>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> welcome back here to New York City. You're watching the Cube, the worldwide leader in Enterprise Tech cover jumps to minimum. My co host for today is Cory Quinn and happy to welcome to the program. A first time guest on the program, says Heart O. B. Who is a senior leader of global business development with Healthcare Life. Scientists know this group and AWS thanks so much for joining us. All right, so you know, we love digging into some of the verticals here in New York City. Of course, it's been a lot of time on the financial service is peas we actually had, Ah, another one of our teams out of the eight of us. Imagine show going on yesterday in Seattle with a lot of the education pieces. So healthcare, life sciences in genomics, little bit of tech involved in those groups, a lot of change going on in that world. So give us a thumbnail if you would as toe what what's happening in your >> world so well just from a scope one of you Health care includes life set paid on provider Life sciences is far more by attacking its most medical device and then genomics and what we're seeing in those spaces. Let's start with health care. It's such a broad thing, will just sort of back to back and forth in health care itself. What we're sort of seeing their customs ask us to focus on and to help them do falls into three categories. First, is a lot of customers ask us to help them personalized the consumer health journey. You and I, all of us, are so accustomed to that frictionless experiences we have elsewhere and in health care. There's a lot more friction. And so we're getting a lot of enquiries and request for us to help them transform that experience. Make it frictionless. So an example That would be if you're familiar with Doc. Doc started here in New York. Actually, when you want a book, an appointment, Doc, Doc, you can normally, if you go online, I have to put information for insurance. You type it all. Then it's full of friction. Have to put all the fields in. They use one of our A I service's image recognition, and you simply hold up your card to the camera and it able to pull your in transporation, determine eligibility and look the right appointment for you. So that's an example of removing friction for the consumer of the health consume over the patient as they're trying to go to that health care and excessive category one frictionless experiences using AWS to support it with a i service is category, too. We're getting a lot of interest for us to help health systems predict patient health events. So anything of value base care the way you actually are able to change the cost. Quality Curve is predicting events, not just dealing with math and so using a i Am L service is on top of data to predict and forecast events is a big part of one example would be with sooner where they moved, they're healthy and 10 platform, which is a launch to a patient record platform onto AWS. About 223,000,000 individuals that are on that platform Men we did a study with him where way consume about 210,000 individual patient data and created a machine learning model this is published where you can predict congestive heart failure 15 months in advance of it actually occurring. So when you look at that, that prediction are forecasting that sort of one of the powers of this princess. What category number two is predicting health events, and then the last one I'd be remiss in leaving out is that you probably have heard a lot of discussion on physician and a clinician. Burnout to the frustrations of the nurses or doctors and Muslims have the heart of that is not having the right information the right time to take care of the right patient. Data liquidity and in Trop ability is a huge challenge, and a lot of our customers are asking us to help solve those problems with them. You know it hims. This year we announced, together with change Healthcare Change Healthcare said they want to provide free and troubling to the country on AWS, with the platform supporting that. So those are sort of three categories. Personalize the consumer health journey. Predicting patient health events and promoting intra ability is sort of the signals that we're seeing in areas that were actively supporting our customers and sort of elevating the human condition. >> It's very easy to look at the regulation around things like health care and say, Oh, that gets in the way and its onerous and we're not gonna deal with it or it should be faster. I don't think anyone actively wants that. We like the fact that our hospitals were safe, that health care is regulated and in some of the ways that it is at least. But I saw an artifact of that means that more than many other areas of what AWS does is your subject to regulatory speed of Sloane. A speed of feature announcement, as opposed to being able to do it as fast technology allows relatively easy example of this was a few years back. In order to run, get eight of us to sign a B A. For hip, a certification, you have to run dedicated tendency instances and will not changed about a year and 1/2 2 years ago or even longer. Depending it's it all starts to run together after a time, but once people learn something, they don't tend to go back and validate whether it's still true. How do you just find that communicating to your customers about things that were not possible yesterday now are, >> yeah, when you look at hip eligibility. So as you know, a devious is about over 100 him eligible service's, which means that these are so this is that so compliance that you start their compliance, Remember, is an outcome, not a future. So compliance is a combination of people process platform, and we bring the platform that's hip eligible, and our customers bring the people in process, if you will, to use that platform, which then becomes complying with regulatory requirements. And so you're absolutely right. There's a diffusion of sort of understanding of eligibility, a platform, and then they worked with customers have to do in order as a shared responsibility to do it. That diffusion is sometimes slower. In fact, there's sometimes misinformation. So we always see it work with our customers and that shared, responsive model so that they can meet their requirements as they come to the cloud. And we can bring platforms that are eligible for hip. They can actually carry out the work clothes they need to. So it's it's that money, you know, the way I think of it is. This when you think of compliance, is that if if I were to build for you a deadbolt for your door and I can tell you that this complies boasted of things, but you put the key under the mat way might not be complying with security and regular requirements for our house. So it's a share responsible. I'll make the platform be eligible and compliant, and so that collective does daytime and dusting. People are saying that there is a flat from this eligible, and then they have to also, in their response to work to the people in process potion to make the totality of it comply with the requirements for regulatory for healthcare regulatory requirements. >> Some of the interesting conversations I've had in the last few years in health care in the industry is collaborations that are going on, you know, how do we share data while still maintaining all of the regulations that are involved? Where does that leave us get involved? There >> should. That's a fact. There is a data sharing part of that did a liquidity story that we talked about earlier in terms of instability. I'll give an example of where AWS actually actively working in that space. You may be familiar with a service we launched last November at Reinvent called Amazon Campion Medical and Campion Medical. What it does is it looks at a medical note and can extract key information. So if you think back to in high school, when you used to read a book in highlighting yellow key concepts that you wanted to remember for an exam Amazon Carmen Medical Same thing exactly, can lift key elements and goes from a text blob, too discrete data that has relationship ontology and that allows data sharing where you where you need to. But then there's one of the piece, so that's when you're allowed to disclose there's one of me. Sometimes you and I want to work on something, but we want to actually read act the patient information that allows data sharing as well. So Amazon coming medical also allows you to read, act. Think of when a new challenge shows that federally protected doctor that's blacked out Amazon com for American also remove patient identifying information. So if you and I want to collaborate on research project, you have a set of data that you wanna anonima de identify. I have data information of I D identified. To put it together, I can use Amazon com Medical Read Act All the patient information Make it d identified. You can do the same. And now we can combine the three of us that information to build models, to look a research and to do data sharing. So whether you have full authority to to share patient information and use the ontological portion of it, or whether you want to do the identifying matter, Amazon competent medical helps you do that. >> What's impressive and incredible is that whether we like it or not, there's something a little special about health care where I can decide I'm not going to be on the Internet. Social media things all stop tweeting. Most people would thank me for that, or I can opt out of ride sharing and only take taxis, for example. But we're all sooner or later going to be customers of the health care industry, and as a result, this is some of that effects, all of us, whether we want to acknowledge that or not. I mean, where some of us are still young enough to believe that we have this immortality streak going on. So far, so good. But it becomes clear that this is the sort of thing where the ultimate customer is all of us. As you take a look at that, does that inform how AWS is approaching this entire sector? >> Absolutely. In fact, I'd like to think that a W brought a physician toe lead sector because they understood that in addition to our customer obsession that we see through the customer to the individual and that we want to elevate the human condition we wanted obsess over our customers success so that we can affect positive action on the lives of individuals everywhere. To me, that is a turn. The reason I joined it of U. S s. So that's it. Certainly practice of healthcare Life's I said on genomic Seti ws has been around for about six years. A doubIe s double that. And so actually it's a mature practice and our understanding of our customers definitely includes that core flame that it's about people and each of us come with a special story. In fact, you know the people that work in the U. S. Healthcare life, science team people that have been to the bedside there, people that have been adventure that I worked in the farm industry, healthcare, population, health. They all are there because of that thing you just said. Certainly I'm there because that on the entire practice of self life sciences is keenly aware of looking through the customers to the >> individual pieces. All right, how much? You know, mix, you know, definitely an area where compute storage are critically important than we've seen. Dramatic change. You know, in the last 5 to 10 years, anything specific you could share on that >> Genomics genomex is an area where you need incredible computer storage on. In our case, for example, alumina, which is one of our customers, runs about 85% of all gene sequencing on the planet is in aws customer stores. All that data on AWS. So when you look at genomex, real power of genomics is the fact that enables precision diagnostics. And so when you look at one of our customers, Grail Grail, that uses genomic fragments in the blood that may be coming from cancer and actually sequences that fragment and then on AWS will use the power of the computer to do machine learning on that Gino Mexicans from to determine if you might have one of those 1 10 to 12 cancers that they're currently screening for. And so when you talk to a position health, it really can't be done without position diagnostics, which depends on genomex, which really is an example of that. It runs on AWS because we bring compute and storage essentially infinite power. To do that you want, For example, you know the first whole genome sequence took 14 years. And how many billions of dollars Children's Hospital Philadelphia now does 1000 whole genome sequences in two hours and 20 minutes on AWS, they spike up 20,000 see few cores, do that desi and then moved back down. Genomics. The field that literally can't be. My humble opinion can't be done outside the cloud. It just the mechanics of needed. The storage and compute power is one that is born in the cloud on AWS has those examples that I shared with you. >> It's absolutely fantastic and emerging space, and it's it's interesting to watch that despite the fact there is a regulatory burden that everything was gonna dispute that and the gravity of what it does. I'm not left with sense that feature enhancement and development and velocity of releases is slower somehow in health care than it is across the entire rest of the stack. Is that an accurate assessment, or is there a bit of a drag effect on that? >> Do you mean in the health care customers are on AWS speaking >> on AWS aside, citizen customers are going to be customers. Love them. We >> do aws. You know, we obviously innovation is a rowdy and we release gosh everything. About 2011 we released 80 front service than features and jumped 1015 where it was like 702 jumped 2018. Where was 1957 features? That's like a 25 fold. Our pace of innovation is not going to slow down. It's going to continue. It's in our blood in our d. N. A. We in fact, hire people that are just not satisfied. The status quo on want to innovate and change things. Just, you know, innovation is the beginning of the end of the story, so, no, I don't have to spend any slowdown. In fact, when you add machine learning models on machine learning service that we're putting in? I only see it. An even faster hockey stick of the service is that we're gonna bring out. And I want you to come to reinvent where we're going to announce the mall and you you will be there and see that. All >> right, well, on that note thank you so much for giving us the update on healthcare Life Sciences in genomics. Absolutely. Want to see the continued growth and innovation in that? >> My pleasure. Thank you for having a show. All >> right. For Cory, Queen of Stupid Men. The Cube's coverage never stops either. We, of course, will be at eight of us reinvent this fall as well as many other shows. So, as always, thanks for watching the cue.

