the of the data. So that date of place underlying a very critical part of applying intelligence, artificial intelligence and I in the organization's right as the organisation move along their automation journey. Like you said, promoting process automation to contain a realisation to establishing data, building the data cubes and managing the massive data leveraging cloud and how Yebda please can help in a significant way to help the data stratification Dana Enablement data analysis and not data clustering classification All aspects of the what we need to do within the between the data space that helps for the Lord scale automation effort, the cloud and and ablest place a significant role to help accelerate and enable the data part. Once you do that, building mission learning models on the top of it liberating containers clusters develops techniques to drive, you know the principles on the top of it is very makes it easier to drive that on foster enablement advancement through cloud technologists. Alternatively, using automation itself to come enable the cloud transformation data transformation data migration aspects to manage the complexity, speed and scale is very important. The book stresses the very importance of fuelling the motion of the entire organisation to agility, embracing new development methods like automation in the cloud develops Davis a cop's and the importance of oral cloud adoptions that bills the foundational elements of, you know, making sure you're automation and air capabilities are established in a way that it is scalable and sustainable within the organisations as they move forward, >>Right? Thank you for that r p vast crime want to come back to this notion of maturity and and just quite automation. So Andy Jossy made the phrase undifferentiated, heavy lifting popular. But that was largely last decade. Apply to it. And now we're talking about deeper business integration. And so you know, automation certainly is solves the problem of Okay, I can take Monday and cast like provisioning storage in compute and automate that great. But what is some of the business problems, that deeper business integration that we're solving through things? And I want to use the phrase they used earlier intelligent automation? What is that? Can you give an example? >>Let's a very good question as we said, that the automation is a journey, you know, if we talk to any blind, so everybody wants to use data and artificial intelligence to transform their business, so that is very simple. But the point is that you cannot reach their anti unless you follow the steps. So in our book, we have explained that the process that means you know, we defined in a five steps. We said that everybody has to follow the foundation, which is primarily tools driven optimise, which is process drivel. An official see improvement, which is primarily are driven. Then comes predictive capability, the organisation, which is data driven, and then intelligence, which is primarily artificial intelligence driven. Now, when I talked about the use of artificial intelligence and this new intelligent in the business, what the what I mean is basically improved decision making in every level in the organisation and give the example. We have given multiple example in this, both in a very simple example, if I take suppose, a financial secretary organisation, they're selling wealth management product to the client, so they have a number of management product, and they have number of their number of clients a different profile. But now what is happening? This artificial intelligence is helping their agents to target the night product for the night customers. So then, at the success rate is very high. So that is a change that is a change in the way they do business. Now some of the platform companies like Amazon on Netflix. He will see that this this killed is a very native skill for them. They used the artificial intelligence try to use everywhere, but there a lot of other companies who are trying to adopt this killed today. Their fundamental problem is they do not have the right data. They do not have the capability. They do not have all the processes so that they can inject the decision making artificial intelligence capability in every decision making to empower their workforce. And that is what we have written in this book. To provide the guidance to this in this book. How they can use the better business decision improved the create, the more business value using artificial intelligence and intelligent automation. >>Interesting. Bhaskar are gonna stay with you, you know, in their book in the middle of last decade, Erik Brynjolfsson and Andy McAfee wrote the second Machine Age, and they made a point in the book that machines have always replaced humans in instead of various tasks. But for the first time ever, we're seeing machines replacing human in cognitive task that scares a lot of people so hardy you inspire employees to embrace the change that automation can bring. What what are you seeing is the best ways to do that? >>This is a very good question. The intelligent automation implementation is not, Iet Project is primarily change management. It's primarily change in the culture, the people in the organisation into embrace this change and how they will get empowered with the machine. It is not about the replacing people by machine, which has happened historically into the earlier stages of automation, which I explained. But in this intelligent automation, it is basically empowering people to do the better. Dwelled the example. That is the thing we have written in the book about about a newspaper, 100 years old newspaper in Italy. And you know, this industry has gone through multiple automation and changes black and white printing, printing to digital. Everything happened. And now what is happening? They're using artificial intelligence, so they're writers are using those technologies to write faster. So when they are writing immediately, they're getting supported with the later they're supporting with the related article they are supporting with this script, even they're supported to the heading of this article. So the question is that it is not replacing the news, you know, the content writer, but is basically empowering them so that they can produce the better quality of product they can, better writing in a faster time. So is very different approach and that is why is, um, needs a change management and it's a cultural change. >>Garden R P What's it for me? Why should we read the automation advantage? Maybe you can talk about some of the key takeaways and, you know, maybe the best places to start on an automation journey. >>Very will cut the fastest MP, Newer automation journey and Claude Adoption Journey is to start simple and start right if you know what's have free one of the process, Guru says, If you don't know where you are on a map, a map won't help you, so to start right, a company needs to know where they are on a map today, identify the right focus areas, create a clear roadmap and then move forward with the structured approach for successful our option. The other important element is if you automate an inefficient process, we are going to make your inefficiency run more efficiently. So it is very important to baseline, and then I established the baseline and know very or on the journey map. This is one of the key teams we discuss in the Automation Advantis book, with principles and tips and real world examples on how to approach each of these stages. We also stress the importance of building the right architecture is for intelligent automation, cloud enablement, security at the core of automation and the platform centric approach. Leading enterprises can fade out adopters and Iraq, whether they are in the early stages of the automation, journey or surrender advanced stage the formation journey. They can look at the automation advantage book and build and take the best practises and and what is provided as a practical tips within the book to drive there. Automation journey. This also includes importance of having right partners in the cloud space, like a loveliest who can accelerate automation, journey and making sure accompanies cloud migration. Strategy includes automation, automation, lead, yea and data as part of their journey. Management. >>That's great. Good advice there. Bring us home. Maybe you can wrap it up with the final final world. >>So, lefty, keep it very simple. This book will help you to create difference in your business with the power of automation and artificial intelligence. >>That's a simple message and will governor what industry you're in? There is a disruptions scenario for your industry and that disruption scenarios going to involve automation, so you better get ahead of editor game. They're The book is available, of course, at amazon dot com. You can get more information. X censure dot com slash automation advantage. Gosh, thanks so much for coming in the Cube. Really appreciate your time. >>Thank you. Thank >>you. >>Eh? Thank you for watching this episode of the eight of US Executive Summit of reinvent made possible by Accenture. Keep it right there for more discussions that educating spy inspire You're watching the queue.

>>from the Cube Studios >>in Palo Alto and >>Boston connecting with thought leaders all around the world. This is a cube conversation. >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're doing a special presentation today really talking about AI and making ai really with two companies that are right in the heart of the Dell EMC as well as Intel. So we're excited to have a couple Cube alumni back on the program. Haven't seen him in a little while. First off from Intel. Lisa Spelman. She is the corporate VP and GM for the Xeon Group in Jersey on and Memory Group. Great to see you, Lisa. >>Good to see you again, too. >>And we've got Ravi Pinter. Conte. He is the SBP server product management, also from Dell Technologies. Ravi, great to see you as well. >>Good to see you on beast. Of course, >>yes. So let's jump into it. So, yesterday, Robbie, you guys announced a bunch of new kind of ai based solutions where if you can take us through that >>Absolutely so one of the things we did Jeff was we said it's not good enough for us to have a point product. But we talked about hope, the tour of products, more importantly, everything from our workstation side to the server to these storage elements and things that we're doing with VM Ware, for example. Beyond that, we're also obviously pleased with everything we're doing on bringing the right set off validated configurations and reference architectures and ready solutions so that the customer really doesn't have to go ahead and do the due diligence. Are figuring out how the various integration points are coming for us in making a solution possible. Obviously, all this is based on the great partnership we have with Intel on using not just their, you know, super cues, but FPG's as well. >>That's great. So, Lisa, I wonder, you know, I think a lot of people you know, obviously everybody knows Intel for your CPU is, but I don't think they recognize kind of all the other stuff that can wrap around the core CPU to add value around a particular solution. Set or problems. That's what If you could tell us a little bit more about Z on family and what you guys are doing in the data center with this kind of new interesting thing called AI and machine learning. >>Yeah. Um, so thanks, Jeff and Ravi. It's, um, amazing. The way to see that artificial intelligence applications are just growing in their pervasiveness. And you see it taking it out across all sorts of industries. And it's actually being built into just about every application that is coming down the pipe. And so if you think about meeting toe, have your hardware foundation able to support that. That's where we're seeing a lot of the customer interest come in. And not just a first Xeon, but, like Robbie said on the whole portfolio and how the system and solution configuration come together. So we're approaching it from a total view of being able to move all that data, store all of that data and cross us all of that data and providing options along that entire pipeline that move, um, and within that on Z on. Specifically, we've really set that as our cornerstone foundation for AI. If it's the most deployed solution and data center CPU around the world and every single application is going to have artificial intelligence in it, it makes sense that you would have artificial intelligence acceleration built into the actual hardware so that customers get a better experience right out of the box, regardless of which industry they're in or which specialized function they might be focusing on. >>It's really it's really wild, right? Cause in process, right, you always move through your next point of failure. So, you know, having all these kind of accelerants and the ways that you can carve off parts of the workload part of the intelligence that you can optimize betters is so important as you said Lisa and also Rocket and the solution side. Nobody wants General Ai just for ai sake. It's a nice word. Interesting science experiment. But it's really in the applied. A world is. We're starting to see the value in the application of this stuff, and I wonder you have a customer. You want to highlight Absalon, tell us a little bit about their journey and what you guys did with them. >>Great, sure. I mean, if you didn't start looking at Epsilon there in the market in the marketing business, and one of the crucial things for them is to ensure that they're able to provide the right data. Based on that analysis, there run on? What is it that the customer is looking for? And they can't wait for a period of time, but they need to be doing that in the near real time basis, and that's what excellent does. And what really blew my mind was the fact that they actually service are send out close to 100 billion messages. Again, it's 100 billion messages a year. And so you can imagine the amount of data that they're analyzing, which is in petabytes of data, and they need to do real time. And that's all possible because of the kind of analytics we have driven into the power It silver's, you know, using the latest of the Intel Intel Xeon processor couple with some of the technologies from the BGS side, which again I love them to go back in and analyze this data and service to the customers very rapidly. >>You know, it's funny. I think Mark Tech is kind of an under appreciated ah world of ai and, you know, in machine to machine execution, right, That's the amount of transactions go through when you load a webpage on your site that actually ideas who you are you know, puts puts a marketplace together, sells time on that or a spot on that ad and then lets people in is a really sophisticated, as you said in massive amounts of data going through the interesting stuff. If it's done right, it's magic. And if it's done, not right, then people get pissed off. You gotta have. You gotta have use our tools. >>You got it. I mean, this is where I talked about, you know, it can be garbage in garbage out if you don't really act on the right data. Right. So that is where I think it becomes important. But also, if you don't do it in a timely fashion, but you don't service up the right content at the right time. You miss the opportunity to go ahead and grab attention, >>right? Right. Lisa kind of back to you. Um, you know, there's all kinds of open source stuff that's happening also in the in the AI and machine learning world. So we hear things about tense or flow and and all these different libraries. How are you guys, you know, kind of embracing that world as you look at ai and kind of the development. We've been at it for a while. You guys are involved in everything from autonomous vehicles to the Mar Tech. Is we discussed? How are you making sure that these things were using all the available resources to optimize the solutions? >>Yeah, I think you and Robbie we're just hitting on some of those examples of how many