>> Narrator: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2017, presented by AWS, Intel, and our ecosystem of partners. >> Hello everyone, welcome to a special CUBE presentation here, live in Las Vegas for Amazon Web Service's AWS re:Invent 2017. This is theCUBE's fifth year here. We've been watching the progression. I'm John Furrier with Justin here as my co-host. Our two next guests are Bob Rogers, the chief data scientist at Intel, and Julie Cardoa, who's the CEO of Thorn. Great guests, showing some AI for good. Intel, obviously, good citizen and great technology partner. Welcome to theCUBE. >> Thank you, thanks for having us! >> So, I saw your talk you gave at the Public Sector Breakfast this morning here at re:Invent. Packed house, fire marshal was kicking people out. Really inspirational story. Intel, we've talked at South by Southwest. You guys are really doing a lot of AI for good. That's the theme here. You guys are doing incredible work. >> Julie: Thank you. >> Tell your story real quick. >> Yeah, so Thorn is a nonprofit, we started about five years ago, and we are just specifically dedicated to build new technologies to defend children form sexual abuse. We were seeing that, as, you know, new technologies emerge, there's new innovation out there, how child sexual abuse was presenting itself was changing dramatically. So, everything from child sex trafficking online, to the spread of child sexual abuse material, livestreaming abuse, and there wasn't a concentrated effort to put the best and brightest minds and technology together to be a part of the solution, and so that's what we do. We build products to stop child abuse. >> John: So you're a nonprofit? >> Julie: Yep! >> And you're in that public sector, but you guys have made a great progress. What's the story behind it? How did you get to do so effective work in such a short period of time as a nonprofit? >> Well, I think there's a couple things to that. One is, well, we learned a lot really quickly, so what we're doing today is not what we thought we would do five years ago. We thought we were gonna talk to big companies, and push them to do more, and then we realized that we actually needed to be a hub. We needed to build our own engineering teams, we needed to build product, and then bring in these companies to help us, and to add to that, but there had to be some there there, and so we actually have evolved. We're a nonprofit, but we are a product company. We have two products used in 23 countries around the world, stopping abuse every day. And I think the other thing we learned is that we really have to break down silos. So, we didn't, in a lot of our development, we didn't go the normal route of saying, okay, well this is a law enforcement job, so we're gonna go bid for a big government RFE. We just went and built a tool and gave it to a bunch of police officers and they said, "Wow, this works really well, "we're gonna keep using it." And it kinda spread like wildfire. >> And it's making a difference. It's really been a great inspirational story. Check out Thorn, amazing work, real use case, in my mind, a testimonial for how fast you can accelerate. Congratulations. Bob, I wanna get your take on this because it's a data problem that, actually, the technology's applying to a problem that people have been trying to crack the code on for a long time. >> Yeah, well, it's interesting, 'cause the context is that we're really in this era of AI explosion, and AI is really computer systems that can do things that only humans could do 10 years ago. That's kind of my basic way of thinking about it, so the problem of being able to recognize when you're looking at two images of the same child, which is the piece that we solved for Thorn, actually, you know, is a great example of using the current AI capabilities. You start with the problem of, if I show an algorithm two different images of the same child, can it recognize that they're the same? And you basically customize your training to create a very specific capability. Not a basic image recognition or facial recognition, but a very specific capability that's been trained with specific examples. I was gonna say something about what Julie was describing about their model. Their model to create that there there has been incredible because it allows them to really focus our energy into the right problems. We have lots of technology, we have lots of different ways of doing AI and machine learning, but when we get a focus on this is the data, this is the exact problem we need to solve, and this is the way it needs to work for law enforcement, for National Center for Missing and Exploited Children. It has really just turned the knob up to 11, so to speak. >> I mean, this is an example where, I mean, we always talk about how tech transformation can make things go faster. It's such an obvious problem. I mean, it's almost everyone kinda looks away because it's too hard. So, I wanna ask you, how do people make this happen for other areas for good? So, for instance, you know, what was the bottlenecks before? What solved the problem, because, I mean, you could really make a difference here. You guys are. >> Well, I think there's a couple things. I think you hit on one, which is this is a problem people turn away from. It's really hard to look at. And the other thing is is there's not a lot of money to be made in using advanced technology to find missing and exploited children, right? So, it did require the development of a nonprofit that said, "We're gonna do this, "and we're gonna fundraise to get it done." But it also required us to look at it from a technology angle, right? I think a lot of times people look at social issues from the impact angle, which we do, but we said, "What if we looked at it "from a different perspective? "How can technology disrupt in this area?" And then we made that the core of what we do, and we partnered with all the other amazing organizations that are doing the other work. And I think, then, what Bob said was that we created a hub where other experts could plug into, and I think, in any other issue area that you're working on, you can't just talk about it and convene people. You actually have to build, and when you build, you create a platform that others can add to, and I think that is one of the core reasons why we have seen so much progress, is we started out convening and really realized that wasn't gonna last very long, and then we built, and once we started building, we scaled. >> So, you got in the market quickly with something. >> Yeah. >> So, one of the issues with any sort of criminal enterprise is it tends to end up in a bit of an arms race, so you've built this great technology but then you've gotta keep one step ahead of the bad guys. So, how are you actually doing that? How are you continuing to invest in this and develop it to make sure that you're always one step ahead? >> So, I can address that on a couple of levels. One is, you know, working with Thorn, and I lead a program at Intel called the Safer Children Program, where we work with Thorn and also the National Center for Missing and Exploited Children. Those conversations bring in all of the tech giants, and there's a little bit of sibling rivalry. We're all trying to throw in our best tech. So, I think we all wanna do as well as we can for these partnerships. The other thing is, just in very tactical terms, working with Thorn, we've actually, Thorn and with Microsoft, we've created a capability to crowdsource more data to help improve the accuracy of these deep learning algorithms. So, by getting critical mass around this problem, we've actually now created enough visibility that we're getting more and more data. And as you said earlier, it's a data problem, so if you have enough data, you can actually create the models with the accuracy and the capability that you need. So, it starts to feed on itself. >> Julie talked about the business logic, how she attacked that. That's really, 'cause I think one thing notable, good use case, but from a tech perspective, how does the cloud fit in with Intel specifically? Because it really, the cloud is an enabler too. >> Bob: Yeah, absolutely. >> How's that all working with Intel? And you go on about whole new territory you guys are forging in here, it's awesome, but the cloud. >> Right, so, for us, the cloud is an incredible way for us to make our compute capability available to anyone who needs to do computing, especially in this data-driven algorithm era where more and more machine learning, more and more AI, more and more data-driven problems are coming to the fore, doing that work on the cloud and being able to scale your work according to how much data is coming in at any time, it makes the cloud a really natural place for us. And of course, Intel's hardware is a core component of pretty much all the cloud that you could connect to. >> And the compute that you guys provide, and Amazon adds to it, their cloud is impressive. Now, I'd like to know what you guys are gonna be talking about in your session. You have a session here at re:Invent. What's the title of the session, what's the agenda, is it the same stuff here, what's gonna be talked about? >> So, we're talking about life-changing AI applications, and in specific we're gonna talk about, at the end Julie will talk about what Thorn has done with the child-finder and the AI that we and Microsoft built for them. We'll also, I'll start out by talking about Intel's role broadly in the computing and AI space. Intel really looks to take all of its different hardware, and networking, and memory assets, and make it possible for anybody to do the kinds of artificial intelligence or machine learning they need to do. And then in the middle, there's a really cool deployment on AWS sandwich that (something) will talk about how they've taken the models and really dialed them up in terms of how fast you can go through this data, so that we can go through millions and millions of images in our searches, and come back with results really, really fast. So, it's a great sort of three piece story about the conception of AI, the deployment at scale and with high performance, and then how Thorn is really taking that and creating a human impact around it. >> So, Bob, I asked you the Intel question because no one calls up Intel and says, "Hey, give me some AI for good." I mean, I wish that would be the case. >> Well, they do now. >> If they do, well, share your strategy, because cloud makes sense. I could see how you could provision easily, get in there, really empowering people to do stuff that's passionable and relevant. But how do you guys play in all of this? 'Cause I know you supply stuff to the cloud guys. Is this a formal program you're doing at Intel? Is this a one-off? >> Yeah, so Safer Children is a formal program. It started with two other folks, Lisa Davis and Lisa Theinai, going to the VP of the entire data center group and saying, "There is an opportunity to make a big impact "with Intel technology, and we'd like to do this." And it started literally because Intel does actually want to do good work for humankind, and frankly, the fact that these people are using our technology and other technology to hurt children, it steams our dumplings, frankly. So, it started with that. >> You've been a team player with Amazon and everyone else. >> Exactly, so then, once we've been able to show that we can actually create technology and provide infrastructure to solve these problems, it starts to become a self-fulfilling prophecy where people are saying, "Hey, we've got this "interesting adjacent problem that "this kind of technology could solve. "Is there an opportunity to work together and solve that?" And that fits into our bigger, you know, people ask me all the time, "Why does Intel have a chief data scientist?" We're a hardware company, right? The answer is-- >> That processes a lot of data! >> Yes, that processes a lot of data. Literally, we need to help people know how to get value from their data. So, if people are successful with their analytics and their AI, guess what, they're gonna invest in their infrastructure, and it sort of lifts Intel's boat across the board. >> You guys have always been a great citizen, and great technology provider, and hats off to Intel. Julie, tell a story about an example people can get a feel for some of the impact, because I saw you on stage this morning with Theresa Carlson, and we've been tracking her efforts in the public sector have been amazing, and Intel's been part of that too, congratulations. But you were kind of emotional, and you got a lot of applause. What's some of the impact? Tell a story of how important this really is, and your work at Thorn. >> Yeah, well, I mean, one of the areas we work in is trying to identify children who are being sold online in the US. A lot of people, first of all, think that's happening somewhere else. No, that's here in this country. A lot of these kids are coming out of foster care, or are runaways, and they get convinced by a pimp or a trafficker to be sold into prostitution, basically. So, we have 150,000 escort ads posted every single day in this country, and somewhere in there are children, and it's really difficult to look through that with your eye, and determine what's a child. So, we built a tool called Spotlight that basically reads and analyzes every ad as it comes in, and we layer on smart algorithms to say to an officer, "Hey, this is an ad you need to pay attention to. "It looks like this could be a child." And we've had over 6,000 children identified over the last year. >> John: That's amazing. >> You know, it happens in a situation where, you know, you have online it says, you know, this girl's 18, and it's actually a 15-year-old girl who met a man who said he was 17, he was actually 30, had already been convicted of sex trafficking, and within 48 hours of meeting this girl, he had her up online for sale. So, that sounds like a unique incident. It is not unique, it happens every single day in almost every city and town across this country. And the work we're doing is to find those kids faster, and stop that trauma. >> Well, I just wanna say congratulations. That's great work. We had a CUBE alumni, founder of CloudAir, Jeff Hammerbacher, good friend of theCUBE. He had a famous quote that he said on theCUBE, then said on the Charlie Rose Show, "The best minds of our generations "are thinking about how to make people click ads. "That sucks." This is an example where you can really put the best minds on some of the real important things. >> Yeah, we love Jeff. I read that quote all the time. >> It's really a most important quote. Well, thanks so much. Congratulations, great inspiration, great story. Bob, thanks for coming on, appreciate it. CUBE live coverage here at AWS re:Invent 2017, kicking off day one of three days of wall-to-wall coverage here, live in Las Vegas. We'll be right back with more after this short break.