>>Hey everyone, welcome to this event, HPE Compute Security. I'm your host, Lisa Martin. Kevin Dee joins me next Senior director, future Surfer Architecture at hpe. Kevin, it's great to have you back on the program. >>Thanks, Lisa. I'm glad to be here. >>One of the topics that we're gonna unpack in this segment is, is all about cybersecurity. And if we think of how dramatically the landscape has changed in the last couple of years, I was looking at some numbers that H P V E had provided. Cybercrime will reach 10.5 trillion by 2025. It's a couple years away. The average total cost of a data breach is now over 4 million, 15% year over year crime growth predicted over the next five years. It's no longer if we get hit, it's when it's how often. What's the severity? Talk to me about the current situation with the cybersecurity landscape that you're seeing. >>Yeah, I mean the, the numbers you're talking about are just staggering and then that's exactly what we're seeing and that's exactly what we're hearing from our customers is just absolutely key. Customers have too much to lose. The, the dollar cost is just, like I said, staggering. And, and here at HP we know we have a huge part to play, but we also know that we need partnerships across the industry to solve these problems. So we have partnered with, with our, our various partners to deliver these Gen 11 products. Whether we're talking about partners like a M D or partners like our Nick vendors, storage card vendors. We know we can't solve the problem alone. And we know this, the issue is huge. And like you said, the numbers are staggering. So we're really, we're really partnering with, with all the right players to ensure we have a secure solution so we can stay ahead of the bad guys to try to limit the, the attacks on our customers. >>Right. Limit the damage. What are some of the things that you've seen particularly change in the last 18 months or so? Anything that you can share with us that's eye-opening, more eye-opening than some of the stats we already shared? >>Well, there, there's been a massive number of attacks just in the last 12 months, but I wouldn't really say it's so much changed because the amount of attacks has been increasing dramatically over the years for many, many, many years. It's just a very lucrative area for the bad guys, whether it's ransomware or stealing personal data, whatever it is, it's there. There's unfortunately a lot of money to be made into it, made from it, and a lot of money to be lost by the good guys, the good guys being our customers. So it's not so much that it's changed, it's just that it's even accelerating faster. So the real change is, it's accelerating even faster because it's becoming even more lucrative. So we have to stay ahead of these bad guys. One of the statistics of Microsoft operating environments, the number of tax in the last year, up 50% year over year, that's a huge acceleration and we've gotta stay ahead of that. We have to make sure our customers don't get impacted to the level that these, these staggering number of attacks are. The, the bad guys are out there. We've gotta protect, protect our customers from the bad guys. >>Absolutely. The acceleration that you talked about is, it's, it's kind of frightening. It's very eye-opening. We do know that security, you know, we've talked about it for so long as a, as a a C-suite priority, a board level priority. We know that as some of the data that HPE e also sent over organizations are risking are, are listing cyber risks as a top five concern in their organization. IT budgets spend is going up where security is concerned. And so security security's on everyone's mind. In fact, the cube did, I guess in the middle part of last, I did a series on this really focusing on cybersecurity as a board issue and they went into how companies are structuring security teams changing their assumptions about the right security model, offense versus defense. But security's gone beyond the board, it's top of mind and it's on, it's in an integral part of every conversation. So my question for you is, when you're talking to customers, what are some of the key challenges that they're saying, Kevin, these are some of the things the landscape is accelerating, we know it's a matter of time. What are some of those challenges and that they're key pain points that they're coming to you to help solve? >>Yeah, at the highest level it's simply that security is incredibly important to them. We talked about the numbers. There's so much money to be lost that what they come to us and say, is security's important for us? What can you do to protect us? What can you do to prevent us from being one of those statistics? So at a high level, that's kind of what we're seeing at a, with a little more detail. We know that there's customers doing digital transformations. We know that there's customers going hybrid cloud, they've got a lot of initiatives on their own. They've gotta spend a lot of time and a lot of bandwidth tackling things that are important to their business. They just don't have the bandwidth to worry about yet. Another thing which is security. So we are doing everything we can and partnering with everyone we can to help solve those problems for customers. >>Cuz we're hearing, hey, this is huge, this is too big of a risk. How do you protect us? And by the way, we only have limited bandwidth, so what can we do? What we can do is make them assured that that platform is secure, that we're, we are creating a foundation for a very secure platform and that we've worked with our partners to secure all the pieces. So yes, they still have to worry about security, but there's pieces that we've taken care of that they don't have to worry about and there's capabilities that we've provided that they can use and we've made that easy so they can build su secure solutions on top of it. >>What are some of the things when you're in customer conversations, Kevin, that you talk about with customers in terms of what makes HPE E'S approach to security really unique? >>Well, I think a big thing is security is part of our, our dna. It's part of everything we do. Whether we're designing our own asics for our bmc, the ilo ASIC ILO six used on Gen 11, or whether it's our firmware stack, the ILO firmware, our our system, UFI firmware, all those pieces in everything we do. We're thinking about security. When we're building products in our factory, we're thinking about security. When we're think designing our supply chain, we're thinking about security. When we make requirements on our suppliers, we're driving security to be a key part of those components. So security is in our D N a security's top of mind. Security is something we think about in everything we do. We have to think like the bad guys, what could the bad guy take advantage of? What could the bad guy exploit? So we try to think like them so that we can protect our customers. >>And so security is something that that really is pervasive across all of our development organizations, our supply chain organizations, our factories, and our partners. So that's what we think is unique about HPE is because security is so important and there's a whole lot of pieces of our reliance servers that we do ourselves that many others don't do themselves. And since we do it ourselves, we can make sure that security's in the design from the start, that those pieces work together in a secure manner. So we think that gives us a, an advantage from a security standpoint. >>Security is very much intention based at HPE e I was reading in some notes, and you just did a great job of talking about this, that fundamental security approach, security is fundamental to defend against threats that are increasingly complex through what you also call an uncompromising focus to state-of-the-art security and in in innovations built into your D N A. And then organizations can protect their infrastructure, their workloads, their data from the bad guys. Talk to us briefly in our final few minutes here, Kevin, about fundamental uncompromising protected the value in it for me as an HPE customer. >>Yeah, when we talk about fundamental, we're talking about the those fundamental technologies that are part of our platform. Things like we've integrated TPMS and sorted them down in our platforms. We now have platform certificates as a standard part of the platform. We have I dev id and probably most importantly, our platforms continue to support what we really believe was a groundbreaking technology, Silicon Root of trust and what that's able to do. We have millions of lines of firmware code in our platforms and with Silicon Root of trust, we can authenticate all of those lines of firmware. Whether we're talking about the the ILO six firmware, our U E I firmware, our C P L D in the system, there's other pieces of firmware. We authenticate all those to make sure that not a single line of code, not a single bit has been changed by a bad guy, even if the bad guy has physical access to the platform. >>So that silicon route of trust technology is making sure that when that system boots off and that hands off to the operating system and then eventually the customer's application stack that it's starting with a solid foundation, that it's starting with a system that hasn't been compromised. And then we build other things into that silicon root of trust, such as the ability to do the scans and the authentications at runtime, the ability to automatically recover if we detect something has been compromised, we can automatically update that compromised piece of firmware to a good piece before we've run it because we never want to run firmware that's been compromised. So that's all part of that Silicon Root of Trust solution and that's a fundamental piece of the platform. And then when we talk about uncompromising, what we're really talking about there is how we don't compromise security. >>And one of the ways we do that is through an extension of our Silicon Root of trust with a capability called S Spdm. And this is a technology that we saw the need for, we saw the need to authenticate our option cards and the firmware in those option cards. Silicon Root Prota, Silicon Root Trust protects against many attacks, but one piece it didn't do is verify the actual option card firmware and the option cards. So we knew to solve that problem we would have to partner with others in the industry, our nick vendors, our storage controller vendors, our G vendors. So we worked with industry standards bodies and those other partners to design a capability that allows us to authenticate all of those devices. And we worked with those vendors to get the support both in their side and in our platform side so that now Silicon Rivers and trust has been extended to where we protect and we trust those option cards as well. >>So that's when, when what we're talking about with Uncompromising and with with Protect, what we're talking about there is our capabilities around protecting against, for example, supply chain attacks. We have our, our trusted supply chain solution, which allows us to guarantee that our server, when it leaves our factory, what the server is, when it leaves our factory, will be what it is when it arrives at the customer. And if a bad guy does anything in that transition, the transit from our factory to the customer, they'll be able to detect that. So we enable certain capabilities by default capability called server configuration lock, which can ensure that nothing in the server exchange, whether it's firmware, hardware, configurations, swapping out processors, whatever it is, we'll detect if a bad guy did any of that and the customer will know it before they deploy the system. That gets enabled by default. >>We have an intrusion detection technology option when you use by the, the trusted supply chain that is included by default. That lets you know, did anybody open that system up, even if the system's not plugged in, did somebody take the hood off and potentially do something malicious to it? We also enable a capability called U EFI secure Boot, which can go authenticate some of the drivers that are located on the option card itself. Those kind of capabilities. Also ilo high security mode gets enabled by default. So all these things are enabled in the platform to ensure that if it's attacked going from our factory to the customer, it will be detected and the customer won't deploy a system that's been maliciously attacked. So that's got >>It, >>How we protect the customer through those capabilities. >>Outstanding. You mentioned partners, my last question for you, we've got about a minute left, Kevin is bring AMD into the conversation, where do they fit in this >>AMD's an absolutely crucial partner. No one company even HP can do it all themselves. There's a lot of partnerships, there's a lot of synergies working with amd. We've been working with AMD for almost 20 years since we delivered our first AM MD base ProLiant back in 2004 H HP ProLiant, DL 5 85. So we've been working with them a long time. We work with them years ahead of when a processor is announced, we benefit each other. We look at their designs and help them make their designs better. They let us know about their technology so we can take advantage of it in our designs. So they have a lot of security capabilities, like their memory encryption technologies, their a MD secure processor, their secure encrypted virtualization, which is an absolutely unique and breakthrough technology to protect virtual machines and hypervisor environments and protect them from malicious hypervisors. So they have some really great capabilities that they've built into their processor, and we also take advantage of the capabilities they have and ensure those are used in our solutions and in securing the platform. So a really such >>A great, great partnership. Great synergies there. Kevin, thank you so much for joining me on the program, talking about compute security, what HPE is doing to ensure that security is fundamental, that it is unpromised and that your customers are protected end to end. We appreciate your insights, we appreciate your time. >>Thank you very much, Lisa. >>We've just had a great conversation with Kevin Depu. Now I get to talk with David Chang, data center solutions marketing lead at a md. David, welcome to the program. >>Thank, thank you. And thank you for having me. >>So one of the hot topics of conversation that we can't avoid is security. Talk to me about some of the things that AMD is seeing from the customer's perspective, why security is so important for businesses across industries. >>Yeah, sure. Yeah. Security is, is top of mind for, for almost every, every customer I'm talking to right now. You know, there's several key market drivers and, and trends, you know, in, out there today that's really needing a better and innovative solution for, for security, right? So, you know, the high cost of data breaches, for example, will cost enterprises in downtime of, of the data center. And that time is time that you're not making money, right? And potentially even leading to your, to the loss of customer confidence in your, in your cust in your company's offerings. So there's real costs that you, you know, our customers are facing every day not being prepared and not having proper security measures set up in the data center. In fact, according to to one report, over 400 high-tech threats are being introduced every minute. So every day, numerous new threats are popping up and they're just, you know, the, you know, the bad guys are just getting more and more sophisticated. So you have to take, you know, measures today and you have to protect yourself, you know, end to end with solutions like what a AM MD and HPE has to offer. >>Yeah, you talked about some of the costs there. They're exorbitant. I've seen recent figures about the average, you know, cost of data breacher ransomware is, is close to, is over $4 million, the cost of, of brand reputation you brought up. That's a great point because nobody wants to be the next headline and security, I'm sure in your experiences. It's a board level conversation. It's, it's absolutely table stakes for every organization. Let's talk a little bit about some of the specific things now that A M D and HPE E are doing. I know that you have a really solid focus on building security features into the EPIC processors. Talk to me a little bit about that focus and some of the great things that you're doing there. >>Yeah, so, you know, we partner with H P E for a long time now. I think it's almost 20 years that we've been in business together. And, and you know, we, we help, you know, we, we work together design in security features even before the silicons even, you know, even born. So, you know, we have a great relationship with, with, with all our partners, including hpe and you know, HPE has, you know, an end really great end to end security story and AMD fits really well into that. You know, if you kind of think about how security all started, you know, in, in the data center, you, you've had strategies around encryption of the, you know, the data in, in flight, the network security, you know, you know, VPNs and, and, and security on the NS. And, and even on the, on the hard drives, you know, data that's at rest. >>You know, encryption has, you know, security has been sort of part of that strategy for a a long time and really for, you know, for ages, nobody really thought about the, the actual data in use, which is, you know, the, the information that's being passed from the C P U to the, the, the memory and, and even in virtualized environments to the, the, the virtual machines that, that everybody uses now. So, you know, for a long time nobody really thought about that app, you know, that third leg of, of encryption. And so a d comes in and says, Hey, you know, this is things that as, as the bad guys are getting more sophisticated, you, you have to start worrying about that, right? And, you know, for example, you know, you know, think, think people think about memory, you know, being sort of, you know, non-persistent and you know, when after, you know, after a certain time, the, the, you know, the, the data in the memory kind of goes away, right? >>But that's not true anymore because even in in memory data now, you know, there's a lot of memory modules that still can retain data up to 90 minutes even after p power loss. And with something as simple as compressed, compressed air or, or liquid nitrogen, you can actually freeze memory dams now long enough to extract the data from that memory module for up, you know, up, up to two or three hours, right? So lo more than enough time to read valuable data and, and, and even encryption keys off of that memory module. So our, our world's getting more complex and you know, more, the more data out there, the more insatiable need for compute and storage. You know, data management is becoming all, all the more important, you know, to keep all of that going and secure, you know, and, and creating security for those threats. It becomes more and more important. And, and again, especially in virtualized environments where, you know, like hyperconverged infrastructure or vir virtual desktop memories, it's really hard to keep up with all those different attacks, all those different attack surfaces. >>It sounds like what you were just talking about is what AMD has been able to do is identify yet another vulnerability Yes. Another attack surface in memory to be able to, to plug that hole for organizations that didn't, weren't able to do that before. >>Yeah. And, you know, and, and we kind of started out with that belief that security needed to be scalable and, and able to adapt to, to changing environments. So, you know, we, we came up with, you know, the, you know, the, the philosophy or the design philosophy that we're gonna continue to build on those security features generational generations and stay ahead of those evolving attacks. You know, great example is in, in the third gen, you know, epic C P U, that family that we had, we actually created this feature called S E V S N P, which stands for SECURENESS Paging. And it's really all around this, this new attack where, you know, your, the, the, you know, it's basically hypervisor based attacks where people are, you know, the bad actors are writing in to the memory and writing in basically bad data to corrupt the mem, you know, to corrupt the data in the memory. So s e V S and P is, was put in place to help, you know, secure that, you know, before that became a problem. And, you know, you heard in the news just recently that that becoming a more and more, more of a bigger issue. And the great news is that we had that feature built in, you know, before that became a big problem. >>And now you're on the fourth gen, those epic crosses talk of those epic processes. Talk to me a little bit about some of the innovations that are now in fourth gen. >>Yeah, so in fourth gen we actually added, you know, on top of that. So we've, we've got, you know, the sec the, the base of our, our, what we call infinity guard is, is all around the secure boot. The, you know, the, the, the, the secure root of trust that, you know, that we, we work with HPE on the, the strong memory encryption and the S E V, which is the secure encrypted virtualization. And so remember those s s and p, you know, incap capabilities that I talked about earlier. We've actually, in the fourth gen added two x the number of sev v s and P guests for even higher number of confidential VMs to support even more customers than before. Right? We've also added more guest protection from simultaneous multi threading or S M T side channel attacks. And, you know, while it's not officially part of Infinity Guard, we've actually added more APEC acceleration, which greatly benefits the security of those confidential VMs with the larger number of VCPUs, which basically means that you can build larger VMs and still be secured. And then lastly, we actually added even stronger a e s encryption. So we went from 128 bit to 256 bit, which is now military grade encryption on top of that. And, you know, and, and that's really, you know, the de facto crypto cryptography that is used for most of the applications for, you know, customers like the US federal government and, and all, you know, the, is really an essential element for memory security and the H B C applications. And I always say if it's good enough for the US government, it's good enough for you. >>Exactly. Well, it's got to be, talk a little bit about how AMD is doing this together with HPE a little bit about the partnership as we round out our conversation. >>Sure, absolutely. So security is only as strong as the layer below it, right? So, you know, that's why modern security must be built in rather than, than, you know, bolted on or, or, or, you know, added after the fact, right? So HPE and a MD actually developed this layered approach for protecting critical data together, right? Through our leadership and, and security features and innovations, we really deliver a set of hardware based features that, that help decrease potential attack surfaces. With, with that holistic approach that, you know, that safeguards the critical information across system, you know, the, the entire system lifecycle. And we provide the confidence of built-in silicon authentication on the world's most secure industry standard servers. And with a 360 degree approach that brings high availability to critical workloads while helping to defend, you know, against internal and external threats. So things like h hp, root of silicon root of trust with the trusted supply chain, which, you know, obviously AMD's part of that supply chain combined with AMD's Infinity guard technology really helps provide that end-to-end data protection in today's business. >>And that is so critical for businesses in every industry. As you mentioned, the attackers are getting more and more sophisticated, the vulnerabilities are increasing. The ability to have a pa, a partnership like H P E and a MD to deliver that end-to-end data protection is table stakes for businesses. David, thank you so much for joining me on the program, really walking us through what am MD is doing, the the fourth gen epic processors and how you're working together with HPE to really enable security to be successfully accomplished by businesses across industries. We appreciate your insights. >>Well, thank you again for having me, and we appreciate the partnership with hpe. >>Well, you wanna thank you for watching our special program HPE Compute Security. I do have a call to action for you. Go ahead and visit hpe com slash security slash compute. Thanks for watching.