ways people have figured out how to apply AI now. So maybe at first it was really driven by just image recognition and image tagging. But now you see so much work being driven in recommendation engines and an object detection for much more industrial use cases, not just consumer enjoyment and also those things you mentioned and hit on where the personalization is a really fine line you walk between. How do you make an experience feel good? Personalized versus creepy personalized is a real challenge and opportunity across so many industries. And so open source like you mentioned, is a great place for that foundation because it gives people the tools to build upon. And I think our strategy is really a stack strategy that starts first with delivering the best hardware for artificial intelligence and again the other is the foundation for that. But we also have, you know, Milat type processing for out of the Edge. And then we have all the way through to very custom specific accelerators into the data center, then on top about the optimized software, which is going into each of those frameworks and doing the work so that the framework recognizes the specific acceleration we built into the CPU. Whether that steel boost or recognizes the capabilities that sit in that accelerator silicon, and then once we've done that software layer and this is where we have the opportunity for a lot of partnership is the ecosystem and the solutions work that Robbie started off by talking about. So Ai isn't, um, it's not easy for everyone. It has a lot of value, but it takes work to extract that value. And so partnerships within the ecosystem to make sure that I see these are taking those optimization is building them in and fundamentally can deliver to customers. Reliable solution is the last leg of that of that strategy, but it really is one of the most important because without it you get a lot of really good benchmark results but not a lot of good, happy customer, >>right? I'm just curious, Lee says, because you kind of sit in the catbird seat. You guys at the core, you know, kind of under all the layers running data centers run these workloads. How >>do you see >>kind of the evolution of machine learning and ai from kind of the early days, where with science projects and and really smart people on mahogany row versus now people are talking about trying to get it to, like a citizen developer, but really a citizen data science and, you know, in exposing in the power of AI to business leaders or business executioners. Analysts, if you will, so they can apply it to their day to day world in their day to day life. How do you see that kind of evolving? Because you not only in it early, but you get to see some of the stuff coming down the road in design, find wins and reference architectures. How should people think about this evolution? >>It really is one of those things where if you step back from the fundamentals of AI, they've actually been around for 50 or more years. It's just that the changes in the amount of computing capability that's available, the network capacity that's available and the fundamental efficiency that I t and infrastructure managers and get out of their cloud architectures as allowed for this pervasiveness to evolve. And I think that's been the big tipping point that pushed people over this fear. Of course, I went through the same thing that cloud did where you had maybe every business leader or CEO saying Hey, get me a cloud and I'll figure out what for later give me some AI will get a week and make it work, But we're through those initial use pieces and starting to see a business value derived from from those deployments. And I think some of the most exciting areas are in the medical services field and just the amount, especially if you think of the environment we're in right now. The amount of efficiency and in some cases, reduction in human contact that you could require for diagnostics and just customer tracking and ability, ability to follow their entire patient History is really powerful and represents the next wave and care and how we scale our limited resource of doctors nurses technician. And the point we're making of what's coming next is where you start to see even more mass personalization and recommendations in that way that feel very not spooky to people but actually comforting. And they take value from them because it allows them to immediately act. Robbie reference to the speed at which you have to utilize the data. When people get immediately act more efficiently. They're generally happier with the service. So we see so much opportunity and we're continuing to address across, you know, again that hardware, software and solution stack so we can stay a step ahead of our customers, >>Right? That's great, Ravi. I want to give you the final word because you guys have to put the solutions together, it actually delivering to the customer. So not only, you know the hardware and the software, but any other kind of ecosystem components that you have to bring together. So I wonder if you can talk about that approach and how you know it's it's really the solution. At the end of the day, not specs, not speeds and feeds. That's not really what people care about. It's really a good solution. >>Yeah, three like Jeff, because end of the day I mean, it's like this. Most of us probably use the A team to retry money, but we really don't know what really sits behind 80 and my point being that you really care at that particular point in time to be able to put a radio do machine and get your dollar bills out, for example. Likewise, when you start looking at what the customer really needs to know, what Lisa hit upon is actually right. I mean what they're looking for. And you said this on the whole solution side house. To our our mantra to this is very simple. We want to make sure that we use the right basic building blocks, ensuring that we bring the right solutions using three things the right products which essentially means that we need to use the right partners to get the right processes in GPU Xen. But then >>we get >>to the next level by ensuring that we can actually do things we can either provide no ready solutions are validated reference architectures being that you have the sausage making process that you now don't need to have the customer go through, right? In a way. We have done the cooking and we provide a recipe book and you just go through the ingredient process of peering does and then off your off right to go get your solution done. And finally, the final stages there might be helped that customers still need in terms of services. That's something else Dell technology provides. And the whole idea is that customers want to go out and have them help deploying the solutions. We can also do that we're services. So that's probably the way we approach our data. The way we approach, you know, providing the building blocks are using the right technologies from our partners, then making sure that we have the right solutions that our customers can look at. And finally, they need deployment. Help weaken due their services. >>Well, Robbie, Lisa, thanks for taking a few minutes. That was a great tee up, Rob, because I think we're gonna go to a customer a couple of customer interviews enjoying that nice meal that you prepared with that combination of hardware, software, services and support. So thank you for your time and a great to catch up. All right, let's go and run the tape. Hi, Jeff. I wanted to talk about two examples of collaboration that we have with the partners that have yielded Ah, really examples of ah put through HPC and AI activities. So the first example that I wanted to cover is within your AHMAD team up in Canada with that team. We collaborated with Intel on a tuning of algorithm and code in order to accelerate the mapping of the human brain. So we have a cluster down here in Texas called Zenith based on Z on and obtain memory on. And we were able to that customer with the three of us are friends and Intel the norm, our team on the Dell HPC on data innovation, injuring team to go and accelerate the mapping of the human brain. So imagine patients playing video games or doing all sorts of activities that help understand how the brain sends the signal in order to trigger a response of the nervous system. And it's not only good, good way to map the human brain, but think about what you can get with that type of information in order to help cure Alzheimer's or dementia down the road. So this is really something I'm passionate about. Is using technology to help all of us on all of those that are suffering from those really tough diseases? Yeah, yeah, way >>boil. I'm a project manager for the project, and the idea is actually to scan six participants really intensively in both the memory scanner and the G scanner and see if we can use human brain data to get closer to something called Generalized Intelligence. What we have in the AI world, the systems that are mathematically computational, built often they do one task really, really well, but they struggle with other tasks. Really good example. This is video games. Artificial neural nets can often outperform humans and video games, but they don't really play in a natural way. Artificial neural net. Playing Mario Brothers The way that it beats the system is by actually kind of gliding its way through as quickly as possible. And it doesn't like collect pennies. For example, if you play Mary Brothers as a child, you know that collecting those coins is part of your game. And so the idea is to get artificial neural nets to behave more like humans. So like we have Transfer of knowledge is just something that humans do really, really well and very naturally. It doesn't take 50,000 examples for a child to know the difference between a dog and a hot dog when you eat when you play with. But an artificial neural net can often take massive computational power and many examples before it understands >>that video games are awesome, because when you do video game, you're doing a vision task instant. You're also doing a >>lot of planning and strategy thinking, but >>you're also taking decisions you several times a second, and we record that we try to see. Can we from brain activity predict >>what people were doing? We can break almost 90% accuracy with this type of architecture. >>Yeah, yeah, >>Use I was the lead posts. Talk on this collaboration with Dell and Intel. She's trying to work on a model called Graph Convolution Neural nets. >>We have being involved like two computing systems to compare it, like how the performance >>was voting for The lab relies on both servers that we have internally here, so I have a GPU server, but what we really rely on is compute Canada and Compute Canada is just not powerful enough to be able to run the models that he was trying to run so it would take her days. Weeks it would crash, would have to wait in line. Dell was visiting, and I was invited into the meeting very kindly, and they >>told us that they started working with a new >>type of hardware to train our neural nets. >>Dell's using traditional CPU use, pairing it with a new >>type off memory developed by Intel. Which thing? They also >>their new CPU architectures and really optimized to do deep learning. So all of that sounds great because we had this problem. We run out of memory, >>the innovation lab having access to experts to help answer questions immediately. That's not something to gate. >>We were able to train the attic snatch within 20 minutes. But before we do the same thing, all the GPU we need to wait almost three hours to each one simple way we >>were able to train the short original neural net. Dell has been really great cause anytime we need more memory, we send an email, Dell says. Yeah, sure, no problem. We'll extended how much memory do you need? It's been really simple from our end, and I think it's really great to be at the edge of science and technology. We're not just doing the same old. We're pushing the boundaries. Like often. We don't know where we're going to be in six months. In the big data world computing power makes a big difference. >>Yeah, yeah, yeah, yeah. The second example I'd like to cover is the one that will call the data accelerator. That's a publisher that we have with the University of Cambridge, England. There we partnered with Intel on Cambridge, and we built up at the time the number one Io 500 storage solution on. And it's pretty amazing because it was built on standard building blocks, power edge servers until Xeon processors some envy me drives from our partners and Intel. And what we did is we. Both of this system with a very, very smart and elaborate suffering code that gives an ultra fast performance for our customers, are looking for a front and fast scratch to their HPC storage solutions. We're also very mindful that this innovation is great for others to leverage, so the suffering Could will soon be available on Get Hub on. And, as I said, this was number one on the Iot 500 was initially released >>within Cambridge with always out of focus on opening up our technologies to UK industry, where we can encourage UK companies to take advantage of advanced research computing technologies way have many customers in the fields of automotive gas life sciences find our systems really help them accelerate their product development process. Manage Poor Khalidiya. I'm the director of research computing at Cambridge University. Yeah, we are a research computing cloud provider, but the emphasis is on the consulting on the processes around how to exploit that technology rather than the better results. Our value is in how we help businesses use advanced computing resources rather than the provision. Those results we see increasingly more and more data being produced across a wide range of verticals, life sciences, astronomy, manufacturing. So the data accelerators that was created as a component within our data center compute environment. Data processing is becoming more and more central element within research computing. We're getting very large data sets, traditional spinning disk file systems can't keep up and we find applications being slowed down due to a lack of data, So the data accelerator was born to take advantage of new solid state storage devices. I tried to work out how we can have a a staging mechanism for keeping your data on spinning disk when it's not required pre staging it on fast envy any stories? Devices so that can feed the applications at the rate quiet for maximum performance. So we have the highest AI capability available anywhere in the UK, where we match II compute performance Very high stories performance Because for AI, high performance storage is a key element to get the performance up. Currently, the data accelerated is the fastest HPC storage system in the world way are able to obtain 500 gigabytes a second read write with AI ops up in the 20 million range. We provide advanced computing technologies allow some of the brightest minds in the world really pushed scientific and medical research. We enable some of the greatest academics in the world to make tomorrow's discoveries. Yeah, yeah, yeah. >>Alright, Welcome back, Jeff Frick here and we're excited for this next segment. We're joined by Jeremy Raider. He is the GM digital transformation and scale solutions for Intel Corporation. Jeremy, great to see you. Hey, thanks for having me. I love I love the flowers in the backyard. I thought maybe you ran over to the Japanese, the Japanese garden or the Rose Garden, Right To very beautiful places to visit in Portland. >>Yeah. You know, you only get him for a couple. Ah, couple weeks here, so we get the timing just right. >>Excellent. All right, so let's jump into it. Really? And in this conversation really is all about making Ai Riel. Um, and you guys are working with Dell and you're working with not only Dell, right? There's the hardware and software, but a lot of these smaller a solution provider. So what is some of the key attributes that that needs to make ai riel for your customers