(upbeat pop music) >> Narrator: Live from Austin, Texas, it's theCUBE. Covering South by Southwest 2017. Brought to you by Intel. Now, here's John Furrier. >> Okay welcome back everyone. We are here live at South by Southwest at the Intel AI lounge. This is SiliconANGLE's theCUBE, talking to some great guests. The theme for this week is AI for Social Good. I'm John Furrier with SiliconANGLE, our next guest is Federico Gomez Suarez, technical advisor and volunteer at Thorn, doing some really amazing things with technology for the betterment of society. Specifically a use case. So Federico, welcome to theCUBE, welcome to the AI Lounge here at Intel. >> Thank you very much for having me. >> So talk about Thorn. First of all, you work for Microsoft, but you're a volunteer? >> Correct. >> Talk about what Thorn is, and what you guys do. It's really a great story. >> So Thorn is a non-profit which focuses on driving technological innovation to fight child sexual exploitation. And it does it two ways. One of them is by doing research to find the new trends and the new ways that this is happening. But also by using the latest technology to find ways that we can actually fight this problem. Thorn has something called an innovation lab, where we're always trying new technology, we're trying AI just to find new ways to fight the problem. >> So this is really a great use case of where technology is being used for the betterment of society and good, because what you're doing is taking really cutting edge big data, machine learning, AI techniques. And the rage right now is facial recognition. >> Oh Yes! >> So talk about where and how it works. And what's the results? And can you share some of the impact? >> Yeah! So as part of my volunteer work, one of the projects that I have been working, is called a child finder service. And the idea of this work is, if we have an image, particularly an image of a child who have been missing, can we use facial recognition to determine whether another image is the same child. And this is actually a pretty challenging problem because the child may have gone missing many years back and now we want to match against another picture where the child may show much growth. >> Depending on the duration, right? >> And you know, if you imagine the impact of actually having this technology, a person who is trying to look for a missing child, if they have to go through a lot of pictures, it's actually hard to determine whether two people are the same person or not. So we're helping in that case. We're helping so that you don't have to go through so many pictures. So that we can highlight the ones that the machine thinks is actually the same person. >> Take us through how it works, in just a use case, just as an illustration. >> Yeah, So when a child goes missing, the National Center for Missing Children, which we work with, they publish a poster and that poster has an image of a missing child. Now once you have that image, you may want to say well are there places where the picture of that child may be showing up. One place that there's usually pictures of children being exploited are online ads. So let's say that there's online ads and you want to say, well in any of these ads that they use for exploitation, could there be the same child in both of them. So that's actually a use case. And just using face recognition technology, we can try to make the problem easier, faster than it would be if you were trying to do it manually. >> And you're doing a demo here in the Intel AI Lounge. What's in the demo? What are you showing? >> So in the demo, I'm showing how difficult it really is to do face recognition by hand. And how by just having some assistance from a machine, you can go from having to look at hundreds of images and spending potentially hours, to doing it seconds. >> So how to do you involved? I mean, this is a volunteer organization, take us through your journey. How did you get involved? And talk about how you guys are getting more people involved, and how can someone get involved? >> Absolutely! So, you know as for Microsoft, there is the Hack for Good community, and they encourage us to go and donate our time, our skill to non-profits. Two years ago, I had this idea, and I did a hackathon. And after the hackathon, I got connected with Thorn. I learn about what they do, and that's how I pretty much got involved. I was really fortunate that Microsoft supported me to actually go spend time with a non-profit. And when I start working with Thorn, I realized, hey there's other tech companies also willing to help. So in this child finder service project, I work with Intel, I work with other companies all coming together to find ways to solve this problem using the cutting edge technology available. And you know, Thorn is always looking for volunteers, we're looking for what we call our Tech Defenders. If you go to our website, which is wearethorn.org/Sxsw, you'll find the link where you can actually volunteer your skills as a technical defender for Thorn. >> So talk about, that's very cool by the way. People should check out Thorn. Is there a website, Thorn? >> Yeah, it's wearethorn.org/sxsw. >> Okay, wearethorn.org/sxsw. For South by Southwest. So talk about the technology, because obviously Intel makes chips, makes stuff go faster, you got more compute, you've got more cores, you got now, cloud technology. And you've seen at Google Next, where they were showcasing their Xeon processor, that the AI trend now is becoming really, really, really big. I know Microsoft as your Amazon web services. They're all having these machine learning libraries, and the big trend is self-learning machines or deep-learning. So this is a tech trend. But now when you apply it to this, it really can work. So, what is some of the technology, and what are some of the data sets that you use, how does it work under the covers? >> Yeah so, we actually start with an open source technology for face recognition. And after we started with this technology, we realized that we had to make it better. So we had to build data sets ourselves. For the data sets we have images of the posters that are published from the National Center. We have also started asking people to donate images over time, of themselves. Because we need images of people when they were children, and when they're older. And that's how we've been building data sets. And then having the data set, we need to go and train them. And that's where we're using hardware, in particularly using GPUs to actually do training is really is key for us. The technology really under this is deep learning for us. We used an existing deep-learning models, and improving them with our particular scenario, cause there's special challenges in our case. Not only with the age, but also a lot of the images that we process. Sometimes there's heavy makeup, sometimes there's things like that. >> Or res, resolution right? Depending on the photo? Right? >> Yeah. And you now, low resolution images particularly they're a challenge, so we need to improve it, we need to keep training to actually get to the point where we feel we have a really robust system. >> I want to ask you a personal question. And this is something we were talking about on our intro segment, and something that I've been thinking a lot about. I haven't written about it yet, but I've been starting to tease it out on some of my thought leader interviews. Is that, in every major inflection point in the business of technology, there's always been a counter-culture movement. And it seems to be that, if you look at all the news, whether it's political or tech company news, and all this stuff happening around the world, there seems to be a social good culture developing. We're seeing a counter-culture where what was once valued, tech or public proprietary algorithms, is now changing to open source, community, societal benefits. There seems to be a lot of activity, and no one's kind of put their finger on it. And you're a great use case of that example. >> And I feel like, the Hack for Good community in Microsoft is growing, and there's people, peers of mine, working on all this kind of interesting projects helping non-profits. >> And that's called Hack for Good? >> Yes. >> What's it called? >> Hack for Good in Microsoft. >> So that's a Microsoft hackathon with employees who just say, hey let's pick something good to do and they apply their programming technical skills to... >> Yeah, and you know there's a lot of support, and we're encouraged to do it. And it's to me inspiring to work in a company that really encourage that, and you know what? I see the same when I look across the industry. I see people willing to spend their evenings, like I spend my evenings working on some of this, or weekends, but we're passionate about making a difference. And I know I'm not alone. I've met a lot of people, and I know there's a lot more out there. >> Is there a community people can check out? Is it on the website? Is there open source community? Is there a certain software groups that are playing more than others? >> Actually I don't know. I know in my space, I think a I think a great place to start is joining Thorn's Digital Defenders. But I would say if someone is passionate about a cause, it could be anything, and say I want to help, there's non-profits out there for that. And when I work with non-profits, they're so passionate about it, and sometimes they just need help in little things. And having so many tech communities go in and help them makes a huge difference. I would invite people to just go. If you're passionate about it, just go for it. Find a non-profit, they'll be happy to work with you. >> Federico, I want to ask you if you could share just some anecdotal impact that you guys have had. Can you share some successes, some advances? Just highlight some of the things. >> Yeah, so Thorn just published their yearly report and it was really encouraging. So, Thorn has a couple of different tools that they build. One of them is called Spotlight. Through the use of this tool last year, about 2,000 children who were victims of trafficking, were recovered from around 6,000 victims. And you know, each victim is a person. And the fact that we're making a difference in those lives is extremely encouraging. And that's just one of the things that we were able to contribute. So that's one of the stories that we have. And to me it's not only that. To me, it's also the fact that I see people who are willing to actually get engaged, learn more about these problems is another huge win. >> Final question for you Federico. Describe the scene here at the AI Lounge at Intel. For folks watching who aren't at South by Southwest, what is the vibe here? What are they showing? Obviously AI is the theme. AI for Social Good is our broadcast here. Hashtag is #intelai, if you're interested in sharing, we'd appreciate if you could retweet and share the love. What's your thoughts on with the vibe here? Describe the scene here. >> You know, when I look around, all the demos are amazing. Like each one of them, you're blown away by it. And it just shows you how in a practical way, AI can be changing lives or doing amazing things. There's the drones there on the video. The drones, I love those, they look amazing. And then there's also the demo around using an art style and getting your picture. I'm going to get mine in a second. I think if you come by, you'll see how AI really in practice, is able to contribute to people's lives. And the vibe is awesome. And I'm loving it here. >> Well I want to say congratulations. You do amazing things. >> Thank you. >> It's really a real testament to where the society's going AI for Social Change. Microsoft has a Hackathon for Good, and this is not a one-off. I mean Microsoft certainly has had that. Google's got the 20% work on your own project. Intel has it. Companies are getting involved, a counter-culture is developing for societal benefits. And all these new things happening, like autonomous vehicles, smart cities, these are paradigm shifting society changes around the world and will require a human involvement. Congratulations, and thanks for sharing. >> Thank you very much. And we have a hashtag just for our product which is #defendhappiness. >> John: Defend happiness? >> Yeah, which is all about stopping sexual exploitation and trafficking all around the world. >> Okay, #defendhappiness. Please put it out there and share it, tweet this video. And for the betterment of society, I'm John Furrier with Federico here at the Intel AI Lounge. More coverage from South by Southwest. Three days of coverage, full day Cube today, some interviews tomorrow. Intel has some amazing super demos they're going to be showing here throughout the weekend. Stay tuned on theCUBE, we'll be covering it. We'll be right back with more, after this short break. 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(digital music) >> And we're back live in New York. It's theCUBE. It's not SNL, it's better than SNL. Lisa Martin and John Furrier here with about 10,000 to 12,000 folks. (John chuckles) There is a ton of energy here. There's a ton of interest in what's going on. But one of the things that we know that AWS is really well-known for is its massive ecosystem. And one of its ecosystem partners is joining us. Please welcome Domenic Ravita, the VP of Product Marketing from SingleStore. Dominic, great to have you on the program. >> Well, thank you. Glad to be here. >> It's a nice opening, wasn't it? (Lisa and John laughing) >> I love SNL. Who doesn't? >> Right? I know. So some big news came out today. >> Yes. >> Funding. Good number. Talk to us a little bit about that before we dig in to SingleStore and what you guys are doing with AWS. >> Right, yeah. Thank you. We announced this morning our latest round, 116 million. We're really grateful to our customers and our investors and the partners and employees and making SingleStore a success to go on this journey of, really, to fulfill our mission to unify and simplify modern, real time data. >> So talk to us about SingleStore. Give us the value prop, the key differentiators, 'cause obviously customers have choice. Help us understand where you're nailing it. >> SingleStore is all about, what we like to say, the moments that matter. When you have an analytical question about what's happening in the moment, SingleStore is your best way to solve that cost-effectively. So that is for, in the case of Thorn, where they're helping to protect and save children from online trafficking or in the case of True Digital, which early in the pandemic, was a company in Southeast Asia that used anonymized phone pings to identify real time population density changes and movements across Thailand to have a proactive response. So really real time data in the moment can help to save lives quite literally. But also it does things that are just good commercially that gives you an advantage like what we do with Uber to help real time pricing and things like this. >> It's interesting this data intensity happening right now. We were talking earlier on theCUBE with another guest and we said, "Why is it happening now?" The big data has been around since the dupe days. That was hard to work with, then data lakes kicked in. But we seem to be, in the past year, everyone's now aware like, "Wow, I got a lot of data." Is it the pandemic? Now we're seeing customers understand the consequences. So how do you look at that? Because is it just timing, evolution? Are they now getting it or is the technology better? Is machine learning better? What's the forces driving the massive data growth acceleration in terms of implementing and getting stuff out, done? (chuckles) >> We think it's the confluence of a lot of those things you mentioned there. First of all, we just celebrate the 15-year anniversary of the iPhone, so that is like wallpaper now. It's just faded into our daily lives. We don't even think of that as a separate thing. So there's an expectation that we all have instant information and not just for the consumer interactions, for the business interactions. That permeates everything. I think COVID with the pandemic forced everyone, every business to try to move to digital first and so that put pressure on the digital service economy to mature even faster and to be digital first. That is what drives what we call data intensity. And more generally, the economic phenomenon is the data intensive era. It's a continuous competition and game for customers. In every moment in every location, in every dimension, the more data hat you have, the better value prop you can give. And so SingleStore is uniquely positioned to and focused on solving this problem of data intensity by bringing and unifying data together. >> What's the big customer success story? Can you share any examples that highlight that? What are some cool things that are happening that can illustrate this new, I won't say bit that's been flipped, that's been happening for a while, but can you share some cutting edge customer successes? >> It's happening across a lot of industries. So I would say first in financial services, FinTech. FinTech is always at the leading edge of these kind of technology adaptions for speeds and things like that. So we have a customer named IEX Cloud and they're focused on providing real time financial data as an API. So it's a data product, API-first. They're providing a lot of historical information on instruments and that sort of thing, as well as real time trending information. So they have customers like Seeking Alpha, for instance, who are providing real time updates on massive, massive data sets. They looked at lots of different ways to do this and there's the traditional, transactionals, LTP database and then maybe if you want to scale an API like theirs, you might have a separate end-memory cache and then yet another database for analytics. And so we bring all that together and simplify that and the benefit of simplification, but it's also this unification and lower latency. Another example is GE who basically uses us to bring together lots of financial information to provide quicker close to the end-of-month process across many different systems. >> So we think about special purpose databases, you mentioned one of the customers having those. We were in the keynote this morning where AWS is like, "We have the broadest set of special purpose databases," but you're saying the industry can't afford them anymore. Why and would it make SingleStore unique in terms of what you deliver? >> It goes back to this data intensity, in that the new business models that are coming out now are all about giving you this instant context and that's all data-driven and it's digital and it's also analytical. And so the reason that's you can't afford to do this, otherwise, is data's getting so big. Moving that data gets expensive, 'cause in the cloud you pay for every byte you store, every byte you process, every byte you move. So data movement is a cost in dollars and cents. It's a cost in time. It's also a cost in skill sets. So when you have many different specialized data sets or data-based technologies, you need skilled people to manage those. So that's why we think the industry needs to be simplified and then that's why you're seeing this unification trend across the database industry and other parts of the stack happening. With AWS, I mean, they've been a great partner of ours for years since we launched our first cloud database product and their perspective is a little bit different. They're offering choice of the specialty, 'cause many people build this way. But if you're going after real time data, you need to bring it. They also offer a SingleStore as a service on AWS. We offer it that way. It's in the AWS Marketplace. So it's easily consumable that way. >> Access to real time data is no longer a nice-to-have for any company, it's table stakes. We saw that especially in the last 20 months or so with companies that needed to pivot so quickly. What is it about SingleStore that delivers, that you talked about moments that matter? Talk about the access to real time data. How that's a differentiator as well? >> I think businesses need to be where their customers are and in the moments their customers are interacting. So that is the real time business-driver. As far as technology wise, it's not easy to do this. And you think about what makes a database fast? A major way of what makes it fast is how you store the data. And so since 2014, when we first released this, what Gartner called at the time, hybrid transaction/analytical processing or HTAP, where we brought transactional data and analytical data together. Fast forward five years to 2019, we released this innovation called Universal Storage, which does that in a single unified table type. Why that matters is because, I would say, basically cost efficiency and better speed. Again, because you pay for the storage and you pay for the movement. If you're not duplicating that data, moving it across different stores, you're going to have a better experience. >> One of the things you guys pioneered is unifying workloads. You mentioned some of the things you've done. Others are now doing it. Snowflake, Google and others. What does that mean for you guys? I mean, 'cause are they copying you? Are they trying to meet the functionality? >> I think. >> I mean, unification. I mean, people want to just store things and make it, get all the table stakes, check boxes, compliance, security and just keep coding and keep building. >> We think it's actually great 'cause they're validating what we've been