>>Welcome to the Cube's Continuing coverage of AMD's fourth generation Epic launch. I'm Dave Nicholson and I'm joining you here in our Palo Alto Studios. We have two very interesting guests to dive into some of the announcements that have been made and maybe take a look at this from an AI and ML perspective. Our first guest is Milland Doley. He's a senior director for software and solutions at amd, and we're also joined by Shamus Jones, who's a director of server engineering at Dell Technologies. Welcome gentlemen. How are you? >>Very good, thank >>You. Welcome to the Cube. So let's start out really quickly, Shamus, what, give us a thumbnail sketch of what you do at Dell. >>Yeah, so I'm the director of technical marketing engineering here at Dell, and our team really takes a look at the technical server portfolio and solutions and ensures that we can look at, you know, the performance metrics, benchmarks, and performance characteristics, so that way we can give customers a good idea of what they can expect from the server portfolio when they're looking to buy Power Edge from Dell. >>Milland, how about you? What's, what's new at a M D? What do you do there? >>Great to be here. Thank you for having me at amd, I'm the senior director of performance engineering and ISV ecosystem enablement, which is a long winter way of saying we do a lot of benchmarks, improved performance and demonstrate with wonderful partners such as Shamus and Dell, the combined leverage that AMD four generation processes and Dell systems can bring to bear on a multitude of applications across the industry spectrum. >>Shamus, talk about that relationship a little bit more. The relationship between a M D and Dell. How far back does it go? What does it look like in practical terms? >>Absolutely. So, you know, ever since AM MD reentered the server space, we've had a very close relationship. You know, it's one of those things where we are offering solutions that are out there to our customers no matter what generation A portfolio, if they're, if they're demanding either from their competitor or a m d, we offer a portfolio solutions that are out there. What we're finding is that within their generational improvements, they're just getting better and better and better. Really exciting things happening from a m D at the moment, and we're seeing that as we engineer those CPU stacks into our, our server portfolio, you know, we're really seeing unprecedented performance across the board. So excited about the, the history, you know, my team and Lin's team work very closely together, so much so that we were communicating almost on a daily basis around portfolio platforms and updates around the, the, the benchmarks testing and, and validation efforts. >>So Melind, are you happy with these PowerEdge boxes that Seamus is building to, to house, to house your baby? >>We are delighted, you know, it's hard to find stronger partners than Shamus and Dell with AMD's, second generation epic service CPUs. We already had undisputable industry performance leadership, and then with the third and now the fourth generation CPUs, we've just increased our lead with competition. We've got so many outstanding features at the platform, at the CPU level, everybody focuses on the high core counts, but there's also the DDR five, the memory, the io, and the storage subsystem. So we believe we have a fantastic performance and performance per dollar performance per what edge over competition, and we look to partners such as Dell to help us showcase that leadership. >>Well. So Shay Yeah, through Yeah, go ahead >>Dave. What, what I'd add, Dave, is that through the, the partnership that we've had, you know, we've been able to develop subsystems and platform features that historically we couldn't have really things around thermals power efficiency and, and efficiency within the platform. That means that customers can get the most out of their compute infrastructure. >>So this is gonna be a big question moving forward as next generation platforms are rolled out, there's the potential for people to have sticker shock. You talk about something that has eight or 12 cores in a, in a physical enclosure versus 96 cores, and, and I guess the, the question is, do the ROI and TCO numbers look good for someone to make that upgrade? Shamus, you wanna, you wanna hit that first or you guys are integrated? >>Absolutely, yeah, sorry. Absolutely. So we, I'll tell you what, at the moment, customers really can't afford not to upgrade at the moment, right? We've taken a look at the cost basis of keeping older infrastructure in place, let's say five or seven year old infrastructure servers that are, that are drawing more power maybe are, are poorly utilized within the infrastructure and take more and more effort and time to manage, maintain and, and really keep in production. So as customers look to upgrade or refresh their platforms, what we're finding right is that they can take a dynamic consolidation sometimes 5, 7, 8 to one consolidation depending on which platform they have as a historical and which one they're looking to upgrade to. Within AI specifically and machine learning frameworks, we're seeing really unprecedented performance. Lin's team partnered with us to deliver multiple benchmarks for the launch, some of which we're still continuing to see the goodness from things like TP C X AI as a framework, and I'm talking about here specifically the CPU U based performance. >>Even though in a lot of those AI frameworks, you would also expect to have GPUs, which all of the four platforms that we're offering on the AM MD portfolio today offer multiple G P U offerings. So we're seeing a balance between a huge amount of C P U gain and performance, as well as more and more GPU offerings within the platform. That was real, that was a real challenge for us because of the thermal challenges. I mean, you think GPUs are going up 300, 400 watt, these CPUs at 96 core are, are quite demanding thermally, but what we're able to do is through some, some unique smart cooling engineering within the, the PowerEdge portfolio, we can take a look at those platforms and make the most efficient use case by having things like telemetry within the platform so that way we can dynamically change fan speeds to get customers the best performance without throttling based on their need. >>Melin the cube was at the Supercomputing conference in Dallas this year, supercomputing conference 2022, and a lot of the discussion was around not only advances in microprocessor technology, but also advances in interconnect technology. How do you manage that sort of research partnership with Dell when you aren't strictly just focusing on the piece that you are bringing to the party? It's kind of a potluck, you know, we, we, we, we mentioned P C I E Gen five or 5.0, whatever you want to call it, new DDR storage cards, Nicks, accelerators, all of those, all of those things. How do you keep that straight when those aren't things that you actually build? >>Well, excellent question, Dave. And you know, as we are developing the next platform, obviously the, the ongoing relationship is there with Dell, but we start way before launch, right? Sometimes it's multiple years before launch. So we are not just focusing on the super high core counts at the CPU level and the platform configurations, whether it's single socket or dual socket, we are looking at it from the memory subsystem from the IO subsystem, P c i lanes for storage is a big deal, for example, in this generation. So it's really a holistic approach. And look, core counts are, you know, more important at the higher end for some customers h HPC space, some of the AI applications. But on the lower end you have database applications or some other is s v applications that care a lot about those. So it's, I guess different things matter to different folks across verticals. >>So we partnered with Dell very early in the cycle, and it's really a joint co-engineering. Shamus talked about the focus on AI with TP C X xci, I, so we set five world records in that space just on that one benchmark with AD and Dell. So fantastic kick kick off to that across a multitude of scale factors. But PPP c Xci is not just the only thing we are focusing on. We are also collaborating with Dell and des e i on some of the transformer based natural language processing models that we worked on, for example. So it's not just a steep CPU story, it's CPU platform, es subsystem software and the whole thing delivering goodness across the board to solve end user problems in AI and and other verticals. >>Yeah, the two of you are at the tip of the spear from a performance perspective. So I know it's easy to get excited about world records and, and they're, they're fantastic. I know Shamus, you know, that, you know, end user customers might, might immediately have the reaction, well, I don't need a Ferrari in my data center, or, you know, what I need is to be able to do more with less. Well, aren't we delivering that also? And you know, you imagine you milland you mentioned natural, natural language processing. Shamus, are you thinking in 2023 that a lot more enterprises are gonna be able to afford to do things like that? I mean, what are you hearing from customers on this front? >>I mean, while the adoption of the top bin CPU stack is, is definitely the exception, not the rule today we are seeing marked performance, even when we look at the mid bin CPU offerings from from a m d, those are, you know, the most common sold SKUs. And when we look at customers implementations, really what we're seeing is the fact that they're trying to make the most, not just of dollar spend, but also the whole subsystem that Melin was talking about. You know, the fact that balanced memory configs can give you marked performance improvements, not just at the CPU level, but as actually all the way through to the, to the application performance. So it's, it's trying to find the correct balance between the application needs, your budget, power draw and infrastructure within the, the data center, right? Because not only could you, you could be purchasing and, and look to deploy the most powerful systems, but if you don't have an infrastructure that's, that's got the right power, right, that's a large challenge that's happening right now and the right cooling to deal with the thermal differences of the systems, might you wanna ensure that, that you can accommodate those for not just today but in the future, right? >>So it's, it's planning that balance. >>If I may just add onto that, right? So when we launched, not just the fourth generation, but any generation in the past, there's a natural tendency to zero in on the top bin and say, wow, we've got so many cores. But as Shamus correctly said, it's not just that one core count opn, it's, it's the whole stack. And we believe with our four gen CPU processor stack, we've simplified things so much. We don't have, you know, dozens and dozens of offerings. We have a fairly simple skew stack, but we also have a very efficient skew stack. So even, even though at the top end we've got 96 scores, the thermal budget that we require is fairly reasonable. And look, with all the energy crisis going around, especially in Europe, this is a big deal. Not only do customers want performance, but they're also super focused on performance per want. And so we believe with this generation, we really delivered not just on raw performance, but also on performance per dollar and performance per one. >>Yeah. And it's not just Europe, I'm, we're, we are here in Palo Alto right now, which is in California where we all know the cost of an individual kilowatt hour of electricity because it's quite, because it's quite high. So, so thermals, power cooling, all of that, all of that goes together and that, and that drives cost. So it's a question of how much can you get done per dollar shame as you made the point that you, you're not, you don't just have a one size fits all solution that it's, that it's fit for function. I, I'm, I'm curious to hear from you from the two of you what your thoughts are from a, from a general AI and ML perspective. We're starting to see right now, if you hang out on any kind of social media, the rise of these experimental AI programs that are being presented to the public, some will write stories for you based on prom, some will create images for you. One of the more popular ones will create sort of a, your superhero alter ego for, I, I can't wait to do it, I just got the app on my phone. So those are all fun and they're trivial, but they sort of get us used to this idea that, wow, these systems can do things. They can think on their own in a certain way. W what do, what do you see the future of that looking like over the next year in terms of enterprises, what they're going to do for it with it >>Melan? Yeah, I can go first. Yeah, yeah, yeah, yeah, >>Sure. Yeah. Good. >>So the couple of examples, Dave, that you mentioned are, I, I guess it's a blend of novelty and curiosity. You know, people using AI to write stories or poems or, you know, even carve out little jokes, check grammar and spelling very useful, but still, you know, kind of in the realm of novelty in the mainstream, in the enterprise. Look, in my opinion, AI is not just gonna be a vertical, it's gonna be a horizontal capability. We are seeing AI deployed across the board once the models have been suitably trained for disparate functions ranging from fraud detection or anomaly detection, both in the financial markets in manufacturing to things like image classification or object detection that you talked about in, in the sort of a core AI space itself, right? So we don't think of AI necessarily as a vertical, although we are showcasing it with a specific benchmark for launch, but we really look at AI emerging as a horizontal capability and frankly, companies that don't adopt AI on a massive scale run the risk of being left behind. >>Yeah, absolutely. There's an, an AI as an outcome is really something that companies, I, I think of it in the fact that they're adopting that and the frameworks that you're now seeing as the novelty pieces that Melin was talking about is, is really indicative of the under the covers activity that's been happening within infrastructures and within enterprises for the past, let's say 5, 6, 7 years, right? The fact that you have object detection within manufacturing to be able to, to be able to do defect detection within manufacturing lines. Now that can be done on edge platforms all the way at the device. So you're no longer only having to have things be done, you know, in the data center, you can bring it right out to the edge and have that high performance, you know, inferencing training models. Now, not necessarily training at the edge, but the inferencing models especially, so that way you can, you know, have more and, and better use cases for some of these, these instances things like, you know, smart cities with, with video detection. >>So that way they can see, especially during covid, we saw a lot of hospitals and a lot of customers that were using using image and, and spatial detection within their, their video feeds to be able to determine who and what employees were at risk during covid. So there's a lot of different use cases that have been coming around. I think the novelty aspect of it is really interesting and I, I know my kids, my daughters love that, that portion of it, but really what's been happening has been exciting for quite a, quite a period of time in the enterprise space. We're just now starting to actually see those come to light in more of a, a consumer relevant kind of use case. So the technology that's been developed in the data center around all of these different use cases is now starting to feed in because we do have more powerful compute at our fingertips. We do have the ability to talk more about the framework and infrastructure that's that's right out at the edge. You know, I know Dave in the past you've said things like the data center of, you know, 20 years ago is now in my hand as, as my cell phone. That's right. And, and that's, that's a fact and I'm, it's exciting to think where it's gonna be in the next 10 or 20 years. >>One terabyte baby. Yeah. One terabyte. Yeah. It's mind bo. Exactly. It's mind boggling. Yeah. And it makes me feel old. >>Yeah, >>Me too. And, and that and, and Shamus, that all sounded great. A all I want is a picture of me as a superhero though, so you guys are already way ahead of the curve, you know, with, with, with that on that note, Seamus wrap us up with, with a, with kind of a summary of the, the highlights of what we just went through in terms of the performance you're seeing out of this latest gen architecture from a md. >>Absolutely. So within the TPC xai frameworks that Melin and my team have worked together to do, you know, we're seeing unprecedented price performance. So the fact that you can get 220% uplift gen on gen for some of these benchmarks and, you know, you can have a five to one consolidation means that if you're looking to refresh platforms that are historically legacy, you can get a, a huge amount of benefit, both in reduction in the number of units that you need to deploy and the, the amount of performance that you can get per unit. You know, Melinda had mentioned earlier around CPU performance and performance per wat, specifically on the Tu socket two U platform using the fourth generation a m d Epic, you know, we're seeing a 55% higher C P U performance per wat that is that, you know, when for people who aren't necessarily looking at these statistics, every generation of servers, that that's, that is a huge jump leap forward. >>That combined with 121% higher spec scores, you know, as a benchmark, those are huge. Normally we see, let's say a 40 to 60% performance improvement on the spec benchmarks, we're seeing 121%. So while that's really impressive at the top bin, we're actually seeing, you know, large percentile improvements across the mid bins as well, you know, things in the range of like 70 to 90% performance improvements in those standard bins. So it, it's a, it's a huge performance improvement, a power efficiency, which means customers are able to save energy, space and time based on, on their deployment size. >>Thanks for that Shamus, sadly, gentlemen, our time has expired. With that, I want to thank both of you. It's a very interesting conversation. Thanks for, thanks for being with us, both of you. Thanks for joining us here on the Cube for our coverage of AMD's fourth generation Epic launch. Additional information, including white papers and benchmarks plus editorial coverage can be found on does hardware matter.com.

