(Caribbean music) >> Narrator: Live, from San Juan, Puerto Rico. It's theCUBE, covering Blockchain Unbound. Brought to you by Blockchain Industries. >> Hello, welcome back everyone. I'm John Furrier, co-host of theCUBE. Exclusive coverage here in Puerto Rico for Blockchain Unbound, it's a global conference where a lot of the leaders are coming together. It's our second day of wall-to-wall coverage. Talking to all the top people: government officials, entrepreneurs, investors, and tons of great action here. Our next guest is Marcus Levin who's the co-founder of XYO Network, xyo.network is the URL. Interesting opportunity really built from the ground up. No outside funding, although it does some interesting things with their community. Great IoT example, great use of the cloud, great example of how real entrepreneurs are working with crypto and blockchain to actually grow. Welcome to theCUBE. >> Thank you, John. >> So, tell me a little bit about what you guys do. Take a minute to explain to the audience what XYO Network is, how did you get here, what is it all about? >> Yeah, sure. So, XYO Network is the world's first decentralized location oracle. "Oracle" means data input into smart contracts. Now you have the problem that a lot of data sources are centralized and hackable or spoofable. So, if you make a bet, for example, you need to look at the results of the bet at a website, the website could be hacked, it could collude with someone to provide wrong data. The same problem exists with GPS. GPS is easily spoofable and hackable, like during the Pokemon Go craze, for example, all the kids just downloaded GPS spoofing apps, they get all the rare Pokemons. Or, allegedly the Iranians took down an American drone a few years back sending up a wrong GPS signal. The drone just landed. So, because of that, you can't do transactions based on location data. Today, most applications for location, GPS location, are navigational but not transactional. We solve this by providing a decentralized location data or network. We do this though IoT devices, mobile phone apps, and other types of partnerships. We are around since 2012. Started as an IoT company which provided location beacons, we call it XY Findit. We have about a million of them out there, and they can recognize each other's location. It's like us two taking a selfie together, we print out two copies, put our signatures on there. When we leave each other, we can prove that were here together. And it's the same thing with those devices. Our own devices but also with partnerships we build this mobile app distributors and IoT companies. What can you do with this? You could, for example, do payment up and delivery for e-commerce. So, you could put a chip, a small chip like an RFID chip into Amazon packaging tape. Once the package arrives at your doorstep, or even in your house, the payment gets triggered. It works by the doorbell, your Tesla in the driveway, your neighbor's cell phone, any type of connected device recognizing that the package is there. The payment automatically gets triggered. One third of Americans experienced porch theft in 2016. You don't know if it was a UPS driver, for example, scanning the package but taking it, or your neighbor took the package, or someone random came by. This way, you can prevent porch theft, or you can discover it. Or you could make sure your kids arrived safely at school, they arrived there with their friends and they took the path you wanted them to take. Or hotel review sites, for example, have the problem that they lose their users because they don't believe that the reviews are real anymore. But if you could prove someone flew from San Diego, that's where we're based, to Puerto Rico, has stayed at this hotel for tonight, and then flew back and wrote the review about it, suddenly you have a location-verified review. So, that's all today, but in the world, in five to ten years, full of AI, robots, self-driving cars, drones, smart cities, you need transactional location data and nobody's providing that today and we want to be the center of the future. >> Awesome. So, that's super-exciting, I got to ask you about the IoT piece because, do you need physical devices out there? Are you going to be deploying sensors? Are you leveraging pre-existing infrastructure? I love that selfie example. I can imagine we do a selfie, share it, it's a location-based opportunity. The phone's got location base. How do you guys interface with this? How does it work? >> Right now the network builds on top of our own devices. We are around since 2012, as I said, so we have a large network already. We are an existing company, it's a little rare in the blockchain space. >> Yeah. >> And we build partnerships now with IoT companies like certain light bulb division company, or fridges, all connected devices, mobile app distributors. >> So, you're providing your customers the IoT device folks who are proliferating out there. >> Yeah, we put our code basically out there. We can-- >> Open source? >> Open source, yeah. >> Okay. >> And you can plug it as an SDK into, let's say, your mobile app. Or you can use it as a monetization tool as well, because you earn tokens as you verify location, and this data is part an answer, and so you could earn XYO tokens, as you become-- We call them "sentinels", location verification device in our network. >> So, how do you guys tie this together on the token side? So, you reward, what behavior do you reward with a token? >> There are four components in our network. There's the sentinel, as I spoke about, which are the IoT devices or mobile phones which verify the location. Then you have bridges which relay the data. They relay it into something we call the archivist, which is a distributed computer system, if you are familiar with storage here in this space, for example, or the old system, like Sentient home from Berkeley, it works like that. So, the data's on people's personal computers. And then we have something we call the diviner algorithm, which provides the answers. It works like mining. So, you might want to ask, "Where's my package right now?" And the question gets sent to the network, a bunch of diviners, which works like mining, Ethereum, transactional things. A bunch of diviners will take the data from the archivist, the distributed computer system, and try to find the best answer and try to find as close as possible the consensus as they can. >> What about spoofing? I mean, people might want to spoof the location. >> Yes. >> How do you prevent spoofing? >> Yeah, that's a good question. So, we two could collude pretty easily. But if this entire room of people is who you usually don't know, it's very difficult to collude. So, one of them is scale. Then we build reputation over time. So, as your answers are probable, you build reputation. For example, if all us say we are here at this hotel right now, but you say, "No, we are in Shanghai," your answer is improbable and your reputation goes down. In addition to that, we disincentivize lying-- >> You're very data-driven. >> Extremely. >> This is big time analytics. >> Extremely data-driven. >> So, what are you guys doing for analytics and what chain are you using? 'Cause performance becomes an issue. >> Yep. >> How's the plumbing work? What's the analytics look like? Take a minute to explain that. >> Yeah, it's very beautiful. We have our own chain: the XYO main chain. So, we are an oracle which plugs into any type of smart contract. You know, you have Ethereum and about 19 other coins which have smart contracts. So, we build on our chain to lower the transaction costs, transaction times, and build a more reliable network for ourselves and then it plugs into all other smart contracts. >> So, you have your own chain to manage this? >> Yes. >> So, that's one of the reasons why you, from an operational standpoint, you want to lock that down. >> Yes. >> So you can control performance. >> Exactly. >> Latency, timestamps, security, whatnot. >> Exactly, that's right. >> The openness is for the smart contracts. Is that what you're saying? >> Yeah. >> I can do any smart contract I want. >> This is basically for old site developers it's like an API, you can plug into it-- >> Got it. >> We connect the real world with the blockchain. So, right now you have very limited applications for blockchain in a lot of cases because you can't take offline things and connect them to the chain. What we allow to do is, we call it the API to the real world, where you take location data, put it into the chain and make it transactional. >> So, I got to ask you a question. This is interesting, I love this, I want to get into more of the token sale and what you guys are doing raising money. In the IoT world, certainly with cloud computing, the big debate is, do you move compute to the edge where the data is, or do you move the data back to the centralized cloud? Here, since you're decentralized with the IoT device, is the data coming back to your central network, or-- >> No, it's not. >> Where is the processing at? At the edge? What's the edge equation? Explain that. >> So, everything is decentralized. We believe that our company doesn't need to necessarily exist in a few years and the network will live on and grow as we grow the community, so the community is very important to us. The devices are decentralized, you own your cell phone. The data storage is decentralized. So, you can define, like, 3% of my personal computing power goes to this, for example, you earn XYO tokens. The mining is decentralized like any mining is decentralized today, so us as a company, once people start to build on the platform, we don't need to exist, which makes it beautiful, right? This is what blockchain is all about. Decentralizing and building this platform layer where people can build on top of. >> So, there's a ton of Bluetooth and GPS out there. >> Yep. >> Talk about where you guys have got your traction. I want you to take a minute to explain. We kind of went off on a tangent on some IoT rant, there, I was interested in. But I want to take it back to mainstream. >> Okay. >> There's GPS out there, you've got Bluetooth, everyone's got Bluetooth devices. So, it's not like this is massive new, it's a requirement. >> Yeah. >> You guys did some interesting things how you funded your first token sale. >> Right. >> You have customers. You've been around for how long? >> 2012. >> 2012. You've been successful. No outside capital. >> Yeah. >> So, you bootstrapped. You made things happen. Had some revenue come in. How'd you do it? Take us through that progression. >> Yeah, so we co-founders worked in various ventures together previously and one of our co-founders, the main founder I would say, Arie Trouw, he started this company in 2012, and we bootstrapped it with seven million dollars of our own cash and one and a half million in venture debt. We really believe in what we do. >> You guys put up a lot of capital. >> Yes. >> Congratulations. >> We believe in what we do. We believe in our capabilities to attract the right teams, we have an amazing team. >> That's skin in the game. >> It's skin in the game and it's actually a low-risk investment for me because I know what we are capable of. >> You are underwriting your own competence. >> Exactly, exactly. >> Okay, so, you had seven million of your own cash. Did you pass the hat around, you all kind of contributed money in, or? >> It was mostly from Arie, actually. (laughs) But we all have skin in the game there. >> So, you have a community, then you launch your idea, what happened next? >> Exactly. So, then the VCs started to come. We did some outreach, VCs started to come, they're interested in our idea, you know, they love what we do. Platform is right, quite sexy right now. In blockchain we are a platform and you can build a lot on top of it. We pushed off the VCs and we said we want to take community money first. The reason is, we believe in building this strong community of evangelists, people who believe in us, who want to code with us. We went to all the developer conferences, not to, like, investor conferences, or something like that. And, so, we marketed to about 2,300 people, our token sale and a little under 500 people put some Ethereum into our token sale and 95% were under 5 ETH. That was a very global community. >> Was that a utility token sale? >> Yes. >> Outside the US, 'cause there's credited investors involved, or what was the-- >> It's clearly a utility token, because you can build on top of it. Last weekend, the city of San Diego and 120 hackers, a IoT company, were in our office to build on top of our chain, traffic flow and parking solutions for the city of San Diego. So, it's clearly a utility token but because of the uncertain regulatory environment we are actually running it like it's a security, so, we have a Reg A, Reg D, Reg S, whatever, we have 115 different jurisdictions we look at, I spoke during the whole process, I'm not lying, it's-- >> That's a lot of work. >> Yeah. 23 lawyers I spoke with. It's a lot of hours with lawyers on the phone. The most aggressive on of them, she suggested to me a structure with no taxes but 20% prison potential, I think. (laughs) On the other side-- >> It's a good cause. You're doing it right. So you spent a lot of money to make sure that your community was involved. >> Yes. And they weren't throwing a lot of money, like they're millionaires, they're like, let's throw a thousand dollars? >> Yep. >> That kind of numbers. >> Yes, exactly. >> So, it's not like you're breaking the bank but they feel ownership. >> Absolutely. If you look at our telegram channel-- >> And you've raised, what, a million, two million, three million, from that? >> One point seven. >> From the community? >> Only community, those 400 people. We had it open for five to six days. We closed it down. We didn't take any money anymore. And since yesterday, I started talking with institutionals again and now we are a sexy story so now they come again, right? (laughs) >> Platforms are sexy. >> Exactly. >> We know, we have one, too. >> (laughs) That's awesome. Love your project. >> Well, the thing about platforms is that, as you know, we talked about last night, is that the platform wars and the platform entrepreneurial thinking has radically changed. In the old days, it was, I've got a platform and I'm going to monetize my platform for my application. Look at Facebook. >> Right. >> They monetize their platform data for advertisers, not users. I am a Google search engine, I need to make the best search result so I can get better advertising. And search results, thats a part. But the new order is the platform value goes to the users or customers. >> Right, right. That's right. >> So not... >> We are not rent-seeking. >> This is an open model with platforming. >> 100% open. There is a lot of the platforms are rent-seeking, where a certain percent of each transaction goes to the company or to some founders or something. We don't have that at all. So, what we do, for every token we sell, we allocate one to the company and after the token sale there is not going to be ever more XYO tokens ever again. And we use our portion to build this network but we don't take any fees or anything there. >> How do you make money? >> Building partnerships with companies, helping them to build on top of the chain, building the community. >> At some point you need to take a small cut of something, right? >> Yeah, if we own half the tokens, hopefully there is some value. >> They could be-- okay, so you'll get the token opportunity? >> Yes. >> So, on the security token, do the investors, the community and now token holders, is that an equity security token, so they own the company through the tokens, right? Non-dilutive, non-voting equity, is that what you're thinking? >> Yeah, it's not an equity token. It's still in our mind a utility token but we do something very interesting. During the token sale event, we are going to launch an equity sale at the same time. So, you can decide if you are comfortable in the blockchain space, you know, all you want to be an equity investor. The disadvantage is you have less liquidity there but you have all the protections an equity gives you. We are a California-based company. It was audited financial since 2012. SEC-qualified and regulated, so equity in our case is a kind of sexy kind of thing. >> Yeah, and they have the long game. They're betting on acquisition or something else. >> Basically. >> Oh, well, they've got to get some revenue going. Well, what's next? What are you guys doing? Token sale done, is it working? What, is it going on now, let me just check it out. You've completed it? >> No, it's going to start on March 20th. It's going to run for two months until May 20th and so now it's a lot of travel, speaking with people, engaging. >> (laughs) >> Yeah, that's next. >> Well, congratulations. >> Thank you. >> So glad that Carrie on Facebook notified me of you guys. Super-impressed with what you're doing and we had a great conversation last night at the monetize roof party. Great to know you guys. I think IoT really needs this kind of model because there's a lot of real critical challenges around the role of data, the role of immutability. There's all kind of sensor devices out there, cameras, you can't go anywhere, digital cities are coming, smart cities. >> Right. >> Self-driving cars. It's going to be wired up, big time, so I think you guys got a good opportunity. Thanks for coming on theCUBE. This is John Furrier here in Puerto Rico for exclusive coverage of Blockchain Unbound. More after this short break. (electronic beats)

>>The Cube Presents HPD Discovered 2020 >>two. >>Brought to You by H. P E >>Good >>Morning Live from the Venetian Expo Centre Lisa Martin Day Volonte Day two of the Cubes Coverage of HP Discover 22 We've had some great conversations yesterday. Today, full day, a content coming your way. We've got one of our alumni back with us. Neil MacDonald joins us, the executive vice president and general manager of Compute at HPD Neale, Great to have you back on the Cube. >>It's great to be back. And how cool is it to be able to do this face to face again instead of on zoom. Right. So >>great. Great. The keynote yesterday absolutely packed, so refreshing to see that many people eager to hear what HP has been doing. It's been three years since we've all gotten together in person. >>It is, and we've been busy. We've been busy. We've got to share some great news yesterday about some of the work that we're doing with HB Green Lake Cloud Platform and really bringing together all the capabilities across the company in a very unified, cohesive way to enable our customers to embrace that as a service experience we committed to Antonio three years ago, said we were gonna deliver everything we do as a company as a service through Green Lake and we've done it. And it's fantastic to see the momentum that that's really building and how it's breaking down the silos from different types of infrastructure and offer to really create integrated solutions for our customers. So that's been a lot of fun. >>Give us the scope of your role, your areas of responsibility. And then I'd love to hear some feedback. You've been a couple of days here around customers. What some of the feedback help us understand that. >>So at HP, I lead the Compute business, which is our largest business. That includes our hardware and software and services in the compute space. Both, um, what flows through the green late model, but also what throws flows through a traditional purchase model. So, um, that's, uh, that's about $13 billion business for the company and the core of so much of what we do, and it's a real honour to be leading a business that's such a a legacy in a franchise with with 30 years of innovation for our customers in an ocean of followers. Um and it's great to be able to start to share some of the next chapters in that with our customers this week. >>Well, it's almost half the business H p e and as we've talked about, it's an awesome time to be in the computer business. What are you seeing in terms of the trends? Obviously you're all in on as a service. But some customers say, Tell me I got a lot of capital. Yeah, absolutely. I'm fine with Capex. What are you hearing from customers in that regard? And presumably you're happy to sell them in a kind of Capex model? >>Absolutely. And in the current environment, in particular with with some of the economic headwinds that we're starting to stare down here, it's really important for organisations to continue to transform digitally but to be able to match their investments with the revenues as they're building new services and new capabilities. And for some organisations, the challenge of investing all the Capex up front is a big lift and there's quite a delay before they can really monetise all of that. So the power of HP Green Lake is enabling them to match their investment in the infrastructure on a pay as you go basis with the actual revenue they're going to generate from their new capability. So for lots of people that works. But for many other customers, it's it's much more palatable to continue in a Capex purchase, but and we're delighted to do that. A lot of my business still is in that mode. What's changing the or what are the needs, whether you're in the green light environment or in the Capex environment? Um, increasingly, the edge has become a bigger and bigger part of all of our worlds, right, the edges where we all live and work. We've all seen over the last couple of years enormous change in how that work experience and how the shape of businesses has changed, and that creates some challenges for infrastructure. So one of the things that we've announced and we shared some more details of this week is HP Green Light for Computer Ops Management, which is a location agnostic, cloud based management set up that enables you to automate and lifecycle, manage your physical compute infrastructure wherever it lies, so that might be in a distributed environment in hotel locations or out at the edge for so much more data is now being gathered and has to be computed on. So we're really excited about that. And the great thing is because it's fully integrated with HP. Green Light Cloud Platform is in there alongside the storage, alongside the connectivity alongside all the other capabilities. And we can bring those together in a very cohesive infrastructure view for our customers and then build workloads and services and tops. And that's that's really exciting. How have >>your customer conversations evolved, especially over the last couple of years as the edge has exploded? But we've been living in such uncertain times. Are you seeing a change there