seeing in the market for years. And obviously, they see that it's needed by customers. And so we welcome them to the party in terms of bringing these unified workloads together. >> Is it easy or hard? >> It's a difficult thing. We started this in 2014. And we've now have lots of production workloads on this. So we know where all the production edge cases are and that capability is also a building block towards a broader, expansive set of capabilities that we've moved onto that next phase and tomorrow actually we have an event called, The Real Time Data Revolution, excuse me, where we're announcing what's in that new product of ours. >> Is that a physical event or virtual? >> It's a virtual event. >> So we'll get the URL on the show notes, or if you know, just go to the new site. >> Absolutely. SingleStore Real Time Data Revolution, you'll find it. >> Can you tease us with the top three takeaways from Revolution tomorrow? >> So like I said, what makes a database fast? It's the storage and we completed that functionality three years ago with Universal Storage. What we're now doing for this next phase of the evolution is making enterprise features available and Workspaces is one of the foundational capabilities there. What SingleStore Workspaces does is it allows you to have this isolation of compute between your different workloads. So that's often a concern to new users to SingleStore. How can I combine transactions and analytics together? That seems like something that might be not a good thing. Well, there are multiple ways we've been doing that with resource governance, workload management. Workspaces offers another management capability and it's also flexible in that you can scale those workloads independently, or if you have a multi-tenant application, you can segment your application, your customer tenant workloads by each workspace. Another capability we're releasing is called Wasm, which is W-A-S-M, Web Assembly. This is something that's really growing in the open source community and SingleStore's contributing to that open source scene, CF project with WASI and Wasm. Where it's been mentioned mostly in the last few years has been in the browser as a more efficient way to run code in the browser. We're adapting that technology to allow you to run any language of your choice in the database and why that's important, again, it's for data movement. As data gets large in petabyte sizes, you can't move it in and out of Pandas in Python. >> Great innovation. That's real valuable. >> So we call this Code Engine with Wasm and- >> What do you call it? >> Code Engine Powered by Wasm. >> Wow. Wow. And that's open source? >> We contribute to the Wasm open source community. >> But you guys have a service that you- >> Yes. It's our implementation and our database. But Wasm allows you to have code that's portable, so any sort of runtime, which is... At release- >> You move the code, not the data. >> Exactly. >> With the compute. (chuckles) >> That's right, bring the compute to the data is what we say. >> You mentioned a whole bunch of great customer examples, GE, Uber, Thorn, you talked about IEX Cloud. When you're in customer conversations, are you dealing mostly with customers that are looking to you to help replace an existing database that was struggling from a performance perspective? Or are you working with startups who are looking to build a product on SingleStore? Is it both? >> It is a mix of both. I would say among SaaS scale up companies, their API, for instance, is their product or their SaaS application is their product. So quite literally, we're the data engine and the database powering their scale to be able to sign that next big customer or to at least sleep at night to know that it's not going to crash if they sign that next big costumer. So in those cases, we're mainly replacing a lot of databases like MySQL, Postgre, where they're typically starting, but more and more we're finding, it's free to start with SingleStore. You can run it in production for free. And in our developer community, we see a lot of customers running in that way. We have a really interesting community member who has a Minecraft server analytics that he's building based on that SingleStore free tier. In the enterprise, it's different, because there are many incumbent databases there. So it typically is a case where there is a, maybe a new product offering, they're maybe delivering a FinTech API or a new SaaS digital offering, again, to better participate in this digital service economy and they're looking for a better price performance for that real time experience in the app. That's typically the starting point, but there are replacements of traditional incumbent databases as well. >> How has the customer conversation evolved the last couple of years? As we talked about, one of the things we learned in the pandemic was access to real time data and those moments that matter isn't a nice-to-have anymore for businesses. There was that force march to digital. We saw the survivors, we're seeing the thrivers, but want to get your perspective on that. From the customers, how has the conversation evolved or elevated, escalated within an organization as every company has to be a data company? >> It really depends on their business strategy, how they are adapting or how they have adapted to this new digital first orientation and what does that mean for them in the direct interaction with their customers and partners. Often, what it means is they realize that they need to take advantage of using more data in the customer and partner interaction and when they come to those new ideas for new product introductions, they find that it's complicated and expensive to build in the old way. And if you're going to have these real time interactions, interactive applications, APIs, with all this context, you're going to have to find a better, more cost-effective approach to get that to market faster, but also not to have a big sprawling data-based technology infrastructure. We find that in those situations, we're replacing four or five different database technologies. A specialized database for key value, a specialized database for search- >> Because there's no unification before? Is that one of the reasons? >> I think it's an awareness thing. I think technology awareness takes a little bit of time, that there's a new way to do things. I think the old saying about, "Don't pave cow paths when the car..." You could build a straight road and pave it. You don't have to pave along the cow path. I think that's the natural course of technology adaption and so as more- >> And the- pandemic, too, highlighted a lot of the things, like, "Do we really need that?" (chuckles) "Who's going to service that?" >> That's right. >> So it's an awakening moment there where it's like, "Hey, let's look at what's working." >> That's right. >> Double down on it. >> Absolutely. >> What are you excited about new round of funding? We talked about, obviously, probably investments in key growth areas, but what excites you about being part of SingleStore and being a partner of AWS? >> SingleStore is super exciting. I've been in this industry a long time as an engineer and an engineering leader. At the time, we were MemSQL, came into SingleStore. And just that unification and simplification, the systems that I had built as a system engineer and helped architect did the job. They could get the speed and scale you needed to do track and trace kinds of use cases in real time, but it was a big trade off you had to make in terms of the complexity, the skill sets you needed and the cost and just hard to maintain. What excites me most about SingleStore is that it really feels like the iPhone moment for databases because it's not something you asked for, but once your friend has it and shows it to you, why would you have three different devices in your pocket with a flip phone, a calculator? (Lisa and Domenic chuckles) Remember these days? >> Yes. >> And a Blackberry pager. (all chuckling) You just suddenly- >> Or a computer. That's in there. >> That's right. So you just suddenly started using iPhone and that is sort of the moment. It feels like we're at it in the database market where there's a growing awareness and those announcements you mentioned show that others are seeing the same. >> And your point earlier about the iPhone throwing off a lot of data. So now you have data explosions at levels that unprecedented, we've never seen before and the fact that you want to have that iPhone moment, too, as a database. >> Absolutely. >> Great stuff. >> The other part of your question, what excites us about AWS. AWS has been a great partner since the beginning. I mean, when we first released our database, it was the cloud database. It was on AWS by customer demand. That's where our customers were. That's where they were building other applications. And now we have integrations with other native services like AWS Glue and we're in the Marketplace. We've expanded, that said we are a multi-cloud system. We are available in any cloud of your choice and on premise and in hybrid. So we're multi-cloud, hybrid and SaaS distribution. >> Got it. All right. >> Got it. So the event is tomorrow, Revolution. Where can folks go to register? What time does it start? >> 1:00 PM Eastern and- >> 1:00 PM. Eastern. >> Just Google SingleStore Real Time Data Revolution and you'll find it. Love for everyone to join us. >> All right. We look forward to it. Domenic, thank you so much for joining us, talking about SingleStore, the value prop, the differentiators, the validation that's happening in the market and what you guys are doing with AWS. We appreciate it. >> Thanks so much for having me. >> Our pleasure. For Domenic Ravita and John Furrier, I'm Lisa Martin. You're watching theCUBE, live from New York at AWS Summit 22. John and I are going to be back after a short break, so come back. (digital pulsing music)

>> Announcer: From Seattle, Washington, it's theCUBE! Covering AWS IMAGINE Nonprofit. Brought to you by Amazon Web Services. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in the waterfront in Seattle, Washington, it's absolutely gorgeous here the last couple of days. We're here for the AWS IMAGINE Nonprofit event. We were here a couple weeks ago for the education event, now they have a whole separate track for nonprofits, and what's really cool about nonprofits is these people, these companies are attacking very, very big, ugly problems. It's not advertising, it's not click here and get something, these are big things, and one of the biggest issues is human trafficking. You probably hear a lot about it, it's way bigger than I ever thought it was, and we're really excited to have an expert in the field that, again, is using the power of AWS technology as well as their organization to help fight this cause. And we're excited to have Brad Myles, he is the CEO of Polaris and just coming off a keynote, we're hearing all about your keynote. So Brad, first off, welcome. >> Yeah, well thank you, thank you for having me. >> Absolutely, so Polaris, give us a little bit about kind of what's the mission for people that aren't familiar with the company. >> Yeah, so Polaris, we are a nonprofit that works full-time on this issue. We both combat the issue and try to get to long-term solutions, and respond to the issue and restore freedom to survivors by operating the National Human Trafficking Hotline for the United States, so, it's part kind of big data and long-term solutions, and it's part responding to day-to-day cases that break across the country every day. >> Right, in preparing for this interview and spending some time on the site there was just some amazing things that just jump right off the page. 24.9 million people are involved in this. Is that just domestically here in the States, or is that globally? >> That's a global number. So when you're thinking about human trafficking, think about three buckets. The first bucket is any child, 17 or younger, being exploited in the commercial sex trade. The second bucket is any adult, 18 or over, who's in the sex trade by force, fraud, or coercion. And the third bucket is anyone forced to work in some sort of other labor or service industry by force, fraud, or coercion. So you've got the child sex trafficking bucket, you've got the adult sex trafficking bucket, and then you've got all the labor trafficking bucket, right? You add up those three buckets globally, that's the number that the International Labour Organization came out and said 25 million around the world are those three buckets in a given year. >> Right, and I think again, going through the website, some of the just crazy discoveries, it's the child sex trafficking you can kind of understand that that's part of the problem, the adult sex trafficking. But you had like 25 different human trafficking business models, I forget the term that was used, for a whole host of things well beyond just the sex trade. It's a very big and unfortunately mature industry. >> Totally, yeah, so we, so the first thing that we do that we're kind of known for is operating the National Human Trafficking Hotline. The National Human Trafficking Hotline leads to having a giant data set on trafficking, it's 50,000 cases of trafficking that we've worked on. So then we analyzed that data set and came to the breakthrough conclusion that there are these 25 major forms, and almost any single call that we get in to the National Hotline is going to be one of those 25 types. And once you know that then the problem doesn't seem so overwhelming, it's not, you know, thousands of different types, it's these 25 things, so, it's 18 labor trafficking types and seven sex trafficking types. And it enables a little bit more granular analysis than just saying sex trafficking or labor trafficking which is kind of too broad and general. Let's get really specific about it, we're talking about these late night janitors, or we're talking about these people in agriculture, or we're talking about these women in illicit massage businesses. It enables the conversation to get more focused. >> Right, it's so interesting right, that's such a big piece of the big data trend that we see all over the place, right? It used to be, you know, you had old data, a sample of old data that you took an aggregate of and worked off the averages. And now, because of big data, and the other tools that we have today, now actually you can work on individual cases. So as you look at it from a kind of a big data point of view, what are some of the things that you're able to do? And that lead directly to, everyone's talking about the presentation that you just got off of, in terms of training people to look for specific behaviors that fit the patterns, so you can start to break some of these cases. >> Exactly, so, I think that the human trafficking field risks being too generic. So if you're just saying to the populace, "Look for trafficking, look for someone who's scared." People are like, that's not enough, that's too vague, it's kind of slipping through my fingers. But if you say, "In this particular type of trafficking, "with traveling magazine sales crews, "if someone comes to your door "trying to sell you a magazine with these specific signs." So now instead of talking about general red flag indicators across all 25 types, we're coming up with red flag indicators for each of the 25 types. So instead of speaking in aggregate we're getting really specific, it's almost like specific gene therapy. And the data analysis on our data set is enabling that to happen, which makes the trafficking field smarter, we could get smarter about where victims are recruited from, we could get smarter about intervention points, and we could get smarter about where survivors might have a moment to kind of get help and get out. >> Right, so I got to dig into the magazine salesperson, 'cause I think we've all had the kid-- >> Brad: Have you had a kid come to you yet? >> Absolutely, and you know, you think first they're hustlin' but their papers are kind of torn up, and they've got their little certificate, certification. How does that business model work? >> Yeah, so that's one of the 25 types, they're called mag crews. There was a New York Times article written by a journalist named Ian Urbina who really studied this and it came out a number of years ago. Then they made a movie about it called "American Honey," if you watch with a number of stars. But essentially this is a very long-standing business model, it goes back 30 or 40 years of like the door-to-door salesperson, and like trying to win sympathy from people going to door-to-door sales. And then these kind of predatory groups decided to prey on disaffected U.S. citizen youth that are kind of bored, or are kind of working a low-wage job. And so they go up to these kids and they say, "Tired of working at the Waffle House? "Well why don't you join our crew and travel the country, "and party every night, and you'll be outdoors every day, "and it's coed, you get to hang out with girls, "you get to hang out with guys, "we'll drink every night and all you have to do "is sell magazines during the day." And it's kind of this alluring pitch, and then the crews turn violent, and there's sometimes quotas on the crew, there's sometimes coercion on the crew. We get a lot of calls from kids who are abandoned by the crew. Where the crew says, "If you act up "or if you don't adhere to our rules, "we'll just drive away and leave you in this city." >> Wherever. >> Is the crews are very mobile they have this whole language, they call it kind of jumping territory. So they'll drive from like Kansas City to a nearby state, and we'll get this call from this kid, they're like, "I'm totally homeless, my crew just left me behind "because I kind of didn't obey one of the rules." So a lot of people, when they think of human trafficking they're not thinking of like U.S. citizen kids knocking on your door. And we're not saying that every single magazine crew is human trafficking, but we are saying that if there's force, and coercion, and fraud, and lies, and people feel like they can't leave, and people feel like they're being coerced to work, this is actually a form of human trafficking of U.S. citizen youth which is not very well-known but we hear about it on the Hotline quite a lot. >> Right, so then I wonder if you could tell us more about the Delta story 'cause most of the people that are going to be watching this interview weren't here today to hear your keynote. So I wonder if you can explain kind of that whole process where you identified a specific situation, you train people that are in a position to make a difference and in fact they're making a big difference. >> Yeah. So the first big report that we released based on the Hotline data was the 25 types, right? We decided to do a followup to that called Intersections, where we reached out to survivors of trafficking and we said, "Can you tell us about "the legitimate businesses that your trafficker used "while you were being trafficked?" And all these survivors were like, "Yeah, sure, "we'll tell you about social media, "we'll tell you about transportation, "we'll tell you about banks, "we'll tell you about hotels." And so we then identified these six major industries that traffickers use that are using legitimate companies, like rental car companies, and airlines, and ridesharing companies. So then we reached out to a number of those corporate partners and said, "You don't want this stuff on your services, right?" And Delta really just jumped at this, they were just like, "We take this incredibly seriously. "We want our whole workforce trained. "We don't want any trafficker to feel like "they can kind of get away with it on our flights. "We want to be a leader in transportation." And then they began taking all these steps. Their CEO, Ed Bastian, took it very seriously. They launched a whole corporate-wide taskforce across departments, they hosted listening sessions with survivor leaders so survivors could coach them, and then they started launching this whole strategy around training their flight attendants, and then training their whole workforce, and then supporting the National Human Trafficking Hotline, they made some monetary donations to Polaris. We get situations on the Hotline where someone is in a dangerous situation and needs to be flown across the country, like an escape flight almost, and Delta donated SkyMiles for us to give to survivors who are trying to flee a situation, who needs a flight. They can go to an airport and get on a flight for free that will fly them across the country. So it's almost like a modern day Underground Railroad, kind of flying people on planes. >> Jeff: Right, right. >> So they've just been an amazing partner, and they even then took the bold step of saying, "Well let's air a PSA on our flights "so the customer base can see this." So when you're on a Delta flight you'll see this PSA about human trafficking. And it just kept going and going and going. So it's now been about a five-year partnership and lots of great work together. >> And catching bad guys. >> Yeah, I mean, their publicity of the National Human Trafficking Hotline has led to a major increase in calls. Airport signage, more employees looking for it, and I actually do believe that the notion of flying, if you're going to be a trafficker, flying on a Delta flight is now a much more harrowing experience because everyone's kind of trained, and eyes and ears are looking. So you're going to pivot towards another airline that hasn't done that training yet, which now speaks to the need that