>>From around the globe. It's the cube with digital coverage of IBM. Think 20, 21 brought to you by IBM, >>Everybody welcome back to IBM. Think 2021. My name is Dave Vellante and you're watching the cubes continuous coverage of this event. We go out to the events, we extract the signal from the noise, but doing that virtually for the better part of a 14 months. Now we're going to get deeper into application modernization. Marie ASHRAE is here. She's the director of marketing at mainline information systems and David burrows. Burrows is an account executive at mainline folks. Welcome to the cube. Great to have you on today. >>Thank you. Nice to be here >>To start with with mainline. Uh, people might not be familiar with, with mainline, but you've transformed over the past five years. I wonder if you could describe that for our audience? >>Yes, we have. Indeed. We have, um, mainline, um, you know, it's a 30 plus year company and, um, and for 30 odd years we had really been focused a lot in hardware, right? Hardware reselling. That's what the market needed. That's what we did a lot of. But then in the past, I would say five to eight years, maybe even 10 years, we started on this transformation project, um, for the business where we started transforming ourselves into really systems integrators versus just hardware reseller. So now we can go to a client and we can say, Hey, now what are you struggling with? Right? What are your business challenges? And then from there, we can integrate a solution that might be hardware. It might be software, it might be some services, it could be managed services. It could be staffing services, um, could be a number of different things and put all that together and then deliver a complete solution that helps them with their, their business requirements. Okay, >>David, that, that must've been an interesting transition because what Marie just described is it used to be every opportunity was a nail and whatever box you were selling was the hammer. And, and that, that has changed dramatically. Of course. So you, you, I wonder what that discussion was like with, with, with clients. You must have heard that early on and said, Oh, this cloud thing is happening. The world is changing. We've got to change too. I wonder if you could chime in on that transformation. >>Yes. That's our, uh, as our clients have been changing, what we've been doing is, uh, you know, making sure that we fully understand what's available not only in the marketplace, but the competition and what, what each industry segment, for example, baking versus insurance versus a utility maybe facing, uh, during this this time. And so, you know, being able to transform as a, as an accounting dedicated, we've been able to, uh, indicate and so provide solutions as Marie indicated. Um, the large focus over the last five years has been networking and security as we move, uh, more compute to the edge, close to the edge. Security has been predominant. Uh, and so, you know, hardware is really almost commoditized through and through and with the exception of, you know, IBM, Z and, and power. Uh, and so, you know, we've had to really, uh, sellers, you know, focus on what customers are dealing with and how they transition. Uh, and as we, uh, you know, through COVID, it's actually been a bigger challenge, a bigger focus on security. And I think we'll talk about that a little bit later in more detail >>Let's, let's, let's do that now. So, so Marie, maybe at a high level, you could talk about those challenges that your clients are facing. And then we can sort of double click on how that was exacerbated by, by COVID. And I'm really interested in your perspectives on sort of the post isolation economy and how those challenges are going to shift, but, but maybe, maybe kick us off at the high level if you could. >>Sure. So, um, so, you know, people, companies were moving toward, um, uh, th the whole digital transformation, right? Probably for the past three to four years, we started seeing more and more that's constantly, everybody sees those buzz words all the time. Um, so clients were shifting in that direction and we were shifting to try to satisfy them with their needs with those solutions, but then came COVID and all of a sudden, right. What people were, were planning on doing for the next, let's say five years. I mean, most of the iOS were saying, yeah, we're going to get there in five years. Well, that had to happen. Right. It had to have brakes went on and it had to happen instantaneously. So that put a big change in focus, a big change in direction for not only our clients. Right. But for our own folks, folks like David, who are trying to service these clients with having to bring them these solutions that we're going to solve their digital business needs, um, today and not five years from now. >>Yeah. So David let's, let's talk about that. I mean, what Marie just described, I call it the forced March to digital, because as Maria, as you were saying, people were on a digital transformation, but there was a little bit of complacency and okay, we'll get there. We're really busy doing some other stuff. And then all of a sudden you've probably seen the meme of the COVID wrecking ball coming, coming into the building, the office building and saying, you know, well, we're doing fine. And all of a sudden, boom, the forest COVID comes in. So, so, so, so how did that affect your clients and how did