in the stakeholders rising up the C suite stack in terms of how do we really fine tune this? Because we've got to be competitive. We've got to be a data company. >>Well, that's so true because everybody has seen seen data as a currency and is desperately innovating and Modernising their business model, and with it, the underlying infrastructure and how they think about development. And nowhere is that truer than in enterprises that really becoming digital. First, organisations more and more companies are doing their own in house full stack, cloud native development and pivoting hard from a more traditional view of in house enterprise i t. And in that regard, >>let's >>start to look a lot like a Saas company or a service provider in terms of the needs of the infrastructure you want linear performance scaling. You want to be very sensitive not just to the cost, as you call it, but also to the environmental cost and the power efficiency. And so yesterday we were really thrilled to announce the HBP Reliant are all 300 General Live in, which is the first of our general living platforms. And that's in partnership with Ampere is the first of several things that we're gonna go do together. We're looking forward to building out the rest of our Gen 11 portfolio broadly with all of our industry partners in the in the coming quarters. But we're thrilled about the feedback that we're starting to get from some of our customers about the gains in power efficiency that they're getting from using this new server line that we've developed with amber. >>So, you know, this is an area that I'm very interested in what I write about this a lot. So tell us the critical aspects of Gen 11, where ampere fits, is it is it being used for primarily offloads and there's a core share with us. So >>if you look at the opportunity here is really as a core compute tool for organisations that are doing that in house full snack cloud native development and in that environment, being able to do it with great power efficiency at a great cost point is the great combination. The maturity of the ecosystem, um, is really, really improving to the point where is much, much more accessible for those loads? And if you consider how the infrastructure evolves underneath it, the gains that you get from power efficiency multiply. It's a TCO benefit. It's obviously an environmental benefit, and we all have much, much more to do as an industry on that journey. But every little helps, and we're really excited about being able to bring that to market. The other thing that we've done is recognising the value that we bring in the prelim experience, everything with our integrated lights out management, all of the security, the, uh, hardware root of trust, the secure boot chains, all of that Reliant family values we brought to that platform, just as we do with our others. But we've also recognised that for some of our service provider customers, there's a lot of interest in leveraging open BMC and being able to integrate the management plane and control that in house and tie it to whatever orchestrations being done in the service product. So we have full support for open BMC out of the box out of the gate with Janna Levin. And that's one of the ways that we're evolving. Are offering to meet our customers where they are, including not just the assassin service providers but the enterprises who are starting to adopt more and more of those practises as they build out digital. First, >>tell us more about the architecture. If you would kneel. I mean, so where does ampere and that partnership add value? That's incremental to what you what you might think is a traditional server architecture. How's that evolving? >>Well, it's another alternative for certain workloads in that full stack in house proud Native Development model. Um, it's another choice. It's another option and something that's very excited about >>That's the right course for the horse, for the course that was back in internal development because it's just more efficient. It's lower power, more sustainable. All those things exactly. >>And the wonderful thing for us in the uh in this juncture in the market is there is so much architectural innovation. There are so many innovators out there in the industry creating different optimizations in technology with the lesson silicon or other aspects of the system. And that gives us a much broader palette to paint from as we meet our customers' needs as their businesses involving the requirements are evolving, we can be much more creative as we bring this all together. It's a real thrill to be able to bring some of these technologies into the HP reliant space because we've always felt that compute matters. We've always known that hardware matters, and we've been leading and innovating and meeting these needs as they've evolved over the decades, and it's really fun to be able to continue to do that. Hardware still >>matters. It doesn't matter. We know that here on the Cube, talk about the influence of the customer with so much architectural innovation. There's a lot of choice for customers in every industry. When you're in customer conversations, how are you helping them make decisions? One of the key differentiators that you articulate that's going to really help them achieve outcomes that they have to achieve? >>Well, I think that's exactly as you say. It's about the outcome. Too often, I think the conversation can get down into the lower level details of component, tree and technology and our philosophy. HP has always been focused on what it is that the customer is trying to achieve. How are they trying to serve their customers? What are their needs? And then we can bring an opinionated point of view on the best way to solve that problem, whether that's recommendations on the particular Capex, infrastructure and architecture to build or increasingly, the opportunity to serve that through HP Green Lake, either as hard or as a service. Or is HP Green Lake services further up the stack? Because when you start talking about what is the outcome you're trying to achieve, you have you have a much, much better opportunity to focus the technology to serve the business and not get wrapped up in managing the infrastructure and that's what we love to do. >>So where? Give us the telescope vision. Maybe not to tell a binocular vision as to where compute is going. We're clearly seeing more diversity in silicon. Uh, it's not just a you know x 86 CPU world anymore. There's all these other supporting components new workloads coming in. Where do you you mentioned Edge, whole new ballgame ai inference sing. And that was kind of new workloads, offloads and things of that. Where do you see it all going in the next 3 to 5 years? >>I think it's gonna be really, really exciting time because more and more of our data is getting captured to the edge. And because of the experiences that companies are trying to deliver and organisations are trying to deliver that requires more and more stories are more and more compute at the edge. The edge is not just about connectivity, and again, that's why with the F B green light cloud platform, the power of bringing together the connectivity with the compute with the storage with the other capabilities in that integrated way gives us the ability to serve that combined need at the edge in a very, very compelling way. The room moves a lot of friction and a lot of work for our customers. But as you see that happen, you're going to see more and more combining of functionalities. The silos are going to start to break down between different classes of building block in the data centre, and you've already seen shifts with more and more software to find more and more hybrid offerings running across a computing substrate. But perhaps delivering storage services are analytic services or other workloads, and you're gonna see that to conduct that continue to evolve. So it's gonna be very fun over the next few years to see that, uh, that diversification and a much more opinionated set of offers for particular use cases and workloads and at our job and value is going to be simplifying that complexity because choices great right up to the point where you're paralysed by too many choices. So the wonderful thing about the world that's been done here is that we're able to bring that opinionated point of view and help guide, and again it's all about starting with what are you trying to achieve. What are the outcomes you're trying to deliver? And if you start there were having a great time helping our customers find the right path forward. >>Wow, it sounds like a fun job. Talk to me about, you know, maybe one of your favourite examples that you really think articulates the value of of the choice and the opportunities that HP can deliver to customers, maybe favourite customer example where you think we really nailed it here and they're achieving some incredible outcomes. >>Well, we're really excited about this week as I was chatting with the CEO of Cloud Sigma, which is a global ideas and pass provider who's actually been using our new HP per client moral 300 general live in Are you on purpose? Server line? And, uh, their CEO was reporting to me yesterday that based on his benchmarking, they're seeing a significant improvement in power efficiency, and that's that's that's cool to an engineer. But what's even better is the next thing, he said. That's enabling them to deliver better cost to their customers and advanced their sustainability goals, which is such a core part of what we as an industry and we as society are going to have to continue to make stepwise progress against over the next decade in order to confront those challenges in the environment so that that's that's really fulfilling, not just to see the tech, which is always interesting to an engineer but actually see the impact that it's having an enabling that outcome foreclosed signal >>so many customers, including Cloud Sigma and customers in every industry. E S G is an incredibly important initiative. And so it's vital for companies that have a core focus on E. S G to partner with companies like HP who will help them facilitate that actually demonstrate outcomes to their own users. >>It's such an important journey and it's gonna be a journey of many steps together. But I think it's one of the most critical partnerships that as an industry and as an ecosystem, we still have a lot of work to do and we have to stay focused on it every day, continuing, moving the bar. >>You >>know, to your point about E. S G. You see these E s G reports. Now that they're unbelievable, the data that is in them and the responsibility that organisations mid and large organisations have to actually publish that and be held accountable. It's actually kind of daunting, but there's a lot of investments going on there. You're absolutely right. The >>accountability is key, and it's it's it's necessary to have an accountability partner and ecosystem that can facilitate that. Exactly. >>We just published last week our Own Living Progress report this year, talking about some of the steps that we're making the commitments that we pulled in in time. Um, and we're looking forward to continue to work on that with our customers and with the industry, because it's so critical that we make faster progress together on that >>last question. What's your favourite comment that you've heard the last couple of days being back in person with about 8000 customers, partners and execs? It's >>not. It's not the common. It's the sparkles in the eyes. It's the energy. It is so great to be back together, face to face. I think we, uh, we've soldiered through a couple of tough years. We've done a lot of things remotely together, but there's no substitute for being back together, and the energy is just palpable and it's it's fantastic to be able to share some of what we've been up to in the interim and see the excitement about getting adopted by customers and partners. >>I agree the energy has been fantastic. We were talking about that yesterday. You brought it today, Neil, Thank you so much for joining us. We're excited about Antonio coming up next, going to unpack all the announcements. Really good customers. Perspective from the top of H P E for Neil and Dave Volonte. I'm Lisa Martin joins us in just a few minutes as the CEO of HP, Antonio Neary joins us next.

(upbeat music) >> Hey everyone. Welcome back to theCUBE's live coverage of Women in Data Science, WiDS 2022, coming to live from Stanford University. I'm Lisa Martin. My next guest is here. Nandi Leslie, Doctor Nandi Leslie, Senior Engineering Fellow at Raytheon Technologies. Nandi, it's great to have you on the program. >> Oh it's my pleasure, thank you. >> This is your first WiDS you were saying before we went live. >> That's right. >> What's your take so far? >> I'm absolutely loving it. I love the comradery and the community of women in data science. You know, what more can you say? It's amazing. >> It is. It's amazing what they built since 2015, that this is now reaching 100,000 people 200 online event. It's a hybrid event. Of course, here we are in person, and the online event going on, but it's always an inspiring, energy-filled experience in my experience of WiDS. >> I'm thoroughly impressed at what the organizers have been able to accomplish. And it's amazing, that you know, you've been involved from the beginning. >> Yeah, yeah. Talk to me, so you're Senior Engineering Fellow at Raytheon. Talk to me a little bit about your role there and what you're doing. >> Well, my role is really to think about our customer's most challenging problems, primarily at the intersection of data science, and you know, the intersectional fields of applied mathematics, machine learning, cybersecurity. And then we have a plethora of government clients and commercial clients. And so what their needs are beyond those sub-fields as well, I address. >> And your background is mathematics. >> Yes. >> Have you always been a math fan? >> I have, I actually have loved math for many, many years. My dad is a mathematician, and he introduced me to, you know mathematical research and the sciences at a very early age. And so, yeah, I went on, I studied in a math degree at Howard undergrad, and then I went on to do my PhD at Princeton in applied math. And later did a postdoc in the math department at University of Maryland. >> And how long have you been with Raytheon? >> I've been with Raytheon about six years. Yeah, and before Raytheon, I worked at a small to midsize defense company, defense contracting company in the DC area, systems planning and analysis. And then prior to that, I taught in a math department where I also did my postdoc, at University of Maryland College Park. >> You have a really interesting background. I was doing some reading on you, and you have worked with the Navy. You've worked with very interesting organizations. Talk to the audience a little bit about your diverse background. >> Awesome yeah, I've worked with the Navy on submarine force security, and submarine tracking, and localization, sensor performance. Also with the Army and the Army Research Laboratory during research at the intersection of machine learning and cyber security. Also looking at game theoretic and graph theoretic approaches to understand network resilience and robustness. I've also supported Department of Homeland Security, and other government agencies, other governments, NATO. Yeah, so I've really been excited by the diverse problems that our various customers have you know, brought to us. >> Well, you get such great experience when you are able to work in different industries and different fields. And that really just really probably helps you have such a much diverse kind of diversity of thought with what you're doing even now with Raytheon. >> Yeah, it definitely does help me build like a portfolio of topics that I can address. And then when new problems emerge, then I can pull from a toolbox of capabilities. And, you know, the solutions that have previously been developed to address those wide array of problems, but then also innovate new solutions based on those experiences. So I've been really blessed to have those experiences. >> Talk to me about one of the things I heard this morning in the session I was able to attend before we came to set was about mentors and sponsors. And, you know, I actually didn't know the difference between that until a few years ago. But it's so important. Talk to me about some of the mentors you've had along the way that really helped you find your voice in research and development. >> Definitely, I mean, beyond just the mentorship of my my family and my parents, I've had amazing opportunities to meet with wonderful people, who've helped me navigate my career. One in particular, I can think of as and I'll name a number of folks, but Dr. Carlos Castillo-Chavez was one of my earlier mentors. I was an undergrad at Howard University. He encouraged me to apply to his summer research program in mathematical and theoretical biology, which was then at Cornell. And, you know, he just really developed an enthusiasm with me for applied mathematics. And for how it can be, mathematics that is, can be applied to epidemiological and theoretical immunological problems. And then I had an amazing mentor in my PhD advisor, Dr. Simon Levin at Princeton, who just continued to inspire me, in how to leverage mathematical approaches and computational thinking for ecological conservation problems. And then since then, I've had amazing mentors, you know through just a variety of people that I've met, through customers, who've inspired me to write these papers that you mentioned in the beginning. >> Yeah, you've written 55 different publications so far. 55 and counting I'm sure, right? >> Well, I hope so. I hope to continue to contribute to the conversation and the community, you know, within research, and specifically research that is computationally driven. That really is applicable to problems that we face, whether it's cyber security, or machine learning problems, or others in data science. >> What are some of the things, you're giving a a tech vision talk this afternoon. Talk to me a little bit about that, and maybe the top three takeaways you want the audience to leave with. >> Yeah, so my talk is entitled "Unsupervised Learning for Network Security, or Network Intrusion Detection" I believe. And essentially three key areas I want to convey are the following. That unsupervised learning, that is the mathematical and statistical approach, which tries to derive patterns from unlabeled data is a powerful one. And one can still innovate new algorithms in this area. Secondly, that network security, and specifically, anomaly detection, and anomaly-based methods can be really useful to discerning and ensuring, that there is information confidentiality, availability, and integrity in our data >> A CIA triad. >> There you go, you know. And so in addition to that, you know there is this wealth of data that's out there. It's coming at us quickly. You know, there are millions of packets to represent communications. And that data has, it's mixed, in terms of there's categorical or qualitative data, text data, along with numerical data. And it is streaming, right. And so we need methods that are efficient, and that are capable of being deployed real time, in order to detect these anomalies, which we hope are representative of malicious activities, and so that we can therefore alert on them and thwart them. >> It's so interesting that, you know, the amount of data that's being generated and collected is growing exponentially. There's also, you know, some concerning challenges, not just with respect to data that's reinforcing social biases, but also with cyber warfare. I mean, that's a huge challenge right now. We've seen from a cybersecurity perspective in the last couple of years during the pandemic, a massive explosion in anomalies, and in social engineering. And companies in every industry have to be super vigilant, and help the people understand how to interact with it, right. There's a human component. >> Oh, for sure. There's a huge human component. You know, there are these phishing attacks that are really a huge source of the vulnerability that corporations, governments, and universities face. And so to be able to close that gap and the understanding that each individual plays in the vulnerability of a network is key. And then also seeing the link between the network activities or the cyber realm, and physical systems, right. And so, you know, especially in cyber warfare as a remote cyber attack, unauthorized network activities can have real implications for physical systems. They can, you know, stop a vehicle from running properly in an autonomous vehicle. They can impact a SCADA system that's, you know there to provide HVAC for example. And much more grievous implications. And so, you know, definitely there's the human component. >> Yes, and humans being so vulnerable to those social engineering that goes on in those phishing attacks. And we've seen them get more and more personal, which is challenging. You talking about, you know, sensitive data, personally identifiable data, using that against someone in cyber warfare is a huge challenge. >> Oh yeah, certainly. And it's one that computational thinking and mathematics can be leveraged to better understand and to predict those patterns. And that's a very rich area for innovation. >> What would you say is the power of computational thinking in the industry? >> In industry at-large? >> At large. >> Yes, I think that it is such a benefit to, you know, a burgeoning scientist, if they want to get into industry. There's so many opportunities, because computational thinking is needed. We need to be more objective, and it provides that objectivity, and it's so needed right now. Especially with the emergence of data, and you know, across industries. So there are so many opportunities for data scientists, whether it's in aerospace and defense, like Raytheon or in the health industry. And we saw with the pandemic, the utility of mathematical modeling. There are just so many opportunities. >> Yeah, there's a lot of opportunities, and that's one of the themes I think, of WiDS, is just the opportunities, not just in data science, and for women. And there's obviously even high school girls that are here, which is so nice to see those young, fresh faces, but opportunities to build your own network and your own personal board of directors, your mentors, your sponsors. There's tremendous opportunity in data science, and it's really all encompassing, at least from my seat. >> Oh yeah, no I completely agree with that. >> What are some of the things that you've heard at this WiDS event that inspire you going, we're going in the right direction. If we think about International Women's Day tomorrow, "Breaking the Bias" is the theme, do you think we're on our way to breaking that bias? >> Definitely, you know, there was a panel today talking about the bias in data, and in a variety of fields, and how we are, you know discovering that bias, and creating solutions to address it. So there was that panel. There was another talk by a speaker from Pinterest, who had presented some solutions that her, and her team had derived to address bias there, in you know, image recognition and search. And so I think that we've realized this bias, and, you know, in AI ethics, not only in these topics that I've mentioned, but also in the implications for like getting a loan, so economic implications, as well. And so we're realizing those issues and bias now in AI, and we're addressing them. So I definitely am optimistic. I feel encouraged by the talks today at WiDS that you know, not only are we recognizing the issues, but we're creating solutions >> Right taking steps to remediate those, so that ultimately going forward. You know, we know it's not possible to have unbiased data. That's not humanly possible, or probably mathematically possible. But the steps that they're taking, they're going in the right direction. And a lot of it starts with awareness. >> Exactly. >> Of understanding there is bias in this data, regardless. All the people that are interacting with it, and touching it, and transforming it, and cleaning it, for example, that's all influencing the veracity of it. >> Oh, for sure. Exactly, you know, and I think that there are for sure solutions are being discussed here, papers written by some of the speakers here, that are driving the solutions to the mitigation of this bias and data problem. So I agree a hundred percent with you, that awareness is you know, half the battle, if not more. And then, you know, that drives creation of solutions >> And that's what we need the creation of solutions. Nandi, thank you so much for joining me today. It was a pleasure talking with you about what you're doing with Raytheon, what you've done and your path with mathematics, and what excites you about data science going forward. We appreciate your insights. >> Thank you so much. It was my pleasure. >> Good, for Nandi Leslie, I'm Lisa Martin. You're watching theCUBE's coverage of Women in Data Science 2022. Stick around, I'll be right back with my next guest. (upbeat flowing music)