out there? >>Yeah, so, you know, it's a it's a complex space. So when you can bring the best of the intel portfolio, which is which is expanding a lot, you know, it's not just the few anymore you're getting into Memory technologies, network technologies and kind of a little less known as how many resources we have focused on the software side of things optimizing frameworks and optimizing, and in these key ingredients and libraries that you can stitch into that portfolio to really get more performance in value, out of your machine learning and deep learning space. And so you know what we've really done here with Dell? It has started to bring a bunch of that portfolio together with Dell's capabilities, and then bring in that ai's V partner, that software vendor where we can really take and stitch and bring the most value out of that broad portfolio, ultimately using using the complexity of what it takes to deploy an AI capability. So a lot going on. They're bringing kind of the three legged stool of the software vendor hardware vendor dental into the mix, and you get a really strong outcome, >>right? So before we get to the solutions piece, let's stick a little bit into the Intel world. And I don't know if a lot of people are aware that obviously you guys make CPUs and you've been making great CPIs forever. But there's a whole lot more stuff that you've added, you know, kind of around the core CPU. If you will in terms of of actual libraries and ways to really optimize the seond processors to operate in an AI world. I wonder if you can kind of take us a little bit below the surface on how that works. What are some of the examples of things you can do to get more from your Gambira Intel processors for ai specific applications of workloads? >>Yeah, well, you know, there's a ton of software optimization that goes into this. You know that having the great CPU is definitely step one. But ultimately you want to get down into the libraries like tensor flow. We have data analytics, acceleration libraries. You know, that really allows you to get kind of again under the covers a little bit and look at it. How do we have to get the most out of the kinds of capabilities that are ultimately used in machine learning in deep learning capabilities, and then bring that forward and trying and enable that with our software vendors so that they can take advantage of those acceleration components and ultimately, you know, move from, you know, less training time or could be a the cost factor. But those are the kind of capabilities we want to expose to software vendors do these kinds of partnerships. >>Okay. Ah, and that's terrific. And I do think that's a big part of the story that a lot of people are probably not as aware of that. There are a lot of these optimization opportunities that you guys have been leveraging for a while. So shifting gears a little bit, right? AI and machine learning is all about the data. And in doing a little research for this, I found actually you on stage talking about some company that had, like, 350 of road off, 315 petabytes of data, 140,000 sources of those data. And I think probably not great quote of six months access time to get that's right and actually work with it. And the company you're referencing was intel. So you guys know a lot about debt data, managing data, everything from your manufacturing, and obviously supporting a global organization for I t and run and ah, a lot of complexity and secrets and good stuff. So you know what have you guys leveraged as intel in the way you work with data and getting a good data pipeline. That's enabling you to kind of put that into these other solutions that you're providing to the customers, >>right? Well, it is, You know, it's absolutely a journey, and it doesn't happen overnight, and that's what we've you know. We've seen it at Intel on We see it with many of our customers that are on the same journey that we've been on. And so you know, this idea of building that pipeline it really starts with what kind of problems that you're trying to solve. What are the big issues that are holding you back that company where you see that competitive advantage that you're trying to get to? And then ultimately, how do you build the structure to enable the right kind of pipeline of that data? Because that's that's what machine learning and deep learning is that data journey. So really a lot of focus around you know how we can understand those business challenges bring forward those kinds of capabilities along the way through to where we structure our entire company around those assets and then ultimately some of the partnerships that we're gonna be talking about these companies that are out there to help us really squeeze the most out of that data as quickly as possible because otherwise it goes stale real fast, sits on the shelf and you're not getting that value out of right. So, yeah, we've been on the journey. It's Ah, it's a long journey, but ultimately we could take a lot of those those kind of learnings and we can apply them to our silicon technology. The software optimization is that we're doing and ultimately, how we talk to our enterprise customers about how they can solve overcome some of the same challenges that we did. >>Well, let's talk about some of those challenges specifically because, you know, I think part of the the challenge is that kind of knocked big data, if you will in Hadoop, if you will kind of off the rails. Little bit was there's a whole lot that goes into it. Besides just doing the analysis, there's a lot of data practice data collection, data organization, a whole bunch of things that have to happen before. You can actually start to do the sexy stuff of AI. So you know, what are some of those challenges. How are you helping people get over kind of these baby steps before they can really get into the deep end of the pool? >>Yeah, well, you know, one is you have to have the resource is so you know, do you even have the resource is if you can acquire those Resource is can you keep them interested in the kind of work that you're doing? So that's a big challenge on and actually will talk about how that fits into some of the partnerships that we've been establishing in the ecosystem. It's also you get stuck in this poc do loop, right? You finally get those resource is and they start to get access to that data that we talked about. It start to play out some scenarios, a theorize a little bit. Maybe they show you some really interesting value, but it never seems to make its way into a full production mode. And I think that is a challenge that has faced so many enterprises that are stuck in that loop. And so that's where we look at who's out there in the ecosystem that can help more readily move through that whole process of the evaluation that proved the r a y, the POC and ultimately move that thing that capability into production mode as quickly as possible that you know that to me is one of those fundamental aspects of if you're stuck in the POC. Nothing's happening from this. This is not helping your company. We want to move things more quickly, >>right? Right. And let's just talk about some of these companies that you guys are working with that you've got some reference architectures is data robot a Grid dynamics H 20 just down the road in Antigua. So a lot of the companies we've worked with with Cube and I think you know another part that's interesting. It again we can learn from kind of old days of big data is kind of generalized. Ai versus solution specific. Ai and I think you know where there's a real opportunity is not AI for a sake, but really it's got to be applied to a specific solution, a specific problem so that you have, you know, better chatbots, better customer service experience, you know, better something. So when you were working with these folks and trying to design solutions or some of the opportunities that you saw to work with some of these folks to now have an applied a application slash solution versus just kind of AI for ai's sake. >>Yeah. I mean, that could be anything from fraud, detection and financial services, or even taking a step back and looking more horizontally like back to that data challenge. If if you're stuck at the AI built a fantastic Data lake, but I haven't been able to pull anything back out of it, who are some of the companies that are out there that can help overcome some of those big data challenges and ultimately get you to where you know, you don't have a data scientist spending 60% of their time on data acquisition pre processing? That's not where we want them, right? We want them on building out that next theory. We want them on looking at the next business challenge. We want them on selecting the right models, but ultimately they have to do that as quickly as possible so that they can move that that capability forward into the next phase. So, really, it's about that that connection of looking at those those problems or challenges in the whole pipeline. And these companies like data robot in H 20 quasi. Oh, they're all addressing specific challenges in the end to end. That's why they've kind of bubbled up as ones that we want to continue to collaborate with, because it can help enterprises overcome those issues more fast. You know more readily. >>Great. Well, Jeremy, thanks for taking a few minutes and giving us the Intel side of the story. Um, it's a great company has been around forever. I worked there many, many moons ago. That's Ah, that's a story for another time, but really appreciate it and I'll interview you will go there. Alright, so super. Thanks a lot. So he's Jeremy. I'm Jeff Frick. So now it's time to go ahead and jump into the crowd chat. It's crowdchat dot net slash make ai real. Um, we'll see you in the chat. And thanks for watching

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. >>Alright, welcome back. Jeff Frick here. And we're excited for this next segment. We're joined by Jeremy Raider. He is the GM digital transformation and scale solutions for Intel Corporation. Jeremy, great to see you. Hey, thanks for having me. I love I love the flowers in the backyard. I thought maybe you ran over to the Japanese, the Japanese garden or the Rose Garden. Right To very beautiful places to visit in Portland. >>Yeah. You know, you only get for a couple Ah, couple weeks here, so we get the timing just right. >>Excellent. All right, so let's jump into it. Really? And in this conversation really is all about making Ai Riel. Um, and you guys are working with Dell and you're working with not only Dell, right? There's the hardware and software, but a lot of these smaller a solution provider. So what is some of the key attributes that that needs to make ai riel for your customers out there? >>Yeah. So you know, it's a It's a complex space. So when you can bring the best of the Intel portfolio, which is which is expanding a lot. You know, it's not just the few anymore you're getting into memory technologies, network technologies and kind of a little less known as how many resources we have focused on the software side of things optimizing frameworks and optimizing and in these key ingredients and libraries that you can stitch into that portfolio to really get more performance in value, out of your machine learning and deep learning space. And so you know what we've really done here with Dell? It has started to bring a bunch of that portfolio together with Dell's capabilities, and then bring in that ai's V partner, that software vendor where we can really take and stitch and bring the most value out of a broad portfolio. Ultimately using using the complexity of what it takes to deploy an AI capability. So a lot going on. They're bringing kind of the three legged stool of the software vendor hardware vendor dental into the mix, and you get a really strong outcome, >>right? So before we get to the solutions piece, let's stick a little bit into the intel world, and I don't know if a lot of people are aware that obviously you guys make CPUs and you've been making great CPS forever. But there's a whole lot more stuff that you've added, you know, kind of around the core CPU, if you will. In terms of of actual libraries and ways to really optimize the seond processors to operate in an AI world. I wonder if you can kind of take us a little bit below the surface on how that works. What are some of the examples of things you can do to get more from your Gambira Intel processors for AI specific applications of workloads? >>Yeah, well, you know, there's a ton of software optimization that goes into this. You know that having the great CPU is definitely step one. But ultimately you want to get down into the libraries like tensor flow. We have data analytics, acceleration libraries. You know, that really allows you to get kind of again under the covers a little bit and look at how do we have to get the most out of the kinds of capabilities that are ultimately used in machine learning in deep learning capabilities, and then bring that forward and trying and enable that with our software vendors so that they can take advantage of those acceleration components and ultimately, you know, move from, you know, less training time or could be a cost factor, right? Those are the kind of capabilities we want to expose to software vendors do these kinds of partnerships >>on, and that's terrific. And I do think that's a big part of the story that a lot of people are probably not as aware of that. There are a lot of these optimization opportunities that you guys have been leveraging for a while. So shifting gears a little bit right AI and machine learning is all about the data. And in doing a little research for this, I found actually you on stage talking about some company that had, like, 350 of road off 315 petabytes of of data, 140,000 sources of those data, and I think probably not great quote of six months access time to get it right and actually work with it. And the company you're referencing was intel. So you guys know a lot about debt data, managing data, everything from your manufacturing and and obviously supporting a global organization for I, t and Brian and, ah, a lot of complexity and secrets and good stuff. So you know what have you guys leveraged as intel in the way you work with data and getting a good data pipeline that's enabling you to kind of put that into these other solutions that you're providing to the customers, >>right? Well is, you know, it's absolutely a journey, and it doesn't happen overnight, and that's what we've you know. We've seen it at Intel on We see it with many of our customers that are on the same journey that we've been on. And so you know, this idea of building that pipeline it really starts with what kind of problems that you're trying to solve. What are the big issues that are holding you back that company where you see that competitive advantage that you're trying to get to? And then ultimately, how do you build the structure to enable the right kind of pipeline of that data? Because that's that's what machine learning and deep learning is that data journey. So really a lot of focus around you know how we can understand those business challenges bring forward those kinds of capabilities along the way through to where we structure our entire company around those assets. And then ultimately, some of the partnerships that we're gonna be talking about these companies that are out there to help us really squeeze the most out of that data as quickly as possible because otherwise it goes stale real fast, sits on the shelf, and you're not getting that value out of right. So, yeah, we've been on the journey. It's ah, it's a long journey. But ultimately we could take a lot of those those kind of learnings and we can apply them to our silicon technology. The software optimization is that we're doing and ultimately, how we talk to our enterprise customers about how they can solve overcome some of the same challenges that we did. >>Well, let's talk about some of those challenges specifically because, you know, I think part of the the challenge is