you respond? I mean, they're asking for VDI and get me some laptops, I need end point security. And so how did that affect the, the application modernization efforts and David, maybe you could comment on that. >>So I, I think for, for me, the biggest challenge was all business, the competition within business to survive COVID, uh, you know, they had to put on first thing was how do we get our, our customer, uh, supported correctly and how do we get our workers supportive, working at home? So the very first thing we did over the initial six months was most companies had to transform immediately within the first 30 to 90 days to allow their workforce to work from home. Uh, that happened throughout my, my customer base, uh, both in Southern California, uh, was customers really focused on, uh, how do we business process, how do we compete in this marketplace and get return on investment speed, you know, time to value or what we invest in these, uh, COVID times so that we can compete with other, uh, businesses that are trying to stay alive, uh, through this transition. And, and now, you know, we're seeing on, uh, on the backend, uh, you know, that time, the value in terms of investment is even more important because some businesses have been significantly impacted from not only cashflow, uh, but you know, certainly in terms of profitability during this time >>Makes sense. And so I'm read, so we were talking earlier about the, sort of the initial path to digital transformation, and I wonder if that's gotta be course corrected. I would think we were forced in to compress, you know, the digital reality, uh, and, and I guess in a way that's good. Uh, but in a way it was, we probably made a lot of mistakes. It was a bit of a Petri dish. So now as we begin to knock on exit COVID, you would think those, those imperatives, uh, adjust and they start to become aligned. What's your take on that, especially as it relates to application and infrastructure modernization. >>Um, so I would agree with that. I think that there's definitely has to be a little bit of a, of a real alignment happening. And I know recently I read that, um, 20, 21 is expected to be a very, um, large year in it spend because all of those, um, initiatives that CEOs and others were going after pre COVID kind of got put on hold, right. So they could then go focus on all of those digital needs that were needed, like, you know, the CDI, you know, work at home, all the security stuff for that. So I think we're going to see, I'm thinking, we're going to see a shift again now, and maybe businesses are going to go back and try to pick up where they were, uh, prior to COVID and now start working on more of really of the application modernization, um, initiatives that were in mind. And I know we wanted to talk about that as well, because David's been working on quite a bit of application modernization with, um, a few of his clients, um, as we're seeing again, businesses change. Um, and, and I don't know that all of that changes because of COVID. I think all of that change was for their competitiveness, um, to get there anyway. So I think that's going to start, as you said before, Dave, I think it's going to start now having to >>Kind of rethink, >>It reminds me of traffic on the David, if you've ever been to driving in, in London when it's slingshots, right. It's that's what's COVID was like Murray you're absolutely right. Last year it spend was down four to 5% this year. I mean, our prediction is going to be in the six to 7% range, which, which kind of aligns with where Gartner and IDC are based on our surveys. But, you know, back in, in April, like I think the 16th of April, it was a headline in the wall street journal that the China grew 18% GDP in the quarter. So it's very hard to predict, but, but it's coming back, you know, we, we can see that David and so, so spending is really gonna accelerate. There's probably some pent-up demand for that application modernization. Maybe it's been a little bit, uh, neglected as we've done, as Maria was saying. And you were saying the work from home. So maybe you could talk a little bit more about the modernization aspects and maybe I'm really interested in the things that you guys deliver in your portfolio with IBM. >>Sure. Uh, so what I have customers in multiple phases within this, uh, current digital transformation, their customer, uh, moving everything to next gen, uh, development, which is, uh, only containerized code, uh, being able to, you know, swiftly go through their development tests, uh, and, uh, hybrid cloud environments where they're, um, they haven't made an investment yet, but they're sampling what it might be like to, uh, change into that world. And then there are customers are still in the, uh, typical environment, uh, the traditional environment, and are looking at what the solutions, as far as packages are available for them moving forward. So they can kind of skip over, uh, any kind of development and being able to, uh, leverage, uh, what I call them next, gen development or next gen systems, uh, immediately, as you know, you asked, you know, what are the, what are the systems that are available? IBM's cloud pack, uh, solution set. It provides a portfolio of capabilities, uh, both in the application, suite, database, suite security. Uh, I have customers today leveraging that. Uh, and, and so that is one of the first pieces, uh, that, that customers I see who