once one member of an industry steps up, all different members of the industry need to follow suit. So we're encouraging a lot of the other airlines to do similar training and we're seeing some others do that, which is great. >> Yeah, and how much of it was from the CEO, or did he kind of come on after the fact, or was there kind of a champion catalyst that was pushing this through the organization, or is that often the case, or what do you find in terms of adoption of a company to help you on your mission? >> That's a great question. I mean, the bigger picture here is trafficking is a $150 billion industry, right? A group of small nonprofits and cops are not going to solve it on their own. We need the big businesses to enter the fight, because the big businesses have the resources, they have the brand, they have the customer base, they have the scale to make it a fair fight, right? So in the past few years we're seeing big businesses really enter the fight against trafficking, whether or not that's big data companies like AWS, whether or not that's social media companies, Facebook, whether or not that's hotel companies, like Wyndham and Marriott, airlines like Delta. And that's great because now the big hitters are joining the trafficking fight, and it happens in different ways, sometimes it's CEO-led, I think in the case of Delta, Ed Bastian really does take this issue very seriously, he was hosting events on this at his home, he's hosted roundtables of other CEOs in the Atlanta area like UPS, and Chick-fil-A, and Home Depot, and Coca-Cola, all those Atlanta-based CEOs know each other well, he'll host roundtables about that, and I think it was kind of CEO-led. But in other corporations it's one die hard champion who might be like a mid-level employee, or a director, who just says, "We really got to do this," and then they drive more CEO attention. So we've seen it happen both ways, whether or not it's top-down, or kind of middle-driven-up. But the big picture is if we could get some of the biggest corporations in the world to take this issue seriously, to ask questions about who they contract with, to ask questions about what's in their supply chain, to educate their workforce, to talk about this in front of their millions of customers, it just puts the fight against trafficking on steroids than a group of nonprofits would be able to do alone. So I think we're in a whole different realm of the fight now that business is at the table. >> And is that pretty much your strategy in terms of where you get the leverage, do you think? Is to execute via a lot of these well-resourced companies that are at this intersection point, I think that's a really interesting way to address the problem. >> Yeah, well, it's back to the 25 types, right? So the strategies depend on type. Like, I don't think big businesses being at the table are necessarily going to solve magazine sales crews, right? They're not necessarily going to solve begging on the street. But they can solve late night janitors that sometimes are trafficked, where lots of big companies are contracting with late night janitorial crews, and they come at 2:00 a.m., and they buff the floors, and they kind of change out the trash, and no one's there in the office building to see those workers, right? And so asking different questions of who you procure contracts with, to say, "Hey, before we contract with you guys, "we're going to need to ask you a couple questions "about where these workers got here, "and what these workers thought they were coming to do, "and we need to ID these workers." The person holding the purse strings, who's buying that contract, has the power to demand the conditions of that contract. Especially in agriculture and large retail buyers. So I think that big corporations, it's definitely part of the strategy for certain types, it's not going to solve other types of trafficking. But let's say banks and financial institutions, if they start asking different questions of who's banking with them, just like they've done with terrorism financing they could wipe out trafficking financing, could actually play a gigantic role in changing the course of how that type of trafficking exists. >> So we could talk all day, I'm sure, but we don't have time, but I'm just curious, what should people do, A, if they just see something suspicious, you know, reach out to one of these kids selling magazines, or begging on the street, or looking suspicious at an airport, so, A, that's the question. And then two, if people want to get involved more generically, whether in their company, or personally, how do they get involved? >> Yeah, so there are thousands of nonprofit groups across the country, Polaris is in touch with 3,000 of them. We're one of thousands. I would say find an organization in your area that you care about and volunteer, get involved, donate, figure out what they need. Our website is polarisproject.org, we have a national Referral Directory of organizations across the country, and so that's one way. The other way is the National Human Trafficking Hotline, the number, 1-888-373-7888. The Hotline depends on either survivors calling in directly as a lifeline, or community members calling in who saw something suspicious. So we get lots of calls from people who were getting their nails done, and the woman was crying and talking about how she's not being paid, or people who are out to eat as a family and they see something in the restaurant, or people who are traveling and they see something that doesn't make, kind of, quite sense in a hotel or an airport. So we need an army of eyes and ears calling tips into the National Human Trafficking Hotline and identifying these cases, and we need survivors to know the number themselves too so that they can call in on their own behalf. We need to respond to the problem in the short-term, help get these people connected to help, and then we need to do the long-term solutions which involves data, and business, and changing business practice, and all of that. But I do think that if people want to kind of educate themselves, polarisproject.org, there are some kind of meta-organizations, there's a group called Freedom United that's kind of starting a grassroots movement against trafficking, freedomunited.org. So lots of great organizations to look into, and this is a bipartisan issue, this is an issue that most people care about, it's one of the top headlines in the newspapers every day these days. And it's something that I think people in this country naturally care about because it references kind of the history of chattel slavery, and some of those forms of slavery that morphed but never really went away, and we're still fighting that same fight today. >> In terms of, you know, we're here at AWS IMAGINE, and they're obviously putting a lot of resources behind this, Teresa Carlson and the team. How are you using them, have you always been on AWS? Has that platform enabled you to accomplish your mission better? >> Yeah, oh for sure, I mean, Polaris crunches over 60 terabytes of data per day, of just like the computing that we're doing, right? >> Jeff: And what types of data are you crunching? >> It's the data associated with Hotline calls, we collect up to 150 variables on each Hotline call. The Hotline calls come in, we have this data set of 50,000 cases of trafficking with very sensitive data, and the protections of that data, the cybersecurity associated with that data, the storage of that data. So since 2017, Polaris has been in existence since 2002, so we're in our 17th year now, but starting three years ago in 2017 we started really partnering with AWS, where we're migrating more of our data onto AWS, building some AI tools with AWS to help us process Hotline calls more efficiently. And then talking about potentially moving our, all of our data storage onto AWS so that we don't have our own server racks in our office, we still need to go through a number of steps to get there. But having AWS at the table, and then talking about the Impact Computing team and this, like, real big data crunching of like millions of trafficking cases globally, we haven't even started talking about that yet but I think that's like a next stage. So for now, it's getting our data stronger, more secure, building some of those AI bots to help us with our work, and then potentially considering us moving completely serverless, and all of those things are conversations we're having with AWS, and thrilled that AWS is making this an issue to the point that it was prioritized and featured at this conference, which was a big deal, to get in front of the whole audience and do a keynote, and we're very, very grateful for that. >> And you mentioned there's so many organizations involved, are you guys doing data aggregation, data consolidation, sharing, I mean there must be with so many organizations, that adds a lot of complexity, and a lot of data silos, to steal classic kind of IT terms. Are you working towards some kind of unification around that, or how does that look in the future? >> We would love to get to the point where different organizations are sharing their data set. We'd love to get to the point where different organizations are using, like, a shared case management tool, and collecting the same data so it's apples to apples. There are different organizations, like, Thorn is doing some amazing big data-- >> Jeff: Right, we've had Thorn on a couple of times. >> How do we merge Polaris's data set with Thorn's data set? We're not doing that yet, right? I think we're only doing baby steps. But I think the AWS platform could enable potentially a merger of Thorn's data with Polaris's data in some sort of data lake, right? So that's a great idea, we would love to get to that. I think the field isn't there yet. The field has kind of been, like, tech-starved for a number of years, but in the past five years has made a lot of progress. The field is mostly kind of small shelters and groups responding to survivors, and so this notion of like infusing the trafficking field with data is somewhat of a new concept, but it's enabling us to think much bigger about what's possible. >> Well Brad, again, we could go on all day, you know, really thankful for what you're doing for a whole lot of people that we don't see, or maybe we see and we're not noticing, so thank you for that, and uh. >> Absolutely. >> Look forward to catching up when you move the ball a little bit further down the field. >> Yeah, thank you for having me on. It's a pleasure to be here. >> All right, my pleasure. He's Brad, I'm Jeff, you're watching theCUBE. We're at AWS IMAGINE Nonprofits, thanks for watching, we'll see you next time. (futuristic music)

>> Narrator: Live from Las Vegas, it's theCube covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. (upbeat music) >> Okay, welcome back everyone. We're here live in Las Vegas. This is theCube's exclusive coverage of Amazon Web Services re:Invent 2017, our fifth year covering AWS re:Invent. I'm John Furrier the founder of SiliconANGLE Media with my co-host Stu Miniman. I'm so excited 45,000 people and boy, I remember when it was just a small, little, fast-growing company. We're here with Teresa Carlson who's been here with us the whole way. She's a Senior Vice President of Public Sector. Teresa, welcome to theCube, good to see you. >> I'm always glad to be here on theCube. >> So, you've been running public sector, you've been really, I've gotta say, I gave a tweet, not to sound that I'm fawning over you right now, but you've really grown the business in a significant way. As Andy was saying, a meaningful way. Take us through, because it's almost mind-blowing. We have already had a few guests on theCube. I went to your breakfast. You are changing the game, but not without scar tissue. You've done a lot of hard work to get there, so, one, congratulations, but give us a state-of-the-union right now for public sector, because you're winning, you're doing great, but it wasn't easy. >> No, it's not been easy, but it's been a lot of fun. I mean, it's been a lot of fun, in fact, as you said, this is our sixth year of doing re:Invent and yesterday or two days ago, we had a public sector breakfast and it was so full, we got shut down by the fire marshal. So that is when you know you've got customers and partners showing up, because they want to be there. We have grown significantly and that has been through the work of both working with customers and partners on security, compliance, policy, acquisition vehicles, to just make sure that we have the right balance of everything needed to really drive and grow the business in the right way. As I've talked about we didn't leave any stone unturned. We had to really go through all the hard processes to do this right and I think it really has paid off because you never want to take short-cuts. You wanna make sure you're doing the right thing in order for customers to have better technology, for us to help drive good government, good education. >> I gotta say, one of the big trends we're seeing here on siliconANGLE, theCube, and Wikibon is the public-private Partnerships are accelerating. You're seeing public sector help on security to the private sector, private sector helping government move faster and so you're seeing a balance and an equilibrium coming together, but also old guard companies sometimes have a federal division or a separate DNA culture. You guys don't, you have one culture at Amazon, but the striking thing for me, is that you're now enabling companies to get into public sector that couldn't before. So I wanted to ask you specifically, is it like that now, we're you're starting to see new people come in with solutions because you guys have done that heavy lifting where before they'd have to wait in line, get certified, are we seeing new solutions, are you enabling that, is that actually happening? >> It absolutely is happening and we never forget our roots of start-ups here at AWS, because they are really a huge reason why we exist and for public sector, I saw a change in my previous life I never had venture capitalists or private equity firms come and say we want our companies in government. We are creating new education tech companies, which was really not even heard of. >> It's a growth strategy for them. >> It's a huge growth strategy, so venture capitalist and private equity like Andreessen Horowitz, Madrona, C5, Bridgewater, we see tons and they come to us saying, we have this portfolio, can you help us talk to them about how they get into government? As a result of that, we do sales and marketing, we work with them on FedRAMP I-E slash security compliance. We ensure that they understand the elements and components of how they work in government and by the way, government loves that we are bringing in innovative new technologies. We can also do that through the marketplace, the AWS marketplace, which allows them to move faster, be more agile, and start getting that business. >> Teresa, I'm wondering if you could share a little more. You talk about innovation, we've been lovin' for years, I love when I talk about regional governments, education, you get non-profits under your umbrella, where it used to be, I didn't have the budget, I can't move fast. Now, we're seeing some great innovation from the private side as well as well as some of the public-private interactions. >> Definitely, in fact, I was in California about a month ago where we announced an innovation center with California Polytechnic University, CalPoly and the president there, Jeff Armstrong, it is amazing, they literally had been looking at what AWS was doing and they took the pillars that they'd been seeing us talk about for public sector and they created an innovation center to work on these opportunities and challenges and just as in public safety, health, agri, sex trafficking and child exploitation, through seeing what Thorn was doing in the International Center for Missing and Exploited Children. >> How is this leveling the playing field? Because everyone, citizens at least in the United States, I'm sure it's happening in other markets as well, they want the government to move faster. And you guys are like the freight train that's out of control speed-wise, just more and more services. How does the government keep up? Because I would imagine that if I am a government official or I'm the public sector, oh my God, I can't handle Amazon. I can't ride that beast, it's too strong. I mean do they say that, is that the wrong vibe, or are they more hey I want you to do, is it more your flywheel, do they have to get involved? What's the relation, what's the sentiment of the government? >> Well, they wanna move fast. In fact, in the U.S. government, the White House does have an entire initiative now on modernization. You're seeing countries like the U.K government go cloud native. You saw the country of Bahrain which is going all-in in the cloud and they've already established new policies and a cloud-first policy of moving. But I would tell you, if you look at groups like the intelligence community in the U.S. government, we just announced our secret region and that allows them to have top-secret capabilities, secret, unclassified in our GovCloud, so they have capabilities across the entire spectrum of workloads and what they've always said to us and our other customers is can we build cloud tools, can we build a cloud? Yes, but can we innovate at the rate and speed you're innovating? No, because we provide them innovation ahead of their demand. >> Yeah, Teresa, I remember when GovCloud launched and it was, like, wow, this is like AWS isn't just like a monolithic service around the globe and everything. It seems like secret region goes along that line. How does the dynamic between AWS as a whole and what you're doing in your organization, how do you work through that and kinda balance, I want services around the globe, yet meet the needs of your clients. >> On the GovCloud region, that was our first entre into doing something unique for government. That region has grown 185% every year since 2011 and we just announced a second region on the east coast for GovCloud, U.S. GovCloud. The interaction with our services team is amazing. Charlie Bell who runs all of our services, we have a tight relationship, we talk to our government customers in these regions, understand their priorities, then we roll them out and it's really that simple. They get the exact same thing in their classified regions as we give our other customers, it's just their network. >> Well, you got the date set, I'm looking at my picture here I took, June 20th and 21st, save the date, AWS Public Sector Summit, #AWSPSSummit as it's called on Twitter hashtag. Every year, you started out in a little conference room, in a ballroom, bigger hotel, now the convention center. Massive growth. >> And theCube was there this year, which I was happy. >> That makes it legitimate, and theCube's there, we'll be there this year, >> Good, yes. >> But of course, this is the growth. V.C.s, private equity, this is a growth market, this is not a unique, siloed market anymore. You guys have leveled the silos within Amazon, I mean you never had silos, but you are now agile to come to the government. What's next for you? You've done a great job, you're now cruising altitude, what's your growth strategy for Public Sector Summit, how are you going to take it to the next level? >> Well, even though we have grown a lot, thank you to our customers and partners, we really are just scratching the surface. It is day one still for us. Our customers are really just still getting going on a lot of mission critical workloads. They're moving in things they really hadn't thought about. They're starting to do things like higher more developers in government, so they can take advantage of the tools used, a lot you saw yesterday. But additionally, what we're seeing is we are spending a lot of time going into countries around the world, helping countries set a strategy for digital transformation. New jobs growth, new companies, economic development, how do they train and educate for a cloud-based workforce, we call it and that's really fun to go in and tell governments, look you really have to prepare your country for a digital transformation and again if you look at groups like Bahrain, what the U.K have done, they are doing that and they are making a massive transformation around this. >> Final question for you, what are you most proud of looking back since you joined AWS seven years ago. I think it was seven years ago you started? >> Yep, seven years ago this month. >> Congratulations, so what are you most proud of and then two, what do you think about the most as you execute day-to-day in growing the business? >> Well, I would say the fact that I have had an amazing brand to work with out of the gate Amazon was such a great brand, and the fact that, again, based on think big, Andy Jassy's leadership, really he and I having a conversation together saying, we can change the world and make it a better place and you've heard me say a lot in my openings, we have two themes that we talk about in public sector, which is paving the way for disruptive innovation and making the world a better place. And if I look back, it's really the things that we're helping to do this that we are driving new policies, companies are seeing results, agencies, and we are making the world a better place. I would say that's humbling and amazing and we're just getting going. >> As a chief of public sector, you're like, you've seen it grow and you're running it every day and you have a great team, do you ever have a pinch me moment once in a while? Kind of say, wow, what have you done? >> Well, I think the pinch me moments are when I hear the customers and partners tell me how fast they're moving and the results they have. We always have a goal of really working with our mission partners and we've hired now more than 17,000 veterans at Amazon and growing. It's things like that that we can do to really help that transformation and not just talk the talk, but walk the walk as a company. I would say for where we wanna go and what I sort of worry about our growth, I guess I worry and stay up a little late at night to make sure that we keep our hiring bar high, that we really maintain our focus on customer obsession, >> John: Security. >> Security is always on my mind. >> Do you sleep at all it must keep you up late a lot. >> No, I don't really, no. But the last thing I would say is just really thinking through ensuring that we're continually pushing hard, that we have a little bit of sharp elbows, going in we're trying to change policy, we don't give up on the things that really matter for doing this massive transformation, for countries, for state and local agencies, for feds, for educational institutions around cloud transformation. >> I really respect your results and I love your hard-charging style. It's fantastic, your success obviously speaks for itself. We'll see you at the Summit in June. This is theCube, Teresa Carlson The Chief of the Public Sector business, she's the Vice President of Public Sector. I'm John Furrier, Stu Miniman. More live coverage here at AWS re:Invent after this short break. (upbeat music)