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

>>Mm. Welcome back to the cubes. Continuous coverage of A W s reinvent 2021 were running one of the industry's most important and largest hybrid tech events of the year with A W S and its ecosystem partners. And, of course, special thanks to a M D for supporting this year's editorial coverage at the event we got to live sets we had to remote sets one in Boston, one in Palo Alto. We've got more than 100 guests coming on the programme and we're looking >>deep into >>the next decade of cloud innovation. We're super excited to be joined by Ali Zafar, who is the senior director of platform strategy and operations at Dropbox Ali. Great to see you. Thanks for coming on. >>Awesome. It's a pleasure to be here with you, Dave. >>So Hey, what's your day job like at Dropbox? What's your role? >>Got it? Yeah. So I actually oversee the global supply chain at Dropbox. Also all of the capacity planning which entails both our budget and also capacity requirements and Dropbox. And then I also focus on the platform product management side which is basically building our build vs buy and our overall roadmap for our platform in the long run. >>Great. Thank you. So I mean, everybody knows Dropbox, But maybe you can talk a little bit about your business, your mission and how that's evolved. Over the past several years. >>Dropbox is a global collaboration platform, and our mission at Dropbox is to help design a more enlightened way of working. Dropbox has over 700 million registered users and over 550 billion pieces of content. So taking a step back, they've dropbox health. Let's use all of your content. Think of this as videos as music. Even your tax returns allows you to organise all of this content. And then you can share this content with anybody at any time. You can also take Dropbox to work. And actually, it makes you even more productive in the workplace integrating all of your tools seamlessly, also allowing you to collaborate with all of your teams internally and also externally. >>Yeah, so thank you. Uh, when Dropbox was founded, I mean, the cloud was really nascent, right? So it was early days, and so a lot has changed since you know, the mid last decade. And of course, with remote work and hybrid work that had to be a real tailwind to your business. But maybe you could explain your cloud and your hybrid cloud strategy. >>You're spot on Dave. So Dropbox has always been hybrid since its inception in 2000 and seven. And when I say hybrid, I mean, we have our own on prime infrastructure, and then we also leverage Public Cloud. Now, Public cloud still to these days remains absolutely critical for Dropbox to serve all of its customer needs. And when we talk about the decision between public or private, we think about three or four key things. One is the total cost of ownership. Look at the market. We also look at our customer requirements and the latest technology that's available in the market and then any international data storage requirements to make the decision of going towards public or private for that specific use case. >>So what if we could follow up on that? Like maybe you can talk about the key business, these conditions as a as a SAS storage provider? What are the real drivers in in your business framework? >>Got it at the end of the day, what really matters for us. There is to actually think about our customers and delight them And what better than to focus on performance, reliability and also security. Right. So we want to make sure that the infrastructure that we have today allows Dropbox to actually solve for the specific use case for our customers. What do they care about while also doing this in a very efficient management Manage, uh, way So to summarise that looking at performance, looking at liability, looking at scalability, looking at efficiency and then also compliance >>So that leads me to My next question is about the EC two instances that you use. I know you. You make heavy use of AMG compute. How >>did you >>come to that decision? Was that these factors was all performance. How did you migrate to really enable that capability? How complex was that? >>MD has has been a key strategic partners the partnership as well over 4 to 5 years right now and we've been leveraging them on our on prem infrastructure for compute. So we've always had aimed in our infrastructure. And when the time came where aws was also leveraging some of the MD instances, we wanted to see how we can expand the partnership with AMG and A W S and also experiment with these instances. So we looked at some of the tooling updates that were required. We also looked at specific instances which are either compute optimised and memory optimised instances. And then we actually build our footprint on M D. And what we saw is that the overall performance improvements and also cost improvements that we got for specific workloads. It was actually extremely, uh, overall awesome results for Dropbox and our customers, and we have been using them ever since. >>What kind of business impact did that make that make a difference to your business? That was noticeable >>on the business side, I think primarily it was more on the TCO side, which is where we got most of the benefits on the cost side. Um, and then also for some of our internal work clothes, we also saw benefit, uh, to our internal developers that are using some of those work clothes. >>Well, so you guys have kind of become the poster child for hybrid. A lot has been talked about about you all, but I wonder if you could help us understand what part of your infrastructure is going to be better served by public cloud versus kind of doing your own. I t on Prem. What are some of the value drivers that are that are making, you know, push workloads into the public cloud? Help us understand that better and squint through that >>got ready. I get asked that question a lot. So public cloud in general allows for faster go to market, Think about this as, like product launches teacher launches also international expansion. It allows us to scale and then also leveraging some of the existing technologies out there in the market for some of the common workloads. So just, you know, taking a step back and thinking about Dropbox. We keep on evaluating also the criteria and then also specific workloads on what makes sense on private or public load. And a W s had some instances, like as three rds and EC to that when we started looking at, we knew that some of our key services, like data platform, some parts of our, um, Melania and even paper platform would make more sense for us to actually leverage. Uh, some of these in public cloud for that. >>So what are the sort of characteristics of the workload that are sort of better suited to be in AWS? You know, what's the ideal workload profile? You know, we talk about ideal customer profile. What's the ideal workload profile for the for the AWS Cloud. >>Got it. So the way we think about it, at least we call it the rule of three at Dropbox. Um, and that means we look at scale. First, we look at technology and innovation. Um, and what I mean by that is, is there faster innovation in the public cloud? And is the workload common enough that there's already a lot of work going on in public Cloud? Then there's no reason for us to actually innovate faster than that. We probably can't. And if the scale is not large enough, right? So when we talk about our storage side like magic pocket, the scale is large enough. We're innovating. There makes sense, and it's better for the end customer, so we will probably go towards private cloud there. But then, when we talk about like international expansion, when we talk about, like, faster go to market or some of the innovation in the space. It really makes sense to use public Cloud because of all of the advancements that we've seen there. >>Yeah, so let me circle back to the sort of business benefits and impact of the sort of a MD based compute specifically. But you talked about TCO before. So there's certain things you mentioned on Prem you sometimes use You mean right. If the thing is hardened, you don't want to necessarily rip and replace it. But if you can accelerate, go to market and you spin up things in the cloud that makes sense. You mentioned customer requirements. So that's just kind of depends. And then the international expansion and scale. So it kind of comes down to those whatever. Four or five factors, right? Tco those other factors that I mentioned kind of the high level benefits, if you could, wouldn't mind summarising for us. Ali. >>Yeah, I think you're spot on there. So it's looking at the overall Decio, right? The cost of serving the overall cloud looking at like go to market in general, like can we leverage public cloud and go to market faster? Obviously, meeting that end customer requirements. We also looked at like international expansion, like any of the customer's data that is stored outside of the US is all on public load for Dropbox. Uh, no plans in the short term to do something different there, Um and then also just looking at, like I mentioned anything in the technology space that is ongoing, that we can leverage features side or the product side for our customers, like at Yale or, uh, VRML. We are going to leverage Public cloud there. >>So of course you know we've we've followed the progression of semiconductor technology for decades. This industry has marched to the cadence of performance improvements. What are the one of the futures hold from a technology roadmap standpoint, particularly as it relates to leveraging AMG EC Two instances, Ali >>got it. So drop boxes in a very unique position where we actually leverage AMG both on Prem and for public le leveraging some of the AWS EC two instances like like you mentioned and epic processors from MDR what we're using today, both on the hybrid infrastructure site and the performance and also the d. C o benefits are real and something that we are observing on a day to day basis. So we are gonna be leveraging that technology even in the future. Um, and the partnership with the MD continues to be very, very strong for Dropbox. >>Well, I really, really appreciate you coming on the cube as part of our coverage is great to have You love to have you back sometime. >>Awesome. Thank you. And also just last thing we wanted to also call out that we are also going to be experimenting with probably Milan that is coming out. Uh, room is the current process is from a m D. That we have been leveraging. And as Milan comes available, we do wanna continue to evaluate it and see how we can fit it in our infrastructure. >>Okay, So their their generations are city based, the all Italian city based. They were going to run out of cities soon. >>God, uh, again, the partnership with both A W s and an M. D is something that I'm very proud of. Execution. Thank you, Dave. >>Great to have you, Ali. And really appreciate you watching. Keep it right there for more action on the cube. Your leader in hybrid tech event coverage. Mhm.