>>President. >>Hello everyone and welcome to wien on 2021. My name is Dave Volonte and you're watching the cubes continuous coverage of the event. You know, VM is a company that made its mark riding the virtualization wave, but quite amazingly has continued to extend its product portfolio and catch the other major waves of the industry. Of course, we're talking about cloud backup. SaS data protection was one of the early players there making moves and containers. And this is the VM on power panel with me or Danny Allen, who is the Ceo and Senior vice president of product strategy at VM. Dave Russell is the vice President of enterprise Strategy, of course, said Vin and Rick Vanover, senior director of product strategy at VM. It's great to see you again. Welcome back to the cube. >>Good to be here. >>Well, it had to be here. >>Yeah, let's do it. >>Let's do this. So Danny, you know, we heard you kind of your keynotes and we saw the general sessions and uh sort of diving into the breakouts. But the thing that jumps out to me is this growth rate that you're on. Uh you know, many companies and we've seen this throughout the industry have really struggled, you know, moving from the traditional on prem model to an an A. R. R. Model. Uh they've had challenges doing so the, I mean, you're not a public company, but you're quite transparent and a lot of your numbers 25% a our our growth year of a year in the last quarter, You know, 400,000 plus customers. You're talking about huge numbers of downloads of backup and replication Danny. So what are your big takeaways from the last, You know, 6-12 months? I know it was a strange year obviously, but you guys just keep cranking. >>Yeah, so we're obviously hugely excited by this and it really is a confluence of various things. It's our, it's our partners, it's the channel. Um, it's our customers frankly that that guide us and give us direction on what to do. But I always focus in on the product because I, you know, we run product strategy here, this group and we're very focused on building good products and I would say there's three product areas that are on maximum thrust right now. One is in the data center. So we built a billion dollar business on being the very best in the data center for V sphere, hyper V, um, for Nutanix, HV and as we announced also with red hat virtualization. So data center obviously a huge thrust for us going forward. The second assess Office 3 65 is exploding. We already announced we're protecting 5.8 million users right now with being back up for Office 3 65 and there's a lot of room to grow there. There's 145 million daily users of Microsoft teams. So a lot of room to grow. And then the third areas cloud, we moved over 100 petabytes of data into the public cloud in Q one and there's a lot of opportunity there as well. So those three things are driving the growth, the data center SaAS and cloud >>Davis. I want to get your kind of former analyst perspective on this. Uh you know, I know, you know, it's kind of become cliche but you still got that D. N. A. And I'm gonna tap it. So when you think about and you were following beam, of course very closely during its ascendancy with virtualization. And back then you wouldn't just take your existing, you know, approaches to back up in your processes and just slap them on to virtualization. That that wouldn't have worked. You had to rethink your backup. And it seems like I want to ask you about cloud because people talk about lift and shift and what I hear from customers is, you know, if I just lift and shift to cloud, it's okay, but if I don't have a plan to change my operating model, you know, I don't get the real benefit out of it. And so I would think back up data protection, data management etcetera is a key part of that. So how are you thinking about cloud and the opportunity there? >>Yeah, that's a good point, David. You know, I think the key area right there is it's important to protect the workload of the environment. The way that that environment is naturally is best suited to be protected and also to interact in a way that the administrator doesn't have to rethink, doesn't have to change their process so early on. Um I think it was very successful because the interface is the work experience looked like what an active directory administrator was used to, seeing if they went to go and protect something with me where to go recover an item. Same is true in the cloud, You don't want to just take what's working well in one area and just force it, you know, around round peg into a square hole. This doesn't work well. So you've got to think about the environment and you've got to think about what's gonna be the real use case for getting access to this data. So you want to really tune things and there's obviously commonality involved, but from a workflow perspective, from an application perspective and then a delivery model perspective, Now, when it comes to hybrid cloud multi cloud, it's important to look like that you belong there, not a fish out of water. >>Well, so of course, Danny you were talking to talking about you guys have product first, Right? And so rick your your key product guy here. What's interesting to me is when you look at the history of the technology industry and disruption, it's it's so often that the the incumbent, which you knew now an incumbent, you know, you're not the startup anymore, but the incumbent has challenges riding these these new waves because you've got to serve the existing customer base, but you gotta ride the new momentum as well. So how rick do you approach that from a product standpoint? Because based on the numbers that we see it doesn't you seem to be winning in both the traditional business and the new business. So how do you adapt from a product standpoint? >>Well, Dave, that's a good question. And Danny set it up? Well, it's really the birth of the Wien platform and its relevance in the market. In my 11th year here at Wien, I've had all kinds of conversations. Right. You know, the perception was that, you know, this smb toy for one hyper Advisor those days are long gone. We can check the boxes across the data center and cloud and even cloud native apps. You know, one of the things that my team has done is invest heavily in both people and staff on kubernetes, which aligns to our casting acquisition, which was featured heavily here at V Mon. So I think that being able to have that complete platform conversation Dave has really given us incredible momentum but also credibility with the customers because more than ever, this fundamental promise of having data backed up and being able to drive a recovery for whatever may happen to data nowadays. You know, that's a real emotional, important thing for people and to be able to bring that kind of outcome across the data center, across the cloud, across changes in what they do kubernetes that's really aligned well to our success and you know, I love talking to customers now. It's a heck of a lot easier when you can say yes to so many things and get the technical win. So that kind of drives a lot of the momentum Dave, but it's really the platform. >>So let's talk about the future of it and I want all you guys to chime in here and Danny, you start up, How do you see it? I mean, I always say the last 10 years, the next 10 years ain't gonna be like the last 10 years whether it's in cloud or hybrid et cetera. But so how Danny do you see I. T. In the future of I. T. Where do you see VM fitting in, how does that inform your roadmap, your product strategy? Maybe you could kick that segment off? >>Yeah. I think of the kind of the two past decades that we've gone through starting back in 2000 we had a lot of digital services built for end users and it was built on physical infrastructure and that was fantastic. Obviously we could buy things online, we could order close we could order food, we we could do things interact with end users. The second era about a decade later was based on virtualization. Now that wasn't a benefit so much to the end user is a benefit to the business. The Y because you could put 10 servers on a single physical server and you could be a lot more flexible in terms of delivery. I really think this next era that we're going into is actually based on containers. That's why the cost of acquisition is so strategic to us. Because the unique thing about containers is they're designed for to be consumption friendly. You spin them up, you spin them down, you provision them, you d provisions and they're completely portable. You can move it >>from on >>premises if you're running open shift to e k s a k s G k E. And so I think the next big era that we're going to go through is this movement towards containerized infrastructure. Now, if you ask me who's running that, I still think there's going to be a data center operations team, platform ups is the way that I think about them who run that because who's going to take the call in the middle of the night. But it is interesting that we're going through this transformation and I think we're in the very early stages of this radical transformation to a more consumption based model. Dave. I don't know what you think about that. >>Yeah, I would say something pretty similar Danny. It sounds cliche day valenti, but I take everything back to digital transformation. And the reason I say that is to me, digital transformation is about improving customer intimacy and so that you can deliver goods and services that better resonate and you can deliver them in better time frame. So exactly what Danny said, you know, I think that the siloed approaches of the past where we built very hard in environments and we were willing to take a long time to stand those up and then we have very tight change control. I feel like 2020 sort of a metaphor for where the data center is going to throw all that out the window we're compiling today. We're shipping today and we're going to get experience today and we're going to refine it and do it again tomorrow. But that's the environment we live in. And to Danny's point why containers are so important. That notion of shift left meaning experience things earlier in the cycle. That is going to be the reality of the data center regardless of whether the data center is on prem hybrid cloud, multi cloud or for some of us potentially completely in the cloud. >>So rick when you think about some of your peeps like the backup admit right and how that role is changing in a big discussion in the economy now about the sort of skills gap we got all these jobs and and yet there's still all this unemployment now, you know the debate about the reasons why, but there's a there's a transition enrolls in terms of how people are using products and obviously containers brings that, what what are you seeing when you talk to like a guy called him your peeps? Yeah, it's >>an evolving conversation. Dave the audience, right. It has to be relevant. Uh you know, we were afforded good luxury in that data center wheelhouse that Danny mentioned. So virtualization platform storage, physical servers, that's a pretty good start. But in the software as a service wheelhouse, it's a different persona now, they used to talk to those types of people, there's a little bit of connection, but as we go farther to the cloud, native apps, kubernetes and some of the other SAAS platforms, it is absolutely an audience journey. So I've actually worked really hard on that in my team, right? Everything from what I would say, parachuting into a community, right? And you have to speak their language. Number one reason is just number one outcomes just be present. And if you're in these communities you can find these individuals, you can talk their language, you can resonate with their needs, right? So that's something uh you know, everything from Levin marketing strategy to the community strategy to even just seating products in the market, That's a recipe that beam does really well. So yeah, it's a moving target for sure. >>Dave you were talking about the cliche of digital transformation and I'll say this may be pre Covid, I really felt like it was a cliche, there was a lot of, you know, complacency, I'll call it, but then the force marks the digital change that uh and now we kind of understand if you're not a digital business, you're in trouble. Uh And so my question is how it relates to some of the trends that we've been talking about in terms of cloud containers, We've seen the SAs ification for the better part of a decade now, but specifically as it relates to migration, it's hard for customers to just migrate their application portfolio to the cloud. Uh It's hard to fund it. It takes a long time. It's complex. Um how do you see that cloud migration evolving? Maybe that's where hybrid comes in And again, I'm interested in how you guys think about it and how it affects your strategy. >>Yeah. Well it's a complex answer as you might imagine because 400,000 customers, we take the exact same code. The exact same ice so that I run on my laptop is the exact same being backup and replication image that a major bank protects almost 20,000 machines and a petabytes of data. And so what that means is that you have to look at things on a case by case basis for some of us continuing to operate proprietary systems on prem might be the best choice for a certain workload. But for many of us the Genie is kind of out of the bottle with 2020 we have to move faster. It's less about safety and a lot more about speed and favorable outcome. We'll fix it if it's broken but let's get going. So for organizations struggling with how to move to the cloud, believe it or not, backup and recovery is an excellent way to start to venture into that because you can start to move data backup ISm data movement engine. So we can start to see data there where it makes sense. But rick would be quick to point out we want to offer a safe return. We have instances of where people want to repatriate data back and having a portable data format is key to that Rick. >>Uh yeah, I had a conversation recently with an organization managing cloud sprawl. They decided to consolidate, we're going to use this cloud, so it was removing a presence from one cloud that starts with an A and migrating it to the other cloud that starts with an A. You know, So yeah, we've seen that need for portability repatriation on prem classic example going from on prem apps to software as a service models for critical apps. So data mobility is at the heart of VM and with all the different platforms, kubernetes comes into play as well. It's definitely aligning to the needs that we're seeing in the market for sure. >>So repatriation, I want to stay on that for a second because you're, you're an arms dealer, you don't care if they're in the cloud or on prem and I don't know, maybe you make more money in one or the other, but you're gonna ride whatever waves the market gives you so repatriation to me implies. Or maybe I'm just inferring that somebody's moved to the cloud and they feel like, wow, we've made a mistake, it was too fast, too expensive. It didn't work for us. So now we're gonna bring it back on prem. Is that what you're saying? Are you saying they actually want their data in both both places. As another layer of data protection Danny. I wonder if you could address that. What are you seeing? >>Well, one of the interesting things that we saw recently, Dave Russell actually did the survey on this is that customers will actually build their work laid loads in the cloud with the intent to bring it back on premises. And so that repatriation is real customers actually don't just accidentally fall into it, but they intend to do it. And the thing about being everyone says, hey, we're disrupting the market, we're helping you go through this transformation, we're helping you go forward. Actually take a slightly different view of this. The team gives them the confidence that they can move forward if they want to, but if they don't like it, then they can move back and so we give them the stability through this incredible pace, change of innovation. We're moving forward so so quickly, but we give them the ability to move forward if they want then to recover to repatriate if that's what they need to do in a very effective way. And Dave maybe you can touch on that study because I know that you talked to a lot of customers who do repatriate workloads after moving them to the cloud. >>Yeah, it's kind of funny Dave not in the analyst business right now, but thanks to Danny and our chief marketing Officer, we've got now half a dozen different research surveys that have either just completed or in flight, including the largest in the data protection industry's history. And so the survey that Danny alluded to, what we're finding is people are learning as they're going and in some cases what they thought would happen when they went to the cloud they did not experience. So the net kind of funny slide that we discovered when we asked people, what did you like most about going to the cloud and then what did you like least about going to the cloud? The two lists look very similar. So in some cases people said, oh, it was more stable. In other cases people said no, it was actually unstable. So rick I would suggest that that really depends on the practice that you bring to it. It's like moving from a smaller house to a larger house and hoping that it won't be messy again. Well if you don't change your habits, it's eventually going to end up in the same situation. >>Well, there's still door number three and that's data reuse and analytics. And I found a lot of organizations love the idea of at least manipulating data, running test f scenarios on yesterday's production, cloud workload completely removed from the cloud or even just analytics. I need this file. You know, those types of scenarios are very easy to do today with them. And you know, sometimes those repatriations, those portable recoveries, Sometimes people do that intentionally, but sometimes they have to do it. You know, whether it's fire, flood and blood and you know, oh, I was looks like today we're moving to the cloud because I've lost my data center. Right. Those are scenarios that, that portable data format really allows organizations to do that pretty easily with being >>it's a good discussion because to me it's not repatriation, it has this negative connotation, the zero sum game and it's not Danny what you describe and rick as well. It was kind of an experimentation, a purposeful. We're going to do it in the cloud because we can and it's cheap and low risk to spin it up and then we're gonna move it because we've always thought we're going to have it on prem. So, so you know, there is some zero sum game between the cloud and on prem. Clearly no question about it. But there's also this rising tide lifts all ship. I want to, I want to change the subject to something that's super important and and top of mind it's in the press and it ain't going away and that is cyber and specifically ransomware. I mean, since the solar winds hack and it seems to me that was a new milestone in the capabilities and aggressiveness of the adversary who is very well funded and quite capable. And what we're seeing is this idea of tucking into the supply chain of islands, so called island hopping. You're seeing malware that's self forming and takes different signatures very stealthy. And the big trend that we've seen in the last six months or so is that the bad guys will will lurk and they'll steal all kinds of sensitive data. And then when you have an incident response, they will punish you for responding. And they will say, okay, fine, you want to do that. We're going to hold you ransom. We're gonna encrypt your data. And oh, by the way, we stole this list of positive covid test results with names from your website and we're gonna release it if you don't pay their. I mean, it's like, so you have to be stealthy in your incident response. And this is a huge problem. We're talking about trillions of dollars lost each year in, in in cybercrime. And so, uh, you know, it's again, it's this uh the bad news is good news for companies like you. But how do you help customers deal with this problem? What are you seeing