>> Announcer: Live, from Las Vegas, it's the Cube, covering AWS Re:invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back everyone, we're here live in Las Vegas for 45,000 tech industry folks and customers with Amazon re:Invent 2017. This is the Cube's exclusive coverage, I'm John Furrier, with my co-host Justin Warren this segment. Our next guest, Bill Magro, is the Chief Technologist for Intel covering HPC high performance computing. Bill, welcome to the Cube. >> Thank you. >> John: Thanks for coming on. You guys, your booth's behind us, I don't if they can see it in the wide shot, but Intel is really taking advantage of the I don't want to say Intel inside the Cloud 'cause that's really what you guys are doing, but you got so much compute, this is your wheelhouse. Compute is what Intel is. >> Bill: Right. >> Andy Jassy at AWS, talking with their customers, they want more compute, edge of the network, so HPC, high performance computing's been around for awhile. What's the state of the art and how should people think about HPC versus the Cloud, are they the same, what's the relationship? >> Intel actually thinks of HPC or high performance computing more in terms of the activity and the workloads than the infrastructure that it runs on. So very early in the days of Cloud computing, there were a lot of people who said that the Cloud was kind of the opposite of HPC and therefore, they could never go together. But we think of Cloud as a delivery vehicle, a way to get access to compute storage networking and HPC is what you're doing. And so then, if you think about HPC as kind of a range of workloads, you can start to think about which ones are a good fit for the Cloud, and which ones aren't. So we talk a little bit about the high performance computing and tailored infrastructure for the most extreme cases of HPC. That's where you see the biggest differences with Cloud, 'cause they're at opposite ends of the spectrum. >> But you see holistically the Cloud is interplaying with HPC. >> Yeah. >> They're not mutually exclusive. >> Absolutely, we see Cloud as a way to deliver HPC capabilities. So if you think of the most demanding HPC problems, the ones that are used in national security, that are used to design commercial airplanes, and so on, those are some of the hardest problems. Predicting the climate change, predicting the weather, paths of hurricanes, those are what we call grand challenge problems. Those are not running in the Cloud. Those are running on dedicated, tailored, infrastructure built for high performance computing at that extreme. And those systems have a lot of characteristics such as very high performance networks, different from ethernet, custom topologies and are designed with software to really minimize variation because it's one large problem that has to move forward. The Cloud is kinda the opposite in a sense. It started as taking a large amount of resources and making it possible to carve them up, right. It's the opposite of aggregating resources. And so that's where a lot of the early thoughts of Cloud and HPC being at odds with each other. >> It seems to be a dream scenario because I mean, in the old days, in 80s and 90s when I was breaking into the business. If you were a database guy or a compute guy, you were a specialist, it was high end kind of computing. Moore's Law, certainly Intel, you guys took advantage of it. But now, you see so much, it's cool to do more compute. So like, it's been democratized. Databases and compute, certainly in all the conversations, for everybody, not just, the technologists. >> Right, where that's where Cloud fits in for HPC. So if you think of HPC in terms of the characteristics of the workload, it's something that's really demanding computationally. The product of the computation is like an intellectual insight. You can design a better airplane wing, a safer car, you can figure out where that hurricane is going and tell which people to evacuate. There's an intellectual product to the compute. And then the last characteristic is when you apply more compute power appropriately, you get a more valuable result. So it could be better prediction of that hurricane path, it could be a safer car because you have more time, you have more capability and were able to build a better design ahead of that deadline to get that model year of the car out. And so, if you think about that, there's a lot, there's a broad spectrum and I talked about some of those most extreme problems, but even in something like designing an airplane, there might be 16, 20, a hundred different small design variations you want to explore. Well those can actually be great for The Cloud, 'cause they're small calculations and you run many of them at the same time. And the elastic capability of The Cloud augments the supercomputer that you might be using to run your hardest problems. >> So the aperture of problem-solving is huge now. >> Bill: That's right. >> You can do more. I mean we had Thorn on yesterday. Thorn was a company that partners with Intel to do, you know, find missing and exploited children. AI for good, so everything's possible. >> Yeah even AI we think of as an example of a high performance computing workload because what does it do? It gives you insights that you didn't have otherwise, it's compute intensive, and it does better when you apply more resources. So that fits our definition. So AI is definitely under the umbrella of high performance computing. >> One of the things, one of the great benefits of Cloud is the elasticity which you mentioned before. It's like, and some of the, we know that Amazon's just brought out the C5 Instances which is a specific instance site, which would be quite useful for HPC. But what is it about the bursting workloads or that elasticity that specifically works well for HPC do you think? >> Well, there's a couple use cases that we think are particularly relevant. One of them is an existing company. Just imagine some Fortune 50 manufacturer. They have a lot of stuff that they really need to build their own supercomputer for, their own high performance computing system, but their usage, even though they keep that system busy all the time, there is some variability and they have opportunity costs of an engineer sitting while their job is in the queue, 'cause you're paying that engineer but you're not giving them insights, right. And so the Cloud can augment that, but we have a lot of examples of large Fortune 500, Fortune 50 companies augmenting their on-premise with Cloud as a way to push those workloads that can run on the Cloud there, to free up those on-prem resources which are much more tailored, much more expensive and get more value out of them. >> Okay, and what's Intel doing to help customers figure out which of those workloads is best suited for Cloud and which ones are better suited for something which is running on site? >> Well, it's mostly through our influencer sales force who engages with many, many major companies and provides consulting, because Intel doesn't sell computers directly to anyone, so it's more of a knowledge, our knowledge and sharing that with people. And what we're trying to help enterprises understand is what workloads need to stay on premise, which ones can go to the Cloud and how this, the elasticity of the Cloud can augment those on-premise resources and thus, you know, go back and forth. >> It's the classic mission for Intel, make the apps go faster, faster, smaller, cheaper, right. >> And get 'em land in the right place. So really, the two biggest considerations we find in deciding whether a workload goes into the Cloud or stays on-premise in high performance computing are the following, one, is really the sensitivity of the IP. There's a lot of workloads that could run in the Cloud and people simply want to keep it on-premise 'cause they're more comfortable knowing that their IP is sitting inside their own firewall. Though the reality is, more and more companies are getting comfortable with Cloud security as they see data breaches. And realize that some of the big Cloud providers, like Amazon, maybe have better access to the security talent than they do. >> I think Goldman-Sachs just announced they're going all in. That's Goldman-Sachs, they never do a testimonial. >> So the privacy and the sensitivity of the data is king, you know, you have to be willing to put it in the Cloud. Then the second question is, is it a technical fit? And that's where this spectrum of workloads comes in. The bigger a workload goes and the more you want to speed it up but keep the workload the same size, that's what we call strong scaling and that starts to stress the network, and stress the system. And that's where these tailored systems come in. And so, you have to look at where things fall on the spectrum. A good example of workloads that would fit is these design space explorations, anything we would call pleasingly parallel or embarrassingly parallel in the industry where the communication does happen, but it's not the limiter of the calculation. So screening for a drug candidates, for personalized medicine, lot of life sciences applications, financial services is a good fit, in manufacturing a design space exploration maybe for different designs and materials for a dashboard or a component of a car. >> Bill, when you were at your Thanksgiving dinner and your family or wherever, you're moving around in your personal life, you're a technologist. How do explain the phenomenon of Amazon Web Services and the Cloud action right now? Because, you know, you're in it every day. You're close to all the action. But I get asked all the time, what's the hub-bub about AWS and it's hard to explain the phenomenon. How would describe the, I mean you're talking about tailored systems, elasticity, I mean it's a tech dream. I mean, how do you explain it to like a normal person? >> The conversation's usually pretty short because my family involves a historian, an English major, an accountant and people who really couldn't have, a musician, a singer, people who really don't have the slightest interest in technology. >> It's hard to talk about lambda, when you're. >> So I'm really the only technologist in my family so I just avoid it, but the question does come up with my parents. You know, parents like to brag on their kids so they like to know what you do, and every year my mom asks me what I do and I try to explain high performance computing to her and she says, oh, I don't get it. But when you explain it in terms of things like climate modeling and being able to support the nuclear test ban that's worldwide, that's done with high performance computing. Safing cars, finding missing children, better quality of life through all the AI that we're now experiencing. >> John: Analytics is a great use case. >> Then people say, oh, you know, they can understand the use cases. The elasticity of the Cloud, really is not something that I discuss with family, but even coworkers, I think, that's what the conversation focuses on. Recognizing that high performance computing is a range of workloads. >> Okay, so I'll rephrase it differently. What's your perspective on, what observations that you get excited about that are enabled now by these new use cases? 'Cause there's new things now that are possible. The number of computations, you got analytics, you mentioned a few of them. What jumps out at you, wow, that's really awesome, we can do that now? >> You know, this is gonna sound a little odd, and maybe not what you expected, but I'm not actually a technology enthusiast, believe it or not, despite. I think technology's cool, I like what it does, but I don't get super excited about technology. One of the things that I'm excited about with the Cloud is probably at the opposite extreme of what you would expect which is, back to, how does the elasticity of the Cloud fit? There's so many companies in this world who could benefit from high performance computing and don't today. A recent study showed that 95 percent of U.S. small medium manufacturers which is over 300,000 are not using HPC today. And so, as they're part of this supply chain, whether it's into a Boeing or and Airbus or a Lockheed Martin or a Honda or a Toyota, there's this whole supply chain. HPC's being used at the top, it's not being used at the bottom, so I think the Cloud is actually really, really exciting because it allows somebody to get over those initial hurdles, the cap-ex, getting access to pay as you go, prove the value proposition, because a small medium business actually has to take a risk to use HPC. They have to divert capital and divert resources. And they could lose a contract. >> So do you see a lot more companies starting to take advantage of some of this high performance computing capability just because it's now, you can rent it by the hour and try it out, give it a bit of a whirl, and then see, actually this is going to be really valuable for us, and then deploy a lot more of it. >> Exactly and that's one of the key things we're promoting is 'cause we want to bring more people into the world of high performance computing. So, AWS provides all the building blocks. Compute, elastic storage and so on. But high performance computing applications really expect a specific type of platform that they can run on, and that platform aggregates the resources so there's a number of companies Rescale is one, Psycho-Computing, and others who are actually providing that platform layer. And then once you've got the platform layer, all the, I'll call it the, geeky stuff that they do, AWS has abstracted away. Now the applications can run and that's that's what's bringing new users in. >> Bill, final question for you. AWS launched its C5 Instances. What's that about, what's it mean for customers? Can you explain a little bit more on that one piece? >> Sure, we're delighted to see Amazon deploying the C5 Instances. It's based on our latest technology in the Xeon product family. We call that the Intel Xeon scalable processor family. It includes, it's based on what we call Skylake technology or code name Skylake. There's a lot of innovations in that processor and that platform that are specifically driven by the needs of high performance computing. There's something called AVX 512, which is a doubling of the vector width. Means that every core can actually do 32 floating point, double-precision floating point operations per clock. That's tremendous, tremendous compute capability, in a 2X over the previous generation. On the memory bandwidth side, which is another huge factor for high performance computing applications, like 66 percent increase in memory bandwidth. So it's a balanced platform, and we're seeing improvements in high performance computing apps of anywhere from 1.7x sometimes almost up to 5x improvement in going from the C4 to C5 Instances on a per note basis. >> This is really going to enable a lot of action. IOT, tons of great stuff. >> Absolutely and as I talked about that range of HPC and you know, what fits and what doesn't fit in the Cloud, every generation of technology, what fits in the Cloud is growing, and C5 is another important step in that direction. >> Bill, thanks for coming on the Cube. Bill Magro, Chief Technologist at Intel, HPC, high performance computing. The Cloud is one big high performance machine in the sky, wherever you want to look at it, really great opportunity at enabling all new use cases, doing things for society benefits, and customers. Great stuff here, Cloud impact is significant. IOT to the Cloud. This is the Cube, doing our share here at AWS in Las Vegas. We'll be right back with more coverage after this short break. (electronic music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017. Presented by AWS, Intel and our ecosystem of partners. >> Hey, welcome back everyone. Live here this is theCUBE in Las Vegas for AWS Amazon Web Services re:Invent 2017. Our 5th year covering the event. Wall to wall coverage. Three days, this is our day two. 45,000 people here. Developers and business connecting together this year. Big show. Amazon continues its growth. I'm John Furrier, my co-host Justin Warren. Our next guest is from Washington County Sheriff's Office using Amazon, Amazon Recognition, Chris Adzima, who is the Senior Information Systems Analyst at the Washington County Sheriff. Welcome to theCUBE. >> Nice to have you. >> So Chris. >> be here. >> So, so tons of cool stuff we saw on stage today. You know they've had polylex out for awhile. But you're gonna start to see some of these multi-media services around. Human identification, transcription, Recognition's been out for awhile. With the power of the cloud, you can start rollin' out some pretty cool services. You have one of 'em, talk about your solution and what you guys are doing with it. >> Sure, about last year when Recognition was announced, I wanted to provide our deputies at the Sheriff's office with the way to identify people based on videos that we get from either surveillance or eyewitnesses. So, I looked into Recognition and decided that we should give it a try by giving all of our booking photos or mugshots up to the cloud for it to be indexed. So, that's what I did. I indexed all, about 300,000 booking photos, we have in the last 10 years, and put that into a Recognition Collection. And now I can use the simple tools that AWS gives me to search against that index for any new image that we get in, either from surveillance or an eyewitness, allowing us to get identification within seconds as opposed to having to go through all 700 employees at the Sheriff's Office for the chance that they might have known the person. >> So the old way was essentially grab the footage, and then do the old mugshot kinda scan manually, right? >> Yeah, manually. It wasn't in a book, it was on a website, but essentially, yeah, you had to-- >> I made my point, it sucks. It's hard as hell. >> It's very difficult, very difficult. >> You see on TV all the magic pictures goin' on and the facial recognition, you see on the movies and stuff. How close are we to that right now in terms of that capability? >> Well as far as facial recognition goes it all depends on the data that you have at your fingertips. Right now I have booking photos, so I can identify people with a very high level of certainty if they've been in our jail. If they haven't been in our jail, I obviously don't have much of a chance of identifying them. So, what you see on the TV where it's like, we looked through all the DMV records. We looked through all of the people on the street and all this stuff, We're pretty far off from that because nobody has a catalog of all those images. >> You need to incorporate of all the pictures, all the data. >> Yeah, but when you have the data, it's very simple. >> Right, and it's a lot like scanning for fingerprints. It's like, people would have seen that. You know, you have a fingerprint that you've collected from the crime scene-- >> Chris: Exactly. >> We see it on NCIS or something where you scan through all of that. So, it's pretty similar to that. >> Yeah, it's similar to that, or DNA, or anything like that. If you have the data set, it's very easy to search for those people. >> Yeah. >> So, faces are no different. >> So, how long did it take you to get up and running? Did you have to ingest the photos? How did you do that or? >> So... >> John: They're on a website so you had 'em on digital already. >> From never knowing anything about Amazon Web Services, to a fully-functional prototype of this product took me 30 days. >> John: Wow. >> I had the photos uploaded and the ability to actually run the searches via the API in three. So, extremely easy. Extremely easy. >> So, given the success that you've had with that particular producr, are there other services at AWS that you're looking into? That say, hey, that would actually be really useful for us? >> Yes, a couple that were announced today. First off, the recognition for video. Something that we