are on the leading edge, or are also kind of trailing, are looking at, uh, these cloud packs to be able to, uh, uh, go time to market and time to value, uh, quickly. >>Yeah. So when I look at your portfolio, I just sort of scan the web. Uh, David just mentioned Marie cloud pack. I mean, we're talking software here. You guys do have a lot of expertise in ZZ Linux power, you mentioned is not a commodity. And it's one of the few pieces of hardware that, and Z they're not a commodity storage. I would think business resiliency fits in there beyond disaster recovery, your red hat, we're talking, you know, things like open OpenShift and Ansible for automation. So these are, these are not your grandfather's main line. These are toolkits are a piece of, you know, parts of the tool bag that you bring to bear to focus on on client outcomes and solutions is, am I getting that right? >>Yes, absolutely. Absolutely. Um, and again, right, that goes back to the original opening comment about how we've transformed as a business, right. To become, uh, an integrator, um, putting all of these different pieces together. I mean, I know that, um, something that, that David recently had worked on, Oh my goodness. If you would have looked at the list of pieces of elements to that solution, um, it was really quite incredible between, um, open source stuff, you know, and a bunch of IBM stuff. Um, yes, it was some storage and yeah, there was some power, um, yes, there was red hat. Right. But then there was other stuff there was VMware. Um, there was, um, some things that, um, I can't even remember now all the names to all the components, but it was, it was a laundry list. Right. And so that's where though mainline stepped in and put the pieces together, uh, for the customer so that the customer then can get done what they needed to get done, which was, which was really solve their business problem, which was trying to become more competitive in their market space. >>Okay, David, so when Maria was sustained was basically, my takeaways is as a system integrator, you've got all these piece parts with these technologies, you've got virtualization, you've got automation, you've got containers and so forth. Uh, and yes, there's there's hardware, but there's this integration that has to occur. And your job is to abstract that complexity, that underlying complexity away so that the customers can focus on the outcome. Maybe you could talk about that and how you do that. >>Sure. I'll give you a good example of a recent customer that we work with who was, uh, basically, I mean, we consider an enterprise data platform that, that, uh, was going to rework their entire data warehouse into something that had governance surrounding it, uh, where they could validate all the data that was coming into their warehouse. And so we underpinned that, uh, with an infrastructure of power, uh, we're running, uh, obviously IBM, uh, uh, pack for data, uh, with DB two warehouse. Uh, we use a combination of that with, uh, Cloudera data flow through IBM, uh, with the streaming and, uh, the governance, uh, IBM governance catalog piece, which is, uh, lots of knowledge catalog. So, uh, we've been able to take not only what their base requirements were, but all the microservices that are packaged in with cloud pack, uh, all running on OpenShift, uh, which was a great acquisition that IBM did last year. And, uh, then, uh, they also required other microservices outside, uh, to support that environment and paint a picture for >>Us as to what the future looks like. Uh, it's, it's much different than the past 30 years, uh, and bring us home please >>Or so, um, I think the future for us is to continue to, um, to find all of the solutions, um, that will, that will help our customers, um, you know, get to their next steps. Right. And, and there's a lot, as you know, there's lots of solutions out there. There's lots of new companies that are popping up all the time. Um, you know, inherently, you know, mainline is an IBM partner. We've been an IBM partner for 30 plus years since our inception. And that's the base of our business is, is IBM. But, but there are other requirements that are needed by, by businesses, by our customers. And that's where we, we reach out and partner up. We probably have gone my goodness, 200 plus partnerships with various companies, various technology companies that we can then, um, lean on and pull in those ancillary solutions, um, to, to, to complete that, that solution for the customer. >>So I think we're going to continue going down that path. We're going to continue making sure that we're partnered with the, um, the, the leading technology companies. So we can build that IBM solution for our customer and, and bolt on the other pieces that are needed. Uh, we're going to continue to grow and enhance our services business because we've got quite a large services business, whether it's implementation services, uh, we do managed services. We have staffing services. I think you're going to see if we're still going to continue to, to grow that business, because that is a piece where companies, you know, they don't want to worry about running all of that stuff, right. They want to know that their system's going to be running 24 seven. And if there is a bump or a burp or something happens, Hey, they could pick up the phone, they can call mainline. We can help them get things corrected. So I think we're going to still see a lot of that going on as well, um, within our, our, our offerings. >>Excellent. Well, congratulations for making it through that. Not a whole lot, not, not every, uh, hardware seller reseller made it through and you guys transformed. It's a, it's an inspiring story. Maria, David, thanks so much for coming on the cube. Thank you. Thank you very much. You're really welcome. And thank you for watching everybody. This is Dave Volante in our continuous coverage and the cube of IBM think 20, 21. Keep it right there.