that kind of knocked big data, if you will in Hadoop, if you will kind of off the rails. Little bit was, there's a whole lot that goes into it. Besides just doing the analysis There's a lot of data practice data collection, data organization, a whole bunch of things that have to happen before You can actually start to do the sexy stuff of AI. So you know, what are some of those challenges? How are you helping people get over kind of these baby steps before they can really get into the deep end of the pool? >>Yeah, well, you know, one is you have to have the resource is so you know, do you even have the resource is if you can acquire those Resource is can you keep them interested in that kind of work that you're doing? So that's a big challenge on and actually will talk about how that fits into some of the partnerships that we've been establishing in the ecosystem. It's also you get stuck in this poc do loop, right? You finally get those resource is and they start to get access to that data that we talked about. They start to play out some scenarios a theorize a little bit. Maybe they show you some really interesting value, but it never seems to make its way into a full production mode. And I think that is a challenge that is facing so many enterprises that are stuck in that loop. And so that's where we look at who's out there in the ecosystem That can help more readily move through that whole process of the evaluation that proved they are a why the POC and ultimately move that thing that capability into production mode as quickly as possible that you know that to me is one of those fundamental aspects of if you're stuck in the POC. Nothing's happening from this. This is not helping your company. We want to move things more quickly, >>right? Right. And let's just talk about some of these companies that you guys are working with that you've got some reference architectures is data robot a Grid Dynamics H 20 just down the road in Antigua. So a lot of the companies we've worked with with Cube and I think you know another part that's interesting. It again we can learn from kind of old days of big data is kind of generalized. Ai versus solution specific. Ai and I think you know where there's a real opportunity is not AI for a sake, but really it's got to be applied to a specific solution. A specific problem so that you have, you know, better chatbots. Better customer service experience, you know, better something. So when you were working with these folks and trying to design solutions or some of the opportunities that you saw to work with, some of these folks to now have an applied a application slash solution versus just kind of AI for ai's sake, >>Yeah. I mean, that could be anything from fraud, detection and financial services, or even taking a step back and looking more horizontally like back to that data challenge. If if you're stuck at the AI built a fantastic data lake, but I haven't been able to pull anything back out of it, who are some of the companies that are out there that can help overcome some of those big data challenges and ultimately get you to where you know, you don't have a data scientist spending 60% of their time on data acquisition pre processing? That's not where we want them, right? We want them on building out that next theory. We want them on looking at the next business challenge. We want them on selecting the right models, but ultimately they have to do that as quickly as possible so that they can move that that capability forward into the next phase. So, really, it's about that that connection of looking at those those problems or challenges in the whole pipeline. And these companies like Data robot in H 20 because you know, they're all addressing specific challenges in the end to end. That's why they've kind of bubbled up as ones that we want to continue to collaborate with, because it can help enterprises overcome those issues more fast. You know more readily. >>Great. Well, Jeremy, thanks for taking a few minutes and giving us the Intel side of the story. Um, it's a great company. Has been around forever. I worked there many, many moons ago. That's Ah, that's a story for another time. But really appreciate it and >>I'll interview you >>will go there. Alright, So super Thanks a lot. So he's Jeremy. I'm Jeff Frick. So now it's time to go ahead and jump into the crowd chat. It's crowdchat dot net slash make ai Really, Um, we'll see you in the chat. And thanks for watching. Yeah, yeah, yeah, yeah

>>live from San Francisco. It's the Q covering Micron Insight 2019 to You by Micron. >>We're back to Pier 27 in lovely San Francisco, Everybody. I'm Dave a lot with my co host, David Floy Er and you're watching the Cube, the leader and live tech coverage. Evan cursed Ellis here. He's a social digital influencer. First time in the Cube. Evan, Great to see you. >>Thanks for having me. First time's the best. >>You Very well. And it is beautiful. Out him in October is the best month in San Francisco. Way better way warmer than July. I mean, you live out here. Holy cow. All right, let's get right into it. You're just fresh off of mobile work. World Congress down in L. A. >>This morning. Yeah, five g on the brain's >>s. So what do we need to know about five g? You >>know, I think my big takeaway as an industry observer is that five g Israel, and it's now I mean, we've seen 5 10 years, maybe of hype, an expectation and marketing buzz and even spin. But I think we're now in the business of practical deployments, scaling rollouts of networks and that's, you know, as a industry observers, quite exciting. >>So what is five g mean for the average user? I mean, is it gonna be like going from dial up toe, high speed Internet or, you know, it's gonna be interesting. >>The average user, I think we'll experience, you know, like a 10 x increase in their current experience on mobile in terms of uploads and downloads and speed and Leighton see, And that kind of thing, which is super exciting, it's it's gonna blow people's mind. >>An ex stoked to get a 10 extra. When can I get this? >>It's when and it's where, right? I mean, if you look at how these networks are evolving, there are hundreds of thousands of small cells of base stations that have to be deployed naturally to get five G ubiquitous across the country. So it's it's when it's where it's how. But we're here. We're at the starting point and look for the next years and months ahead to see that riel attraction. >>If I look now when I travel around the country, I still have four G. I still have three g. I still have edge. I have a ll the old ones are still there, and it's taken forever, even just to get to 40. So isn't lesson. Isn't the rollout of this going to take a long time ago or 10 year horizon? >>I think, to get ubiquitous coverage indoor, outdoor, suburban, urban, rural It's going to take 10 years. But if you look at those hot spots that generate a lot of activity, whether it's, you know, indoor coverage in the Enterprise, whether it's, you know, the Bruins playing in Boston Garden I mean those air where five G is really going to come into play first and then it's going to sort of go outside of those urban dense areas. >>You mean like the fan experience in the fan experience in the venue >>is huge? I mean, if you go to any you know, baseball, basketball, football game, you know what the experience is like Pretty pretty bad, right? So horrible. So those kind of hot spots are ripe for five g like right away today. Now, >>so by the way, David, sometimes I get five g on my that's right, and I feel like it's fake. Five years like HD ready. What's that all about? Well, you know, >>these networks evolve, and so the carriers are maximizing for G, including biggest speed on four G and five. Gene is really if overlay to these existing networks. And so, as you get your next Samsung, you know five G enabled devices. Apple next year comes out with a five G iPad. You'll then begin to use. The service is as you use your existing device. >>Can you help us understand the fundamental architecture of five G? My understanding is it's, you know, no basis more distributed on. That's part of the reason why it's taking so long to roll out. But what do we need to know about that E? >>I think it's a brand new editor interface. So if you think about the current radio on for G, they reinvented the wheel with five G, which means you can support a huge number of endpoints of I o. T devices of wearables of home access points. And so it enables almost a 10 to 100 ex war devices in terms of scale. So while the end user may think this is business as usual, what's really happening on the network side is pretty revolutionary And once the networks are primed and built and ready, what's gonna be happening on the device side is gonna be really extraordinary. You're talking about a K A video on a mobile device or augmented reality through in new kinds of glasses. And so it's sort of a chicken and a little bit. You know what? She's gonna come first, the network or the incredible new devices. So we're seeing now the network's being put in place for those wave of devices, >>which makes sense. Device manufactures don't want over rotate into something that's not quite. >>But if you look at the network, it's you have to have a lot of device is very close to each other. I in my area that all these the holdings holding these hearings about radiation, everything else like that, which is never, never really a problem unless you're underneath. >>Yeah. I mean, there's a lot of fun, you know, fear, uncertainty around five G. >>Yeah, and I'm just the practical thing. You gotta have all of these lots of these very close in the The exposure to having a gap of some sort is pretty high. >>Yeah, I think it's an issue of frequencies as well. Right now, we're seeing very high frequency five deployed for those dense urban suburban areas. We're going to Seymour Spectrum rolled out next year. The FCC is putting out new auction so you'll see lower bit rate five g rolled out for suburban and rural areas. So it's a It's a work in progress, but the fact that we have first devices first silicon for software first networks. It's kind of a big inflection >>point, but some bumps. I'm inferring this ATT the back end. It could be a lot of machine to machine communications, so that's kind of sets up this whole coyote and an edge discussion. And of course, that means more data. What can you tell us about how that's going to affect really the amount of data and how we use that data? >>The data explosion is extraordinary. I mean, we experience this as early adopters here at the table every day, and so no one's ever said, you know, my network is fast enough is good enough, secure enough. There's always that insatiable appetite now, given the connected world in which we live. And so it's not just the network speed it's the input output of the device. I mean, we have Leighton see that frankly, from these networks operates at the speed of the human brain, you know, in in milliseconds, in terms of input output on the network. And so that's really gonna change the user experience to when the way you do gaming or collaboration or video conferencing video calls and all these service is we use today will be much more tuned to how we live and work. >>So dial upto high speed Internet obvious Are you want? I'll update you say you go back. I'm also I know remember this stuff But that was a significant change. Obvious step change, really a step function. Exactly. But subsequent to that it was I could doom. Or but it was just so much more data and acts were flowing through the network that it really didn't change the experience a little bit. Maybe, actually, you know, be careful. I watched the Patriots game on the plane on the NFL app on the way out here, which could probably have done a year or two ago, but so that was that's goodness. But generally speaking, the experience is substantially similar. Will you said a 10 X before? Will the user actually see a difference like that kind of dial up to high speed step function? Or is it going to be sort of a slow roll? >>I think the user will see a big a big improvement because of the efficiencies of the network and the way in which data is kind of throttled and limited. Today, with three and four for G networks, I think more interestingly, is how businesses and enterprises and sm bees will consume. Five g. I mean, there are a lot of antiquated networks out there, whether it's legacy wired Network, D S. L. Whether it's, you know, crappy WiFi that we all experience in hotel rooms, five g has the opportunity to come in and really displace all of that legacy crap that that's in our networks and give users in those enterprises hotels, venues, a brand new experience. And when's the last time you had a bad hotel? WiFi, for the idea of, of getting rid of a legacy network and delivering those high speed service is from a public network. It's her Private networking is a really exciting opportunity for the carriers and, really, for the B two B enterprise. >>Well, the technology suppliers are pumped about their pumped and their >>look at their profitability, their revenue, their sales. Everything's up. >>Well, the thing is that that is, the carriers, like you say they have no choice but to remain competitive. They have to consume. They have to spend more >>on what a great time in the mobile industry. I mean to be a consumer of devices and service is, I mean, the consumers that businesses are winning in this march. >>So tell us about Mobile World Congress. What was the vibe? It was >>very buzzy. I mean, there were lots of Rhea World applications on display, whether wearable devices for health care and hospital T applications. There were examples of remote controlled autonomous shipping and autonomous trucking monitored, supervised with five G. There were examples of vehicle to vehicle communications for accident, safety purposes being deployed in the next generation of cars baked in, and so five. He's gotten very practical. Now it's like, Okay, we've built this network, we have silicon, we have software we have storage memory out of we deploy it so is very focused on deployment usage and an application. >>If you take that one of automotive, for example, if you're a god, health and life on your If you If you can't guarantee that you've got connectivity toe, what's the value wouldn't do? For example, wouldn't you prefer vehicle to vehicle direct communication, as opposed to going outside to some much faster? >>Exactly. Exactly. And there's a new technology called vehicle Be two extra people vehicle standards that are being baked so that that's not funny. It's based on the five of the family of standards, and so one of the technologies within the five G family is vehicle to vehicle. Qualcomm's doing some amazing work there. And once the automobile manufacturers baked that technology into cars, the car manufacturers can then build in vehicle avoidance, vehicle collision technology and so forth. >>So I'm worried that was some talk about a I right? I mean, lots of talk that mobile world Congress, you're gonna hear a lot about here. What about the ecosystem that's emerging to support five G? There's gotta be a whole value chain specialized chips. I mean, obviously, micron, you know? Yeah, you know, the >>whole supply chain has to come together and Micron powering all of these devices with memory and storage to the application developers to the O E ems to the network providers. And so that ecosystem is getting really baked, fully baked and and integrated. And that was on display at MWC, too. So all these things are coming together, and I think it's pretty exciting. As a long time skeptic like yourself. I saw some real world. >>I say, I'm excited about it. I just I'm just not holding my breath. Don't >>hold your breath. Not >>recommended weight. That's great, Evan. Thanks very much for coming in. Thanks so much. Appreciate your insights. Thanks so much. Thank you for watching. Keep it right there. But it will be back from Micron Insight 2019 from San Francisco. You're watching the Cube?