have a problem with, and I'm hoping recognition for video's going to help with is when you have a surveillance camera, people are moving all the time. Therefore, trying to get a screenshot is going to get a blurry image. We're not getting good results with low-light or low frame rate. But recognition for video is gonna be able to take that movement and still look at the face. Hopefully we're gonna be able to get a better facial identification that way. >> Justin: Okay. >> Another thing that I want to look into is this DeepLens they just announced today. >> John: Awesome. >> That looks extremely promising in the way of me being able to teach it things that we need. A great example of what I would use this for is when a inmate comes in, we take pictures of scars, marks and tattoos. That way, we have a database of all the scars, marks and tattoos on somebody. In case, if they recommit a crime and our eye-witness says, "They had a skull tattoo on their chest" we can then look through all of the people that have a skull tattoo and say, "These are our list of possible suspects." The problem with that is, is that you may enter somebody in as a skull, and you may enter it in as crossbones. Somebody else might put an accidental I in there. So it's very hard to do a text search against that. But if recognition were to come through, or it wouldn't be recognition in this case. If whatever model I built with the DeepLens came through, and said this is a skull and this is the word we use, then I'd be able to index all of those images, quickly pull them up, so we wouldn't even need a picture. We would just need to know, from an eye-witness, that there was a skull on that person's chest. >> John: We had a guest on yesterday from Thorn, which Intel is doing AI for good, and they use essentially, and they didn't say Craigslist, but trying to look for women who were being sold for prostitution, and exploited children and whatnot. And it's all machine learning, and some natural language processing. When you look at the Sage announcement, that looks promising, 'cause they're gonna make, as I was try to democratize the heavy-lifting around all of this, you know, voodoo machine learning. Which, I mean, if you're totally a computer science geek and that's all you do, yeah, you could probably master machine learning. But if you're a practitioner, you're just whipping up. >> Well, yeah, and that's a good example. Because I am not a data scientist. I have no idea how this stuff works in the back end. But being able to utilize, stand on the shoulders of these giants, so to speak, is allowing people like me who A, I only have seven people on my team to devote to this kind of thing. We don't have a lot of resources. We wouldn't be able to get a data scientist. But opening this stuff up to us allows us to build these things, like this facial recognition and other things based on machine learning. And ultimately keep our citizens safe through the work that AWS does in getting this to us. >> Justin: Yeah, and we've been saying at a couple of different interviews so far, that humans don't scale. So these tools that provide the humans that you do have a lot more leverage to get things done. So, we were talking just before, before we started recording that these are tools that assist the humans. You're not replacing the humans with machines that just go oh we're gonna cede all decision-making to you. This is just another tool like being able to fingerprint people and search that. It's one more way of doing the standard policing that you are already doing. >> Exactly, and the tool that I've already created, and any tool I create after that, doesn't ever look to replace our deputies or our detectives. We give them things so that they don't have to do the things like flipping through that book for hours upon hours. They can be out in the field, following the leads, keeping the community safe and apprehending these criminals. >> Do they have on body cameras too? >> Not yet. We are currently looking into body cameras. >> John: That's a trend. They're gonna be instrumented basically like warriors: fully loaded, you know, cameras. >> I tend not to think of it like that. Only because, again, that's a tool that we use. Not to, you know, be that land-warrior so to speak. But more of a-- >> Documentation, I mean, you see 'em on cars when people get pulled over. >> Exactly. >> You've got the evidence. >> It's documentation, just like anything else. It's just that one more tool that helps that deputy, that detective, that police officer get a better idea of the entire situation. >> Maybe I shouldn't have said war. Maybe I'm just into the Twitch culture where they're all geared up with all the gear. Okay, so next question for you is what's your vibe on the show? Obviously you have great experience working at Amazon. You're a success study because you're trying to get a job done, you got some tools and, >> Right. >> making it happen. What's your take this year? What's your vibe of the show? >> I'm really excited about a lot of stuff I'm seeing at the show. A lot of the announcements seemed like they were almost geared towards me. And I know they weren't obviously, but it really felt like announcement after announcement were these things that I'm wanting to go home and immediately start to play with. Anywhere from the stuff that was in the machine learning to the new elastic containers that they are announcing, to the new LAM defunctions that they're talking about. I mean, just all over the board. I'm very excited for all these new things that I get to go home and play with. >> What do you think, Justin? What's your take on the vibe show? >> I find that it's an interesting show. I'm finding it a little different than what I was expecting. This is my first time here at AWS re:Invent. I go to a lot of other trade shows and I was expecting more of like a developer show. Like I'm going to CubeCon next week and that's full of people with spiky hair, and pink shoes, and craziness. >> John: That's the area, by the way. >> Oh that's the area, right. It's a bit more casual than some of the other more businessy sort of conferences. I mean, here I am, wearing a jacket. So I don't feel completely out of place here, but it does feel like it's that blending of business and use cases and the things that you actually get done with it as well as there being people who have the tools that they want to go and build amazing new things with. >> Chris: Right, right, yeah. >> So it's a nice blend, I think. >> Yeah, I've found that it definitely doesn't feel like any other developer conference I've been to. But being in the public sector, I tend to go to the more business-suit conferences. >> John: This is like total developer for you, from a public sector perspective. >> From where I'm coming from, this is very laid back. And extremely... >> Oh yeah. >> But at the same time, it's very like a mixture. Like you said, you see executives mingling with the developers talking about things-- >> John: You're a good example I think of Amazon. First of all, there's the builder thing in the area is supposed to be pretty cool. I was told to go there last night. People came back, it was very much builder, kind of maker culture. They're doing prototypes, it was very developer-oriented. But the public sector, I'm astonished by Amazon's success there because the stuff is easy and low-cost to get in. And public sector is not known for its agility. >> Chris: No. >> I mean, it's music to your ears, right? I mean, if you're in the public sector, you're like, "What? Now I can get it done?" >> Very much so. And one thing I love to share about our solution is the price, right? Because I spent $6 a month for my AWS bill. Right? >> John: Wow. >> That's extremely easy to sell to tax payers, right? It's extremely easy to sell to the higher-ups in government to say, I'm gonna tinker around with this, but even if we solve one crime, we've already seen a return on our investment above and beyond what we expected. >> Yeah. >> No brainer, no brainer. Chris, thanks so much for sharing your story. We really appreciate it. Congratulations on your success and keep in touch with theCube. Welcome to theCube Alumni Club. >> Alright. >> John: For coming out, it's theCube here. Amazon re:Invent, bringing all the action down, all of the success stories, all of the analysis. I'm John Furrier with theCube. More live coverage after this short break. (upbeat music)

>> Announcer: Live, from Las Vegas, it's theCUBE, covering AWS re:Invent 2017. Presented by AWS, Intel, and our ecosystem of partners. >> Welcome back everyone, live here in Las Vegas it's AWS re:Invent, it's theCUBE exclusive coverage of re:Invent 2017, our 5th year covering Amazon, watching the explosive growth. I'm John Furrier, the co-founder of SiliconANGLE Media, with Justin Warren my co-host here for this segment. Our next guest is Raejeanne Skillern, Vice President of the Data Center Group and also General Manager of the Cloud Service Provider, part of Intel. Welcome to theCUBE. >> Thank you very much, it's nice to be here again. >> So, Intel inside the Cloud is big growth for you, what's the numbers look like, your earnings look pretty good, what's the business update? >> You know, it is growing, and it's growing in so many different angles, it's coming from multiple fronts. Part of it is just these killer workloads that are driving the need for change. Artificial Intelligence, immersive media, network transformation to handle all the data. It is causing this real spur in growth, from both the very largest of Cloud service providers across the ecosystem, and one of the things when I look at the growth, I try to say, now where is it really coming from? Yes, Amazon is just insanely growing fast and the big guys are doing well, their global expansion, But, also, the next wave of Cloud service providers, and regions, and different countries, are doing really well too, they're actually growing faster, so the whole ecosystem is growing with demand. >> Yeah, it's certainly not slowing down. I can't see any way in which that it would slow down at all, if anything it's just gonna get faster. >> I think so, and when I track trends like CapEx spending and analyst predictions on the future, consumer demand, everything indicates we're gonna see another strong 5-10 years. >> Justin: Yep. >> So how do the Cloud service providers shake out because if you look at this creativity of software renaissance, the interactivity, all the amazing use cases, from Thorn, finding missing exploited children, to, you know, high end HPC scientists, genome sequencing stuff. Massive use cases. >> Raejeanne: Right. >> So that's going to be a tsunami of software developers, Changing. How does that shape the Cloud providers, does it segment them into tiers, how are you guys looking at that business? >> Well I think it breeds a lot of new opportunity. So, yes, you see more and more new services and capabilities to enable developers to more easily develop code, to more quickly, to get better utilization out of their code. But I also think just the concept of a mocking performance and ease, means new insights, new services, new capabilities, things that we just couldn't, a developer, we could not have done before. So it's that, just like electricity, when you make it cheaper and easier to consume, we use more of it. I think Cloud computing is the same way. So we're seeing kind of a natural tam expansion, market expansion, around these things you just couldn't do without the Cloud. >> And new workloads, too. >> And new workloads. >> And all of those workloads, Intel is basically completely repositioning itself from just being a chip company, it's like, you're a data company now. So, what are some of the things that Intel's doing to help people understand how they can make use of these new software techniques, and these new tools, and the capabilities of the Intel chips they're dependent on. So what are some of the things that Intel's doing there? >> So obviously it starts at the bottom, with the best silicon, not just compute, but compute, network, and storage, and accelerators, for all different workloads. We move up to the platforms, we do a lot of hardware engineering with the ecosystem, with our top CSPs, actually many top CSPs, we do direct engineering work to get better systems of architecture. We have a host of libraries we're creating that ease of use, and mocking performance out of it. Reference architectures, co-partners, and solutions. So for us when we talk about being a data company, we can't do it from just even being a chip, we have to be a solutions partner, with Cloud service providers, enterprise, IOT edge solutions, we try to be there. >> You guys always enabled some very cool demos in the day, even back on the PC you always had interactivity, you pioneered multimedia. You always had that eye on the applications. Okay, on stage today all this greatness is out there: NFL demos, all this cool stuff. That's really powering your business, so talk about your relationship with Amazon web services, what's it like, how do you guys engage with them, what's the relationship, 'cause you guys are power engine for AWS. >> Yeah, well we try to be. We wanna be the best performance into their data center. We've had a many, many, many year deep relationship with Amazon. It started from simple co-development and engineering, and is extended much more pervasively across their environment and it poured sometimes into the services. We just, we want to one, make sure that what we're delivering today has been already optimized specifically for their unique environment, and that means we have to start a year or two before, if not earlier, to really understand where they're going, and get their feedback, so that when we either optimize a product or technology across compute network or storage, or create something potentially custom for them, right, it takes a number of years of work, so our partnership has a lot of in-depth engineering, it has a lot of future and near-term enabling, and then we hope to see an expansion. What we really want to do is use our technology to differentiate Amazon. We want their services better because of the technologies or capabilities we put in, so wherever they wanna align in terms of strategic investment and growth markets, we wanna make sure the silicon can enable it. >> Intel always marched to the cadence of Moore's law, and you guys have always been a rapid machine, execution. Amazon looks good, I mean, they're executing. >> Raejeanne: They're fast. >> I mean, what's it like? Share some story, I mean, they're years ahead, what's it like working with Amazon? >> Well I think, I mean, they are fast. It's amazing how quickly they can move and innovate, how rapidly those innovations roll out to the market. I will be honest, there are times where we miss windows because we are slow, and they just look at us like, "Well we told you "this four weeks ago, here it is, right?" (laughing) >> Can't design a chip in four weeks. We don't have kubernetes, no containers for chips. >> I mean they are just, they have it down. So what we're trying to do is part of this transition from being a client company, to a Cloud and data center company, and IOT company, means everything we have to do is faster. So we have to design our chips more quickly, we have to put in more modularity for faster derivatives, and we have to move at Cloud speed, not classic Intel speed. >> Right, yeah. So what are some of the lessons that other companies can take from Intel, I mean it's a hardware company, or it was originally a hardware company, and now you've transitioned to being a Cloud company, and you're being pushed by Amazon to move faster and faster. So what are some of the lessons that you can share with other companies who are trying to start moving at Cloud speed? >> You know, I think, I love Jeff Bezos' approach, customer-obsessed. If you aren't understanding how the end customers, starting with Amazon's customers, but also then my customer, Amazon, how they're using and consuming technology, we can't really create good technology. I would say a lot of companies create a great thing and then try to go sell it at markets, >> Yep. >> Versus starting with the market, and creating the specific thing. The other thing we've learned, I mean, Intel is a very data driven company, both in our decision making, as well as our company growth, this is, and we talk about it from a developer envirogroup, but it's the same iterate fast. Fail quickly and move on. You don't need perfect. This is one of our learnings, right? Don't wait six months for perfect, move fast, get 70-80% of the way there, I've heard governments say they get 40-50 way percent of there, make decisions, because they have to move that quickly. For military or other exercises. So what we're trying to do is match that type of speed as well. >> It's a world of compute now, I mean, I was at Alibaba Conference, they had their Cloud coachings hearing it here, the same message: more compute. They're not saying I need more little chips, they're saying I want more horsepower. >> Raejeanne: Right. >> And you guys just announced the C5 instance, recently, a couple weeks. >> And the budget. >> What is that gonna do? I mean, it's fairly new. >> Raejeanne: Yes. >> What does that mean? Is that gonna be an IOT edge opportunity? Is it all workloads? That's gonna be like, a pretty big deal. What's your take on it? >> It is, their C instant line has always been for high performances growing workloads. We're seeing like, for HPC workloads, anywhere from two to four-and-a-half X the performance moving from C4 to C5, right? This is an instance that can handle the most demanding workloads from high performance compute to artificial Intelligence to others. So, you know, we have our latest and greatest Intel ZN scalable process in there, a very high performant one, that we customized specifically for their environment, but then they do all this amazing software work and efficiency work around it, to really unlock. I was really glad to see when they talked about those C5 instances launching, 25% on workload's price performance up to 50% price performance improvements on some others. So, I mean, once again, when you can take more compute and make it more cost effective, it's just a lot more things people can do in the industry, so we're very excited about that instance. >> What's the biggest thing in the past five years that jumped out at you in the massive change in the industry? Application, startups, business growth? What amazes you? >> Yeah, there's so much, I would kind of combine it under what the industry calls Digital Transformation. You know, when I look at it, one of the points that always sticks in my mind, is CEOs, 70% of them have digital transformation at the heart because the data suggests that by the end of 2018, the top 40% of the top 20, 40% of the top 20 industries are gonna be disrupted. So that to me, that amount of disruption happening, and the company's trying to disrupt themselves whether it's healthcare, retail, manufacturing, oil and glass, the use and pervasiveness of where technology and Cloud can fit has really kind of astonished me and I love, once again, I love that they're making what they do today better. But the new things that they're doing, I mean, in healthcare, right? It's just amazing. >> I mean, we used to use the word back in the day when I broke into the biz in the '80s, Data Processing Department. I mean, the Cloud is one big data processor. >> It is. It is a compute power. We call it the brain, right? If Cloud is now ubiquitous, right? It is, from public Cloud to private to Edge, and everything in between, it's that brain, right? >> John: It's the brain. >> That's enabling the compute, so we have to-- >> You people have always been on the inside of everything, so congratulations on your success, on the Cloud growth. General manager of the Cloud service provider and Vice President of Data Center Group, Raejeanne Skillern, here inside theCUBE with Intel, I'm Jeff Furrier with Justin Warren, back with more live coverage, here in Las Vegas, for Amazon web services 2017 re:Invent. More after this short break. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2017. Presented by: AWS, Intel and our ecosystem of partners. (lively electronic music) >> Welcome back everyone, this is theCUBE special exclusive coverage of AWS re:Invent 2017. CUBE's our flagship program, we go out to the events and we extract the signal noise. I'm John Furrier your co-host. With me today is Justin Moore, an analyst. We have two sets here in Las Vegas. Our next guest is Sumeet Singh, Vice President of Cloud Analytics with Juniper Networks, formerly of AppFormix, which was bought about a year ago. CUBE alumni back. New team, Juniper, welcome back. Last time we chatted with you you were entrepreneurial. >> Yeah. >> Taking names, kicking ass, now you're-- >> Bought out Juniper Networks, yeah. >> You bought out Juniper Net, what's going on? >> So we've essentially been building, building more and more and it's actually been a totally awesome experience. So, Last year when we spoke, we were essentially looking at a whole lot of private cloud deployment. Looking at OpenStack, looking at (mumbles), looking at VMware, and since, what we've now started really expanding into is, of course, the multi-cloud and hybrid cloud scenario. And looking at how to secure these clouds on prem, in the cloud, multi-cloud, as well as bring rich analytics into real-time operations insight as to what's going on in all of these environments. And how to optimize them. >> Yeah, that whole multi-cloud hybrid cloud thing is really exploded in the last 12 months. I'm hearing from customers a lot more that they are pursuing a multi-cloud strategy, but it seems that there's just this proliferation of things that you've now got to monitor and secure. So, how are you helping customers to do that? >> So, I mean, you're going to start with the basics. Right? So, the first thing that we got to realize is there are, of course, those companies that are born in the cloud. But then, there's a whole bunch of others who have for long run their own data centers and run their application stacks on prem, who are now looking to migrate to the public cloud and build all that multi-cloud scenario. In that situation, I would say, you need a little bit of hand-holding. You need to understand how your application's running on prem, which ones can be moved to the cloud, how can they be moved to the cloud, you want to ensure that those policies that you were implementing on prem you'll be able to implement those same policies in the public cloud, as well. The monitoring really starts on prem. All of those policies that operation starts on prem, and then you take them and you build them and you >> I'll get your take on, we'll have to get your take too, Justin, on something that's going on that I see clear visibility on. Infrastructure operations, data center cloud, get your house in order, networks, migration, hybrid cloud, multi-cloud, and then all that stuff. Then you've got this developer tsunami going on, a renaissance of real new development, new kinds of development, multiple databases using in app, IoT, so, the software development methodologies are changing for developers. That's obvious. What's the impact to the infrastructure guys, because you're starting to see Lambda and Server List as a way for saying complete infrastructure is code. How does that change the notion of, what the hell the data center is? Because you could argue that's just an edge now. So, what's the software, what are some of the software practices you see that are notable? >> The ones truly amazing, like in all these things that you're saying, is that you no longer need to use one approach to build anything. Any product that we put out, or any service that you put out, now uses a combination of all of these things. It could be Lambda, it could be IoT, it could be a wholesale application that's office started using (mumbles), that's spanning that multi-cloud environment. So, it's the beauty of all of this is the power of choice. We have so much more choice available to us. Right? But then, when choices, with choice comes that explosion and that complexity. It's >> Complexity is key, but speed is also there. You see. So, the question is, at what point does the cream rise to the top, and the people that are slow get run over. >> We're just seeing another evolution in obstruction, really, it's like, we don't write an assembly code anymore. We're writing directly to the hardware. We added in high-level programming languages, and now, in terms of the infrastructure, developers don't care about infrastructure as much as people talk about dev ops, and the thing like dev ops is a thing, developers don't want to deal with the infrastructure. They want to deal with code, cuz that's where they live. And the infrastructure folks, well, a lot of them are actually becoming developers now. So, they're learning how to use tools like, using development tools to actually get their job done. Which is where we're seeing infrastructure is going. So, there's a lot more ob abstraction into pure software, so you don't have to worry about the underlying obstructions, at least, not very much. >> All right, Sumeet, question to you now on that is, that requires the network guys, Juniper, you're part of that, and all the analytics to think differently about what you're instrumenting. To do what he said, to make it free, you gotta enable a lot of policy, a lotta data analytics, take us through what's the current state of the art there. >> So, the current state of the art, is essentially, if you talk about Juniper products, we have our family of SRX products, where you can have on prem firewalls, as well as virtual firewalls in the cloud, and using these tools, you can have consistent policies on prem and in the cloud. You can free up transit VPCs. Then there are the obligations in the multi cloud world, and do all kinds of fancy things. But where we also going with our solutions is to make them much more simpler to consume. It's truly all about simplicity, right? Because now you have all this choice, and you can have Lambda, and you can have all these new ways to bring up your applications. What becomes key is that the policies that you wanna implement become automatic. Right? And the way to do that is, the way we are doing that is, essentially, doing this auto-learning of your environment. Right? Automatically understanding, Automation, right? But, not, automation in two parts, as in automatically detect what's going on, but then automatically apply the policies as well, no matter where the workload is and where it's scaling, we automatically apply the policies to it. >> So, it's a lot of investment in this mart of underly-- Making something simple is actually quite complex to do. So, you need to understand what are the right things to automate, and what are the few things where you actually wanna give humans that choice, without it becoming overwhelming, so that, okay, I have to choose between one of 800 different ways of doing this. That's just not something that humans cope well with, whereas machines are actually really good at that. >> And that's the value here. We want to hide all the complexity under the hood. You know, use those advanced logarithms, use, you know, where they be on prem or in the cloud, but running all the analysis, implementing all the right policies for you, right? And new, new workload comes up it should automatically get the policy, right? And we are now able to do that both in the private data center, as well as in the public cloud, and bridge those policies together for you, automatically. >> The common theme we're seeing in cloud, we had a guest on from Thorn, where they automate, essentially, police officers writing down notes in a notebook to fully spotting with machine learning and all this great stuff, to find missing and exploited children, manual sucks, basically. Manual's slow-- >> The workload's too dominant now for you to think about manual. >> I want real-time. So most organizations, what's going on there? How do you guys help there, what's the progress? >> Oh. So, this is actually a great question, by the way, so, and this is part of the reason why we like, as a company, as a start up, maybe, we're like, doing all this cool stuff, and, you know, not really thinking about all the, hey, this is slowing me down. The reason why we went to Juniper, if you look at the history of Juniper, and the product portfolio, and the stock at Juniper, when it comes to automation, when it comes to things like ABI, when it comes to things like policy, they've always kind of like led the pack in that networking space, and now this is the opportunity to take that that wealth of knowledge, and scale it out, and take it to a little bit broader multi-cloud, hybrid cloud space. But, that's truly where it is, and even if you, kind of like go down low level to the devices, all Juniper devices are able to stream real-time elements. We are able to do ML in real-time, even on the physical devices, right? Similar for all virtual devices, and now, with our Formix, we even bring in the performance and operations inside, from the running infrastructure, whether it's on prem and in the cloud, not just networking, but the compute, the databases, your applications, your clusters, all of that, to build for you this end-to-end view, right? Not just the networks, your servers, Vms, workloads, the underlying network, the connectivity, all of it. >> How does that, because the developers, they live in application land, and again, they don't really care about that infrastructure, but as it turns out, sometimes it's quite useful to know which particular network devices, or what the infrastructure is that underpins things, like where you sometimes need to be able to drop into assembly code to really optimize things, so are you making that information about the infrastructure visible to developers in a way that they like to, to know and consume? >> Absolutely, so, one key thing about, you know, our product portfolio, and how we are releasing our services, essentially, we've wrapped everything around, you know, these role-based access interfaces. Where both the operators are able to get their views, they're able to construct views that the developers are able to see, and then both can implement their own policies, right? If, let's say, there's some infrastructure that's down, or is unhealthy, then having that global topology view helps you in real-time totally, and in real-time informs you what the impact of that outage is. Like who are the developers who would be impacted, what are their obligations? And, you know, we can bring that insight, and consume it to run the automation. So, if, let's just say, some infrastructure's unhealthy, can you read off the graph? >> Sumeet, talk about what you guys are doing here. How's Amazon, big learning conference, but it's a massive show, 45,000 people here, across multiple hotels. A lot of sessions. What do you guys talk about? What's the big cloud piece for you guys? >> For us, really, first, it's just visibility, right? We have a product portfolio that gives you visibility. Like, both for your physical infrastructure, and your virtual structure. Then, the next thing is, of course, You know, yeah, you have the visibility. But then, at our scale, no human can consume all that information. It's too slow. It's too slow. So, you've gotta have the machine-learning built in. So, it's promoting that visibility into insights in real time, and then, it's about how do you secure your workloads? So, consuming all of that insight to implement all of the policies, implement all of the automation, to ensure that everything is running as you want it to. >> What's your Juniper message to the developers here? Is there a new face to Juniper, a new vibe? You mentioned Juniper's always had great products, like, you move packets around at lightning speeds, you know, wire speeds, all that great stuff. How do you, what's new? What's it mean for me as a developer, what is Juniper, how's it make my life easier? >> What's new is that now it's easier for developers to consume our products. Our products are now available in the Amazon marketplace, right? Our visibility products, our machine-learning products, our security products, right? You can just click, install, and start using them. That's new for Juniper, right? I mean, traditionally you would think of-- >> You probably get Juniper goodness just by treating it like a library. >> That's it. You can just download, not even download, right? You're -- >> It's server-less. It's router-less. It's device-less. >> There you go. You can just start consuming them. And then, if you do have that knowledge of how do you use those devices on prem, then you can apply that knowledge in the cloud, and then use them all. >> Must be computing back in, what, like 20 years ago. I mean, is it just like a grid now. >> Oh, yeah, pretty much, yeah. >> It's a fabric. >> It's the same, if you already know how to use it one place, you know how to use it everywhere. >> Yeah, but, I mean, it's, really, the value of the cloud is making it even simpler, right? Running all of that automation, like we talked about Lambda, like even within our products family, we can, we use Lambda to constantly see what's changing, and that's how we process lots of our internal transactions, as well. >> Sumeet, congratulations on your acquisition and your entrepreneurial journey, and now you're at Juniper. Looking forward to keeping in touch. Sumeet Singh, Vice President of Cloud Analytics, and now at Juniper Networks, formerly AppFormix, CUBE alumni, thanks for coming on and sharing your commentary. I'm John Furrier, and Justin Moore, here on theCUBE, main stage in Las Vegas at AMS re:Invent We'll be back with more after this short break. (lively electronic music)

>> Announcer: Live from Washington, D.C., it's theCUBE, covering .conf2017. Brought to you by Splunk. >> Welcome back. Here on theCUBE, we continue our coverage of .conf2017, Splunk's get together here with some 7,000 plus attendees, 65 countries, we're right on the showfloor. A lot of buzz happening down here and it's all good. Along with Dave Vellante, I'm John Walls. We are live, as I said, in our nation's capital, and we're joined by a guest who represents her organization that is a member of the Splunk4Good program. We're going to explain that in just a little bit, but Sherrie Caltagirone is the founder and executive director of the Global Emancipation Network, and Sherry, thanks for being with us. We appreciate your time. >> Thanks so much for having me on, John. >> So your organization has to do with countering and combating global trafficking, human trafficking. >> That's right. >> We think about sex trafficking, labor trafficking, but you're a participant in the Splunk4Good program, which is their ten year pledge to support organizations such as yours to the tune of up to $100 million over that ten years to all kinds of organizations. So first off, let's just talk about that process, how you got involved, and then we want to get into how you're actually using this data that you're mining right now for your work. So first off, how'd you get involved with Splunk? >> Absolutely. It was really organic in that it's a really small community. There are a lot of people in the tech space who I found really want to use their skills for good, and they're very happy to make connections between people. We had a mutual friend actually introduce me to Monzy Merza, who's the head of security here at Splunk, and he said, "I'm really passionate about trafficking, I want to help "fight trafficking, let me connect you with Corey Marshall "at Splunk4Good." The rest is really history, and I have to tell you, yes, they have pledged up to $100 million to help, and in products and services, but what's more is they really individually care about our projects and that they are helping me build things, I call them up all the time and say, "Hey let's brainstorm an idea, "let's solve a problem, "let's figure out how we can do this together, and they really are, they're part of my family. They're part of GEN and Global Emancipation Network. >> That's outstanding. The size of the problem struck me today at the keynote when we talked about, first off, the various forms of trafficking that are going on; you said up to two dozen different subsets of trafficking, and then the size and the scale of 25 to 40-some million people around the globe are suffering. >> Yeah. >> Because of trafficking conditions. That puts it all in a really different perspective. >> You're right. Those weren't even numbers that we can really fathom what that means, can we? We don't know what 20 million looks like, and you're right, there's such a wide discrepancy between the numbers. 20 million, 46 million, maybe somewhere in between, and that is exactly part of the problem that we have is that there is no reliable data. Everyone silos their individual parts of the data that they have for trafficking, all the the different stakeholders. That's government, NGOs, law enforcement, academia, it's all kinds. It runs the gamut, really, and so it's really difficult to figure out exactly what the truth is. There's no reliable, repeatable way to count trafficking, so right now it's mostly anecdotal. It's NGOs reporting up to governments that say, "We've impacted this many victims," or, "We've encountered so-and-so who said that the "trafficking ring that they escaped from had 20 other people "in it," things like that, so it's really just an estimate, and it's the best that we have right now, but with a datalet approach, hopefully we'll get closer to a real accurate number. >> So talk more about the problem and the root of the problem, how it's manifesting itself, and we'll get into sort of what we can do about it. >> Yeah. It's really interesting in that a lot of the things that cause poverty are the same things that cause trafficking. It really is, you know, people become very vulnerable if they don't have a solid source of income or employment, things like that, so they are more willing to do whatever's necessary in order to do that, so it's easy to be lured into a situation where you can be exploited, for example, the refugee crisis right now that's happening across Europe and the Middle East is a major player for trafficking. It's a situation completely ripe for this, so people who are refugees who perhaps are willing to be smuggled out of the country, illegally, of course, but then at that point they are in the mercy and the hands of the people who smuggled them and it's very easy for them to become trafficked. Things like poverty, other ways that you're marginalized, the LGBTQ community is particularly vulnerable, homeless population, a lot of the same issues that you see in other problems come up, creates a situation of vulnerability to be exploited, and that's all trafficking really is: the exploitation of one individual through force, coercion, fraud, position of authority, to benefit another person. >> These individuals are essentially what, enslaved? >> Yeah. It's modern day slavery. There's lots of different forms, as you mentioned. There's labor trafficking, and that's several different forms; it can be that you're in a brick factory, or maybe you're forced into a fishing boat for years and years. Usually they take away your passport if you are from another country. There's usually some threats. They know where your family lives. If you go tell anyone or you run away, they're going to kill your family, those sorts of things. It is, it's modern day slavery, but on a much, much bigger scale, so it's no longer legal, but it still happens. >> How does data help solve the problem? You, as an executive director, what kind of data, when you set the North Star for the organization from a data perspective, what did that look like, and how is it coming into play? >> Well, one of the benefits that we have as an organization that's countering trafficking is that we are able to turn the tables on traffickers. They are using the internet in much the way that other private enterprises are. They know that that's how they move their product, which in this case is sadly human beings. They advertise for victims online. They recruit people online. They're using social media apps and things like Facebook and Kick and Whatsapp and whatnot. Then they are advertising openly for the people that they have recruited into trafficking, and then they are trying to sell their services, so for example, everyone knows about Backpage. There's hundreds of websites like that. It runs the gamut. They're recruiting people through false job advertisements, so we find where those sites are through lots of human intelligence and we're talking to lots of people all the time, and we gather those, and we try to look for patterns to identify who are the victims, who are the traffickers, what can we do about it? The data, to get back to your original question, is really what is going to inform policy to have a real change. >> So you can, in terms of I guess the forensics that you're doing, or whatever you're doing with that data, you're looking at not only the websites, but also the communications that are being spawned by those sites and looking to where those networks are branching off to? >> Yeah. That's one of the things that we really like to try to do. Instead of getting a low-level person, we like to try to build up an entire network so we can take down an entire ring instead of just the low fish. We do, we extract all the data from the website that we can to pull out names, email addresses, physical addresses, phone numbers, things like that, and then begin to make correlations; where else have we seen those phone numbers and those addresses on these other websites that we're collecting from, or did this person make a mistake, which we love to exploit mistakes with traffickers, and are they using the same user handle on their personal Flickr page, so then we can begin to get an attribution. >> John: That happens? >> Absolutely. >> It does, yeah. >> Sherrie: Without giving away all my secrets, exactly. >> Yeah, I don't to, don't give away the store, here. How much, then, are you looking internationally as opposed to domestically, then? >> We collect right now from 22 different countries, I think 77 individual cities, so a lot of these websites are usually very jurisdictionally specific, so, you know, like Craigslist; you go into Washington state and click on Seattle, something like that. We harvest from the main trafficking points that we can. We're collecting in six different languages right now. A lot of the data that we have right now is from the U.S. because that's the easier way to start is the low-hanging fish. >> What does your partner ecosystem look like? It comprises law enforcement, local agencies, federal agencies, presumably, NGOs. Will you describe that? >> Yeah. We do, we partner with attorneys general, we partner with law enforcement, those are the sort of operational partners we look for when we have built