>> Live, from San Francisco, it's theCUBE covering IBM Think 2019. Brought to you by IBM. >> Hello everyone, welcome back to theCUBE's live coverage here in San Francisco for IBM Think 2019. I'm John Furrier, Stu Miniman with theCUBE. Stu, it's been a great day. We're on our fourth day of four days of wall to wall coverage. A theme of AI, large scale compute with Cloud and data that's great. Great topics. Got two great guests here. Rohit Badlaney, who's the director of IBM Z As a Service, IBM Systems. Real great to see you. And Nataraj Nagaratnam, Distinguished Engineer and CTO and Director of Cloud Security at IBM and Hybrid Cloud, thanks for joining us. >> Glad to be here. >> So, the subtext to all the big messaging around AI and multi-cloud is that you need power to run this. Horsepower, you need big iron, you need the servers, you need the storage, but software is in the heart of all this. So you guys had some big announcements around capabilities. The Hyper Protect was a big one on the securities side but now you've got Z As a Service. We've seen Linux come on Z. So it's just another network now. It's just network computing is now tied in with cloud. Explain the offering. What's the big news? >> Sure, so two major announcements for us this week. One's around our private cloud capabilities on the platform. So we announced our IBM Cloud Private set of products fully supported on our LinuxOne systems, and what we've also announced is the extensions of those around hyper-secure workloads through a capability called the Secure Services Container, as well as giving our traditional z/OS clients cloud consumption through a capability called the z/OS Cloud Broker. So it's really looking at how do we cloudify the platform for our existing base, as well as clients looking to do digital transformation projects on-premise. How do we help them? >> This has been a key part of this. I want to just drill down this cloudification because we've been talking about how you guys are positioned for growth. All the REORG's are done. >> Sure, yeah >> The table's all set. Products have been modernized, upgraded. Now the path is pretty clear. Kind of like what Microsoft's playbook was. Build the core cloudification. Get your core set of products cloudified. Target your base of customers. Grow that and expand into the modern era. This is a key part of the strategy, right? >> Absolutely right. A key part of our private cloud strategy is targeted to our existing base and moving them forward on their cloud journey, whether they're looking to modernize parts of their application. Can we start first with where they are on-premise is really what we're after. >> Alright, also you have the Hyper Protect. >> Correct. >> What is that announcement? Can you explain Hyper Protect? >> Absolutely. Like Rohit talked about, taking our LinuxOne capabilities, now that enterprise trusts the level of assurance, the level of security that they're dependent on, on-premise and now in private cloud. We are taking that further into the public cloud offering as Hyper Protect services. So these are set of services that leverage the underlyings of security hardening that nobody else has the level of control that you can get and offering that as a service so you don't need to know Z or LinuxOne from a consumption perspective. So I'll take two examples. Hyper Protect Crypto Service is about exposing the level of control. That you can manage they keys. What we call "keep your own keys" because encryption is out there but it's all about key management so we provide that with the highest level of security that LinuxOne servers from us offer. Another example is database as a service, which runs in this Hyper Secure environment. Not only encryption and keys, but leveraging down the line pervasive encryption capabilities so nobody can even get into the box, so to say. >> Okay, so I get the encryption piece. That's solid, great. Internet encryption is always good. Containers, there's been discussions at the CNCF about containers not being part of the security boundaries and putting a VMware around it. Different schools of thought there. How do you guys look at the containerization? Does that fit into Secure Protect? Talk about that dynamic because encryption I get, but are you getting containers? >> Great question because it's about the workload, right? When people are modernizing their apps or building cloud-native apps, it's built on Kubernetes and containers. What we have done, the fantastic work across both the IBM Cloud Private on Z, as well as Hyper Protect, underlying it's all about containers, right? So as we deliver these services and for customers also to build data services as containers or VM's, they can deploy on this environment or consume these as a compute. So fundamentally it's kubernetes everywhere. That's a foundational focus for us. When it can go public, private and multicloud, and we are taking