>>mhm Yes. >>Welcome back to the Cube coverage of Red Hat summit 21 2021. I'm john for host of the Cubans virtual this year as we start preparing to come out of Covid a lot of great conversations here happening around technology. This is the emerging technology with Red hat segment. We've got three great guests steve watt manager, distinguished engineer at Red Hat hurl saying senior software engineer Red Hat and luke Hines, who's the senior software engineer as well. We got the engineering team steve, you're the the team leader, emerging tech within red hat. Always something to talk about. You guys have great tech chops that's well known in the industry and I'll see now part of IBM you've got a deep bench um what's your, how do you view emerging tech um how do you apply it? How do you prioritize, give us a quick overview of the emerging tech scene at Redhead? >>Yeah, sure. It's quite a conflated term. The way we define emerging technologies is that it's a technology that's typically 18 months plus out from commercialization and this can sometimes go six months either way. Another thing about it is it's typically not something on any of our product roadmaps within the portfolio. So in some sense, it's often a bit of a surprise that we have to react to. >>So no real agenda. And I mean you have some business unit kind of probably uh but you have to have first principles within red hat, but for this you're looking at kind of the moon shot, so to speak, the big game changing shifts. Quantum, you know, you got now supply chain from everything from new economics, new technology because that kind of getting it right. >>Yeah, I think we we definitely use a couple of different techniques to prioritize and filter what we're doing. And the first is something will pop up and it will be like, is it in our addressable market? So our addressable market is that we're a platform software company that builds enterprise software and so, you know, it's got to be sort of fit into that is a great example if somebody came up came to us with an idea for like a drone command center, which is a military application, it is an emerging technology, but it's something that we would pass on. >>Yeah, I mean I didn't make sense, but he also, what's interesting is that you guys have an open source D N A. So it's you have also a huge commercial impact and again, open sources of one of the 4th, 5th generation of awesomeness. So, you know, the good news is open source is well proven. But as you start getting into this more disruption, you've got the confluence of, you know, core cloud, cloud Native, industrial and IOT edge and data. All this is interesting, right. This is where the action is. How do you guys bring that open source community participation? You got more stakeholders emerging there before the break down, how that you guys manage all that complexity? >>Yeah, sure. So I think that the way I would start is that, you know, we like to act on good ideas, but I don't think good ideas come from any one place. And so we typically organize our teams around sort of horizontal technology sectors. So you've got, you know, luke who's heading up security, but I have an edge team, cloud networking team, a cloud storage team. Cloud application platforms team. So we've got these sort of different areas that we sort of attack work and opportunities, but you know, the good ideas can come from a variety of different places. So we try and leverage co creation with our customers and our partners. So as a good example of something we had to react to a few years ago, it was K Native right? So the sort of a new way of doing service um and eventing on top of kubernetes that was originated from google. Whereas if you look at Quantum right, ibms, the actual driver on quantum science and uh that originated from IBM were parole. We'll talk about exactly how we chose to respond to that. Some things are originated organically within the team. So uh luke talking about six law is a great example of that, but we do have a we sort of use the addressable market as a way to sort of focus what we're doing and then we try and land it within our different emerging technologies teams to go tackle it. Now. You asked about open source communities, which are quite interesting. Um so typically when you look at an open source project, it's it's there to tackle a particular problem or opportunity. Sometimes what you actually need commercial vendors to do is when there's a problem or opportunity that's not tackled by anyone open source project, we have to put them together to create a solution to go tackle that thing. That's also what we do. And so we sort of create this bridge between red hat and our customers and multiple different open source projects. And this is something we have to do because sometimes just that one open source project doesn't really care that much about that particular problem. They're motivated elsewhere. And so we sort of create that bridge. >>We got two great uh cohorts here and colleagues parole on the on the Quantum side and you got luke on the security side. Pro I'll start with you. Quantum is also a huge mentioned IBM great leadership there. Um Quantum on open shift. I mean come on. Just that's not coming together for me in my mind, it's not the first thing I think of. But it really that sounds compelling. Take us through, you know, um how this changes the computing landscape because heterogeneous systems is what we want and that's the world we live in. But now with distributed systems and all kinds of new computing modules out there, how does this makes sense? Take us through this? >>Um yeah john's but before I think I want to explain something which is called Quantum supremacy because it plays very important role in the road map that's been working on. So uh content computers, they are evolving and they have been around. But right now you see that they are going to be the next thing. And we define quantum supremacy as let's say you have any program that you run or any problems that you solve on a classical computer. Quantum computer would be giving you the results faster. So that is uh, that is how we define content supremacy when the same workload are doing better on content computer than they do in a classical computer. So the whole the whole drive is all the applications are all the companies, they're trying to find avenues where Quantum supremacy are going to change how they solve problems or how they run their applications. And even though quantum computers they are there. But uh, it is not as easily accessible for everyone to consume because it's it's a very new area that's being formed. So what, what we were thinking, how we can provide a mechanism that you can you don't connect this deal was you have a classical world, you have a country world and that's where a lot of thought process been. And we said okay, so with open shift we have the best of the classical components. You can take open shift, you can develop, deploy around your application in a country raised platform. What about you provide a mechanism that the world clothes that are running on open shift. They are also consuming quantum resources or they are able to run the competition and content computers take the results and integrate them in their normal classical work clothes. So that is the whole uh that was the whole inception that we have and that's what brought us here. So we took an operator based approach and what we are trying to do is establish the best practices that you can have these heterogeneous applications that can have classical components. Talking to our interacting the results are exchanging data with the quantum components. >>So I gotta ask with the rise of containers now, kubernetes at the center of the cloud native value proposition, what work clothes do you see benefiting from the quantum systems the most? Is there uh you guys have any visibility on some of those workloads? >>Uh So again, it's it's a very new, it's very it's really very early in the time and uh we talk with our customers and every customers, they are trying to identify themselves first where uh these contacts supremacy will be playing the role. What we are trying to do is when they reach their we should have a solution that they that they could uh use the existing in front that they have on open shift and use it to consume the content computers that may or may not be uh, inside their own uh, cloud. >>Well I want to come back and ask you some of the impact on the landscape. I want to get the look real quick because you know, I think security quantum break security, potentially some people have been saying, but you guys are also looking at a bunch of projects around supply chain, which is a huge issue when it comes to the landscape, whether its components on a machine in space to actually handling, you know, data on a corporate database. You guys have sig store. What's this about? >>Sure. Yes. So sick store a good way to frame six store is to think of let's encrypt and what let's encrypt did for website encryption is what we plan to do for software signing and transparency. So six Door itself is an umbrella organization that contains various different open source projects that are developed by the Six door community. Now, six door will be brought forth as a public good nonprofit service. So again, we're very much basing this on the successful model of let's Encrypt Six door will will enable developers to sign software artifacts, building materials, containers, binaries, all of these different artifacts that are part of the software supply chain. These can be signed with six door and then these signing events are recorded into a technology that we call a transparency log, which means that anybody can monitor signing events and a transparency log has this nature of being read only and immutable. It's very similar to a Blockchain allows you to have cryptographic proof auditing of our software supply chain and we've made six stores so that it's easy to adopt because traditional cryptographic signing tools are a challenge for a lot of developers to implement in their open source projects. They have to think about how to store the private keys. Do they need specialist hardware? If they were to lose a key then cleaning up afterwards the blast radius. So the key compromise can be incredibly difficult. So six doors role and purpose essentially is to make signing easy easy to adopt my projects. And then they have the protections around there being a public transparency law that could be monitored. >>See this is all about open. Being more open. Makes it more secure. Is the >>thief? Very much yes. Yes. It's that security principle of the more eyes on the code the better. >>So let me just back up, is this an open, you said it's gonna be a nonprofit? >>That's correct. Yes. Yes. So >>all of the code is developed by the community. It's all open source. anybody can look at this code. And then we plan alongside the Linux Foundation to launch a public good service. So this will make it available for anybody to use if your nonprofit free to use service. >>So luke maybe steve if you can way into on this. I mean, this goes back. If you look back at some of the early cloud days, people were really trashing cloud as there's no security. And cloud turns out it's a more security now with cloud uh, given the complexity and scale of it, does that apply the same here? Because I feel this is a similar kind of concept where it's open, but yet the more open it is, the more secure it is. And then and then might have to be a better fit for saying I. T. Security solution because right now everyone is scrambling on the I. T. Side. Um whether it's zero Trust or Endpoint Protection, everyone's kind of trying everything in sight. This is kind of changing the paradigm a little bit on software security. Could you comment on how you see this playing out in traditional enterprises? Because if this plays out like the cloud, open winds, >>so luke, why don't you take that? And then I'll follow up with another lens on it which is the operate first piece. >>Sure. Yes. So I think in a lot of ways this has to be open this technology because this way we have we have transparency. The code can be audited openly. Okay. Our operational procedures can be audit openly and the community can help to develop not only are code but our operational mechanisms so we look to use technology such as cuba netease, open ship operators and so forth. Uh Six store itself runs completely in a cloud. It is it is cloud native. Okay, so it's very much in the paradigm of cloud and yeah, essentially security, always it operates better when it's open, you know, I found that from looking at all aspects of security over the years that I've worked in this realm. >>Okay, so just just to add to that some some other context around Six Law, that's interesting, which is, you know, software secure supply chain, Sixth floor is a solution to help build more secure software secure supply chains, more secure software supply chain. And um so um there's there's a growing community around that and there's an ecosystem of sort of cloud native kubernetes centric approaches for building more secure software. I think we all caught the solar winds attack. It's sort of enterprise software industry is responding sort of as a whole to go and close out as many of those gaps as possible, reduce the attack surface. So that's one aspect about why 6th was so interesting. Another thing is how we're going about it. So we talked about um you mentioned some of the things that people like about open source, which is one is transparency, so sunlight is the best disinfectant, right? Everybody can see the code, we can kind of make it more secure. Um and then the other is agency where basically if you're waiting on a vendor to go do something, um if it's proprietary software, you you really don't have much agency to get that vendor to go do that thing. Where is the open source? If you don't, if you're tired of waiting around, you can just submit the patch. So, um what we've seen with package software is with open source, we've had all this transparency and agency, but we've lost it with software as a service, right? Where vendors or cloud service providers are taking package software and then they're making it available as a service but that operationalize ng that software that is proprietary and it doesn't get contributed back. And so what Lukes building here as long along with our partners down, Lawrence from google, very active contributor in it. Um, the, is the operational piece to actually run sixth or as a public service is part of the open source project so people can then go and take sixth or maybe run it as a smaller internal service. Maybe they discover a bug, they can fix that bug contributed back to the operational izing piece as well as the traditional package software to basically make it a much more robust and open service. So you bring that transparency and the agency back to the SAS model as well. >>Look if you don't mind before, before uh and this segment proportion of it. The importance of immune ability is huge in the world of data. Can you share more on that? Because you're seeing that as a key part of the Blockchain for instance, having this ability to have immune ability. Because you know, people worry about, you know, how things progress in this distributed world. You know, whether from a hacking standpoint or tracking changes, Mutability becomes super important and how it's going to be preserved in this uh new six doorway. >>Oh yeah, so um mutability essentially means cannot be changed. So the structure of something is set. If it is anyway tampered or changed, then it breaks the cryptographic structure that we have of our public transparency service. So this way anybody can effectively recreate the cryptographic structure that we have of this public transparency service. So this mutability provides trust that there is non repudiation of the data that you're getting. This data is data that you can trust because it's built upon a cryptographic foundation. So it has very much similar parallels to Blockchain. You can trust Blockchain because of the immutable nature of it. And there is some consensus as well. Anybody can effectively download the Blockchain and run it themselves and compute that the integrity of that system can be trusted because of this immutable nature. So that's why we made this an inherent part of Six door is so that anybody can publicly audit these events and data sets to establish that there tamper free. >>That is a huge point. I think one of the things beyond just the security aspect of being hacked and protecting assets um trust is a huge part of our society now, not just on data but everything, anything that's reputable, whether it's videos like this being deep faked or you know, or news or any information, all this ties to security again, fundamentally and amazing concepts. Um I really want to keep an eye on this great work. Um Pearl, I gotta get back to you on Quantum because again, you can't, I mean people love Quantum. It's just it feels like so sci fi and it's like almost right here, right, so close and it's happening. Um And then people get always, what does that mean for security? We go back to look and ask them well quantum, you know, crypto But before we get started I wanted, I'm curious about how that's gonna play out from the project because is it going to be more part of like a C. N. C. F. How do you bring the open source vibe to Quantum? >>Uh so that's a very good question because that was a plan, the whole work that we are going to do related to operators to enable Quantum is managed by the open source community and that project lies in the casket. So casket has their own open source community and all the modification by the way, I should first tell you what excuse did so cute skin is the dedicate that you use to develop circuits that are run on IBM or Honeywell back in. So there are certain Quantum computers back and that support uh, circuits that are created using uh Houston S ticket, which is an open source as well. So there is already a community around this which is the casket. Open source community and we have pushed the code and all the maintenance is taken care of by that community. Do answer your question about if we are going to integrate it with C and C. F. That is not in the picture right now. We are, it has a place in its own community and it is also very niche to people who are working on the Quantum. So right now you have like uh the contributors who who are from IBM as well as other uh communities that are specific specifically working on content. So right now I don't think so, we have the map to integrated the C. N. C. F. But open source is the way to go and we are on that tragic Torri >>you know, we joke here the cube that a cubit is coming around the corner can can help but we've that in you know different with a C. But um look, I want to ask you one of the things that while you're here your security guru. I wanted to ask you about Quantum because a lot of people are scared that Quantum is gonna crack all the keys on on encryption with his power and more hacking. You're just comment on that. What's your what's your reaction to >>that? Yes that's an incredibly good question. This will occur. Okay. And I think it's really about preparation more than anything now. One of the things that we there's a principle that we have within the security world when it comes to coding and designing of software and this aspect of future Cryptography being broken. As we've seen with the likes of MD five and Sha one and so forth. So we call this algorithm agility. So this means that when you write your code and you design your systems you make them conducive to being able to easily swap and pivot the algorithms that use. So the encryption algorithms that you have within your code, you do not become too fixed to those. So that if as computing gets more powerful and the current sets of algorithms are shown to have inherent security weaknesses, you can easily migrate and pivot to a stronger algorithms. So that's imperative. Lee is that when you build code, you practice this principle of algorithm agility so that when shot 256 or shot 5 12 becomes the shar one. You can swap out your systems. You can change the code in a very least disruptive way to allow you to address that floor within your within your code in your software projects. >>You know, luke. This is mind bender right there. Because you start thinking about what this means is when you think about algorithmic agility, you start thinking okay software countermeasures automation. You start thinking about these kinds of new trends where you need to have that kind of signature capability. You mentioned with this this project you're mentioning. So the ability to actually who signs off on these, this comes back down to the paradigm that you guys are talking about here. >>Yes, very much so. There's another analogy from the security world, they call it turtles all the way down, which is effectively you always have to get to the point that a human or a computer establishes that first point of trust to sign something off. And so so it is it's a it's a world that is ever increasing in complexity. So the best that you can do is to be prepared to be as open as you can to make that pivot as and when you need to. >>Pretty impressive, great insight steve. We can talk for hours on this panel, emerging tech with red hat. Just give us a quick summary of what's going on. Obviously you've got a serious brain trust going on over there. Real world impact. You talk about the future of trust, future of software, future of computing, all kind of going on real time right now. This is not so much R and D as it is the front range of tech. Give us a quick overview of >>Yeah, sure, yeah, sure. The first thing I would tell everyone is go check out next that red hat dot com, that's got all of our different projects, who to contact if you're interested in learning more about different areas that we're working on. And it also lists out the different areas that we're working on, but just as an overview. So we're working on software defined storage, cloud storage. Sage. Well, the creator of Cf is the person that leads that group. We've got a team focused on edge computing. They're doing some really cool projects around um very lightweight operating systems that and kubernetes, you know, open shift based deployments that can run on, you know, devices that you screw into the sheet rock, you know, for that's that's really interesting. Um We have a cloud networking team that's looking at over yin and just intersection of E B P F and networking and kubernetes. Um and then uh you know, we've got an application platforms team that's looking at Quantum, but also sort of how to advance kubernetes itself. So that's that's the team where you got the persistent volume framework from in kubernetes and that added block storage and object storage to kubernetes. So there's a lot of really exciting things going on. Our charter is to inform red hats long term technology strategy. We work the way my personal philosophy about how we do that is that Red hat has product engineering focuses on their product roadmap, which is by nature, you know, the 6 to 9 months. And then the longer term strategy is set by both of us. And it's just that they're not focused on it. We're focused on it and we spend a lot of time doing disambiguate nation of the future and that's kind of what we do. We love doing it. I get to work with all these really super smart people. It's a fun job. >>Well, great insights is super exciting, emerging tack within red hat. I'll see the industry. You guys are agile, your open source and now more than ever open sources, uh, product Ization of open source is happening at such an accelerated rate steve. Thanks for coming on parole. Thanks for coming on luke. Great insight all around. Thanks for sharing. Uh, the content here. Thank you. >>Our pleasure. >>Thank you. >>Okay. We were more, more redhead coverage after this. This video. Obviously, emerging tech is huge. Watch some of the game changing action here at Redhead Summit. I'm john ferrier. Thanks for watching. Yeah.