Danny? Maybe you can chime in and others who have thoughts? >>Well we're certainly seeing the rise of cyber like crazy right now and we've had a focus on this for a while because if you think about the last line of defense for customers, especially with ransomware, it is having secure backups. So whether it be, you know, hardened Linux repositories, but making sure that you can store the data, have it offline, have it, have it encrypted immutable. Those are things that we've been focused on for a long while. It's more than that. Um it's detection and monitoring of the environment, which is um certainly that we do with our monitoring tools and then also the secure recovery. The last thing that you want to do of course is bring your backups or bring your data back online only to be hit again. And so we've had a number of capabilities across our portfolio to help in all of these. But I think what's interesting is where it's going, if you think about unleashing a world where we're continuously delivering, I look at things like containers where you have continues delivery and I think every time you run that helm commander, every time you run that terra form command, wouldn't that be a great time to do a backup to capture your data so that you don't have an issue once it goes into production. So I think we're going towards a world where security and the protection against these cyber threats is built into the supply chain rather than doing it on just a time based uh, schedule. And I know rick you're pretty involved on the cyber side as well. Would you agree with that? I >>would. And you know, for organizations that are concerned about ransomware, you know, this is something that is taken very seriously and what Danny explained for those who are familiar with security, he kind of jumped around this, this universally acceptable framework in this cybersecurity framework there, our five functions that are a really good recipe on how you can go about this. And and my advice to IT professionals and decision makers across the board is to really align everything you do to that framework. Backup is a part of it. The security monitoring and user training. All those other things are are areas that that need to really follow that wheel of functions. And my little tip here and this is where I think we can introduce some differentiation is around detection and response. A lot of people think of backup product would shine in both protection and recovery, which it does being does, but especially on response and detection, you know, we have a lot of capabilities that become impact opportunities for organizations to be able to really provide successful outcomes through the other functions. So it's something we've worked on a lot. In fact we've covered here at the event. I'm pretty sure it will be on replay the updated white paper. All those other resources for different levels can definitely guide them through. >>So we follow up to the detection is what analytics that help you identify whatever lateral movement or people go in places they shouldn't go. I mean the hard part is is you know, the bad guys are living off the land, meaning they're using your own tooling to to hack you. So they're not it's not like they're introducing something new that shouldn't be there. They're they're just using making judo moves against you. So so specifically talk a little bit more about your your detection because that's critical. >>Sure. So I'll give you one example imagine we capture some data in the form of a backup. Now we have an existing advice that says, you know what Don't put your backup infrastructure with internet connectivity. Use explicit minimal permissions. And those three things right there and keep it up to date. Those four things right there will really hedge off a lot of the different threat vectors to the back of data, couple that with some of the mutability offline or air gapped capabilities that Danny mentioned and you have an additional level of resiliency that can really ensure that you can drive recovery from an analytic standpoint. We have an api that allows organizations to look into the backup data. Do more aggressive scanning without any exclusions with different tools on a flat file system. You know, the threats can't jump around in memory couple that with secure restore. When you reintroduce things into the environment From a recovery standpoint, you don't want to reintroduce threats. So there's protections, there's there's confidence building steps along the way with them and these are all generally available technologies. So again, I got this white paper, I think we're up to 50 pages now, but it's a very thorough that goes through a couple of those scenarios. But you know, it gets the uh, it gets quickly into things that you wouldn't expect from a backup product. >>Please send me a copy if you, if you don't mind. I this is a huge problem and you guys are global company. I admittedly have a bit of a US bias, but I was interviewing robert Gates one time the former defense secretary and we're talking about cyber war and I said, don't we have the best cyber, can't we let go on the offense? He goes, yeah, we can, but we got the most to lose. So this is really a huge problem for organizations. All right, guys, last question I gotta ask you. So what's life like under, under inside capital of the private equity? What's changed? What's, what's the same? Uh, do you hear from our good friend ratner at all? Give us the update there. >>Yes. Oh, absolutely fantastic. You know, it's interesting. So obviously acquired by insight partners in February of 2020, right, when the pandemic was hitting, but they essentially said light the fuse, keep the engine's going. And we've certainly been doing that. They haven't held us back. We've been hiring like crazy. We're up to, I don't know what the count is now, I think 4600 employees, but um, you know, people think of private equity and they think of cost optimizations and, and optimizing the business, That's not the case here. This is a growth opportunity and it's a growth opportunity simply because of the technology opportunity in front of us to keep, keep the engine's going. So we hear from right near, you know, on and off. But the new executive team at VM is very passionate about driving the success in the industry, keeping abreast of all the technology changes. It's been fantastic. Nothing but good things to say. >>Yes, insight inside partners, their players, we watched them watch their moves and so it's, you know, I heard Bill McDermott, the ceo of service now the other day talking about he called himself the rule of 60 where, you know, I always thought it was even plus growth, you know, add that up. And that's what he was talking about free cash flow. He's sort of changing the definition a little bit but but so what are you guys optimizing for you optimizing for growth? Are you optimising for Alberta? You optimizing for free cash flow? I mean you can't do All three. Right. What how do you think about that? >>Well, we're definitely optimizing for growth. No question. And one of the things that we've actually done in the past 12 months, 18 months is beginning to focus on annual recurring revenue. You see this in our statements, I know we're not public but we talk about the growth in A. R. R. So we're certainly focused on that growth in the annual recovering revenue and that that's really what we tracked too. And it aligns well with the cloud. If you look at the areas where we're investing in cloud native and the cloud and SAAS applications, it's very clear that that recurring revenue model is beneficial. Now We've been lucky, I think we're 13 straight quarters of double-digit growth. And and obviously they don't want to see that dip. They want to see that that growth continue. But we are optimizing on the growth trajectory. >>Okay. And you see you clearly have a 25% growth last quarter in A. R. R. Uh If I recall correctly, the number was evaluation was $5 billion last january. So obviously then, given that strategy, Dave Russell, that says that your tam is a lot bigger than just the traditional backup world. So how do you think about tam? I'll we'll close there >>and uh yeah, I think you look at a couple of different ways. So just in the backup recovery space or backup in replication to paying which one you want to use? You've got a large market there in excess of $8 billion $1 billion dollar ongoing enterprise. Now, if you look at recent i. D. C. Numbers, we grew and I got my handy HP calculator. I like to make sure I got this right. We grew 44.88 times faster than the market average year over year. So let's call that 45 times faster and backup. There's billions more to be made in traditional backup and recovery. However, go back to what we've been talking around digital transformation Danny talking about containers in the environment, deployment models, changing at the heart of backup and recovery where a data capture data management, data movement engine. We envision being able to do that not only for availability but to be able to drive the business board to be able to drive economies of scale faster for our organizations that we serve. I think the trick is continuing to do more of the same Danny mentioned, he knows the view's got lit. We haven't stopped doing anything. In fact, Danny, I think we're doing like 10 times more of everything that we used to be doing prior to the pandemic. >>All right, Danny will give you the last word, bring it home. >>So our goal has always been to be the most trusted provider of backup solutions that deliver modern data protection. And I think folks have seen at demon this year that we're very focused on that modern data protection. Yes, we want to be the best in the data center but we also want to be the best in the next generation, the next generation of I. T. So whether it be sas whether it be cloud VM is very committed to making sure that our customers have the confidence that they need to move forward through this digital transformation era. >>Guys, I miss flying. I mean, I don't miss flying, but I miss hanging with you all. We'll see you. Uh, for sure. Vim on 2022 will be belly to belly, but thanks so much for coming on the the virtual edition and thanks for having us. >>Thank you. >>All right. And thank you for watching everybody. This keeps continuous coverage of the mon 21. The virtual edition. Keep it right there for more great coverage. >>Mm

>> Announcer: From theCUBE studios in Palo Alto and Boston, it's theCUBE, covering IBM Think brought to you by IBM. >> Hi, there, this is Dave Vellante. We're back at the IBM Think 2020 Digital Event Experience are socially responsible and distant. I'm here in the studios in Marlborough, our team in Palo Alto. We've been going wall to wall coverage of IBM Think, Kit Chee here is the Vice President, and general manager of Cloud and Enterprise sales at Intel. Kit, thanks for coming on. Good to see you. >> Thank you, Dave. Thank you for having me on. >> You're welcome, and Evaristus Mainsah, Mainsah is here. Mainsah, he is the general manager of the IBM Cloud Pack Ecosystem for the IBM Cloud. Evaristus, it's good to see you again. Thank you very much, I appreciate your time. >> Thank you, Dave. Thank you very much. Thanks for having me. >> You're welcome, so Kit, let me start with you. How are you guys doing? You know, there's this pandemic, never seen it before. How're things where you are? >> Yeah, so we were quite fortunate. Intel's had an epidemic leadership team. For about 15 years now, we have a team consisting of medical safety and operational professionals, and this same team has, who has navigated as across several other health issues like bad flu, Ebola, Zika and each one and one virus then navigating us at this point with this pandemic. Obviously, our top priority as it would be for IBM is protecting the health and well being of employees while keeping the business running for our customers. The company has taken the following measures to take care of it direct and indirect workforce, Dave and to ensure business continuity throughout the developing situation. They're from areas like work from home policies, keeping hourly workers home and reimbursing for daycare, elderly care, helping with WiFi policies. So that's been what we've been up to Intel's manufacturing and supply chain operations around the world world are working hard to meet demand and we are collaborating with supply pains of our customers and partners globally as well. And more recently, we have about $16 Million to support communities, from frontline health care workers and technology initiatives like online education, telemedicine and compute need to research. So that's what we've been up to date. Pretty much, you know, busy. >> You know, every society that come to you, I have to say my entire career have been in the technology business and you know, sometimes you hear negative toward the big tech but, but I got to say, just as Kit was saying, big tech has really stepped up in this crisis. IBM has been no different and, you know, tech for good and I was actually I'm really proud. How are you doing in New York City? >> Evaristus: No, thank you, Dave, for that, you know, we are, we're doing great and, and our focus has been absolutely the same, so obviously, because we provide services to clients. At a time like this, your clients need you even more, but we need to focus on our employees to make sure that their health and their safety and their well being is protected. And so we've taken this really seriously, and actually, we have two ways of doing this. One of them is just on to purpose as a, as a company, on our clients, but the other is trying to activate the ecosystem because problems of this magnitude require you to work across a broad ecosystem to, to bring forth in a solution that are long lasting, for example, we have a call for code, which where we go out and we ask developers to use their skills and open source technologies to help solve some technical problems. This year, the focus was per AVADA initiatives around computing resources, how you track the Coronavirus and other services that are provided free of charge to our clients. Let me give you a bit more color, so, so IBM recently formed the high performance computing consortium made up of the feYderal government industry and academic leaders focus on providing high performance computing to solve the COVID-19 problem. So we're currently we have 33 members, now we have 27 active products, deploying something like 400 teraflops as our petaflop 400 petaflops of compute to solve the problem. >> Well, it certainly is challenging times, but at the same time, you're both in the, in the sweet spot, which is Cloud. I've talked to a number of CIOs who have said, you know, this is really, we had a cloud strategy before but we're really accelerating our cloud strategy now and, and we see this as sort of a permanent effect. I mean, Kit, you guys, big, big on ecosystem, you, you want frankly, a level playing field, the more optionality that you can give to customers, you know, the better and Cloud is really been exploding and you guys are powering, you know, all the world's Clouds. >> We are, Dave and honestly, that's a huge responsibility that we undertake. Before the pandemic, we saw the market through the lens of four key mega trends and the experiences we are all having currently now deepens our belief in the importance of addressing these mega trends, but specifically, we see marketplace needs around key areas of cloudification of everything below point, the amount of online activities that have spiked just in the last 60 days. It's a testimony of that. Pervasive AI is the second big area that we have seen and we are now resolute on investments in that area, 5G network transformation and the edge build out. Applications run the business and we know enterprise IT faces challenges when deploying applications that require data movement between Clouds and Cloud native technologies like containers and Kubernetes will be key enablers in delivering end to end data analytics, AI, machine learning and other critical workloads and Cloud environments at the edge. Pairing Intel's data centric portfolio, including Intel's obtain SSPs with Red Hat, Openshift, and IBM Cloud Paks, enterprise can now break through storage bottlenecks and have unconstrained data availability in the hybrid and multicloud environments, so we're pretty happy with the progress we're making that together with IBM. >> Yeah, Evaristus, I mean, you guys are making some big bets. I've, you know, written and discussed in my breaking analysis, I think a lot of people misunderstand IBM Cloud, Ginni Rometty arm and a bow said, hey, you know, we're after only 20% of the workloads are in cloud, we're going after the really difficult to move workloads and the hybrid workloads, that's really the fourth foundation that Arvin you know, talks about, that you and IBM has built, you know, your mainframes, you have middleware services, and in hybrid Cloud is really that fourth sort of platform that you're building out, but you're making some bets in AI. You got other services in the Cloud like, like blockchain, you know, quantum, we've been having really interesting discussions around quantum, so I wonder if you can talk a little bit about sort of where you're allocating resources, some of the big bets that, that you're making for the next decade. >> Well, thank you very much, Dave, for that. I think what we're seeing with clients is that there's increasing focus on and, and really an acceptance, that the best way to take advantage of the Cloud is through a hybrid cloud strategy, infused with data, so it's not just the Cloud itself, but actually what you need to do to data in order to make sure that you can really, truly transform yourself digitally, to enable you to, to improve your operations, and in use your data to improve the way that you work and improve the way that you serve your clients. And what we see is and you see studies out there that say that if you adopt a hybrid cloud strategy, instead of 2.5 times more effective than a public cloud only strategy, and Why is that? Well, you get thi6ngs such as you know, the opportunity to move your application, the extent to which you move your applications to the Cloud. You get things such as you know, reduction in, in, in risk, you, you get a more flexible architecture, especially if you focus on open certification, reduction and certification reduction, some of the tools that you use, and so we see clients looking at that. The other thing that's really important, especially in this moment is business agility, and resilience. Our business agility says that if my customers used to come in, now, they can't come in anymore, because we need them to stay at home, we still need to figure out a way to serve them and we write our applications quickly enough in order to serve this new client, service client in a new way. And well, if your applications haven't been modernized, even if you've moved to the Cloud, you don't have the opportunity to do that and so many clients that have made that transformation, figure out they're much more agile, they can move more easily in this environment, and we're seeing the whole for clients saying yes, I do need to move to the Cloud, but I need somebody to help improve my business agility, so that I can transform, I can change with the needs of my clients, and with the demands of competition and this leads you then to, you know, what sort of platform do you need to enable you to do this, it's something that's open, so that you can write that application once you can run it anywhere, which is why I think the IBM position with our ecosystem and Red Hat with this open container Kubernetes environment that allows you to write application once and deploy it anywhere, is really important for clients in this environment, especially, and the Cloud Paks which is developed, which I, you know, General Manager of the Cloud Pak Ecosystem, the logic of the Cloud Paks is exactly that you'll want plans and want to modernize one, write the applications that are cloud native so that they can react more quickly to market conditions, they can react more quickly to what the clients need and they, but if they do so, they're not unlocked in a specific infrastructure that keeps them away from some of the technologies that may be available in other Clouds. So we have talked about it blockchain, we've got, you know, Watson AI, AI technologies, which is available on our Cloud. We've got the weather, company assets, those are key asset for, for many, many clients, because weather influences more than we realize, so, but if you are locked in a Cloud that didn't give you access to any of those, because you hadn't written on the same platform, you know, that's not something that you you want to support. So Red Hat's platform, which is our platform, which is open, allows you to write your application once and deploy it anyways, particularly our customers in this particular environment together with the data pieces that come on top of that, so that you can scale, scale, because, you know, you've got six people, but you need 600 of them. How do you scale them or they can use data and AI in it? >> Okay, this must be music to your ears, this whole notion of you know, multicloud because, you know, Intel's pervasive and so, because the more Clouds that are out there, the better for you, better for your customers, as I said before, the more optionality. Can you6 talk a little bit about the rela6tionship today between IBM and Intel because it's obviously evolved over the years, PC, servers, you know, other collaboration, nearly the Cloud is, you know, the latest 6and probably the most rel6evant, you know, part of your, your collaboration, but, but talk more about what that's like you guys are doing together that's, that'6s interesting and relevant. >> You know, IBM and Intel have had a very rich history of collaboration starting with the invention of the PC. So for those of us who may take a PC for granted, that was an invention over 40 years ago, between the two companies, all the way to optimizing leadership, IBM software like BB2 to run the best on Intel's data center products today, right? But what's more germane today is the Red Hat piece of the study and how that plays into a partnership with IBM going forward, Intel was one of Red Hat's earliest investors back in 1998, again, something that most people may not realize that we were in early investment with Red Hat. And we've been a longtime pioneer of open source. In fact, Levin Shenoy, Intel's Executive Vice President of Data Platforms Group was part of COBOL Commies pick up a Red Hat summit