that journey into the most austere environment with a performance and scale of Z and LinuxONE. >> Alright, so Rohit, help bring us up to date. We've been talking about this hybrid and multi-cloud stuff for a number of years, and the idea we've heard for many years is, "I want to have the same stack on both ends. I want encryption all the way down to the chip set." I've heard of companies like Oracle, like IBM say, "We have resources in both. We want to do this." We understand kubernetes is not a magic layer, it takes care of a certain piece you know and we've been digging in that quite a bit. Super important, but there's more than that and there still are differences between what I'm doing in the private cloud and public cloud just naturally. Public cloud, I'm really limited to how many data centers, private cloud, everything's different. Help us understand what's the same, what's different. How do we sort that out in 2019? >> Sure, from a brand perspective we're looking at private cloud in our IBM Cloud Private set of products and standardizing on that from a kubernetes perspective, but also in a public cloud, we're standardizing on kubernetes. The key secret source is our Secure Services Container under there. It's the same technology that we use under our Blockchain Platform. Right, it brings the Z differentiation for hyper-security, lockdown, where you can run the most secure workloads, and we're standardizing that on both public and private cloud. Now, of course, there are key differences, right? We're standardizing on a different set of workloads on-premise. We're focusing on containerizing on-premise. That journey to move for the public cloud, we still need to get there. >> And the container piece is super important. Can you explain the piece around, if I've got multi-cloud going on, Z becomes a critical node on the network because if you have an on-premise base, Z's been very popular, LinuxONE has been really popular, but it's been for the big banks, and it seems like the big, you know, it's big ire, it's IBM, right? But it's not just the mainframe. It's not proprietary software anymore, it's essentially large-scale capability. >> Right. >> So now, when that gets factored into the pool of resources and cloud, how should customers look at Z? How should they look at the equation? Because this seems to me like an interesting vector into adding more head room for you guys, at least on the product side, but for a customer, it's not just a use case for the big banks, or doing big backups, it seems to have more legs now. Can you explain where this fits into the big picture? Because why wouldn't someone want to have a high performant? >> Why don't I use a customer example? I had a great session this morning with Brad Chun from Shuttle Fund, who joined us on stage. They know financial industry. They are building a Fintech capability called Digital Asset Custody Services. It's about how you digitize your asset, how do you tokenize them, how you secure it. So when they look at it from that perspective, they've been partnering with us, it's a classic hybrid workload where they've deployed some of the apps on the private cloud and on-premise with Z/LinuxONE and reaching out to the cloud using the Hyper Protect services. So when they bring this together, built on Blockchain under the covers, they're bringing the capability being agile to the market, the ability for them to innovate and deliver with speed, but with the level of capability. So from that perspective, it's a Fintech, but they are not the largest banks that you may know of, but that's the kind of innovation it enables, even if you don't have quote, unquote a mainframe or a Z. >> This gives you guys more power, and literally, sense of pretty more reach in the market because what containers and now these kubernetes, for example, Ginni Rometty said "kubernetes" twice in her keynote. I'm like, "Oh my God. The CEO of IBM said 'kubernetes' twice." We used to joke about it. Only geeks know about kubernetes. Here she is talking about kubernetes. Containers, kubernetes, and now service missions around the corner give you guys reach into the public cloud to extend the Z capability without foreclosing the benefits of Z. So that seems to be a trend. Who's the target for that? Give me an example of who's the customer or use case? What's the situation that would allow me to take advantage of cloud and extend the capability to Z? >> If you just step back, what we're really trying to do is create a higher shorten zone in our cloud called Hyper Protect. It's targeted to our existing Z base, who want to move on this enterprise out journey, but it's also targeted to clients like Shuttle Fund and DAX that Raj talked about that are building these hyper secure apps in the cloud and want the capabilities of the platform, but wanted more cloud-native style. It's the breadth of moving our existing base to the cloud, but also these new security developers who want to do enterprise development in the cloud. >> Security is key. That's the big drive. >> And that's the beauty of Z. That's what it brings to the table. And to a cloud is the hyper lockdown, the scale, the performance, all those characteristics. >> We know that security is always an on-going journey, but one of the ones that has a lot of people concerned is when we start adding IoT into the mix. It increased the surface area by orders of magnitude. How do those type of applications