>>Good afternoon and welcome back to our audience here in Asia pacific This is Sandeep again uh from my home studio in Singapore, I hope you found the session to be insightful. I thought it was a key takeaway in terms of how you know the the world is going through a massive transformation, driven by underpinning the workload optimized solutions around up by round of security, 3 60 degree security. As Neil Mcdonald talked about underpinned by the scale, you know, whether you're on exa scale, compute public cloud or on the edge and that's kind of underpinning the digital transformation that our customers are going to go through. I have two special guests with me. Uh let me just quickly introduce them Santos restaurant martin who uh is the Managing director for intel in A P. K. And Dorinda Kapoor, Managing Director for HB Initial pacific So, good afternoon, both you gentlemen. >>Good afternoon. >>So Santos. My first question is to you, first of all, a comment, you know, the passion at which uh, pad Kill Singer talked through the four superpowers. That was amazing. You know, I could see that passion comes through the screen. You know, I think everybody in the audience could relate with that. We are like, you know, as you know, on the words of the launch, the gentle plus by power, but it's isolate processor from intel, what are you seeing and what do our customers should expect improvements, especially with regard to the business outcomes. >>Yeah, So first of all, thank you so much for having me in this session and, and as you said, Sandeep, I mean, you could really see how energized we are. And you heard that from pad as well. Uh, so we launched the third gen, intel, Xeon processors or isolate, you know about a couple of weeks ago and I'm sure, you know, there's lots of benefits that you get in these new products. But I thought what I'll do is I'll try and summarize them in three key buckets. The first one is about the performance benefits that these new products bring in. The 2nd 1 is the value of platforms and I think the last pieces about the partnerships and how it makes deployment really easy and simple for our customers. Let me start with the first one which is about performance and the and the big jump that we're staying. It's about a 46% performance, increased generation over generation. It's flexible, it's optimized performance from the edge to the cloud where you would see about 1.5 to 1.7 X improvements on key war clouds like the cloud five G I O D HPC and AI that are so critical all around us. It's probably the only data center processor that has built in A I acceleration that helps with faster analytics. It's got security optimist on intel SGX that basically gives you a secure on cliff when when sensitive data is getting transacted and it also has crypto acceleration that reduces any performance impact because of the pervasive encryption that we have all around us. Now The second key benefit is about platform and if you remember when we launch sky lake in 2017, we laid out a strategy that said that we are here to help customers >>move, >>store and process data. So it's not just the CPU that we announced with the third genitals, jOHn Announcements. We also announce products like the obtained persistent memory, 200 cds That gives you about a 32 higher memory bandwidth and six terabytes of memory capacity on stock. It the obtain S S D S, the intel internet, 800 cities adapter that gives you about 200 Gbps per port, which means you can move data much more faster and you have the intellectual X F P G s that gives you about a double the better fabric performance for what? Which means if there's key workloads that you want to go back and offloaded to a to a steak or a specific uh CPU then you have the F P G s that can really help you there Now. What does the platform do for our customers? It helps them build higher application and system level performance that they can all benefit from the last b which is the partnerships area is a critical one because we've had decades of experience of solution delivery with a broad ecosystem and with partners like HP and we build elements like the Intel select solution and the market ready solution that makes it so much more easier for our customers to deploy with Over 50 million Xeon scalable processes that is shipped around the world. A billion Xeon cores that are powering the cloud since 2013 customers have really a proven solution that they can work with. So in summary, I want you to remember the three key piece that can really >>help you be >>successful with these new products, the performance uplifted, you get generation over generation, the platform benefits. So it's not just the CPU but it's things around that that makes the system and the application work way better. And then the partnerships that give you peace of mind because you can go deploy proven solutions that you can go and implement in your organization and serve your customers better. >>Thanks. Thanks thanks and Tosha for clearly outlining, you know, the three PS and kind of really resonates well. Um, so let me just uh turn over you know, to Dorinda there in the hot, you know, there's a lot of new solutions, you're our new treaties that santos talked about security, you get a lot of performance benefits and yet our customers have to go through a massive amount of change from a digital transformation perspective in order that they take all the advantages in state competitive. We're using HP Iran addressing the needs for the challenges of our customers and how we really helping them accelerate their transformation journey. >>Yeah, sure. Sandeep, thanks a lot for the question. And you are right. Most of the businesses actually need to go uh digital transformation in order to stay relevant in the current times. And in fact actually COVID-19 has further accelerated the pace of digital transformation for uh most of our customers. And actually the digital transformation is all about delivering differentiated experiences and outcomes at the age by converting data collected from multiple different sources to insights and actions. So we actually an HP believe that enterprise of the future is going to be eight centric data driven and cloud enabled And with our strategy of providing H2 cloud platform and having a complete portfolio of uh software, networking computer and the storage solutions both at the age and court uh to of course collect, transmit secure, analyze and store data. I believe we are in the best position to help our customers start and execute on their transformation journey. Now reality is various enterprises are at different stages of their transformation journey. You know, uh we in HP are able to help our customers who are at the early stage or just starting the transformation journey to to help build their transformation broad maps with the help of our advisory teams and uh after that helped them to execute on the same with our professional services team. While for the customers who are already midway in the transformation journey, we have been helping them to differentiate themselves by delivering workload optimized solutions which provide latency, flexibility and performance. They need to turn data into insights and innovations to help their business. Now, speaking of the workload optimized solutions, HP has actually doubled down in this area with the help of our partners like Intel, which powers our latest Gentlemen plus platform. This brings more compute power, memory and storage capacity which our customers need as they process more data and solve more complex challenges within their business. >>Thank you. Thanks. And er in there I think that's really insightful. Hopefully you know our customer base, I will start joined in here, can hear that and take advantage of you know, how HP is helping you know, fast track the exploration. I come back to you something you don't like during the talk about expanding capacities and we saw news about you know Intel invest $20 billion dollars or so, something like that in terms of you know, adding capacities or manufacturing. So I'd like to hear from your perspective, you know how this investments which intel is putting is a kind of a game changer, how you're shaping the industry as we move forward. >>Yeah, I mean as we all know, I think there's accelerated demand for semiconductors across the world digitization especially in an environment that we're that we're going through has really made computing pervasive and it's it's becoming a foundation of every industry and our society, the world just needs more semiconductors. Intel is in a unique position to rise to that occasion and meet the growing demand for semiconductors given our advanced manufacturing scale that we have. So the intel foundry services and the that you mentioned is is part of the Intel's new I. D. M. Torrado strategy that Bad announced which is a differentiated winning formula that will really deliver the new era of innovation, manufacturing and product leadership. We will expand our manufacturing capacity as you mentioned with that 20 billion investments and building to fabs in Arizona. But there's more to come in the year ahead and these fans will support the expanding requirements of our current products and also provide committed capacity for our foundry customers. Our foundry customers will also be able to leverage our leading edge process, the treaty packaging technology, a world class I. P. Portfolio. So >>I'm really really >>excited. I think it's a truly exciting time for our industry. The world requires more semiconductors and Intel is stepping in to help build the same. >>Fantastic, fantastic. Thank you. Some potion is really heartening to know and we really cherish the long partnership, HP and Intel have together. I look forward that you know with this gentleman plus launch and the partnership going forward. You know, we have only motivation and work together. Really appreciate your taking the time and joining and thank you very much for joining us. >>Thank you. >>Thanks. >>Okay, so with that I will move on to our second segment and in white, another special guest and this is Pete Chambers who is the managing director for A N D N A P K. Good afternoon Pete. You can hear us Well >>I can. Thank you. Sandy, Great to be >>here. Good and thanks for joining me. Um I thought I just opened up, you know, like a comment around the 19 world Records uh, am D. N. H. We have together and it's a kind of a testament to the joint working model and relationship and the collaboration. And so again, really thank you for the partnership. We have any change. Uh, let me just quickly get to the first question. You know, when it comes to my mind listening over to what Antonio and Liza were discussing, you know, they're talking about there's a huge amount of flow of data. You know, the technology and the compute needs to be closer to where the data is being generated and how is A. M. D. You know, helping leverage some of those technologies to bring feature and benefits and driving outcome for customers here in asia. >>Yeah, as lisa mentioned, we're now in a high performance computing mega cycle driven by cloud computing, digital transformation five DNA. Which means that everyone needs and wants more computer IDC predicts that by 20 23/65 percent of the impact GDP will be digitized. So there's an inflection coming with digital transformation at the fall, businesses are ever increasingly looking for trusted partners like HP and HP and and to help them address and adapt to these complex emerging technologies while keeping their IT infrastructure highly efficient, you know, and is helping enable this transformation by bringing leadership performance such as high court densities, high PC and increased I. O. But at the same time offering the best efficiency and performance for what all third gen Epic. CPU support 100 and 28 lanes of superfast PC for connectivity to four terabytes of memory and multiple layers of security. You know, we've heard from our customers that security continues to be a key consideration, you know? And he continues to listen. And with third gen, Epic, we're providing a multitude of security features such as secure root of trust at the bios level which we work very closely with HP on secure encrypted virtualization, secure memory encryption and secure nested paging to really giving the customers confidence when designing Epic. We look very closely at the key workloads that our customers will be looking to enable. And we've designed Epic from the ground up to deliver superior experience. So high performance computing is growing in this region and our leadership per socket core density of up to 64 cause along with leading IO and high memory bandwidth provides a compelling solution to help solve customers most complex computational problems faster. New HP Apollo 6500 and 10 systems featuring third gen, Epic are also optimist for artificial intelligence capabilities to improve training and increased accuracy and results. And we also now support up to eight and instinct accelerators. In each of these systems, hyper converged infrastructure continues to gain momentum in today's modern data center and our superior core density helps deliver more VMS per CPU supported by a multitude of security virtualization features to provide peace of mind and works very closely with industry leaders in HD like HP but also Nutanix and VM ware to help simplify the customers infrastructure. And in recent times we've seen video. I have a resurgence as companies have looked to empower their remote employee remote employees. Third gen, Epic enables more video sessions per CPU providing a more cost optimized solution, simply put Epics higher core density per CPU means customers need fewer service. That means less space required, lower power and cooling expenditure and as a result, a tangibly lower total cost of ownership add to this the fact, as you mentioned that Andy Epic with HP of 19 world records across virtualization, energy efficiency, decision support, database workloads, etc. And service side java. And it all adds up to a very strong value proposition to encourage Cdos to embark on their next upgrade cycle with HP and Epic >>Interstate. Thank you Peter and really quite insightful. And I've just done that question over to Narendra Pete talked about great new technologies, new solution, new areas that are going to benefit from these technology enhancements at the same time. You know, if I'm a customer, I look at every time we talk about technology, you know, you need to invest and where is you know, the bigger concern for customers always wears this money will come from. So I want to uh, you know, uh, the if you share your insights, how is actually helping customers to be able to implement these technology solutions, giving them a financial flexibility so that they can drive business outcomes. >>Yes, and the very important point, you know, from how HP is able to help our customers from their transformation. Now, reality is that most of the traditional enterprises are being challenged by this new digital bond businesses who have no doubt of funding and very low expectation of profitability. But in reality, majority of the capital of these traditional enterprises has uh tied up in their existing businesses as they do need to keep current operations running while starting their digital transformation at the same time. This of course creates real challenges and funding their transformation. Now with HP, with our Green Lake Cloud services, we are able to help customers fund their transformation journey. Were instead of buying up front, customers pay only for what they consume as the scale. We are not only able to offer flexible consumption model for new investments but are also able to help our customers, you know, for monetize their capital, which is tied up in the old ICT infrastructure because we can buy back that old infrastructure and convert that into conception of frank. So while customers can continue to use those assets to run their current business and reality is HIV is the leader in the this as a service space and probably the only vendor to be able to offer as a service offering for all of our portfolio. Uh, if you look at the ideas prediction, 70 of the applications are not ready for public cloud and will continue to run in private environments in addition. And everybody talked about the beef for a I and you know, HPC as well as the edge and more and more workloads are actually moving to the edge where the public cloud will have for less and less a role to play. But when you look at the customers, they are more and more looking for a cloud, like business model for all the workloads, uh, that they're running outside the public cloud. Now, with our being like offering, we are able to take away all the complexity from customers, allowing them to run the workloads wherever they want. That means that the edge in the data center or in the cloud and consume in the way they want. In other words, we're able to provide cloud, like experience anytime, anywhere to our