just last week, you should definitely go listen to that session, but in summary, together Intel and Red Hat have made commercial open source viable and enterprise and worldwide competing globally. Basically, now we've65 used by nearly every vertical and horizontal industr6y. We are bringing our customers choice, scalability and speed of innovation for key technologies today, such as security, Telco, NFV, and containers, or even at ease and most recently Red Hat Openshift. We're very excited to see IBM Cloud Packs, for example, standardized on top of Openshift as that builds the foundation for IBM chapter two, and allows for Intel's value to scale to the Cloud packs and ultimately IBM customers. Intel began partnering with IBM on what is now called Pax over two years ago and we 6are committed to that success and scaling that, try ecosystem, hardware partners, ISVs and our channel. >> Yeah, so theCUBE by the way, covered Red Hat summit last week, Steve Minima and I did a detailed analysis. It was awesome, like if we do say so ourselves, but awesome in the sense of, it allowed us to really sort of unpack what's going on at Red Hat and what's happening at IBM. Evaristus, so I want to come back to you on this Cloud Pack, you got, it's, it's the kind of brand that you guys have, you got Cloud Packs all over the place, you got Cloud Packs for applications, data, integration, automation, multicloud management, what do we need to know about Cloud pack? What are the relevant components there? >> Evaristus: I think the key components is so this is think of this as you know, software that is designed that is Cloud native is designed for specific core use cases and it's built on Red Hat Enterprise Linux with Red Hat Openshift container Kubernetes environment, and then on top of that, so you get a set of common services that look right across all of them and then on top of that, you've got specific both open source and IBM software that deals with specific plant situations. So if you're dealing with applications, for example, the open source and IBM software would be the run times that you need to write and, and to blow applications to have setups. If you're dealing with data, then you've got Cloud Pack to data. The foundation is still Red Hat Enterprise Linux sitting on top of with Red Hat Openshift container Kubernetes environment sitting on top of that providing you with a set of common services and then you'll get a combination of IBM zone open, so IBM software as well as open source will have third party software that sits on top of that, as well as all of our AI infrastructure that sits on top of that and machine learning, to enable you to do everything that you need to do, data to get insights updates, you've got automation to speed up and to enable us to do work more efficiently, more effectively, to make your smart workers better, to make management easier, to help management manage work and processes, and then you've got multicloud management that allows you to see from a single pane, all of your applications that you've deployed in the different Cloud, because the idea here, of course, is that not all sitting in the same Cloud. Some of it is on prem, some of it is in other Cloud, and you want to be able to see and deploy applications across all of those. And then you've got the Cloud Pack to security, which has a combination of third party offerings, as well as ISV offerings, as well as AI offerings. Again, the structure is the same, REL, Red Hat Openshift and then you've got the software that enables you to manage all aspects of security and to deal with incidents when, when they arise. So that gives you data applications and then there's integration, as every time you start writing an application, you need to integrate, you need to access data security from someplace, you need to bring two pipes together for them to communicate and we use a Cloud Pack for integration to allow us to do that. You can open up API's and expose those API so others writing application and gain access to those API's. And again, this idea of resilience, this idea of agility, so you can make changes and you can adapt data things about it. So that's what the Cloud Pack provides for you and Intel has been an absolutely fantastic partner for us. One of the things that we do with Intel, of course, is to, to work on the reference architectures to help our certification program for our hardware OEMs so that we can scale that process, get many more OEMs adopt and be ready for the Cloud Packs and then we work with them on some of the ISV partners and then right up front. >> Got it, let's talk about the edge. Kity, you mentioned 5G. I mean it's a really exciting time, (laughs) You got windmills, you got autonomous vehicles, you got factories, you got to ship, you know, shipping containers. I mean, everything's getting instrumented, data everywhere and so I'm interested in, let's start with Intel's point of view on the edge, how that's going to evolve, you know what it means to Cloud. >> You know, Dave, it's, its definitely the future and we're excited to partner with IBM here. In addition to enterprise edge, the communication service providers think of the Telcos and take advantage of running standardized open software at the Telco edge, enabling a range of new workloads via scalable services, something that, you know, didn't happen in the past, right? Earlier this year, Intel announced a new C on second generation, scalable, atom based processes targeting the 5G radio access network, so this is a new area for us, in terms of investments going to 5G ran by deploying these new technologies, with Cloud native platforms like Red Hat Openshift and IBM Cloud Packs, comm service providers can now make full use of their network investments and bring new services such as Artificial Intelligence, augmented reality, virtual reality and gaming to the market. We've only touched the surface as it comes to 5G and Telco but IBM Red Hat and Intel compute together that I would say, you know, this space is super, super interesting, as more developed with just getting started. >> Evaristus, what do you think this means for Cloud and how that will evolve? Is this sort of a new Cloud that will form at the edge? Obviously, a lot of data is going to stay at the edge, probably new architectures are going to emerge and again, to me, it's all about data, you can create more data, push more data back to the Cloud, so you can model it. Some of the data is going to have to be done in real time at the edge, but it just really extends the network to new horizons. >> Evaristus: It does exactly that, Dave and we think of it and which is why I thought it will impact the same, right? You wouldn't be surprised to see that the platform is based on open containers and that Kubernetes is container environment provided by Red Hat and so whether your data ends up living at the edge or your data lives in a private data center, or it lives in some public Cloud, and how it flows between all of them. We want to make it easy for our clients to be able to do that. So this is very exciting for us. We just announced IBM Edge Application Manager that allows you to basically deploy and manage applications at endpoints of all these devices. So we're not talking about 2030, we're talking about thousands or hundreds of thousands. And in fact, we're working with, we're getting divided Intel's device onboarding, which will enable us to use that because you can get that and you can onboard devices very, very easily at scale, which if you get that combined with IBM Edge Application Manager, then it helps you onboard the devices and it helps you divide both central devices. So we think this is really important. We see lots of work that moving on the edge devices, many of these devices and endpoints now have sufficient compute to be able to run them, but right now, if they are IoT devices, the data has been transferred to hundreds of miles away to some data center to be processed and enormous pass and then only 1% of that actually is useful, right? 99% of it gets thrown away. Some of that actually has data residency requirements, so you may not be able to move the data to process, so why wouldn't you just process the data where the data is created around your analytics where the data is spread, or you have situations that are disconnected as well. So you can't actually do that. You don't want to stop this still in the supermarket, because there's, you lost connectivity with your data center and so the importance of being able to work offline and IBM Edge Application Manager actually allows you so it's tournament so you can do all of this without using lots of people because it's a process that is all sort or automated, but you can work whether you're connected or you're disconnected, and then you get replication when you get really, really powerful for. >> All right, I think the developer model is going to be really interesting here. There's so many new use cases and applications. Of course, Intel's always had a very strong developer ecosystem. You know, IBM understands the importance of developers. Guys, we've got to wrap up, but I wonder if you could each, maybe start with Kit. Give us your sense as to where you want to see this, this partnership go, what can we expect over the next, you know, two to five years and beyond? >> I think it's just the area of, you know, 5G, and how that plays out in terms of edge build out that we just touched on. I think that's a really interesting space, what Evaristus has said is spot on, you know, the processing, and the analytics at the edge is still fairly nascent today and that's growing. So that's one area, building out the Cloud for the different enterprise applications is the other one and obviously, it's going to be a hybrid world. It's not just a public Cloud world on prem world. So the whole hybrid build out What I call hybrid to DoD zero, it's a policy and so the, the work that both of us need to do IBM and Intel will be critical to ensure that, you know, enterprise IT, it has solutions across the hybrid sector. >> Great. Evaristus, give us the last word, bring us home. >> Evaristus: And I would agree with that as well, Kit. I will say this work that you do around the Intel's market ready solutions, right, where we can bring our ecosystem together to do even more on Edge, some of these use cases, this work that we're doing around blockchain, which I think you know, again, another important piece of work and, and I think what we really need to do is to focus on helping clients because many of them are working through those early cases right now, identify use cases that work and without commitment to open standards, using exactly the same standard across like what you've got on your open retail initiative, which we're going to do, I think is going to be really important to help you out scale, but I wanted to just add one more thing, Dave, if you if you permit me. >> Yeah. >> Evaristus: In this COVID era, one of the things that we've been able to do for customers, which has been really helpful, is providing free technology for 90 days to enable them to work in an offline situation to work away from the office. One example, for example, is the just the ability to transfer files and bandwidth, new bandwidth is an issue because the parents and the kids are all working from home, we have a protocol, IBM Aspera, which will make available customers for 90 days at no cost. You don't need to give us your credit card, just log on and use it to improve the way that you work. So your bandwidth feels as if you are in the office. We have what's an assistant that is now helping clients in more than 18 countries that keep the same thing, basically providing COVID information. So those are all available. There's a slew of offerings that we have. We just want listeners to know that they can go on the IBM website and they can gain those offerings they can deploy and use them now. >> That's huge. I knew about the 90 day program, I didn't realize a sparrow was part of that and that's really important because you're like, Okay, how am I going to get this file there? And so thank you for, for sharing that and guys, great conversation. You know, hopefully next year, we could be face to face even if we still have to be socially distant, but it was really a pleasure having you on. Thanks so much. Stay safe, and good stuff. I appreciate it. >> Evaristus: Thank you very much, Dave. Thank you, Kit. Thank you. >> Thank you, thank you. >> All right, and thank you for watching everybody. This is Dave Volante for theCUBE, our wall to wall coverage of the IBM Think 2020 Digital Event Experience. We'll be right back right after this short break. (upbeat music)

>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service is >> Welcome back to New York City. This is a W s summit and I'm stew Minutemen. My co host is Corey Quinn. We've talked to Amazon executives. We've talked to some customers. We've also talked to some of the partners and part of the partner ecosystem is course these startups aws very robust ecosystem that they've been building out. And one of the pieces were real excited to dig into in the surveillance space habit of revering program for first time. Ken Robinson, the CEO and founder of Goto Software who is the maker of cloud pegboard, take so much for joining us >> having to be here so exciting. >> Alright, So, Cloud pegboard, you had us hooked when we talked about you know, serverless you know, the the information overload that we all feel in the United with world. Cory's got a full time job helping with that and other things related to it s oh, bring us a little bit about, you know, pegboard in your background. >> Yeah, I want to help you out. So my background is I ran a major cloud transformation to Amazon. My past job, which I left in January and really solve problems, information overload, was slowing people down, people making sub optimal choices. They're spending a lot of time trying to keep up. Sometimes we have to be fact because they didn't have the right information the right time. And I realized we need to solve this. And it wasn't just in our organization. Every Amazon practitioner across the planet really needs help to keep up. When I talked with people, these conferences, it that's like the main comment, like, I can't consume it >> all. How you keep up can it is staggering. Actually, I stopped asking about two years ago how you keep up because I talked to some amazingly smart, well connected people and they're like, No, no, it's impossible. But I want you to comment on something I used to be. When you talking about, I need to start this. I should have started a year ago, but I didn't, so I should start now and now it feels like, Well, if I could, I actually should wait a couple of months or six months or even a year but I absolutely get started. So I guess I might as well start now because things change at such a pace. I mean, that that, you know. Oh, wait. If I could just wait a little bit longer Gonna be Maurin better and cheaper and faster s O. You know what you're taking kind of pace of change in the industry. >> Well, you know, one thing is, I think you just have to keep agile and buy into the fact you're going to have to throw away things like don't get so buried filled with what you can do today as best you can. But be ready to re factor and get rid of it. >> Oh! Oh, my God. I had the i t organization and the whole our quarters. Everything in i t is additive. Nothing ever dies. But I do agree with you. We have been for more than a decade. You know why our analyst team and talking, You have to get rid of stuff that needs to be able to do that. You know, sunk costs is something you're familiar with. Economics is you know, I need to understand that that even have been doing it for a while. We need to be able to cut that. But way have these attachments to the things we've been doing and how we've been doing it. No change isn't necessarily easy, >> right? Well, there's a reason some of the attacks is because there's a lot of investment to build up in the first place. And when you put so much sweat into it, then I don't want to undo it. When it gets easier to build, it's easier to throw away. So I was just giving this talk earlier and saying I religiously stick with infrastructure is code because if you do that, it's just so easy to make incremental changes. And again, Serverless makes everything so much easier if we don't get married to something. If it's changing like one window function, yeah, it's just kind of a bench of a big deal. So if you invest a little bit lessons easier by making use of special, the high level managed service is then it's easier to the pivot from one thing to another. One needs to. >> Yeah, something I found is I play with this stuff myself in a very similar space, with less comprehensiveness and far more sarcasm, I suspect than your service does, is that when you're building everything out of composited Lambda Functions tied together in a micro service's style. Re factoring one of those micro service is usually doesn't take more than a day or two as opposed to, Oh, just rebuild the entire monolith from scratch, which it feels like everyone tries to do. At some point, it almost enforces good behavior. It makes it easier to evolve as I've been your experience it differently. >> Absolutely. So this two things it helps. It's easy to re factor and throw things out because it's small and it's again, you're not married to it as much, but also easy to incrementally add on. So I have this whole tier of these micro service. Is that a captain? All this data that we're pulling in from multiple sources, whether it's Amazon's Web site or terror, for more get up any source I confined that has data that I want to organize help with my users. So we get Henry finding new data sources, leaks new data sources, essentially a new lambda function. It's independent, and if I change it, we actually had one recently I found a better data source. I just threw up the old one and plugged in the new one. And it really was less than a day to write the new function and a brilliant into production. So, yeah, >> can you know, one of the answers I've had for a long time is you know, I need to rely on, you know, my consultants and my suppliers because, you know, you don't even understand some of these architectural things that are going on. And things are changing so fast. So you know, how much can software solve this for us? And you know that the tools itself, I have to imagine there's still a lot of people involved. >> Yeah. There's always gonna be a lot of people involved. And there is no free lunch that, you know, every architect or developer of the Amazon. You still need to get yourself trained, get the certifications, read the white papers, keep up to date with all the changes. And we really do is we're running inside again. That's my past. Life is an enterprise. You really want to build internal excellence. Certainly we can use outside help when you need it. Augmentation. and blasts my people everywhere. But you definitely wanna have some internal expertise. And people are committed to growing and continuing going to New York summit, going to reinvent talking to people and always constantly learning It's going to take human effort to help, uh, filter down and find out. Where is the trend that I really need to start thinking about? Hopefully people. It is a tool helps people be much more efficient and focus in much easier. But nothing will replace engineers, which is a good thing, >> right? And for those who are outside of the, I guess very small fraternity we have apparently built. Now there are two of us who track this stuff for a living. It's it is far more complex than most people would accept. Why don't you just sign up for the R. S s feed? Well, for starters, there's over a dozen official aws R s s feed, and they're not all inclusive. You have to look at poor request getting merchant there a p I updates. You see it in cloud formation and terra form from time to time. And I am certainly not comprehensive. In fact, when I built my newsletter. Originally my thought was that someone was gonna point out something like Cloud Backboard and say, Well, idiot, use this instead. And then I shut it down and admit defeat, and that was the plan. Instead, a bunch of people signed up, and now I want people to read it for the joke's not because it's the only half sensible way to figure out what happened last week. No, I'm a huge fan of the problem you're solving in the way you've got about doing it. That said, when we talk about service architectures, you mentioned spinning up Lambda functions and tying it back into other things. But as they mention Nicky, no today server. This goes beyond just functions as a service. There's a lot more to it than that. What else is your architecture >> includes everything. Serverless exclusively. So >> So they're poking on. So you're collecting every service thing they offer and then some just a get style points there, regardless. >> Well, so you know, one of the half several strategic principles and one of them is to rely solely on serve Ellis because I just can't afford a small start up to be building out Mon function requirements that are building the business. So S O. S to be hosting dynamodb cloudfront ap Gateway. Then we use will all these features Not only do I use all serverless, but we're also using for disaster recovery designed so that we're using some additional features within these, so it's easier fail over. So cloudfront, for example, has Arjun fail over a relatively new feature and it's really amazing, right? I can go to my S three and I have the benefits of estimates service hosting. But now, in a failure cloudfront relative my alternate region continue our operating same thing with dynamodb using global table replication only >> and continuous backup, which they released. I'm not kidding. Three days after I really needed it. It's that seems like that's always the case where they have these features and they come in right after you need to read if you build a crappy version of it and it's one of those. But I love about things at a relatively small scale like this is the economics are ridiculous. It's well, watch out for continuous backups that could be expensive, and I wound up checking it, and it wound up being something like two cents a month. Yeah, I work real hard to bring enough in to cover the back up. Yeah, I >> had someone come up to me after one of the talks and asking like he's not in Amazon. He's thinking the moving there. It's like how much you I have something a little bit similar to what you're doing, and how much will it cost? How much like Budget and I