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Welcome to this cube competition here at the Palo Alto Cube Studios. I'm John for a host of the Cube. Were here a special guests to keep alumni investor An entrepreneur who do Sudhakar, would you Good to see you again, John. Always a pleasure. You've been on as an entrepreneur, founder. As an investor, you're always out. Scour in the Valley was a great conversation. I want to get your thoughts as kind of a guest analyst on this segment around the state of the Union for Enterprise Tech. As you know, we covering the price tag. We got all the top enterprise B to B events. The world has changed and get reinvent coming up. We got VM World before that. The two big shows, too to cap out this year got sprung a variety of other events as well. So a lot of action cloud now is pretty much a done deal. Everyone's validating it. Micro cells gaining share a lot of growth areas around cloud that's been enable I want to get your thoughts first. Question is what are the top growth sectors in the enterprise that you're seeing >> papers. Thank you for having me. It's always a pleasure talking to you over the years. You and me have done this so many times. I'm learning a lot from you. So thank you. You are so yeah, I think Let's dig into the cloud side and in general market. So I think that there are 34 areas that I see a lot that's happening a lot. Cloud is still growing, a lot 100% are more growth and cloud and dog breeders. And what is the second? I see, a lot of I T services are close services. This includes service management. The areas that service now isn't They're >> still my ops was Maybe >> they opt in that category. E I said With management, the gutter is coming with the new canticle a service management. So they're replacing idea some with a different. So that's growing 800% as a category tourist. RP according to again, the industry analysts have seen that it's going at 65 to 70% so these three areas are going a lot in the last one that I see a lot of user experience. Can you build? It's like it's a 20,000,000,000 market cap, something. So if you let it out, it's a cloud service Management services RP user experience cos these are the four areas I see a lot dating all the oxygen rest. Everybody is like the bread crumbs. >> Okay, and why do you think the growth in our P A. So how's the hype? Is it really what? What is going on in our pee, In your opinion, >> on the rumors I'm hearing or there is some companies are already 1,000,000,000 revenue run great wise. That's a lot in our piece. So it's not really a hype that really so that if you look and below that, what's happening is I'd be a Companies are automating automation. The key for here is if I can improve the user experience and also automate things. RPS started doing screen scraping right in their leaders, looking at any reservations supply chain any workflow automation. So every company is so complex. Now somebody has to automate the workflow. How can you do this with less number of people, less number, resources, and improve the productivity >> coming? R P A. Is you know, robotic process automation is what it stands for, but ultimately it's software automation. I mean, it's software meets cloud meets automation. It seems to be the big thing. That's also where a I can play a part. Your take on the A I market right now. Obviously, Cloud and A I are probably the two biggest I think category people tend to talk about cloud and a eyes kind of a big kind of territories. RPG could fall under a little bit of bulls, but what you take on a guy, >> Yeah, so I think if you look at our pier, I actually call the traditional appears to be historical legacy. Wonders and R P companies are doing a good job to transform themselves to the next level, right? But our pianist Rocky I score. It's no longer the screen skipping tradition, making the workflow understanding. So there are new technology called conversational Rp. There's actually a separate market. Guys been critical conversation within a Can I talk to in a dialogue manner like what you experienced Instagram are what using what's up our dialogue flow? How can I make it? A conversational RPS is a new secretary is evolving it, but our becomes have done a good job. They leave all their going out. A >> lot has been has great success. We've been covering them like a blanket on a single cube. Um, I got it. I got to get your take on how this all comes into the next generation modern era because, um, you know, we're both been around the block. We've seen the waves of innovation. The modern error of clouds certainly cloud one Dato Amazon. Now Microsoft has your phone. Google anywhere else really goes. Dev Ops, The devil's movement cloud native amazing, create a lot of value continues to do well, but now there's a big culture on cloud 2.0, what is your definition of cloud two point? Oh, how do you see Cloud 2.0, evolving. But >> I like the name close to party. I think it's your third. It is going to continue as a trained. So look, throw two point with eyes. I don't know what it will be, but I can tell you what it should be and what it can have. Some other things that should do in the cloud is cloud is still very much gun to human beings. Lot of develops people. Lot of human being The next addition to a daughter should have things done programmatically I don't need tens of thousands off Assad ease and develops people. So back to your air, upside and everything. Some of those things should become close to become proactive. I don't want to wait until Amazon. Easter too is done. If I'm paying him is on this money. Amazon should be notifying me when my service is going to be done. The subsidy eaters They operated Chlo Trail Cloudwatch Exeter. But they need to take it to a notch level. But Amazon Azure. >> So making the experience of deploying, running and building APS scalable. Actually, that's scales with Clavet. Programmable kind of brings in the RPI a mean making a boat through automation edge of the network is also interesting. Comes up a lot like Okay, how do you deal with networking? Amazons Done computing storage and meet amazing. Well, cloud and networking has been built in, I guess to me, the trend of networking kicks in big because now it's like, OK, if you have no perimeter, you have a service area with I o t. >> There's nothing that >> cloud to point. It has to address riel time programming ability. Things like kubernetes continues to rise. You're gonna need to have service has taken up and down automatically know humans. So this >> is about people keep on fur cloak. What should be done before the human in the to rate still done. It develops. People are still using terror from lot of scripting. Lot of manual. Can you automata? That's one angle The second angle I see in cloud 2.0 is if you step back and say What, exactly? The intrinsic properties of Claude Majors. It's the work floor. It's automation, but it's also able to do it. Pro, actually. So what I don't have to raise if I'm playing club renders this much money. Tell me what outrageous are happening. Don't wait until outage happens. Can you predict voted? Yes, they have the capability to women. It should be Probably steal it. No, not 100%. So I want to know what age prediction. I wonder what service are going down. Are notified the user's that will become a a common denominator and solutions will be start providing, even though you see small startups doing this. Eventually they become features all these companies, and they'll get absorbed by the I called his aircraft carriers. You have Masson agile DCP. They're going to absorb all this, a ups to the point that provide that as the functionality. >> Yeah, let's get the consolidation in second. I want to get your thoughts on the cloud to point because we really getting at is that there's a lot of white space opportunity coming in. So I gotta ask you to start up. Question as you look at your investor, prolific investor in start ups. Also, you're an entrepreneur yourself. What >> is? >> They have opportunities out there because we'll get into the big the big whales Amazon, who were building and winning at scale. So embarrassed entry or higher every day, even though it's open sources, They're Amazons, betting on open source. Big time. We had John Thompson talk about that. That was excessive. Something Nutella. And so what? What if I was a printer out there? Would what do I do? I mean, is there Is there any real territory that I could create a base camp on and make money? >> That's plenty. So there's plenty of white faces to create. Look, first of all your look at what's catering, look at what's happening. IBM is auto business in service management, CSL itself to Broadcom. BMC is sold twice to private companies. Even the CEO got has left our war It is. Then you have to be soldiers of the Micro Focus. The only company that's left is so it's not so in that area, you can create plenty of good opportunities. That's a big weight. >> Sensors now just had a bad quarter. So actually, clarity will >> eventually they're gonna enough companies to go in that space. That play that's based can support 23 opportunities so I can see a publicly traded company in service. No space in next five years. My production is they'll be under company will go a p o in the service management space. Same things would happen. Rp, Rp vendors won't get acquired A little cleared enough work for automation. They become the next day because of the good. I can see a next publicly traded company. What happened in the 80 operations? Patriotism Probably. Computer company Pedro is doing really well. Watch it later. Don't. They're going to go public next. So that area also, you see plenty of open record companies in a UPS. >> So this is again back to the growth areas. Cloud hard to compete on Public Cloud. Yes, the big guys are out there. There's a cloud enablers, the people who don't have the clouds. So h p tried to do a cloud hp They had to come out, they'll try to cloud couldn't do It s a P technically is out there with a cloud. They're trying to be multi cloud. So you have a series of people who made it an oracle still on the fence. They still technically got a cloud, but it's really more Oracle and Oracle. So they're kind of stuck in the middle between the cloud and able nervous. The Cloud player. If you're not a cloud player large enterprise, what is the strategy? Because you got HP, IBM, Cisco and Dell. >> So I don't know. You didn't include its sales force in that If I'm Salesforce, I want sales force to get in. They have a sales cloud marketing cloud commerce code. Mark is not doing anything in the area of fighting clothes. They cannot go from 100,000,000,000 toe, half a trillion trillion market cap. Told I D. They have to embrace that and that's 100% growth area. You know, people get into this game at some point. It'll be is already hard and 50,000,000,000 market cap. Then that leaves. What is this going to do? Cisco has been buying more security software assets, but they don't wanna be a public company, their hybrid club. But they have to figure out How can they become an arms dealer in escape and by ruining different properties off close services? And that's gonna happen. And I've been really good job by acquiring Red Heart. So I think some place really figuring out this what is happening. But they have to get in the gaming club they have to do. Other service management have begun and are here. They have to get experience. None of these guys have experienced in this day and age that you killed and who are joining the workforce. They care for Airbnb naked for we work. They care for uber. They care for Netflix. It is not betting unders. So if I'm on the border, Francisco, I'm not talking about experience That's a problem to me. Hey, tree boredom is not talking about that. That's what if I'm I know Mark is on the board. Paramount reason. But Mark is investing in all the slack. Cos then why is it we are doing it either hit special? Get a separate board member. They should get somebody else. >> Why? He wouldn't tell. You have to move. Maybe. I don't know. We don't talk about injuries about that. But I want to get back to this experience thing because experience has become the new expectation. Yes, that's been kind of a design principle kind of ethos. Okay, so let's take that. The next little younger generation, they're consuming Airbnb. They're using the serious like their news and little chunks be built a video service for that. So things are changing. What is? I tease virgin as the consumption is a product issue. So how does I t cater to these new experience? What are some of those experiences? I >> think all of them. But I think I d for Social Kedrick, every property, every product should figure out how to offer to the young