customers. And of course, all these Green Lake offerings are powered by our latest compute capabilities that HP has to offer. >>Thank you. Thank you, surrender. That's really, really, very insightful. I have a minute or two, so let me try to squeeze another question from your feet, you know, MD is just now introduced the third generation of epics and congratulations on that. How are you seeing that? Excellent. Helping you accelerate in this growth, in the impact? Uh, you know, the geography as as such. >>Sure, great question. And as I mentioned, you know, third gen Epic with me and and once again delivers industry leading solutions, bending the curve on performance efficiency and TCO helping more than ever to deliver along with HP the right technologies for today and tomorrow. You know, in the service space, it's not just about what you can offer today. You need to be able to predictably deliver innovation over the long term. And we are committed to doing just that, you know, and strategy is to focus on the customer. We continue to see strong growth both globally and in a pack in HPC cloud and Web tech manufacturing, Fc telco and public and government sectors are growth plan is focused on getting closer to our customers directly, engaging with HP and our partners and the end customer to help guide them on the best solution and assist them in solving their computing pain points cost effectively. A recent example of this is our partnership with palsy supercomputing center in Australia, where HP and M. D will be helping to provide some 200,000 cause across 1600 nodes and over 750 radio on instinct accelerators empowering scientists to solve today's most challenging problems. We have doubled ourselves and F8 teams in the region over the past year and will continue to invest in additional customer facing sales and technical people through 2021, you know, and has worked very closely with HP to co design and co developed the best technologies for our customers needs. We joined forces over seven years ago to prepare for the first generation of Epic at launch and you fast forward to today and it's great to see that HP now has a very broad range of Andy Epic servers spanning from the edge two extra scale. So we are truly excited about what we can offer the market in partnership with HP and feel that we offer a very strong foundation of differentiation for our channel partners to address their customers need to accelerate accelerate their digital transformation. Thank you. Sandy, >>thank you. Thanks Peter. And really it's been amazing partnering with the NDP here and thanks for your sponsorship on that. And together we want to work with you to create another 19 world records right from here in the issue. Absolutely. So with that we are coming to the end of the event. Really thanks for coming pete and to our audience here because the pig is being a great a couple of hours. I hope you all found these sessions very, very insightful. You heard from our worldwide experts as to where, you know, divorce, moving in terms of the transformation, what your hp is bringing to our compute workload optimized solutions which are going to go from regardless of what scale of computing you're using and wrapped around 3 60 security and then offer truly as a service experience. But before you drop off, I would like to request you to please scan the QR code you see on your screen and fill in the feedback form we have, you know, lucky draw for some $50 worth of vultures for the five lucky winners today. So please click up your phone and, you know, spend a minute or two and give us a feedback and thank you very much again for this wonderful day. And I wish everybody a great day. Thank you.

(upbeat electronic music) >> Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey, welcome back everyone! This is theCUBE's live coverage here in Las Vegas for Amazon Web Services re:Invent. I'm John Furrier with Lauren Cooney, your hosts here at theCUBE. You got two sets. We have a great guest, CUBE alumni Ronen Schwartz, who's the senior vice president and general manager of Cloud, Big Data and Data Integration for Informatica. As you know, we cover their events. Great to see you. >> Great to see you as well. >> So, one thing that jumps out me here at this show, and I want to get your reaction right out of the gate is, Amazon's scale is unprecedented. And they're using that scale to create differentiation and competitive advantage. This is something that's familiar to you guys. You guys have scale with your data. Big data at scale now is something that's become, I won't say en vogue, it's popular because people are now obviously seeing I need to do better with my data. I need a data platform. No data platform, I'm not successful. Your thoughts. >> I think you're absolutely right, and scale is the key word for customer to be successful. And I truly believe that the cloud is offering this ability of infinite scale and who better than Amazon to actually demonstrate that. We definitely have a lot of customer that are demonstrating scale in a repeatable mode. One of my favorite statistics about Informatica cloud is the fact that the amount of data that we process actually doubles every six months. And every time when I look into the number, the number now is five trillion records in a month. Every time I look at the numbers, I say-- >> In your cloud? >> Just going through our cloud, right? And I'm looking at this number and I'm saying like, can we really double it once again? So far in the last five years, that had actually been a statistic, so, I agree with you, scale is part of the game. >> Talk about what you guys are doing here at re:Invent this year. Obviously your partnership has been there for a while. What's you guys announcing? What's the story? What's the conversation this week for Informatica? >> Informatica is announcing here a solution that we build together with AWS and Tableau, really introducing next generation analytics. If you had want to modernize the way you look and work with data, you actually can get a best-of-breed integration, a data catalog, together with a modern data warehouse in the cloud from Amazon, and basically Tableau, Tableau Cloud, to reach out self-service. All of that could be now started in one button, everything is already integrated, working, optimized for customers, new and existing, to really get value from their data. >> And the future of your business is what? Fill in the blank. The future of Informatica is blank. Fill in the blank. >> Enterprise cloud data management. Really supporting customers in a data-driven, in a data-driven world. Helping customer navigate that, the huge transformation that is happening now with the market with data. >> Ronen, what do you think about Amazon moving up the stack? Obviously there's a lot of services you've seen. Redshift, Kinesis, Aurora, all these are new. Give me those, not just EC2 anymore, although they're touting a lot of EC2, they have the big groundbreaking news around the satellites. It's called, Ground. Something earth's. Satellite provisioning. Ground Station. The provisioning connectivity. So your data's going to get more foam. They're going to create more edge data. >> Right, the world for IT is changing in an unbelievable way. And I do think that Amazon is changing it, some of it is in the upmarket, but they are changing the way operations works, they are changing the way the backend is working. And you're right, I mean, any way, from trucks that go with data to satellites, they are changing the way people work. >> There's kind of changes to the edge, but they're also highlighting analytics, right? Machine learning, AI, this is something that you guys have been doing as well. It's going to put more emphasis on analytics and automation. How does that affect your business? How do you talk to your customers saying, what does this mean for me? I'm an Informatica customer. >> For Informatica, the more data the customer have, the more data the end users are enabled to use, the more business it is for us. It actually means that data is more important. Data is more important means that data management is more important, and this is really where we help customer get value. >> So I have a question, and this is kind of a clarification. So are you talking about when your customers consume, or can understand their data? So is it information or is data? >> You're touching a really important point, which is the difference between raw data and basically valuable data, information, and conclusion. Informatica is helping the customer from identifying the data, discovering the right data, all the way into improving the data with data quality, with normalization, et cetera, all the way to the place that the data is ready to be investigated. To become information. And basically this is our role, and it actually complements really, really nicely the real changes that are happening with the storage, with analytics, analytics and scale. And definitely with the rise of AI, people are not just looking backwards into what the data mean in the past, they actually trying to leverage data in order to guess and understand what will happen going forward. >> So can you give me a use case? Like a customer use case that you have. Understanding that you may or may not be able to talk about a specific customer, but just in general. >> Let me give you a few examples. One of my favorite examples is a lot of the medicines hae been discovered by a practitioner, usually a doctor, identifying something that happened to two of his patients. But the human memory in a single practitioner, like a doctor, that he can remember what happened a few months back, a few years back, for only his patients. Informatica, actually together with AWS, is supporting MD Anderson in a massive implementation of a data lake that collects what happens to millions of patients from hundreds and thousands of hospitals, so that you can actually identify repeatable patterns that can lead to new medicine and new investigation. >> It's also faster innovation because that's when you're running through that data to get the results from the clinical studies and things like that. That is tremendous. That would really increase the speed there. >> You're absolutely right. The next part of that is actually, how do you make innovation faster? This is instead of human beings connecting the dots, machine learning, AI, and other advanced methodologies that help you identify, basically, these patterns. These unique situation that actually can drive somebody to invent a new medicine, it can drive somebody else to sell more effectively, a third-party to do maintenance better, and so on. >> So have you thought about pushing the business a little bit further and innovating with a customer? Co-creation and things along those lines. >> Innovate with the customer, sorry, can you repeat? >> Innovation with a customer. Once they are kind of turning the data into information, and are you looking at co-creating with your customers? Is that something that you're into? >> So Informatica is actually making sure that the data that is driving the innovation is the right data, in the right shape, in the right quality, and is available for the innovation. The innovation that is driven from the data is where tools like AWS, AI, and machine learning, the data warehousing, and others, are actually being leveraged. >> Okay. >> Talk about the update on Amazon's relationship. You guys have had a partnership with them. Is there any updates? What's the current status? >> Definitely. So Informatica basically empowers all of its customers to run any of their Informatica implementation on AWS without any additional cost, and so on. What we have done in the last few years is more than that. We actually helped them optimize how they're running existing workloads, leveraging the power of cloud, or to scaling, automatic performance adjustment, scale up and scale down, in a very effective way. And what we're doing right now to get together with AWS is actually empowering customer to drive migration of data to the cloud. Helping customer identify security and vulnerabilities on the data layer. All of that in an automated way. Where I want to end it up is that today if you're leveraging any of the Amazon data services, any of the storage, et cetera, Informatica is offering an optimized way to bring data from on-premise, from other clouds, to AWS. >> The data catalog is a dream for AI and machine learning. Really, if you think about it, if the brains are going to be in the cloud, data catalog is kind of like the connective tissue. >> I totally agree. I mean it's actually interesting that the classical bottleneck which was compute is actually disappeared. (John laughing) You have an infinite amount of power to compute. Even your ability to have access to advance algorithms, and so on, has been resolved. They're all available as a service to be used. However, these sophisticated, really bright AI users, they're, you're right, they're bottleneck is can I find that data that is needed for me for my algorithm? Can I make sure this data is the right data? The data catalog, or Informatica enterprise data catalog, the catalog don't just go to one place, but to the whole enterprise, is key to reach good AI. >> The FBI just talked today. A big speech this morning at Teresa Carlson's event. They can't put the pieces together on these investigations fast enough for the bad guys because of the database problem. They need to have the catalogs to these data lakes, they need the AI, they need the compute. You guys got it all! Ronen, thanks for joining us. Thanks for sharing your insights again. >> Thank you. >> Hey, my pleasure, really exciting show. A lot, a lot of exciting news. >> Great to see you. >> Thank you. >> All the stuff we talked about three years ago is happening now! Informatica, check it out! Of course theCUBE covers Informatica's events. I do a lot of hosting there. I'm here with Lauren Cooney, here at Amazon re:Invent. Wall-to-wall coverage, three days of programming. Stay with us for more after this short break. (futuristic beep) (futuristic electronic music)

>> Hi, welcome once again to Action Item. (funky electronic music) I'm Peter Burris and this is Wikibon's weekly research meeting where we bring together some of the best minds in Silicon Valley to talk about some of the trends that are most important. We're broadcasting from here in the Cube studios in beautiful Palo Alto, California. And in the studio, I'm being joined by George Gilbert and David Floyer and on the phone we have Neil Raden, Jim Kobielus, Dave Vellante. Team, thanks very much for being part of this conversation today. What we're going to do today is we're going to bring forward some of Wikibon's predictions for 2018. In a previous show, we discussed what we learned in 2017, so some of the trends and some of the expectations that didn't play out as expected. This year we're going to dig a little bit deep into what we think is going to happen in 2018 and it all starts with a proposition that even as we go through significant industry change, we're not necessarily going to see the economics of the industry change as fast, which leads to prediction number one. David Floyer, what is it? >> So, my prediction is that volume is going to take a key role in the evolution of disruptive technologies. So for example, in AI and IOT and in true private cloud, volume is going to be the key determination of when it starts to take off, when it starts to hockey stick. >> So this has been something that's been featured in the industry for a while, Dave, but give us an example. What's the relationship between volume and AI? >> So if we take the relationship between AI and volume, AI is going sideways, and I would predict that it's going to go sideways in 2018 because every implementation is a snowflake until there are solutions out there which can be delivered in volume by vendors. Then that will the point at which things will take off. So an example, for example, automated cars. They are AI, when they start to come out in volume, there'll be volume manufacturers, volume of the census, volume of the processes, the on-processes, volume of everything that will drive down costs and make those implementations so quickly. >> And it's still software, so we're still worried about support and service on a very, very broad scale. >> David: Yeah. >> So that leads to our second quick prediction. Dave Vellante, build on this notion of volume. What's going to be the impact on a lot of the innovative smaller companies in 2018? >> Dave: So Peter, my prediction is got to go scale or go home, AKA go out of business. So we expect massive industry consolidation is going to take place in the next two years, certainly through 2019 as the business models of VC-backed tech startups are getting smashed by cloud and, to a great extent, open source. In a turnabout from the historical norms, innovations and cost reductions from the largest cloud players are moving at a pace that's faster than many, if not most startups are