say, To be honest, I've got some credits, Levin warning, but I can't spend them. I can't. I want to accelerate by spending money. I can't do it, especially with dynamodb. Used to be that you would provisions something, a lot of eye ops and that would rack up really fast. Now I'm using the on demand, and it's just not costing anything. So that's what again. This Burn was talking about not paying for idle time, >> and some of the monitoring tools in the surveillance space air still approaching it from an economic first perspective, which for anything that isn't already scaled out, is ludicrous. It has, like warnings, going arrows going up or down on my spend on my land is every month, and it's 22 cents. It's I appreciate where you're going with this, but maybe that's not the driving concern right now. So I >> had a funny experience where I turned on Macy so we could get some good inspection on the anomaly buckets. And on the first of the month, I got a notice saying, Hey, you exceeded the free tier. I was in a bit of a panic has been more than once. I'm sad to say that I've let things run longer than they should and paid the price, and I owe something has run amok. Well, it turns out, just because of the metadata scans, it does kind of use a lot of access is. But then still was under a buck for the whole month by the time outs and done because I came in to begin the month with a bunch of scanning. Yeah, it's just a big fan of service. I did this thing. >> Yeah, I was just Kennedy. Speaking of survival is an Amazon event Bridge was announced this morning. Really building that event ecosystem around Lambda. Curious what impact that will have on you will cloud pegboard be able to go outside of AWS to kind of understand some of these sacks applications. >> I have to learn more about it. I was not in on a preview or anything, so I don't know exactly get. But But yes, we will rip apart meeting with other providers anywhere. There's an information source that can help developers hone in better and kind of get everything in the right place at the right time on. So, yes, things like that will help, especially if it can work through. I don't want to be opening up sqs cues way worried about the I am the cross account. That could be complicated, so I'll be interested to learn. And I don't know yet if that will help in those sorts of integrations, especially on the office. Can't authentication and authorization aspects of it? >> Yeah, there's a lot of promise in the idea of being able to give the minimum viable, required a p. I call for something third party. It seems like there they'll integrate into something like that. Well, here's how I am works and then we have to worry about access controls and oh yeah, there's no direct i p address the white list. And on and on and on. It's challenging to forcibly upgrade third parties. Unless you're effectively a giant, world spanning company, you can demand that they do it. So this it really feels like we're meeting third parties in some ways where they are. >> Yeah, I think so. And I think this is looking forward to them because I want to both consume maybe eyes. But also all my data is available via AP I So today it's a bit of a traditional. No, he and rest would have been the face, but if I could export that in other ways, that would be very interesting as well. >> I think it's too easy to get stuck in the economic story of times. I know it's weird is a cloud economist to be saying that, But when it comes to server list, the value is less about cost control, and saving money on it is you don't have to worry about entire subsets of problems capacity planning your effectively when it comes to things like Lambda Dynamodb and the rest. The constraint on scaling is going to be your budget. I promise. No matter who these budgets are, go for me. This is what they run amazon dot com on. I don't think I'm gonna do more business than that. Unless I really miss configure something. Challenge accepted. >> Yeah. Yeah. So I totally agree that scaling is the value, but it's also this more right. The scaling is absolutely one. And then, in addition to fragility, because survivalist means service. But now the term is getting confused, right? It means so many things. So I was saving serverless managed service is to help Seo. I'm talking about more than compute, but it also means is I'm getting a very high level function. So I'm getting so for David, we're using Comprehend. That's an awful lot of stuff going on under there that I don't have to worry about. I mean, I literally have an intern in a couple of days, completed a task to do some entity extraction of such a Amazon service stains out of unstructured data. She was able to do it. She just finished a freshman year, right? I was able to do this with minimal training because it's survivalist shouldn't worry about scalability. What she needed to know is that oh, I can use this function. I could read maybe I documentation, and I could just use it for me. Another big function behind step, but also no maintenance low, maybe a more accurate term. But essentially, it's no maintenance, especially for a small start up. I used to have businesses way back when pre Internet I ran an aviation weather service in my life was the bane of my existence because it had to be. At 24 7 I had satellite dishes that would get snowed on. I was an idiot. Did this in New England. They have to shovel him off at four in the morning. I don't like waking up in the middle of the night to serve my computers. They should serve me. And in the service of the fact that there's no maintenance stuff, just runs. You think about the times. How many times have you had a serve in the past when you just thought you should reboot it every week? Because maybe >> because tradition, >> tradition and maybe there's a leak somewhere, Melinda function reboots. Every invocation. It just never happens that I have run out of resource is something that I'm just a love affair. >> All right, so So Ken. It's obvious how you feel about server list, but as a start up, just give us a final thoughts on what it's like to be a startup that is on with and, you know, using AWS. >> Well, for me, it's fantastic. It allows me to focus on the problem, to solve immediately and by using high in the stack like you're saying surveillance capabilities. I'm not worried about the infrastructure. I read a little bit of confirmation. I deploy it, and I'm always working on business logic and functionality, and I'm not worrying about well, its scale. Do I have to maintain it, I think, really focus on the problems to solve, and that's where they've been very helpful to make. So now we have something where I can scale. I'm hoping I'm not there yet, but every Amazon practitioner should want to use cloud pegboard. I think it helps with a general problem, so I need to be able to scale to millions. Firstly, I don't know what the doctor is going to be, but I have confidence because I'm using all these service capabilities. S3 will do it. Amazon Gateway in Lambda will do it, so I don't worry about it. So for a start up, to not have to worry about that is it's really pretty powerful. >> And by the time you wind up in a cost prohibitive situation, we're okay. Running some baseline level load that something that isn't server Lis begins to make significant economic sense. At that point, your traffic volumes definitional hier so high that by that point there's a team of people who will be able to focus on that. You don't need to bring those people into get off the ground in >> the same way, right? It's that fast start, and we gotta learn. There's so much to learn here with any start up. But you know, in mind as well to really get some of the user experience, get the feedback. It's We have a lot of good ideas, and I think what we have now is helpful. I have a long term road map with a lot of great ideas, but it's gonna take a lot of user feedback to say, Is this working and the service lets you tried things quickly. I could get in front of people, get that learning cycle going and iterated fast as possible. So that will be really important. All right, >> Ken Robbins really help you appreciate you educating our audience. Climb aboard. Wish you best of luck with >> it. I appreciate being here. >> All right. For Cory Quinn. I'm still minimum, and we'll be back with more coverage here from eight of US Summit in New York City. Thanks. Always for watching the cue.

>> live from Mountain View, California. It's the queue covering definite create twenty nineteen. Brought to You by Cisco >> Welcome back to the cave. Lisa Martin with John Fourier. Live at Cisco Definite Create twenty nineteen at the Computer History Museum in Mountain View, California John Mayer, please to welcome to the Cube Jeff Levin, sailor collaboration Engineer from Presidio Jeff, It's great to have you joining us today. >> Yes, great to be here. >> So lots of energy. You can hear all this noise behind us. We heard this morning in the key note that the definite community is now well over half a million strong. You mentioned before we went line. This is your second definite creates before we get into our city and Cisco. Tell me a little bit about your involvement in the definite community. >> Uh, so I got >> started just looking for support, and it's not like it's a supported product. This is a new venture for everybody. So you go out and you find these little avenues to get questions answered. And WebEx teams has a great community support and just ask a question ended up answering more questions than I was asking, and, you know, that kind of like got me started down this path of, you know, people bounce ideas off each other So really, this is Ah, homecoming. And it's just people inspiring each other If you really want to learn And deep dive Obviously I'm a self learner, so I'll just sit down and really get into it. But I come here to get inspired and the Kino just >> Will you wait? Yeah. What was the key? What was the highlight for you on the Kino? What was >> anything Ashutosh has to talk about? Ashutosh is on the I guess, the incubator side. He comes up with these things, and his job is to get people excited about the FBI's. So today he had an augmented reality app with his phone and he would go around and show network coverage of a WiFi hot spot. You can go up to an access point and troubleshoot network of problems by seeing if on access, points registered or not. So my mind, I'm thinking how many times I go in the data center and look, I have to plug in a laptop to look to see what the lands on a port. Now, Aiken take that same approach too, you know, put my phone out in a data center, and okay, this witch has ah, this V lands here. I could plug it. Antonito even need to plug my laptop. >> I mean, he first introduced the beginning of that demo at Cisco Live in Barcelona. Totally blown away. He's a demo. God first. Yeah, he's amazing. But it shows the automation right and also shows the new kind of experiences. I think to me what is inspiring to me about this community. I'd love to get your reaction. This is that It kind of shows a new way to do work. And it's all about making life easier, But it's also more capability. You can see all the configurations and then ultimately writing new apse. That seems to be the theme. Create definite curiosity with all these capabilities. Is that kind of something that you're seeing as well? What's your reaction to that? That kind of this new way of doing things. >> Wow. I mean, it's we have a code competition are Presidio called Shark Tank, and it's really just to inspire people. Uh, tell me a business use case for this Use cases really ninety percent of it. You confined help you confined mentors your work. But, uh, really Just finding a use case and stuff like this coming here just thinking about new ways to do things and do things to create >> in collaboration What? Some of the things that you see that are low hanging fruit use cases of either mundane tasks or stuff that just needs to be kind of like, abstracted away. What are some of the things >> I have a ton of those s o. Somebody came to me, a law firm that had these attorney's secretary assignments, and they wanted Secretary is to be able to schedule meetings for attorneys. You could do that in a gooey, but we're seeing more and more is away from the buoy. And it's becoming this FBI first. So anything that's not in the gooey, it's in the AP, I So that's where our values integrators has really become. This gap between the jury and the FBI. So what we did, or what I did is going active directory, have some fields filled out because they're already populated. One thing for this I read from that, and then I goto WebEx a p I and I populated, and that runs a nightly basis. >> You automate thataway. Yeah, piece of cake. But this is the trend. This is kind of what we're seeing happening with Cloud the question that comes up in the enterprises. Look, att. Hey, you know, we've been doing this thing for long times the way we do it. We, You know, ten years ago we built out this system. Don't touch it. But I love the new stuff. How do I get the new stuff in? How do I deal the old stuff, The legacy. And we got containers. Got some news stuff. A p. I's a big part of this integration fabric composing APS. I think you have to show >> that the business value it's it's saving time. It's saving people ours, and it's really checking code into get is something you wouldn't think about. Checking network config. Thing to get is something you wouldn't really think about, Uh, just a year ago. But that's really becoming the trend and having a testable code and, uh, you know, kind of Ah, if something goes wrong, I have a backup. You have somebody you know exactly who did what before it was just people hacking away. >> So let's talk about unlocking value for a second. When you were talking with John about what some of the things that blew your mind during this morning's keynote one I was hearing from you and one senses how how much easier certain functions of yourjob are going to be because of this? What value are you seeing that even just a few things that we were announced this morning is going to bring, too? Not just you and your business, but for city and Cisco's customers? >> Well, I mean So, for instance, the Iraqi thing, uh, they released bulk actions. So AP eyes. Typically, if you write the code one of the time, that's goingto limit your ability to do certain functions. Having all these AP eyes in one and point immediately, I'm thinking cloud formation templates. Name is on but ism Iraqi solution, so you could take this entire network and copy and paste. It is one slice of code. That's tremendous. >> What's the community vibe here? Definite. I mean big invention. >> It's a homecoming. I know all these people have met so many people from other areas and people competitors. We're all friends here, you know, And it's not a marketing ventured all you don't see a lot of people you know, scanning badges and bugging you on email later. This is all about just people hurting out about What they've done >> is we're getting >> the show until >> I like >> that. It's not just the hacker fond, you know, Hey, revenue event. They throw a hackathon over it and it turns out the most these events trees, a marketing event. It's completely eyes that >> unorganized as I would want it to be. There's conversations just passing by in the hallway, and I get just as much out of that as I do in a workshop. >> So you're giving a breakout session later today. Contact center. A eye for more efficient governments. >> Yes, that's a twenty minute lightning talk on just a recent project I did and taking an arm from a solution and be able to do Mohr by moving it up to the cloud. This's Amazon connect could be another one, but just basically enabling through the cloud different functionalities we're using Alexe pot, reason, elastic search, reason Landa and we're we're taking the top ten tickets this help desk would receive and trying to automate this. So I need to reset my pen. I need to transfer me to this person that was an operator before in an Excel spreadsheet. So what we did was completely not change your workflow. They're going to upload it, excels for a cheat and has three. It's going to take a Landau function to separate that spread she into a dynamo database Elastic search, going to read that database. And then Lex Boss is goingto interact with elastic search >> and his all in real time. >> It's all in real time. >> And they thought, this all natural language talking together you're working together, >> working together >> to solve those customer problems or get well that And I guess, get the customer that the ticket routed appropriately. >> Yeah, so there's take a look ups to get creation to get clothes and anything that you would typically anything that you can automate. We've done it within the ivy are and we've measured containment rates. So >> yeah, this is exactly why we've been covering. This is our third year, but here in the beginning, at the creation of the event, because what you just described is so valuable and so kind of basic. If you think about it, the number one tickets that everyone that stack ranked haven't over and over again. But breaking towns this going database for this? I got a database for this. I got a database for this. The old world. You have a waterfall process, you have a product. Project manager. People would go in a round trip meeting after meeting, arguing aboutthe ski mus and databases. And I mean, what would it be like in the old days, if you like, went through the traditional models versus his agile? Hey, let's just put it together. Hackett string up. So maybe eyes sling the FBI's rolling up, wiring up >> siding. Me, you're moving from a static ivy are too self service. And then even more what I think you forget who coined the term. But selfie service. You know more about a user you're able to predictably say, I see you have a ticket open or go a step further and say, I see have email on this phone and we're having active sync issues and only alert those people of issues and not bother everybody else. I see you work out of this office and you're calling in. Are you calling about, uh, you know, your office closure? Because we have a temporary office for you over here, So being able to get ahead of anything and predict that's the next thing >> I know. This really also highlights when we tend to talk about us when these data conferences, where the underlying value being here is the creation and stitching together with solutions. But it's the data that's driving it right. The tickets that ranking the the task getting if these reasoning aspect of reasoning with the data predictive are prescriptive, is a personalization benefit thes air. The things that are exposed on this new way of creating >> there's there's some real exciting, very consumable AP eyes out there. One of them all name is in dico io, and this is something that you could just plug in some data. Then I'll make a prediction using just a bunch of learned data set that it already has, and I'LL give you an example WebEx team space way just chat away, and for months and months, I funnel that data to a simple FBI and it comes back and tells me Who's the angriest person who's the happiest person? There's an f b I for Who's a conservative who's a liberal. There's an A p I. For the Myers Briggs test. >> I'LL get all of this. You are the girl. What's the emiko dot io? Indeed, In dico dico i n d >> i c e o dot io >> Awesome. Well, thanks for sharing that on the AP. I think I want to get your expert opinion on this because this comes up a lot recently. At these conferences, we go to where some oh new way to develop modern applications. Blah, blah, blah, waterfalls going away. Fiber Clavell. That's good stuff. Check, check, Check. At the end of the day that the key ingredient all this is AP AP Eyes are becoming the centre point for one data sharing integration coding Middle, where a new kind of middleware evolving? What's your view on this? Because this is an essential part of integration to like If someone wants to adopt a new product, I want to bring it in. It's really >> recognizing that your use case isn't everybody's used case, so you come from a static, fully functioning product to an FBI first approach, you build the FBI, then you build things around it. So when WebEx teams is released, for instance, it had certain functionality there and certain functionality wasn't there. But you could do it to the FBI. So it's partners and Cisco kind of competing at the same time to come up with a better solution. Any time you compete, you know it's good in any time something is open. It's good. So you have these Open A P I's and you have a community trying to come up with the best solution on DH. It's >> and that's really where communities of shining too right now, because you're going to community. They're great at giving feedback. If something something's not right, raise their hand. Appoint honest >> feedback, right? >> Yeah, competition. So Cisco telling Cisco something's not working. You know, you bring in some other people that maybe they're mohr AP to tell you when something's not working. They don't have any dog in the fight. You know, they'LL tell you if something's not working, they'LL give you feedback, and it really enables a better in product and a product that's more form to tailor fit for that user. That use case, >> which is exactly how it should be. Right? So last question, Jeff, before we wrap up, you already talked about how excited you were with some of the things in the Kino was day one of to >> me >> kind of expectations or hopes and dreams for what you're going to learn the rest of today and tomorrow that will help evolve the Presidio Cisco partnership. >> I mean, one thing is just making connections out here, Uh, but learning? I think so. I'm a collab guy and I'm getting to be more of a developer, and that's making me more of a generalist again. Because as a developer, yu have to interact with more than just collab FBI's. I'm getting into wireless and enterprise and everything security. So what I get out of combat is like, this is going around seeing what's happening and other technologies and other verticals and once again, competitive ideas seeing what other people are doing. Adding to that telling them what I'm doing A >> lot of collaboration pun intended. >> Yeah, You like it If you like puns. The keynote tomorrow is gonna be amazing. >> Is it way watching? Excellent. Jeff, Thanks so much for joining. Joining me on the Cube today. We appreciate your time for Joe inferior. I'm Lisa Martin. You're watching the Cube live from Cisco Dove Net. Create twenty nineteen. Thanks for watching.