dreamers how they were contributed offer to the businesses on the B two baby to see. So the eye has to think every product or not. Should I start thinking about how my user should consume this and how should out for new experiences and how they want to see this in a new way, right? It's not in the same the same computer networking. How can a deluded proactively How can a dealer to a point where people can consume it and make other medications so darn edition making? That's where the air comes in. Don't wait for me toe. Ask the question. Suggest it's like Gmail auto complete. Every future should be thinking through problem. Still, what can I do to improve the experience that changes the product? Management's on? And that's what I'm looking at, companies who are thinking like that connection and see Adam Connection security. But that has to happen in the product. >> I was mentioning the people who didn't have clouds HP, IBM, Cisco and Dell you through sales force in there, I kind of would think sales were six, which is technically a cloud. They were cloud before cloud was even cloud. They built basically oracle for the cloud that became sales force. But you mentioned service now. Sales force. You got adobe, You got work day. These are application clouds. So they're not public clouds per se they get Amazon Web service is, you know, at Adobe runs on AWS, right? A lot of other people do. Microsoft has their own cloud, but they also have applications as well. Office 3 65 So what if some of these niche cloud these application clouds have to do differently? Because if you think about sales force, you mentioned a good point. Why isn't sales were doing more? People generally don't like Salesforce. You think that it's more of a lock inspect lesson with a wow. They've done really innovative things. I mean, I don't People don't really tend to talk about sales force in the same breath as innovation. They talk about Well, we run sales for us. We hate it or we use it and they never really break into these other markets. What's your take on them? >> I think Mark has done a good job to order. Yes, acquiring very cos it has to start from the top and at the market. His management team should say, I want to get in a new space. He got in tow. Commerce. Claudia got into marketing. He has to know, decide to get into idea or not. Once he comes out, he's really taken because today, science. What is below the market cap? Com Part of it'll be all right. If I am sales force, I need to go back down. Should I go after service? No. Industry should go after entire 80 services industry. Yes or no, But they have to make a suggestion. Something with Toby Toby is not gonna be any slower. They will get into. I decide. They're already doing the eyesight and experience. They're king of experience. Their king off what they're doing. Marketing site. They will expand. Writing. >> What does something We'll just launched a platform. Yes, that's right. The former executive from IBM. That's an interesting direction. They all have these platforms. Okay, so I got together to the Microsoft Amazon, Um, Google, the big clouds and then everybody else. A lot of discussion around consolidation. A lot of people say that the recession's coming next year. I doubt that. No, nos. The consolidation continues to happen. You can almost predict that. But where do you see the consolidation of you got some growth areas as you laid out cloud I t service is our p a experience based off where looks like where's the consolidation happening? If growth is happening, they're words to tell. >> It was happening. Really Like I see a lot in cyber security. I'm in Costa Rica, live in public. You have the scaler, the whole bunch of companies. So the next level of cos you always saw Sisko Bart, do your security followed has been buying aggressively companies. So secret is already going to a lot of consolidation. You're not seeing other people taking it, but in the I T services industry, you'll start seeing that you're already seeing that in the community space. That game is pretty much over right. Even the ember barred companies, even Net are barred companies and the currency. So I think console is always going to happen. People are picking up the right time. It's happening across the board. It's a great time to be an entrepreneur creator value. They come this public. So it's like I think it's cannot anymore very time. Look to your point where the decision happens or not. Nobody can predict. But if a chance now, it's best time to raise money. Build a company. >> Well, we do. I think the analysis, at least from my perspective, is looking at all the events we go to is the same theme comes up over and over. And Andy Jassy this heat of a tigress always talks about Old Garden new Guard. I think there's two sides of the streets developing old way in a new way, and I think the modern architect of the modern era of computer industry is coming, and it looks a lot different than it. Waas. So I think the consolidate is happening on those companies that didn't make the right bets, either technically or business model wise, for they took on too much technical debt and could not convert over to the cloud world or these really robust software environment. So I think consolidations from just just the passing of holder >> seems pretty set up for a member of the first men. First Main Computing was called mainframe Era, then, with clients Herrera and Kim, the club sodas 6 2009 13 years old, the new Errol called. Whatever the name, it will be something with a n mission in India that things would be so automated. That's what we have new area of computing, So that's I would like to see. So that's a new trick, this vendetta near turn. So even though we go through this >> chance all software software sales data 11. Yeah, it's interesting. And I think the opportunity, for starters is to build a new brands. His new branch would come out. Let's take an example of a company that but after our old incumbent space dying market share not not very attractive from a VC standpoint. From market space standpoint, Zoom Zoom went after Web conferencing, and they took on WebEx and portability. And they did it with a very simple formula. Be fast, be cloud native and go after that big market and just beat them on speed and simple >> experience. They give your greatest experience just on the Web, conferencing it and better than sky better than their backs better than anybody else in that market. Paid them with reward. Thanks, Vic. He had a good >> guy and he's very focused. He used clouds. Scale took the value proposition of WebEx. Get rid of all the other stuff brought its simple to video conference. And Dr Mantra is one >> happening. The A applying to air for 87 management. A ops A customer surveys. >> So this is what our Spurs could do. They can target big markets debt and go directly at either a specific differentiation. Whether it's experience or just a better mouse trap in this case could win, >> right? And one more thing we didn't talk about is where their underpants go after is the area number. Many of these abs are still enterprise abs. Nobody really focused on moving this enterprise after the club. Hollis Clubbers are still struggling with the thing. How can I move my workload number 10%. We're closing the club 90% still on track. So somebody needs to figure out how to migrate these clouds to the cloud really seamlessly. The Alps are gonna be born in the cloud club near the apse. So how do you address truckload in here? So there's enough opportunity to go after enterprise applications clouded your application. Yeah, >> I mean, I do buy the argument that they will still be on premises activity, but to your point will be stealing massive migration to the cloud either sunsetting absent being born the cloud or moving them over on Prem All in >> all the desert I keep telling the entree and follow the money. When there is a thing you look for it Is there a big market? Are people catering there? If people are dying and the old guard is there to your point and is that the new are you? God will happen. And if you can bet on the new guard in your experience, market will reward you. >> Where is the money? Follow the money. Worse. What do we follow? Show me where it is. Tell me where it is >> That all of the clothes, What is the big I mean, if you're not >> making money in the club for the cloud, you are a fool right now. If there any company on making out making in the club as a CEO, a board member, you need to think through it. Second automation whether you go r p a IittIe automation here to make money on, said his management. Whether it's from customer service to support the operation, you got to take the car. Start off it if you are Jesse ever today and you're not making birds that cementing. I see it mostly is that still don't want to take it back. They want to build empires. The message to see what's right, Nice. Either you do it or get out. Get the job to somebody that >> I hold a lot of sea cells and prayer. Preparing for reinforce Amazon's new security cloud security conference and overwhelmingly response from the sea. So's chief security officer is we are building stacks internally. When I asked him about multi cloud, you know what they said? Multi cloud is B s. I said, Why? Because Well, we have a secondary cloud, but I don't want to fork my development team. I want to keep my people focused on one cloud. It's Amazon. Go Amazon. It's azure. We stay with Azure. I don't wanna have three development teams. So this a trend to keep the stack building internally. That means they're investing in building their own text. Axe your thoughts on that >> look, I mean, that's again. There's no one size fits all. There will be some CEOs who want to have three different silos. Some people have a hard, gentle stack like I've seen companies. Right now. They write, the court wants it, compiles, and it's got an altar cloth. That's a new irritability you're not. We locate a stack for each of them. You're right. The court order to users and NATO service is but using the same court base. That's the whole The new startups are building it. If somebody's writing it like this, that's all we have. Thing is the CEO. So there's that. The news he always have to think through. How can you do? One court works on our clothes? >> Great. You do. Thank you for coming on again. Always great to get your commentary. I learned a lot from you as well. Appreciate it. I gotta ask the final question as you go around the VC circles. You don't need to mention any names you can if you want, but I want to get a taste of the market size of rounds, Seed Round A and B. What are hot rounds? What sizes of Siri's am seeing? Maur? No. 10,000,000? 15,000,000? Siri's >> A. >> Um >> Siri's bees are always harder to get than Siri's. A seeds. I always kind of easier. What's your take on the hot rounds that are hot right now. And what's the sizes of the >> very good question? So I'm in the series the most easy one, right? Your concept. But the seed sizes went up from 200 K to know mostly drones are 1,000,000 2 1,000,000 Most city says no oneto $10,000,000. So if you're a citizen calmly, you're not getting 10 to 15. Something's wrong because that become the norm because there's more easy money. It also helps entrepreneurs. You don't have to look for money. See, this beast are becoming $2025 $5,000,000 pounds, Siri sees. If you don't raise a $50,000,000 then that means you're in good company. So the minimum amount of dries 50,000,000 and CDC Then after that, you're really looking for expansions. $100,000,000 except >> you have private equity or secondary mortgage >> keys, market valuations, all the rent. So I tell entrepreneurs when there is an opportunity, if you have something, you can command the price. So if you're doing a serious be a $20,000,000 you should be commanding $100,000,000.150,000,000 dollars, 2,000,000 evaluations right if you're not other guys are getting that you're giving too much of your company, so you need to think through all of that. >> So serious bees at 100,000,000 >> good companies are much higher than that. That'll be 1 52 100 And again, this is a buyer's market. The underpinnings market. So he says, more money in the cash. Good players they're putting. Whether you have 1,000,000 revenue of 5,000,000 revenue, 10,000,000 series is the most hardest, but its commanding good premium >> good time to be in our prayers were with bubble. Always burst when it's a bite, mark it on the >> big money. Always start a company >> when the market busts. That's always my philosophy. Voodoo. Thanks for coming. I appreciate your insight. Always as usual. Great stuff way Do Sudhakar here on the Q investor friend of the Cube Entrepreneur, I'm John for your Thanks >> for watching. Thank you.