able to deliver. So finding white space is much, much harder. We see private equity as playing a key role here, providing capital for M and A and doing roll-ups that are going to create scale and large portfolios that can compete. >> So Neil Raden, as we think about what Dave just said, one of the key things that's happening is a lot of money's being put into some of the new technologies that are intended to provide more intelligence in a lot of different places. One of the large company leaders indicating or describing how this was going to play out was IBM with its Watson story. What's been going on with Watson? What's our prediction for how that's playing out and likely, what's a likely 2018 scenario for IBM and Watson? >> Neil: Well, not to sugarcoat it but Watson's been a dismal failure, and I think that IBM is going to reassess their whole approach to cognitive computing in 2018. Numbers don't lie, let me give you some numbers from 2016. They obviously don't have '17 yet. But these are reliable numbers from some institutional clients of mine. Their goal for 2016 was over 8,000 clients. They achieved 500. Their goals for business partners was over 4,000 and they achieved 329. So, you know, the numbers speak for themselves, but Watson hasn't caught on. It's a solution in search of a problem. It was a marketing stunt, really, that someone thought to be turned into a 20 billion dollar per year business. It's not even a product, really. It's dozens of subsystems that are linked with APIs. Some of them are interesting, but most already are available in the open source world. >> Well one of the things we talked about last week, Neil, was the idea that we're going to see more buy, as opposed to build, and we talked about the volume play there, and then we asked the question, is there going to be more software or is there going to be more services? It sounds like IBM's play to be a dominate player in AI-related services has not gone as well as expected. Is that kind of where we are right now? >> Neil: Well, yeah. If you look at one of the more public failures of Watson, which was MD Anderson Cancer Center, they pulled the plug on the project after 62 million dollars, but IBM only got about 20 million dollars of that, the rest of it went to PWC. So how they intend to split that business between global services and their partners, I really don't know. And the failure of Watson at MD Anderson wasn't entirely IBM's fault. A lot of it had to do with PWC's project management, and a lot of it had to do with the people at Anderson who basically started the project by looking at a very well-understood type of leukemia that had a well-understood etiology and treatment options. So when the auditors looked at it, they said we haven't learned anything for 62 million dollars, and that's been repeated at other projects. >> So it sounds like this is, again, tied back to the idea of scale, volume, and related issues. But it also sounds like there's a lot of question, ultimately, about what is AI? What isn't AI? What role is Watson going to play? Is it going to be private data? Is it going to be public data? A lot of questions are going to emerge over the course of next year. But there are domains where AI, ML, DL are likely to have some important success. And George, we've got a prediction about where they're likely to be successful in 2018. What are we thinking, what's one domain where we think at least machine learning is going to have a significant impact in 2018? >> Well, keying off David's point about volume, volume economics, we think that IT operations management is going to be one of the first horizontal applications that embeds machine learning. It's not about presenting, modeling, and tools to developers, it's just part of the application. The reason it's important, there's really two key reasons. We're building out shared ephemeral infrastructure, which is very different from the dedicated silos that we had for mission-critical applications. And this infrastructure, and the application landscape on top of it, is extremely hard to manage, and machine learning can help greatly. And I think investment in that will be driven also by a realization that this is training wheels for IOT in the sense that you're monitoring machines through data telemetry that they throw off, and you're using models to figure out how they should be operating versus how they are operating. >> So this has significant applications across IOT, ML, and how we get to volume because it's a controlled and pretty well-defined space. By that I mean, but nonetheless, it's related to the problem space, and by that I mean that bespoke applications, whether they're from AI or whatnot, are going to create new needs for new types of monitoring. But the classification of the tools and the classifications of the devices that will be monitored are pretty well-understood and they're controlled by the IT industry, so they ought to have pretty good definitions. Is that what we're thinking here, George? >> Yes, precisely, and the bespoke pieces can be modeled because they fall within a well-known domain. But I just want to add on the go to market side that keys off of what Dave Vellante said, which is that these IT operations management applications, they can come from cloud vendors, they can come from enterprise software vendors, but especially the ones that are going to be hybrid cloud are going to need enterprise sales forces to get them to market. You hear millions of, virtually millions of startups say our go to market strategy is land and expand. That doesn't get you enterprise wide, and for that you need an enterprise sales force, most expensive migratory workforce in the world, and startups don't have them. And that's why, one of the reasons, we will see roll-ups for scale. >> So we've talked about the need for scale, the impact on start-ups, the impact on big companies like IBM. One of the domains we think this is going to play out most successfully is in ITOM, IT operations management for some of these new technologies. But underneath all of this is a lot of new complexity because of distribution of function, distribution of data, distribution of application, and there needs to be a new technology concept that allows for that distribution to take place under control. And we talked about this a few weeks ago, but Jim Kobielus, what's our prediction for the world of blockchain or blockchain-like technologies are going to take in facilitating this new distribution of capability around digital business? >> Jim: Yeah, blockchain, we're predicting, it will be as fundamental to the growth of the worldwide digital infrastructure and digital markets as 40 plus, 30 to 40 years ago TCPIP was to the growth of what became the web and the internet. And why is that? Well, you know, when you look at the basic principles for development of any infrastructure where there's an innovation on the infrastructure side that is shared or standardized, robust, meaning secure, and distributed, it quickly becomes a common bond enabling growth of sharing and teaming and markets and so forth. So really, it's a layering process where we have TCPIP and you know, DNS and URL providing this shared address space. Layered on top of that was public key infrastructure, which is the foundation of the security that makes blockchain so strong. You know, PKI and SSL and all that is an enabler, that's another robust, shared common infrastructure. And then on top of that, what we see on top of that is they distributed robust shared record of transactions. That's blockchain, and really blockchain as an enabler for the new generation of digital crypto currencies such as bitcoin, enabling a shared robust and distributed currency or means of payment across the worldwide economy. So, in many ways, blockchain is an enabler for this new generation of truly robust and shared currency and transactions with a mutable, secured, shared record. It's just going to be a growth accelerator for the world economy in the 21st century going forward. >> So in many respects, technology takes off when network formation occurs. TCPIP was a foundation for network formation for distributed computing. What we're basically saying is a blockchain becomes a crucial feature of how application networks get constructed over the course of the next 10 years. Have I got that right, David Floyer? >> Absolutely, that's the key. The guy who sold the first telephone was a genius, the second was easier, and it gets easier and easier as that work grows, and blockchain is a key contributor to the development of those networks, and a one-to-one relationship, many, many one-to-one relationships that can occur from that, away from centralization and to a much more distributed environment. >> So I think we've got time for one more prediction really quickly, and I'll bring it up, and then I want to open it up for conversation because this is an interesting one. We come back to this notion of global network formation, blockchain being what we think, or blockchain-like technologies being a crucial element of that. But let's talk about how the relationship between technology, the cloud, and global economies are likely to evolve. For the most part, when people think about the cloud today, we think about US-based companies: Amazon, Microsoft, Google, Facebook, IBM also in there. But there's some other companies are going to have a say on how the cloud industry evolves over the course of the next five years: Alibaba, Tencent, Baidu. So our prediction is that in 2018, we're going to see a lot more conversation about the role that China plays in establishing some of the new rules for how cloud, application networks, and security plays on a global basis, and that's going to facilitate the emergence of Alibaba, Tencent, and Baidu, also on the global stage as cloud-computing companies. What are you guys' thoughts? Dave Vellante, let me start with you. >> Dave: Well I think we're going to see the emergence of, we've seen the emergence of the China cloud and we're going to see that seep through other parts of Asia Pacific. As we discussed earlier as a team in our private meeting, Europe is going to be a very interesting pivot point because if China can control at least portions of Europe and use that as a lure for China, that's going to give them a leg up on global cloud. >> So that leads ultimately to a series of questions about what will be the relationship between formation of cloud industries, the evolution of the cloud industries, and geopolitical concerns. And I think what we need to do, guys, is dedicate an entire research meeting to that question because it's going to be one of the most important dictators of how the industry evolves over the next few years, and ultimately how businesses and enterprises need to start establishing crucial partnerships with their key and strategic suppliers. So look in the last couple minutes we want to do our Action Item round. Now, what we do here at the Action Item show is we start off having a conversation and then we go into the Action Item, what are you going to do differently Monday as a consequence of the information we're talking about? So let's do that now, hit some Action Items, what you heard from the five, six predictions that we talked about. David Floyer, what's your Action Item? >> So my Action Item is for CIOs and CTOs, is to take a pause on IOT and look for vendors that have solutions which can be put in easily and quickly and span OT and IT in the IOT space. >> Neil Raden, what's your Action Item? >> Neil: Well, I think there's a lot of activity around AI and there's going to be an explosion of it in 2018 but most of it's not really going to be AI, it's going to be machine learning, and machine learning is really just math and floating points. AI is different. AI is neuroscience, it's neurology, it's biology and physics and sociology, it's more science. I think that some machine learning is there on the event horizon of AI, but it's not. So we need to make sure we're clear about what announcements and what technology is machine-learning versus artificial intelligence. >> Jim Kobielus, what's your Action Item? >> Jim: I think my Action Item is to revisit IBM's prospects in the AI market in deep learning going forward. And revisit on a positive note actually because IBM officially turned around their cognitive strategy in the last year. Do they focus on the power AI flight form which is really framework agnostic and so forth. And really the AI space that's actually shaping up is different from the one that IBM and others envisioned at the start of this decade, and so it really is 2018, we're going to see IBM come out strong, I believe, as a provider of, one of the providers of the core framework agnostic data deep learning development platforms in the industry, that's my prediction. >> David Vellante, what's your Action Item? >> Dave: I think if you're a startup, you really have to take a hard look at your business and the value that you're bringing to market and be honest, if you're not delivering something that the cloud guys can't deliver or don't want to deliver, then I think you've really got to think about pivoting or exiting the business that you're in. And as part of that, I think you've got to find, to George's point, distribution channels and distribution partners that can help you with go to market at scale or you're in big trouble. >> George Gilbert, Action Item. >> We've been talking about sort of the cloud wars and my recommendation to CIOs and senior IT leaders would be that if you want to hedge your bets, you don't want to be all in on one cloud, it's not dividing a workload across different clouds. Pick a cloud for a workload or for an application because its portability is, it's sort of more of a dream than a reality. It's not about moving containers around, you're in an API ecosystem, you're subject to data gravity, so it's almost like if you're going to do the equivalent of distributed computing, you're going to put some part of the application on one cloud and some part in another cloud. >> So the Action Item is be smart about the relationship between new style of applications and architecture and cloud choices. Okay, let me summarize the meeting very quickly. This has been a great conversation about predictions in 2018, you expect to see more from us over the course of the next month, this is going to be a major theme of ours in November and into December. So, quickly the findings are these. The technology industry made a major mistake with the dot com boom, and the mistake was a presumption that technology change necessarily meant economic change. That is a false assumption. The economics of technology have been pretty well understood for quite some time and they're going to assert themselves even as we go through this significant transformative period in the technology industry. And the economics of volume are going to continue to be important. And we expect that those economics, coupled with the three factors of what's driving cloud architecture decisions, the realities of physics, geopolitical concerns, and literature property concerns, are going to lead to some significant changes in 2018 that we've only just conceived of. One, we expect that we're going to see an emergence of true private cloud that will continue to be crucial to how businesses think about their information technology overall infrastructure and plant, and that's going to have an impact ultimately on where AI gets developed, more from software vendors based on volume. Two, we expect to see a significant impact on, ultimately, what happens in the VC fronted world as startups, which have historically just presumed that there was no need for go to market, that everything was going to be try and buy and then we'd scale from there, start to hit the business realities of the consistency of the economics of volume. Three, IBM we think is repositioning, and somewhat paradoxically is likely to become more successful as a consequence, as a provider of the technologies that make possible some of these new comprehensive, complex AI and related oriented technologies, and not just as a service provider. Very importantly, ITOM is going to become increasingly important and we'll see AI, machine learning be an essential feature of that, in fact, one of the places where we learn how to do it right. And the final one is lots going on with blockchain, but we expect greater distribution of applications, greater distribution of data, and the security technologies and the technologies for bringing that together and supporting the network formation of data and applications must be in place, and that's going to be a major area of technology and innovation in 2018. Alright, so this closes out our Action Item for this week. Once again, I'm Peter Burris. I'd like to, as always, thank the Wikibon team for participating with me today and we look forward to once again visiting with you from the Cube studios here in Palo Alto, California on the next Action Item. Thank you very much. (funky electronic music)