>> Announcer: Live from San Jose, California, it's the CUBE, covering Big Data Silicon Valley 2017. (upbeat synthesizer music) >> Live with the CUBE coverage of Big Data Silicon Valley or Big Data SV, #BigDataSV in conjunction with Strata + Hadoop. I'm John Furrier with the CUBE and my co-host George Gilbert, analyst at Wikibon. I'm excited to have our next guest, Yaron Haviv, who's the founder and CTO of iguazio, just wrote a post up on SiliconANGLE, check it out. Welcome to the CUBE. >> Thanks, John. >> Great to see you. You're in a guest blog this week on SiliconANGLE, and always great on Twitter, cause Dave Alante always liked to bring you into the contentious conversations. >> Yaron: I like the controversial ones, yes. (laughter) >> And you add a lot of good color on that. So let's just get right into it. So your company's doing some really innovative things. We were just talking before we came on camera here, about some of the amazing performance improvements you guys have on many different levels. But first take a step back, and let's talk about what this continuous analytics platform is, because it's unique, it's different, and it's got impact. Take a minute to explain. >> Sure, so first a few words on iguazio. We're developing a data platform which is unified, so basically it can ingest data through many different APIs, and it's more like a cloud service. It is for on-prem and edge locations and co-location, but it's managed more like a cloud platform so very similar experience to Amazon. >> John: It's software? >> It's software. We do integrate a lot with hardware in order to achieve our performance, which is really about 10 to 100 times faster than what exists today. We've talked to a lot of customers and what we really want to focus with customers in solving business problems, Because I think a lot of the Hadoop camp started with more solving IT problems. So IT is going kicking tires, and eventually failing based on your statistics and Gardner statistics. So what we really wanted to solve is big business problems. We figured out that this notion of pipeline architecture, where you ingest data, and then curate it, and fix it, et cetera, which was very good for the early days of Hadoop, if you think about how Hadoop started, was page ranking from Google. There was no time sensitivity. You could take days to calculate it and recalibrate your search engine. Based on new research, everyone is now looking for real time insights. So there is sensory data from (mumbles), there's stock data from exchanges, there is fraud data from banks, and you need to act very quickly. So this notion of and I can give you examples from customers, this notion of taking data, creating Parquet file and log files, and storing them in S3 and then taking Redshift and analyzing them, and then maybe a few hours later having an insight, this is not going to work. And what you need to fix is, you have to put some structure into the data. Because if you need to update a single record, you cannot just create a huge file of 10 gigabyte and then analyze it. So what we did is, basically, a mechanism where you ingest data. As you ingest the data, you can run multiple different processes on the same thing. And you can also serve the data immediately, okay? And two examples that we demonstrate here in the show, one is video surveillance, very nice movie-style example, that you, basically, ingest pictures for S3 API, for object API, you analyze the picture to detect faces, to detect scenery, to extract geolocation from pictures and all that, all those through different processes. TensorFlow doing one, serverless functions that we have, do other simpler tasks. And in the same time, you can have dashboards that just show everything. And you can have Spark, that basically does queries of where was this guys last seen? Or who was he with, you know, or think about the Boston Bomber example. You could just do it in real time. Because you don't need this notion of pipeline. And this solves very hard business problems for some of the customers we work with. >> So that's the key innovation, there's no pipe lining. And what's the secret sauce? >> So first, our system does about a couple of million of transactions per second. And we are a multi-modal database. So, basically, you can ingest data as a stream, exactly the same data could be read by Spark as a table. So you could, basically, issue a query on the same data. Give me everything that has a certain pattern or something, and could also be served immediately through RESTful APIs to a dashboard running AngularJS or something like that. So that's the secret sauce, is by having this integration, and this unique data model, it allows you all those things to work together. There are other aspects, like we have transactional semantics. One of the challenges is how do you make sure that a bunch of processes don't collide when they update the same data. So first you need a very low ground alert. 'cause each one may update to different field. Like this example that I gave with GeoData, the serverless function that does the GeoData extraction only updates the GeoData fields within the records. And maybe TensorFlow updates information about the image in a different location in the record or, potentially, a different record. So you have to have that, along with transaction safety, along with security. We have very tight security at the field level, identity level. So that's re-thinking the entire architecture. And I think what many of the companies you'll see at the show, they'll say, okay, Hadoop is given, let's build some sort of convenience tools around it, let's do some scripting, let's do automation. But serve the underlying thing, I won't use dirty words, but is not well-equipped to the new challenges of real time. We basically restructured everything, we took the notions of cloud-native architectures, we took the notions of Flash and latest Flash technologies, a lot of parallelism on CPUs. We didn't take anything for granted on the underlying architecture. >> So when you found the company, take a personal story here. What was the itch you were scratching, why did you get into this? Obviously, you have a huge tech advantage, which is, will double-down with the research piece and George will have some questions. What got you going with the company? You got a unique approach, people would love to do away with the pipeline, that sounds great. And the performance, you said about 100x. So how did you get here? (laughs) Tell the story. >> So if you know my background, I ran all the data center activities in Mellanox, and you know Mellanox, I know Kevin was here. And my role was to take Mellanox technology, which is 100 gig networking and silicon, and fit it into the different applications. So I worked with SAP HANA, I worked with Teradata, I worked on Oracle Exadata, I work with all the cloud service providers on building their own object storage and NoSQL and other solutions. I also owned all the open source activities around Hadoop and Saf and all those projects, and my role was to fix many of those. If a customer says I don't need 100 gig, it's too fast for me, how do I? And my role was to convince him that yes, I can open up all the bottleneck all the way up to your stack so you can leverage those new technologies. And for that we basically sowed inefficiencies in those stacks. >> So you had a good purview of the marketplace. >> Yaron: Yes. >> You had open source on one hand, and then all the-- >> All the storage players, >> vendors, network. >> all the database players and all the cloud service providers were my customers. So you're a very unique point where you see the trajectory of cloud. Doing things totally different, and sometimes I see the trajectory of enterprise storage, SAN, NAS, you know, all Flash, all that, legacy technologies where cloud providers are all about object, key value, NoSQL. And you're trying to convince those guys that maybe they were going the wrong way. But it's pretty hard. >> Are they going the wrong way? >> I think they are going the wrong way. Everyone, for example, is running to do NVMe over Fabric now that's the new fashion. Okay, I did the first implementation of NVMe over Fabric, in my team at Mellanox. And I really loved it, at that time, but databases cannot run on top of storage area networks. Because there are serialization problems. Okay, if you use a storage area network, that mean that every node in the cluster have to go and serialize an operation against the shared media. And that's not how Google and Amazon works. >> There's a lot more databases out there too, and a lot more data sources. You've got the Edge. >> Yeah, but all the new databases, all the modern databases, they basically shared the data across the different nodes so there are no serialization problems. So that's why Oracle doesn't scale, or scale to 10 nodes at best, with a lot of RDMA as a back plane, to allow that. And that's why Amazon can scale to a thousand nodes, or Google-- >> That's the horizontally-scalable piece that's happening. >> Yeah, because, basically, the distribution has to move into the higher layers of the data, and not the lower layers of the data. And that's really the trajectory where the traditional legacy storage and system vendors are going, and we sort of followed the way the cloud guys went, just with our knowledge of the infrastructure, we sort of did it better than what the cloud guys did. 'Cause the cloud guys focused more on the higher levels of the implementation, the algorithms, the Paxos, and all that. Their implementation is not that efficient. And we did both sides extremely efficient. >> How about the Edge? 'Cause Edge is now part of cloud, and you got cloud has got the compute, all the benefits, you were saying, and still they have their own consumption opportunities and challenges that everyone else does. But Edge is now exploding. The combination of those things coming together, at the intersection of that is deep learning, machine learning, which is powering the AI hype. So how is the Edge factoring into your plan and overall architectures for the cloud? >> Yeah, so I wrote a bunch of posts that are not published yet about the Edge, But my analysis along with your analysis and Pierre Levin's analysis, is that cloud have to start distribute more. Because if you're looking at the trends. Five gig, 5G Wi-Fi in wireless networking is going to be gigabit traffic. Gigabit to the homes, they're going to buy Google, 70 bucks a month. It's going to push a lot more bend with the Edge. On the same time, a cloud provider, is in order to lower costs and deal with energy problems they're going to rural areas. The traditional way we solve cloud problems was to put CDNs, so every time you download a picture or video, you got to a CDN. When you go to Netflix, you don't really go to Amazon, you got to a Netflix pop, one of 250 locations. The new work loads are different because they're no longer pictures that need to be cashed. First, there are a lot of data going up. Sensory data, upload files, et cetera. Data is becoming a lot more structured. Censored data is structured. All this car information will be structured. And you want to (mumbles) digest or summarize the data. So you need technologies like machine learning, NNI and all those things. You need something which is like CDNs. Just mini version of cloud that sits somewhere in between the Edge and the cloud. And this is our approach. And now because we can string grab the mini cloud, the mini Amazon in a way more dense approach, then this is a play that we're going to take. We have a very good partnership with Equinox. Which has 170 something locations with very good relations. >> So you're, essentially, going to disrupt the CDN. It's something that I've been writing about and tweeting about. CDNs were based on the old Yahoo days. Cashing images, you mentioned, give me 1999 back, please. That's old school, today's standards. So it's a whole new architecture because of how things are stored. >> You have to be a lot more distributive. >> What is the architecture? >> In our innovation, we have two layers of innovation. One is on the lower layers of, we, actually, have three main innovations. One is on the lower layers of what we discussed. The other one is the security layer, where we classify everything. Layer seven at 100 gig graphic rates. And the third one is all this notion of distributed system. We can, actually, run multiple systems in multiple locations and manage them as one logical entity through high level semantics, high level policies. >> Okay, so when we take the CUBE global, we're going to have you guys on every pop. This is a legit question. >> No it's going to take time for us. We're not going to do everything in one day and we're starting with the local problems. >> Yeah but this is digital transmissions. Stay with me for a second. Stay with this scenario. So video like Netflix is, pretty much, one dimension, it's video. They use CDNs now but when you start thinking in different content types. So, I'm going to have a video with, maybe, just CGI overlayed or social graph data coming in from tweets at the same time with Instagram pictures. I might be accessing multiple data everywhere to watch a movie or something. That would require beyond a CDN thinking. >> And you have to run continuous analytics because it can not afford batch. It can not afford a pipeline. Because you ingest picture data, you may need to add some subtext with the data and feed it, directly, to the consumer. So you have to move to those two elements of moving more stuff into the Edge and running into continuous analytics versus a batch on pipeline. >> So you think, based on that scenario I just said, that there's going to be an opportunity for somebody to take over the media landscape for sure? >> Yeah, I think if you're also looking at the statistics. I seen a nice article. I told George about it. That analyzing the Intel cheap distribution. What you see is that there is a 30% growth on Intel's cheap Intel Cloud which is faster than what most analysts anticipate in terms of cloud growth. That means, actually, that cloud is going to cannibalize Enterprise faster than what most think. Enterprise is shrinking about 7%. There is another place which is growing. It's Telcos. It's not growing like cloud but part of it is because of this move towards the Edge and the move of Telcos buying white boxes. >> And 5G and access over the top too. >> Yeah but that's server chips. >> Okay. >> There's going to be more and more computation in the different Telco locations. >> John: Oh you're talking about computer, okay. >> This is an opportunity that we can capitalize on if we run fast enough. >> It sounds as though because you've implemented these industry standard APIs that come from the, largely, the open source ecosystem, that you can propagate those to areas on the network that the vendors, who are behind those APIs can't, necessarily, do. Into the Telcos, towards the Edge. And, I assume, part of that is cause of the density and the simplicity. So, essentially, your footprint's smaller in terms of hardware and the operational simplicity is greater. Is that a fair assessment? >> Yes and also, we support a lot of Amazon compatible APIs which are RESTful, typically, HTTP based. Very convenient to work with in a cloud environment. Another thing is, because we're taking all the state on ourself, the different forms of states whether it's a message queue or a table or an object, et cetera, that makes the computation layer very simple. So one of the things that we are, also, demonstrating is the integration we have with Kubernetes that, basically, now simplifies Kubernetes. Cause you don't have to build all those different data services for cloud native infrastructure. You just run Kubernetes. We're the volume driver, we're the database, we're the message queues, we're everything underneath Kubernetes and then, you just run Spark or TensorFlow or a serverless function as a Kubernetes micro service. That allows you now, elastically, to increase the number of Spark jobs that you need or, maybe, you have another tenant. You just spun a Spark job. YARN has some of those attributes but YARN is very limited, very confined to the Hadoop Ecosystem. TensorFlow is not a Hadoop player and a bunch of those new tools are not in Hadoop players and everyone is now adopting a new way of doing streaming and they just call it serverless. serverless and streaming are very similar technologies. The advantage of serverless is all this pre-packaging and all this automation of the CICD. The continuous integration, the continuous development. So we're thinking, in order to simplify the developer in an operation aspects, we're trying to integrate more and more with cloud native approach around CICD and integration with Kubernetes and cloud native technologies. >> Would it be fair to say that from a developer or admin point of view, you're pushing out from the cloud towards the Edge faster than if the existing implementations say, the Apache Ecosystem or the AWS Ecosystem where AWS has something on the edge. I forgot whether it's Snowball or Green Grass or whatever. Where they at least get the lambda function. >> They're field by the way and it's interesting to see. One of the things they allowed lambda functions in their CDS which is going the direction I mentioned just for a minimal functionality. Another thing is they have those boxes where they have a single VM and they can run lambda function as well. But I think their ability to run computation is very limited and also, their focus is on shipping the boxes through mail and we want it to be always connected. >> Our final question for you, just to get your thoughts. Great save up, by the way. This is very informative. Maybe be should do a follow up on Skype in our studio for Silocon Friday show. Google Next was interesting. They're serious about the Enterprise but you can see that they're not yet there. What is the Enterprise readiness from your perspective? Cause Google has the tech and they try to flaunt the tech. We're great, we're Google, look at us, therefore, you should buy us. It's not that easy in the Enterprise. How would you size up the different players? Because they're all not like Amazon although Amazon is winning. You got