>> from Washington, D. C. It's the queue covering science logic. Symposium twenty nineteen. Brought to you by Science Logic. >> Hi, I'm student men and this is the Cubes coverage of Science Logic. Symposium twenty nineteen here at the Ritz Carlton in Washington, D. C. Been four hundred sixty. People here just finished the afternoon Kino, and they've actually gone off to the evening event. It's thie yet to be finished. Spy Museum. They get a good three sixty view of Washington D. C. So the hallways are a little echoing in quiet but really excited to have on the final guest of the day. Eric Gordon, who's the vice president of business development and alliances as science logic. Erik, thanks so much for joining me, >> thanks to you. Great to be here. >> All right, so busy. Dev and Alliances. I've talked to a number of your partner's. I've gone through a lot of things, but you wear, I think, just like your CEO. A few different hats. Ah, and your old let's let's get into what your role is that the company? >> Yeah, it's actually changed over time, but for the most part I've to court responsibilities. One is I'm looking after our ecosystem of technology partners. And so we have from key strategic CE that we work with in the marketplace, in the cloud space on the data center, all across the ecosystem, a lot of different technologies. But we also have products that we resell input on our priceless that combined to create a solution for our customers in the second half of what my responsible is really focused on. What is our product strategy around integration? Automation? Because those Air Corps components to our platform and I look after that with several different teams. >> So let's talk about that the ecosystem pit person, the alliances. Because I got a lot of shows. I talked to a lot of companies, and it's all too easy for companies to be like, Oh, we're we're the best and we do so many different things. And when I first heard about the space in a ops, it's like, Oh, well, I I Ops is replacing a lot of waves and, you know, your average customer replaces fourteen tools. I heard there's one customer who replaces fifty tools, but at the same time, there was a strong focus about integrations in deeper even some of the products that you say, Yeah, there's overlap in that competitive, you know, you're working with those environments, so give us a little bit of the philosophy, how you balance that, you know, we want to do it all and help our customers to do lots of different things. And especially when you get to big customers and service providers, we understand that it's a big world and there never is that, you know, mythical single pane of glass. >> Yeah, no, totally agree. And we hear this a lot. You know, I've got a tool for this. I got a tool for that and or I had to Vendor come in and say that they could do it all. And you know, really, At the end of the day, if there's there's no one vendor on DH, you know the Venn diagrams of functionalities, air overlapping. That's the nature of the industry. And when we saw this on the early days of it with the big monopolies. But I think right now it's it's around. How do we saw the customer problem? Mohr effectively, From our perspective, we look at the combination of things. First is is what solutions out there give us good data data that we can use data that we can enrich, how we can leverage that to help drive better insights from other types of data that we collect so that theirs is where integration is a keep part of this on DH. What we know is that ultimately in our space, we're doing about monitoring a core collection. We're goingto have to click with everybody, so we're gonna have to integrate with any partner that might have some form of I. P are connected through an I p address to some sort of a p I. We need that data. So we have partnerships on that side. I think really, what's interesting is when we think about things like workflow or orchestration or types of mediation, we might integrate with other technologies to enrich that data further. So we look for partners that ultimately our customers air using things that we can do consolidation and drive better outcome with that enrich date experience. >> Yes, so let's drill down one little bit if you talk about like, you know a PM and SM tools out there some recent announcements and and you digging deeper on there. What what are some of the highlights? So one >> thing is, if you already have, like, agents are often come up, Our customs says, Well, I've got an A P M. Agent that's already doing some things. Well, that's great. We can leverage that, that there's some good insight that we can gather from either to apologies or other metrics or like in user experience. But we also go deeper on other aspects, like on the network side or on the infrastructure side, or on the the cloud service aside. So, you know, ultimately, it's a conversation of say, what? What can we leverage? What, what's accurate, what's in real time? And if there's things that we can, you know, gather, then that's our primary strategy. So I you know, I do think the ecosystem plays a key role in a i ops, but really, to do that, it's run automation because anything that we do, we have to do with scale and we have to do with security. We have to do it with the intent of driving some form of outcome. And so, you know, those are the key principles behind selecting technology partners. >> Okay, Let's talk some about that automation. It was a big discussion in the keynote this morning. Really talking about the maturity model. One of the analysts up there says you really want to make sure you separate things like, you know, the machine learning piece of it with the automation. The observation I've made a couple of times is, you know, yes. We all know you can automate a really bad process. And so I need toe, you know, make sure, you know, do I have good data And, you know, how am I making automation make me better Not just, you know, to change things. >> Yeah, well, I think it's Science Lodge that we look at. Automation is in every part of what we do within the product. From the from the collection of how we automate it scale how we consolidate that data. And then we're doing a lot of the data preparation using automation technologies. And then when we start to analyze and enrich that data, we're also using it Other algorithmic approaches, for example, topology and context. So if we know that some things connected weaken Dr An automation to make an inference and that data then feeds into the final step, which is around how we action on that. So we drive automation in the classic sense to say trigger workflow or, let's say, update another system of record or system of truth like a C M G B or a notification. And so one of things that we did hear from Garden this morning is engaging in an SM process. Is a core part of AI ai ops as muchas data collection and driving other forms of automation. >> All right, Do you have some examples of you know how automation you're helping your customers love any customer stories you've got along that line? >> Well, >> really. You know, there's so many stories we're hearing the halls of Symposium, and so it's it's it's hard to pick one, but, you know, I think all ten times what we say is, what what's driving your service desk time like you've got people you know, looking at all of these different dispirit systems, and we can look at it. Let's say a top end of your most sort of frequented events or alerts, or even look at your top service desk incidents and say, How could we automate that, you know. And some of that automation could be at the technology level, you know, simplest as restarting a service or prove you re provisioning of'Em. Or it could be clearing a log or even maybe shutting down an event because it's irrelevant. So there's There's several different examples in the cloud as well. Terms of how things air provisioning attached. And if we see something out of a policy, we can alarm that say, hey, maybe my storage costs are going to accelerate because someone made a bad change. So there's different ways that we can apply automation during the life cycle. But I think enhancing the service management component perhaps is one of the most impactful ones, >> you know. So, Eric, we azan industry automation been something we've been talking about for quite a while now, and they're they're sometimes pushback of, you know, from the end, users especially, you know, some of the practitioners out there as you know. Well, I could do it better. You know, the fear that you're going to lose your job. How are you seeing that progressing and you know, how were things different today? Both from a technology standpoint, as well as from your customers. Can't wait. >> I think if you asked any enterprise CIA already service provider, service delivery manager, they'd always say, I'd love to operate as much as I can when you get down on the practitioner level. You know, obviously I think there's some sort. Like I I do my job, Thank you very much. I have my favorite wit, my process. So I think there's a conversation depending on. You know, if we're saying hey from the practitioner side, is there set of data that you need or set of scripts? Or are things that you're doing manually that we can put into a workflow? And at the at the business layer, it's like, Do you feel like you're getting the value from some of the investments you've made? And is, how is automation? Help you realize that an example there is. We see oftentimes is around the quality of data that's going into the C, M. D. B and from AA AA. Lot of times we see that their investment in technology is like service now, and other platforms is fairly high expense, and they want to optimize that, and they want to realize the power of automation at the at the service level. So if we can, if we can convince, if you will, through a set of really concrete use cases that the data coming from science logic at the speed and the quality can actually improve the seemed to be to >> the level of >> really efficient automation. All of a sudden, people start to see that as a change as an opportunity. And that's where I think a I Ops is helping change the narrative, to say how automation Khun B really, really applied rather than just being this mystical concept that is hard to do. And, you know, people don't liketo think that a robot's taking their job. I think what's gonna happen is that machine learning algorithms are going to make jobs easier and, you know, ultimately were far, far from the point where a ized doing something and some sort of, you know, crazy automata way. But I think it's the deep learning, moving a machine learning to you. No good quality data sets that dr meaningful insights that's giving us a lot better view until where automation could play in the >> future. Yeah, absolutely. It's our belief that you know, automation. There's certain things that you probably don't want to do because repetitive, it's boring or mistake prone on DH. Therefore, you know automation can really help those environments move forward. You could move up the stack. You can manage those environment. There's definitely some retraining that that needs to happen often. But you know that the danger is if you're if you're doing now what you were doing five years ago, chances are your competition is moving along and, you know, finding a better way to do it. >> You know, just a point on this soup is really around the velocity of data that's coming in. So we're seeing, you know, we talked about the three bees. You know, the volume of data. You have to use automation to be able to manage that huge amount of different data sources, the variety. There's no human that can process the amount of machine information from the amount of technologies that you have on DH that you know. Obviously it's speed, right. The velocity and that is that is clearly not going to be something that any human could be capable of doing. And so there's a relationship here between technology and human processes and science logics and a really interesting position right now to really kind of help with that process. But more importantly, accelerate the value by being all to process it and make it intelligent. >> Wait, Erica, you're saying I'm not neo from the Matrix and I can't, you know, read through everything and be able to move faster than physics allows. Give >> yourself maybe fifteen, twenty years. We might be. You know that that you know, I don't think that that many people can really predict the impact of the you know, we'LL say machinery, evolving toe, artificial intelligence and there's it's going to be very used, case specific. But we do know one thing is that algorithms? Air helping. But algorithms are dependent on that clean data stack, right? And And if you can't handle the scale, then obviously there's going. It's going to be minimized in terms. Is total utility >> alright? Well, Eric, I get the good to let you give us that the final word from science logic from Symposium twenty nineteen on the Cube. >> So you know, the first thing is is this is there's two things that we learned from this event. The first thing is, is how our customers you're evolving in this dynamic space. And what we know is that if if you don't change, it's going to be a problem. Because the only consistent thing is change and change is happening faster on it. And we call that disruption. And so what we want to do is we want to understand how science AJ is a technology company. I can really help that customer go through that transition with confidence. And then, more importantly, is what could we do? Delivering better, more enrich solutions to our customers that actually are changing the way the game is played. And so we feel like we're a disrupter in the A ops market. We are. Certainly Forrester has helped us recognize that. But But we're not done work. We're continuing on this journey. >> All right, Well, Eric, routine. Thank you so much for sharing your insights and the journey towards Aye, Aye, Ops. Thanks so much to. All right. Well, that comes to an end of what we're doing here at science Logic. Symposium twenty nineteen. I know. I learned a lot. I hope you did too. I'm stew Minutemen. Thanks so much from our whole crew. Here it's Silicon Angle Media's The Cube. Check out the cube dot net for all the videos from this show, as well as where we'LL be in the future. Reach out if you have any questions and once again, thanks for joining us.