out intelligence. Who do we give it to now, because data is useless unless we do something with it, right? So we we build out these target packages and intelligence and give it to people who can do something with it, so those are really easy people to do something with. >> How hard is that, because you've got different jurisdictions and different policies, and it's got to be like herding cats to get guys working with you. >> It is, and it's actually something that they're begging for, and so, it's a good tool that they can use to deconflict with each other, 'cause they are running different trafficking-related operations all the time, and jurisdictions, they overlap in many cases, especially when you're talking about moving people, and they're going from one state to another state, so you have several jurisdictions and you need to deconflict your programs. >> Okay, so they're very receptive to you guys coming to them with they data. >> They are; they really want help, and they're strapped for resources. These are for the most part, not technically savvy people, and this is one of the good things about our nonprofit is that it is a staff of people who are very tech-savvy and who are very patient in explaining it and making it easy and usable and consumable by our customers. >> So if I'm an NGO out there, I'm a non-profit out there, and I'm very interested in having this kind of service, what would you say to them about what they can pursue, what kind of relationship you have with Splunk and the value they're providing, and what your experience has been so far. >> It's been wonderful. I've been over at the Splunk4Good booth all day helping out and it's been wonderful to see not only just the non-profits who have come up and said, "Hey, I run a church, "I'm trying to start a homeless shelter for drug-addicted "individuals, how can you help me," and it's wonderful when you start to see the light bulbs go off between the non-profit sector and the tech sector, between the philanthropic organizations like Splunk4Good, the non-profits, and then, we can't forget the third major important part here, which is, those are the tech volunteers, these are the people who are here at the conference and who are Splunk employees and whatnot and teaching them that they can use their skills for good in the non-profit sector. >> Has cryptocurrency, where people can conduct anonymous transactions, made your job a lot more difficult? >> No, it hasn't, and there's been a lot of research that has gone into block chain analysis, so for example, Backpage, all the adds are purchased with Bitcoin, and so there's been a wonderful amount of research then, trying to time the post to when the Bitcoin was purchased, and when the transactions happen, so they've done that, and it's really successful. There are a couple of other companies who do just that, like Chainalysis, that we partner with. >> You can use data to deanonymize? >> That's correct. It's not as anonymous as people think it is. >> Love it. >> Yeah, exactly. We love to exploit those little things like that. A lot of the websites, they put their wallets out there, and then we use that. >> Dave: You're like reverse hackers. >> That's right. It's interesting that you say that, because a lot of our volunteers actually are, they're hacker hunters. They're threat and intel analysts and whatnot, and so, they've learned that they can apply the exact same methods and techniques into our field, so it's brilliant to see the ways in which they do that. >> Dave: That's a judo move on the bad guys. >> Exactly. How long does this go on for you? Is this a year-to-year that you renew, or is it a multi-year commitment, how does that work? >> It's a year-to-year that we renew our pledge, but they're in it for the long haul with us, so they know that they're not getting rid of me and nor do they want me to, which is wonderful. It's so good, because they help, they sit at the table with me, always brainstorming, so it's year-to-year technically, but I know that we're in it together for the long haul. >> How about fundraising? A big part of your job is, you know. >> Of course it is. >> Fundraising. You spend a lot of time there. Maybe talk about that a little bit. >> Yeah, absolutely. Some of our goals right now, for example, is we're really looking to hire a full-time developer, we want a full-time intelligence analyst, so we're always looking to raise donations, so you could donate on our website. >> John: Which is? >> Which is globalemancipation.ngo. Globalemancipation.ngo. We're also always looking for people who are willing to help donate their time and their skills and whatnot. We have a couple of fundraising goals right now. We're always looking for that. We receive a lot of product donations from companies all over the world, mostly from the tech sector. We're really blessed in that we aren't spending a lot of money on that, but we do need to hire a couple of people so that's our next big goal. >> I should have asked you this off the top. Among your titles, executive director and founder, what was the founder part? What motivated you to get involved in this, because it's, I mean, there are a lot of opportunities to do non-profit work, but this one found you, or you found it. >> That's right. It's a happy circumstance. I've always done anti-human trafficking, since my college days, actually. I started volunteering, or I started to intern at the Protection Project at Johns Hopkins University, which was a legislative-based program, so it was really fantastic, traveling the world, helping countries draft legislation on trafficking, but I really wanted to get closer and begin to measure my impact, so that's when I started thinking about data anyways, to be able to put our thumb, is what we're doing. Working. How are we going to be able to measure success and what does that look like? Then I started volunteering for a rescue operations organization; the sort of knock down the doors, go rescue people group, and so, I really liked having the closer impact and being able to feel like hey, I can do something about this problem that I know is terrible and that's why it spread. A lot of the people I worked with, including my husband, come from the cyberthreat intelligence world, so I feel like those ideas and values have been steeped in me, slowly and surely, over the last decade, so that just ages myself a little bit maybe, but yes, so those ideas have been percolating over time, so it just kind of happened that way. >> Well, you want to feel young, hang around with us. (laughing) I should speak for myself, John, I'm sorry. >> No, no, you're right on, believe me. I was nodding my head right there with you. >> Can you comment on the media coverage? Is it adequate in your view? Does there need to be more? >> On trafficking itself? You know, it's really good that it's starting to come into the forefront a lot more. I'm hearing about it. Five years ago, most of the time, if I told people that there are still people in slavery, it didn't end with the Civil War, they would stand at me slackjawed. There have been a few big media pushes. There's been some films, like Taken, Liam Neeson's film, so that's always the image I use, and that's just one type of trafficking, but I'm hearing more and more. Ashton Kutcher runs a foundation called Thorn that's really fantastic and they do a similar mission to what I do. He has been able to raise the spotlight a lot. Currently there's a debate on the floor of the Senate right now, too, talking about section 230 of the CDA, which is sort of centered around the Backpage debate anyway. Where do we draw the line between the freedom of speech on the internet, with ESPs in particular, but being able to still catch bad guys exactly. The Backpage sort of founder idea. It's really hot and present in the news right now. I would love to see the media start to ask questions, drill down into the data, to be able to ask and answer those real questions, so we're hoping that Global Emancipation Network will do that for the media and for policy makers around the world. >> Well it is extraordinary work being done by an extraordinary person. It's a privilege to have you on with us, here on theCUBE. We thank you, not only for the time, but for the work you're doing, and good luck with that. >> Thank you very much for having me on. I really appreciate it. >> You bet. That's the Global Emancipation Network. Globalemancipation.ngo right? Fundraising, always helpful. Back with more here on theCUBE in Washington D.C., right after this. (electronic beats)

(electronic music) >> Announcer: Live from Austin, Texas, it's The Cube. Covering South By Southwest 2017. Brought to you by Intel. Now, here's John Furrier. >> Hey, welcome back, everyone, we're here live in Austin, Texas, for South By Southwest Cube coverage at the Intel AI Lounge, #IntelAI if you're watching, put it out on Twitter. I'm John Furrier of Silicon Angle for the Cube. Our next guest is Alison Yu who's with Cloudera. And in the news today, although they won't comment on it. It's great to see you, social media manager at Cloudera. >> Yes, it's nice to see you as well. >> Great to see you. So, Cloudera has a strategic relationship with Intel. You guys have a strategic investment, Intel, and you guys partner up, so it's well-known in the industry. But what's going on here is interesting, AI for social good is our theme. >> Alison: Yes. >> Cloudera has always been a pay-it-forward company. And I've known the founders, Mike Olson and Amr Awadallah. >> Really all about the community and paying it forward. So Alison, talk about what you guys are working on. Because you're involved in a panel, but also Cloudera Cares. And you guys have teamed up with Thorn, doing some interesting things. >> Alison: Yeah (laughing). >> Take it away! >> Sure, thanks. Thanks for the great intro. So I'll give you a little bit of a brief introduction to Cloudera Cares. Cloudera Cares was founded roughly about three years ago. It was really an employee-driven and -led effort. I kind of stepped into the role and ended up being a little bit more of the leader just by the way it worked out. So we've really gone from, going from, you know, we're just doing soup kitchens and everything else, to strategic partnerships, donating software, professional service hours, things along those lines. >> Which has been very exciting to see our nonprofit partnerships grow in that way. So it really went from almost grass-root efforts to an organized organization now. And we start stepping up our strategic partnerships about a year and a half ago. We started with DataKind, is our initial one. About two years ago, we initiated that. Then we a year ago, about in September, we finalized our donation of an enterprise data hub to Thorn, which if you're not aware of they're all about using technology and innovation to stop child-trafficking. So last year, around September or so, we announced the partnership and we donated professional service hours. And then in October, we went with them to Grace Hopper, which is obviously the largest Women in Tech Conference in North America. And we hosted a hackathon and we helped mentor women entering into the tech workforce, and trying to come up with some really cool innovative solutions for them to track and see what's going on with the dark web, so we had quite a few interesting ideas coming out of that. >> Okay, awesome. We had Frederico Gomez Suarez on, who was the technical advisor. >> Alison: Yeah. >> A Microsoft employee, but he's volunteering at Thorn, and this is interesting because this is not just donating to the soup kitchens and what not. >> Alison: Yeah. >> You're starting to see a community approach to philanthropy that's coding RENN. >> Yeah. >> Hackathons turning into community galvanizing communities, and actually taking it to the next level. >> Yeah. So, I think one of the things we realize is tech, while it's so great, we have actually introduced a lot of new problems. So, I don't know if everyone's aware, but in the '80s and '90s, child exploitation had almost completely died. They had almost resolved the issue. With the introduction of technology and the Internet, it opened up a lot more ways for people to go ahead and exploit children, arrange things, in the dark web. So we're trying to figure out a way to use technology to combat a problem that technology kind of created as well, but not only solving it, but rescuing people. >> It's a classic security problem, the surface area has increased for this kind of thing. But big data, which is where you guys were founded on in the cloud era that we live in. >> Alison: Yeah. >> Pun intended. (laughing) Using the machine learning now you start with some scale now involved. >> Yes, exactly, and that's what we're really hoping, so we're partnering with Intel in the National Center of Missing Exploited Children. We're actually kicking off a virtual hackathon tomorrow, and our hope is we can figure out some different innovative ways that AI can be applied to scraping data and finding children. A lot of times we'll see there's not a lot of clues, but for example, if we can upload, if there can be a tool that can upload three or four different angles of a child's face when they go missing, maybe what happens is someone posts a picture on Instagram or Twitter that has a geo tag and this kid is in the background. That would be an amazing way of using AI and machine learning-- >> Yeah. >> Alison: To find a child, right. >> Well, I'll give you guy a plug for Cloudera. And I'll reference Dr. Naveen Rao, who's the GM of Intel's AI group, was on earlier. And he was talking about how there's a lot of storage available, not a lot of compute. Now, Cloudera, you guys have really pioneered the data lake, data hub concept where storage is critical. >> Yeah. >> Now, you got this compute power and machine learning, that's kind of where it comes together. Did I get that right? >> Yeah, and I think it's great that with the partnership with Intel we're able to integrate our technology directly into the hardware, which makes it so much more efficient. You're able to compute massive amounts of data in a very short amount of time, and really come up with real results. And with this partnership, specifically with Thorn and NCMEC, we're seeing that it's real impact for thousands of people last year, I think. In the 2016 impact report, Thorn said they identified over 6,000 trafficking victims, of which over 2,000 were children. Right, so that tool that they use is actually built on Cloudera. So, it's great seeing our technology put into place. >> Yeah, that's awesome. I was talking to an Intel person the other day, they have 72 cores now on a processor, on the high-end Xeons. Let's get down to some other things that you're working on. What are you doing here at the show? Do you have things that you're doing? You have a panel? >> Yeah, so at the show, at South by Southwest, we're kicking off a virtual hackathon tomorrow at our Austin offices for South by Southwest. Everyone's welcome to come. I just did the liquor order, so yes, everyone please come. (laughing) >> You just came from Austin's office, you're just coming there. >> Yeah, exactly. So we've-- >> Unlimited Red Bull, pizza, food. (laughing) >> Well, we'll be doing lots and lots tomorrow, but we're kicking that off, we have representatives from Thorn, NCMEC, Google, Intel, all on site to answer questions. That's kind of our kickoff of this month-long virtual hackathon. You don't need to be in Austin to participate, but that is one of the things that we are kicking off. >> And then on Sunday, actually here at the Intel AI Lounge we're doing a panel on AI for Good, and using artificial intelligence to solve problems. >> And we'll be broadcasting that live here on The Cube. So, folks, SiliconAngle.tv will carry that. Alison, talk about the trend that, you weren't here when we were talking about how there's now a new counterculture developing in a good way around community and social change. How real is the trend that you're starting to see these hackathons evolve from what used to be recruiting sessions to people just jamming together to meet each other. Now, you're starting to see the next level of formation where people are organizing collectively-- >> Yeah. >> To impact real issues. >> Yeah. >> Is this a real trend or where is that trend, can you speak to that? >> Sure, so from what I've seen from the hackathons what we've been seeing before was it's very company-specific. Only one company wanted to do it, and they would kind of silo themselves, right? Now, we're kind of seeing this coming together of companies that are generally competitors, but they see a great social cause and they decide that they want to band together, regardless of their differences in technology, product, et cetera, for a common good. And, so. >> Like a Thorn. >> For Thorn, you'll see a lot of competitors, so you'll see Facebook and Twitter or Google and Amazon, right? >> John: Yeah. >> And we'll see all these different competitors come together, lend their workforce to us, and have them code for one great project. >> So, you see it as a real trend. >> I do see it as a trend. I saw Thorn last year did a great one with Facebook and on-site with Facebook. This year as we started to introduce this hackathon, we decided that we wanted to do a hackathon series versus just a one-off hackathon. So we're seeing people being able to share code, contribute, work on top of other code, right, and it's very much a sharing community, so we're very excited for that. >> All right, so I got to ask you what's they culture like at Cloudera these days, as you guys prepare to go public? What's the vibe internally of the company, obviously Mike Olson, the founder, is still around, Amr's around. You guys have been growing really fast. Got your new space. What's the vibe like in Cloudera now? >> Honestly, the culture at Cloudera hasn't really changed. So, when I joined three years ago we were much smaller than we are now. But I think one thing that we're really excited about is everyone's still so collaborative, and everyone makes sure to help one another out. So, I think our common goal is really more along the lines of we're one team, and let's put out the best product we can. >> Awesome. So, what's South by Southwest mean to you this year? If you had to kind of zoom out and say, okay. What's the theme? We heard Robert Scoble earlier say it's a VR theme. We hear at Intel it's AI. So, there's a plethora of different touchpoints here. What do you see? >> Yeah, so I actually went to the opening keynote this morning, which was great. There was an introduction, and then I don't know if you realized, but Cory Booker was on as well, which is great. >> John: Yep. >> But I think a lot of what we had seen was they called out on stage that artificial intelligence is something that will be a trend for the next year. And I think that's very exciting that Intel really hit the nail on the head with the AI Lounge, right? >> Cory Booker, I'm a big fan. He's from my neighborhood, went to the same school I went to, that my family. So in Northern Valley, Old Tappan. Cory, if you're watching, retweet us, hashtag #IntelAI. So AI's there. >> AI is definitely there. >> No doubt, it's on stage. >> Yes, but I think we're also seeing a very large, just community around how can we make our community better versus let's try to go in these different silos, and just be hyper-aware of what's only in front of us, right? So, we're seeing a lot more from the community as well, just being interested in things that are not immediately in front of us, the wider, either nation, global, et cetera. So, I think that's very exciting people are stepping out of just their own little bubbles, right? And looking and having more compassion for other people, and figuring out how they can give back. >> And, of course, open source at the center of all the innovation as always. (laughing) >> I would like to think so, right? >> It is! I would testify. Machine learning is just a great example, how that's now going up into the cloud. We started to see that really being part of all the apps coming out, which is great because you guys are in the big data business. >> Alison: Yeah. >> Okay, Alison, thanks so much for taking the time. Real quick plug for your panel on Sunday here. >> Yeah. >> What are you going to talk about? >> So we're going to be talking a lot about AI for good. We're really going to be talking about the NCMEC, Thorn, Google, Intel, Cloudera partnership. How we've been able to do that, and a lot of what we're going to also concentrate on is how the everyday tech worker can really get involved and give back and contribute. I think there is generally a misconception of if there's not a program at my company, how do I give back? >> John: Yeah. >> And I think Cloudera's a shining example of how a few employees can really enact a lot of change. We went from grassroots, just a few employees, to a global program pretty quickly, so. >> And it's organically grown, which is the formula for success versus some sort of structured company program (laughing). >> Exactly, so we definitely gone from soup kitchen to strategic partnerships, and being able to donate our own time, our engineers' times, and obviously our software, so. >> Thanks for taking the time to come on our Cube. It's getting crowded in here. It's rocking the house, the house is rocking here at the Intel AI Lounge. If you're watching, check out the hashtag #IntelAI or South by Southwest. I'm John Furrie. I'll be back with more after this short break. (electronic music)