Amazon, Azure and Google. Your thoughts on the cloud players. >> The way we attack Enterprise, we don't attack it from an Enterprise perspective or IT perspective, we take it from a business use case perspective. Especially, because we're small and we have to run fast. You need to identify a real critical business problem. We're working with stock exchanges and they have a lot of issues around monitoring the daily trade activities in real time. If you compare what we do with them on this continuous analytics notion to how they work with Excel's and Hadoops, it's totally different and now, they could do things which are way different. I think that one of the things that Hadook's customer, if Google wants to succeed against Amazon, they have to find the way of how to approach those business owners and say here's a problem Mr. Customer, here's a business challenge, here's what I'm going to solve. If they're just going to say, you know what? My VM's are cheaper than Amazon, it's not going to be a-- >> Also, they're doing the whole, they're calling lift and shift which is code word for rip and replace in the Enterprise. So that's, essentially, I guess, a good opportunity if you can get people to do that but not everyone's ripping and replacing and lifting and shifting. >> But a lot of Google advantages around areas of AI and things like that. So they should try and leverage, if you think about Amazon approach to AI, this fund the university to build a project and then set it's hours where Google created TensorFlow and created a lot of other IPs and Dataflow and all those solutions and consumered it to the community. I really love Google's approach of contributing Kubernetes, to contributing TensorFlow. And this way, they're planting the seeds so the new generation this is going to work with Kubernetes and TensorFlow who are going to say, "You know what?" "Why would I mess with this thing on (mumbles) just go and. >> Regular cloud, do multi-cloud. >> Right to the cloud. But I think a lot of criticism about Google is that they're too research oriented. They don't know how to monetize and approach the-- >> Enterprise is just a whole different drum beat and I think that's the only thing on my complaint with them, they got to get that knowledge and/or buy companies. Have a quick final point on Spanner or any analysis of Spanner that went from paper, pretty quickly, from paper to product. >> So before we started iguazio, I started Spanner quite a bit. All the publication was there and all the other things like Spanner. Spanner has the underlying layer called Colossus. And our data layer is very similar to how Colossus works. So we're very familiar. We took a lot of concepts from Spanner on our platform. >> And you like Spanner, it's legit? >> Yes, again. >> Cause you copied it. (laughs) >> Yaron: We haven't copied-- >> You borrowed some best practices. >> I think I cited about 300 research papers before we did the architecture. But we, basically, took the best of each one of them. Cause there's still a lot of issues. Most of those technologies, by the way, are designed for mechanical disks and we can talk about it in a different-- >> And you have Flash. Alright, Yaron, we have gone over here. Great segment. We're here, live in Silicon Valley, breakin it down, getting under the hood. Looking a 10X, 100X performance advantages. Keep an eye on iguazio, they're looking like they got some great products. Check them out. This is the CUBE. I'm John Furrier with George Gilbert. We'll be back with more after this short break. (upbeat synthesizer music)

>> Announcer: Live from Boston, Massachusetts this is the CUBE covering Spark Summit East 2017 brought to you by Databricks. Now, here are your hosts Dave Vellante and George Gilbert. >> Welcome back to Boston everybody this is the CUBE. We're live here at Spark Summit East in the Hynes Convention Center. This is the CUBE, check out SiliconANGLE.com for all the news of the day. Check out Wikibon.com for all the research. I'm really excited about this session here. Al Essa is here, he's the vice president of analytics and R&D at McGraw-Hill Education. And I'm so excited because we always talk about digital transformations and transformations. We have an example of 150 year old company that has been, I'm sure, through many transformations. We're going to talk about a recent one. Al Essa, welcome to the CUBE, thanks for coming on. >> Thank you, pleasure to be here. >> So you heard my little narrative up front. You, obviously, have not been with the company for 150 years (laughs), you can't talk about all the transformations, but there's certainly one that's recent in the last couple of years, anyway which is digital. We know McGraw Hill is a print publisher, describe your business. >> Yeah, so McGraw Hill Education has been traditionally a print publisher, but beginning with our new CEO, David Levin, he joined the company about two years ago and now we call ourselves a learning science company. So it's no longer print publishing, it's smart digital and by smart digital we mean we're trying to transform education by applying principles of learning science. Basically what that means is we try to understand, how do people learn? And how they can learn better. So there are a number of domains, cognitive science, brain sciences, data science and we begin to try to understand what are the known knowns in these areas and then apply it to education. >> I think Marc Benioff said it first, at least the first I heard he said there were going to be way more Saas companies that come out of non-tech companies than tech companies. We're talking off camera, you're a software company. Describe that in some detail. >> Yeah, so being a software company is new for us, but we've moved pretty quickly. Our core competency has been really expert knowledge about education. We work with educators, subject matter experts, so for over a hundred years, we've created vetted content, assessments, and so on. So we have a great deal of domain expertise in education and now we're taking, sort of the new area of frontiers of knowledge, and cognitive science, brain sciences. How can learners learn better and applying that to software and models and algorithms. >> Okay, and there's a data component to this as well, right? >> So yeah, the way I think about it is we're a smart digital company, but smart digital is fueled by smart data. Data underlies everything that we do. Why? Because in order to strengthen learners, provide them with the optimal pathway, as well as instructors. We believe instructors are at the center of this new transformation. We need to provide immediate, real-time data to students and instructors on, how am I doing? How can I do better? This is the predictive component and then you're telling me, maybe I'm not on the best path. So what's my, "How can I do better?" the optimal path. So all of that is based on data. >> Okay, so that's, I mean, the major reason. Do you do any print anymore? Yes, we still do print, because there's still a huge need for print. So print's not going to go away. >> Right. Okay, I just wanted to clarify that. But what you described is largely a business model change, not largely, it is a business model change. But also the value proposition is changing. You're providing a new service, related, but new incremental value, right? >> Yeah, yeah. So the value proposition has changed, and here again, data is critical. Inquiring minds want to know. Our customers want to know, "All right, we're going to use your technology "and your products and solutions, "show us "rigorously, empirically, that it works." That's the bottom line question. Is it effective? Are the tools, products, solutions, not just ours, but are our products and solutions have a context. Is the instruction effective? Is it effective for everyone? So all that is reliant on data. >> So how much of a course, how much of the content in a course would you prepare? Is it now the entire courseware and you instrument the students interaction with it? And then, essentially you're selling the outcomes, the improved outcomes. >> Yeah, I think that's one way to think about it. Here's another model change, so this is not so much digital versus non-digital, but we've been a closed environment. You buy a textbook from us, all the material, the assessments is McGraw Hill Education. But now a fundamental part of our thinking as a software company is that we have to be an open company. Doesn't mean open as in free, but it's an open ecosystem, so one of the things that we believe in very much is standards. So there's a standard body in education called IMS Global. My boss, Stephen Laster, is on the board of IMS Global. So think of that as, this encompasses everything from different tools working together, interoperability tools, or interoperability standards, data standards for data exchange. So, we will always produce great content, great assessments, we have amazing platform and analytics capability, however, we don't believe all of our customers are going to want to use everything from McGraw Hill. So interoperability standards, data standards is vital to what we're doing. >> Can you explain in some detail this learning science company. Explain how we learn. We were talking off camera about sort of the three-- >> Yeah, so this is just one example. It's well known that memory decays exponentially, meaning when you see some item of knowledge for the first time, unless something happens, it goes into short-term memory and then it evaporates. One of the challenges in education is how can I acquire knowledge and retain knowledge? Now most of the techniques that we all use are not optimal. We cram right before an exam. We highlight things and that creates the illusion that we'll be able to recall it. But it's an illusion. Now, cognitive science and research in cognitive science tells us that there are optimal strategies for acquiring knowledge and recalling it. So three examples of that are effort for recall. If you have to actively recall some item of knowledge, that helps with the stickiness. Another is space practice. Practicing out your recall over multiple sessions. Another one is interleaving. So what we do is, we just recently came out with a product last week called, StudyWise. What we've done is taken those principles, written some algorithms, applies those algorithms into a mobile product. That's going to allow learners to optimize their acquisition and recall of knowledge. >> And you're using Spark to-- >> Yeah, we're using Spark and we're using Databricks. So I think what's important there is not just Spark as a technology, but it's an ecosystem, it's a set of technologies. And it has to be woven together into a workflow. Everything from building the model and algorithm, and those are always first approximations. We do the best we can, in terms of how we think the algorithm should work and then deploy that. So our data science team and learning science team builds the models, designs the models, but our IT team wants to make sure that it's part of a workflow. They don't want to have to deal with a new set of technologies, so essentially pressing the button goes into production and then it doesn't stop there, because as Studywise has gone on the market last week, now we're collecting data real-time as learners are interacting with our products. The results of their interactions is coming in to our research environment and we're analyzing that data, as a way of updating our models and tuning the models. >> So would it be fair to say that it was interesting when you talked about these new ways of learning. If I were to create an analogy to Legacy Enterprise apps, they standardize business transactions and the workflows that went with them. It's like you're picking out the best practices in learning, codifying them into an application. And you've opened it up so other platforms can take some or all and then you're taking live feedback from the models, but not just tuning the existing model, but actually adding learning to the model over time as you get a better sense for how effort of recall works or interleaving works. >> Yeah, I think that's exactly right. I do want to emphasize something, an aspect of what you just said is we believe, and it's not just we believe, the research in learning science shows that we can get the best, most significant learning gains when we place the instructor, the master teacher, at the center of learning. So, doing that, not just in isolation, but what we want to do is create a community of practitioners, master teachers. So think of the healthcare analogy. We have expert physicians, so when we have a new technique or even an old technique, What's working? What's not working? Let's look at the data. What we're also doing is instrumenting our tools so that we can surface these insights to the master practitioners or master teachers. George is trying this technique, that's working or not working, what adjustments do we need to make? So it's not just something has to happen with the learner. Maybe we need to adjust our curriculum. I have to change my teaching practices, my assessments. >> And the incentive for the master practitioners to collaborate is because that's just their nature? >> I think it is. So let's kind of stand back, I think the current paradigm of instruction is lecture mode. I want to impart knowledge, so I'm going to give a lecture. And then assessment is timed tests. In the educational, the jargon for that is summit of assessments, so lecture and tests. That's the dominant paradigm in education. All the research evidence says that doesn't work. (laughs) It doesn't work, but we still do it. >> For how many hundreds of years? >> Yeah. Well, it was okay if we needed to train and educate a handful of people. But now, everyone needs to be educated and it's lifelong learning rate, so that paradigm doesn't work. And the research evidence is overwhelming that it doesn't work. We have to change our paradigm where the new paradigm, and this is again based on research, is differentiated instruction. Different learners are at different stages in their learning and depending on what you need to know, I'm at a different stage. So, we need assessments. Assessments are not punitive, they're not tests. They help us determine what kind of knowledge, what kind of information each learner needs to know. And the instructor helps with the differentiated instruction. >> It's an alignment. >> It's an alignment, yeah. Really to take it to the next stage, the master practitioners, if they are armed with the right data, they can begin to compare. All right, practices this way of teaching for these types of students works well, these are the adjustments that we need to make. >> So, bringing it down to earth with Spark, these models of how to teach, or perhaps how to differentiate the instruction, how to do differentiated assessments, these are the Spark models. >> Yeah, these are the Spark models. So let's kind of stand back and see what's different about traditional analytics or business intelligence and the new analytics enabled by Spark, and so on. First, traditional analytics, the questions that you need to be able to answer are defined beforehand. And then they're implemented in schemas in a data warehouse. In the new order of things, I have questions that I need to ask and they just arise right now. I'm not going to anticipate all the questions that I might want to be able to ask. So, we have to be enable the ability to ask new questions and be able to receive answers immediately. Second, the feedback loop, traditional analytics is a batch mode. Overnight, data warehouse gets updated. Imagine you're flying an airplane, you're the pilot, a new weather system emerges. You can't wait a week or six months to get a report. I have to have corrective course. I have to re-navigate and find a new course. So, the same way, a student encounters difficulty, tell me what I need to do, what course correction do I need to apply? The data has to come in real-time. The models have to run real-time. And if it's at scale, then we have to have parallel processing and then the updates, the round trip, data back to the instructor or the student has to be essentially real-time or near real-time. Spark is one of the technologies that's enabling that. >> The way you got here is kind of interesting. You used to be CIO, got that big Yale brain (laughs) working for you. You're not a developer, I presume, is that right? >> No. >> How did you end up in this role? >> I think it's really a passion for education and I think this is at McGraw Hill. So I'm a first generation college student, I went to public school in Los Angeles. I had a lot of great breaks, I had great teachers who inspired me. So I think first, it's education, but I think we have a major, major problem that we need to solve. So if we look at... So I spent five years with the Minnesota state colleges and university system, most of the colleges, community colleges are open access institutions. So let me just give you a quick statistic. 70% of students who enter community colleges are not prepared in math and english. So seven out of 10 students need remediation. Of the seven out of 10 students who need remediation, only 15% not 5-0, one-five succeed to the next level. This is a national tragedy. >> And that's at the community college level? >> That's at the community college level. We're talking about millions of students who are not making it past the first gate. And they go away thinking they've failed, they incurred debt, their life is now stuck. So this is playing itself out, not to tens of thousands of students, but hundreds of thousands of students annually. So, we've got to solve this problem. I think it's not technology, but reshaping the paradigm of how we think about education. >> It is a national disaster, because often times that's the only affordable route for folks and they are taking on debt, thinking okay, this is a gateway. Al, we have to leave it there. Awesome segment, thanks very much for coming to the CUBE, really appreciate it. >> Thank you very much. >> All right, you're welcome. Keep it right there, my buddy, George and I will be back with our next guest. This is the CUBE, we're live from Boston. Be right back. (techno music) >> Narrator: Since the dawn of the cloud