>> Live, from Washington, D.C. It's theCUBE, covering the AWS Public Sector Summit 2018. Brought to you by Amazon Web Services, and its ecosystem partners. (futuristic music) >> Hey, welcome back everyone. We're live in Washington, D.C. for Amazon Web Services Public Sector Summit. This is their big show for the public sector. It's like a mini reinvent for specifically the public sector. I'm John Furrier, your host, with Stu Miniman, my co-host this segment, and Stewart Mclaurin, president of the White House Historic Association, is our guest. I heard him speak last night at a private dinner with Teresa Carlson and their top customers. Great story here, Amazon success story, but I think something more we can all relate to. Stewart, thank you for joining us and taking the time, appreciate it. >> Thanks John, it's just great to be with you. >> Okay, so let's jump into it; what's your story? You work for the White House Historical Association, which means you preserve stuff? Or, you provide access? Tell the story. >> Well, we have a great and largely untold story, and a part of our partnership with Amazon Web Services is to blow that open so more people know who we are and what we do, and have access to the White House, because it's the people's house. It doesn't belong to any one particular president; it's your house. We were founded in 1961 by First Lady Jacqueline Kennedy, who realized that the White House needed a nonprofit, nonpartisan partner. We have no government funding whatsoever, completely private. So we fund the acquisition of art, furnishings, decorative arts for the White House, if a new rug is needed, or new draperies are needed on the State Floor, or a frame needs to be regilded. We also acquire the china, the presidential and first lady portraits that are done; we fund those. But more importantly, in my view, is our education mission that Mrs. Kennedy also started, to teach and tell the stories of White House history going back to 1792, when George Washington selected that plot of land and the architect to build that house that we know today. So we unpack those stories through publications, programs, lectures, symposia, and now this new multifaceted partnership with AWS. >> Let's talk about, first of all, a great mission. This is the people's house; I love that. But it's always the secret cloak and dagger, kind of what's going on in there? The tours are not always, they're probably packed when people go through there, but the average person on the street doesn't have access. >> Sure, well, your cable news channels handle the politics and the policy of the place. We handle the building and the history, and all that's taken place there, including innovation and technology. If you think of Thomas Edison and Alexander Graham Bell, and others that evolved their early technologies through the White House, about 500,000 people get a chance to go through the White House every year. And when you think about in that small space, the president and his family lives, the president and his staff work, it's the ceremonial stage upon which our most important visitors are received, and then about 500,000 people schlep through, so you imagine 500,000 people that are going through your house, and all of that takes place. But it's very important to us for people to be able to see up close and personal, and walk through these spaces where Lincoln walked, and Roosevelt worked. >> Is that what the book you have, and share the book 'cause it's really historic, and the app that you have with Amazon, I think this is a great-- >> Sure, this is a real prize from our office. Mrs. Kennedy wanted us to teach and tell the stories of White House history, and so the first thing she wanted was a guide book, because the White House never had one. So in 1962, she published this guide book with us, and this is her actual copy. Her hands held this book. This was her copy of the book. Now, we continue to update this. It's now in its 24th edition, and each new edition has the latest renovations and updates that the latest president has added. But it's now 2018. So books are great, but we want to be able to impart this information and experience to people not only around Washington, who are going through the White House, but across the country and around the world. So this app that we've developed, you get through WHExperience at the App Store, you have three different tours. If you're walking through the White House, tours are self-guided, so unless you know what you're looking at, you don't know what you're looking at. So you can hold up an image, you can see, it brings to life for you everything that you're looking at in every room. Two other types of tours; if you're outside the White House in President's Park, it will unpack and open the doors of these rooms for you virtually, so you can see the Oval Office, and the Cabinet Room, and the Blue Room, and the Green Room. If you're around the world, there's a third tour experience, but the best part of it is, empowered by Amazon recognition technology, and it allows people to take a selfie, and it analyzes that selfie against all presidential portraits and first lady portraits, and the spatial features of your face, and it will tell you you're 47% Ronald Reagan, or 27% Jackie Kennedy, and people have a lot of fun with that part of the app. >> (laughs) That's awesome. >> Stewart, fascinating stuff. You know, when I go to a museum a lot of times, it's like, oh, the book was something you get on the way home, because maybe you couldn't take photos, or the book has beautiful photos. Can you speak a little bit about how the technology's making the tours a little bit more interactive? >> Sure, well we love books, and we'll publish six hardbound books this year on the history of the White House, and those are all available at our website, whitehousehistory.org. But the three facets of technology that we're adapting with Amazon, it's the app that I've spoken about, and that has the fun gamification element of portrait analysis, but it also takes you in a deeper depth in each room, even more so than the book does. And we can update it for seasons, like we'll update it for the Fall Garden Tour, we'll update it for the Christmas decorations, we'll update it for the Easter Egg Roll. But another part of the partnership is our digital library. We have tens of thousands of images of the White House that have literally been in a domestic freezer, frozen for decades, and with AWS, we're unpacking those and digitizing them, and it's like bringing history to life for the first time. We're seeing photographs of Kennedy, Johnson, other presidents, that haven't been seen by anybody in decades, and those are becoming available through our digital library. And then third, we're launching here a chatbot, so that through a Lex and Polly technology, AWS technology, you'll be able to go to Alexa and ask questions about White House history and the spaces in the White House, or keyboard to our website and ask those questions as well. >> It's going to open up a lot of windows to the young folks in education too. >> It is. >> It's like you're one command away; Hey, Alexa! >> It takes a one-dimensional picture off of a page, or off of a website, and it gives the user an experience of touring the White House. >> Talk about your vision around modernization. We just had a conversation with the CEO of Tellus, when we're talking about government has a modernization approach, and I think Obama really put the stake in the ground on that; former President Obama. And that means something to a lot of people, for you guys it's extending it forward. But your digital strategy is about bringing the experience digitally online from historical documents, and then going forward. So is there plans in the future, for virtual reality and augmented reality, where I can pop in and-- >> That's right. We're looking to evolve the app, and to do other things that are AR and VR focused, and keep it cool and fun, but we're here in a space that's all about the future. I was talking at this wonderful talk last night, about hundreds of thousands of people living and working on Mars, and that's really great. But we all need to remember our history and our roots. History applies to no matter what field you're in, medicine, law, technology; knowing your history, knowing the history of this house, and what it means to our country. There are billions of people around the world that know what this symbol means, this White House. And those are billions of people who will never come to our country, and certainly never visit the White House. Most of them won't even meet an American, but through this app, they'll be able to go into the doors of the White House and understand it more fully. >> Build a community around it too; is there any online social component? You guys looking around that at all? >> All of this is just launched, and so we do want to build some interactive, because it's important for us to know who these people are. One simple thing we're doing with that now, is we're asking people to socially post and tag us on these comparative pictures they take with presidents and first ladies. So there's been some fun from that. >> So Stewart, one of the things I've found interesting is your association, about 50 people, and what you were telling me off-camera, there's not a single really IT person inside there, so walk us through a little bit about how this partnership began, who helps you through all of these technical decisions, and how you do some pretty fun tech on your space. >> Unfortunately, a lot of historical organizations are a little dusty, or at least perceived to be that way. And so we want to be a first mover in this space, and an influencer of our peer institutions. Later this summer, we're convening 200 presidential sites from around the country, libraries, birthplaces, childhood homes, and we're going to share with them the experience that we've had with AWS. We'll partner or collaborate with them like we're already doing with some, like the Lincoln Library in Illinois, where we have a digitization partnership with them. So with us, it's about collaboration and partnership. We are content rich, but we are reach-challenged, and a way to extend our reach and influence is through wonderful partnerships like AWS, and so that's what we're doing. Now another thing we get with AWS is we're not just hiring an IT vendor of some type. They know our mission, they appreciate our mission, and they support our mission. Teresa Carlson was at the White House with us last Friday, and she had the app, and she was going through and looking at things, and it came to life for her in a new real and fresh way, and she'd been to the White House many times on business. >> That's great; great story. And the thing is, it's very inspirational on getting these other historic sites online. It's interesting. It's a digital library, it's a digital version. So, super good. Content rich, reach-challenged; I love that line. What else is going on? Who funds you guys? How do you make it all work? Who pays the bills? Do you guys do donations, is it philanthropy, is it-- >> We do traditional philanthropy, and we'd love for anybody to engage us in that. During the Reagan Administration in 1981, someone had the brilliant idea, now if I'd been in the room when this happened, I probably would have said, "Okay, fine, do that." But thank goodness we did, because it has funded our organization all these years. And that's the creation of the annual, official White House Christmas ornament, and we feature a different president each year sequentially so we don't have to make a political decision. This year, it's Harry Truman, and that ornament comes with a booklet, and it has elements of that ornament that talk about those years in the White House. So with Truman, it depicts the south balcony, the Truman Balcony on the south portico. The Truman seal that eventually evolved into being the Presidential Seal. On the reverse is the Truman Blue Room of the White House. So these are teaching tools, and we sell a lot of those ornaments. People collect them; once you start, you can't stop. A very traditional thing, but it's an important thing, and that's been a lifeblood. Actually, Teresa Carlson chairs our National Council on White House History. John Wood, that you just had on before me, is on our National Council on White House History. These are some of our strong financial supporters who believe in our mission, and who are collaborating it with us on innovative ways, and it's great to have them involved with us because it brings life in new ways, rather than just paper books. >> Stewart, I had a non-technical question for you. According to your mission, you also obtained pieces. I'm curious; what's the mission these days? What sort of things are you pulling in? >> Well, there's a curator in the White House. It's a government employee that actually manages the White House collection. Before President and Mrs. Kennedy came into the White House, a new president could come in and get rid of anything they wanted to, and they did. That's how they funded the new, by selling the old. That's not the case anymore. With the Kennedys, there's a White House collection, like a museum, and so we'll work with the White House and take their requests. For example, a recent acquisition was an Alma Thomas painting. Alma Thomas is the first African American female artist to have a work in the White House collection; a very important addition. And to have a work in the White House collection, the artist should be deceased and the work over 25 years old, so we're getting more of the 21st century. The great artists of the American 20th century are becoming eligible to have their works in the collection. >> Stewart, thanks so much for coming on theCUBE and sharing your story. It's good to see you speak, and thanks for the ornament we got last night. >> Sure. Well, you've teased this ornament. Everybody's going to want and need one now, so go to whitehousehistory.org. >> John, come on, you have to tell the audience who you got face matched recognition with on the app. >> So who did you get face matched with? >> I think I'm 20% James Buchanan, but you got the Gipper. >> I'm Ronald Reagan. Supply-side economics, trickle-down, what do they call it? Voodoo economics, was his famous thing? >> That's right. >> He had good hair, John. >> Well, you know, our job is to be story tellers, and thank you for letting us share a little bit of our story here today. We love to make good friends through our social channels, and I hope everyone will download this app and enjoy visiting the White House. >> We will help with the reach side and promote your mission. Love the mission, love history, love the digital convergence while preserving and maintaining the great history of the United States. And a great, good tool. It's going to open up-- >> Amazon gave us these stickers for everybody who had downloaded the app, so I'm officially giving you your downloaded app sticker to wear. Stu, this is yours. >> Thank you so much. >> Thanks guys, really appreciate it. >> Thank so much, great mission. Check out the White House-- >> Historical Association. >> Historicalassociation.org, and get the White House app, which is WHExperience on the App Store. >> That's right. >> Okay, thanks so much. Be back with more, stay with us. Live coverage here at AWS, Amazon Web Services Public Sector Summit. We'll be right back. (futuristic music)