fit into these offerings? >> Great question. As a matter of fact, I didn't give you the question by the way, but this morning, KONE joined me on stage. >> We actually talked about it on Twitter. (laughs) >> KONE joined us on stage. It's about in the residential workflow, how they're enabling here their integration, access, and identity into that. As an example, they're building on our IoT platform and then they integrate with security services. That's the beauty of this. Rohit talked about developers, right? So when developers build it, our mission is to make it simple for a developer to build secure applications. With security skill shortage, you can't expect every developer to be a security geek, right? So we're making it simple, so that you can kind of connect your IoT to your business process and your back-end application seamlessly in a multi-cloud and hybrid-cloud fashion. That's where both from a cloud native perspective comes in, and building some of these sensitive applications on Hyper Protect or Z/LinuxONE and private cloud enables that end to end. >> I want to get you guys take while you're here because one of the things I've observed here at Think, which is clearly the theme is Cloud AI and developers all kind of coming together. I mean, AI, Amazon's event, AI, AI, AI, in cloud scale, you guys don't have that. But developer angle is really interesting. And you guys have a product called IBM Cloud Private, which seems to be a very big centerpiece of the strategy. What is this product? Why is it important? It seems to be part of all the key innovative parts that we see evolving out of the thing. Can you explain what is the IBM Cloud Private and how does it fit into the puzzle? >> Let me take a pass at it Raj. In a way it is, well, we really see IBM Cloud Private as that key linchpin on-premise. It's a Platform as a Service product on-premise, it's built on kubernetes and darker containers, but what it really brings is that standardized cloud consumption for containerized apps on-premise. We've expanded that, of course, to our Z footprint, and let me give you a use case of clients and how they use it. We're working with a very big, regulated bank that's looking to modernize a massive monolithic piece of WebSphere application server on-premise and break it down into micro-services. They're doing that on IBM Cloud Private. They've containerized big parts of the application on WebSphere on-premise. Now they've not made that journey to the cloud, to the public cloud, but they are using... How do you modernize your existing footprint into a more containerized micro-services one? >> So this is the trend we're seeing, the decomposition of monolithic apps on-premise is step one. Let's get that down, get the culture, and attract the new, younger people who come in, not the older guys like me, mini-computer days. Really make it ready, composable, then they're ready to go to the cloud. This seems to be the steps. Talk about that dynamic, Raj, from a technical perspective. How hard is it to do that? Is it a heavy lift? Is it pretty straight-forward? >> Great question. IBM, we're all about open, right? So when it comes to our cloud strategy open is the centerpiece offered, that's why we have banked on kubernetes and containers as that standardization layer. This way you can move a workflow from private to public, even ICP can be on other cloud vendors as well, not just IBM Cloud. So it's a private cloud that customers can manage, or in the public cloud or IBM kubernetes that we manage for them. Then it's about the app, the containerized app that can be moved around and that's where our announcements about Multicloud Manager, that we made late last year come into play, which helps you seamlessly move and integrate applications that are deployed on communities across private, public or multicloud. So that abstraction venire enables that to happen and that's why the open... >> So it's an operational construct? Not an IBM product, per say, if you think about it that way. So the question I have for you, I know Stu wants to jump in, he's got some questions. I want to get to this new mindset. The world's flipped upside down. The applications and workloads are dictating architecture and programmability to the DevOps, or infrastructure, in this case, Z or cloud. This is changing the game on how the cloud selection is. So we've been having a debate on theCUBE here, publicly, that in some cases it's the best cloud for the job decision, not a procurement, "I need multi-vendor cloud," versus I have a workload that runs best with this cloud. And it might be as if you're running 365, or G Suite as Google, Amazon's got something so it seems to be the trend. Do you agree with that? And certainly, there'll be many clouds. We think that's true, it's already happened. Your thoughts on this workload driving the requirements for the cloud? Whether it's a sole purpose cloud, meaning for the app. >> That's right. I'll start and Rohit will add in as well. That's where this chapter two comes into play, as we call Chapter Two of Cloud because it is about how do you take enterprise applications, the mission-critical complex workloads, and then look for the enablers. How do you make that modernization seamless? How do you make the cloud native seamless? So in that particular journey, is where IBM cloud and our Multicloud and Hybrid Cloud strategy come into play to make that transition happen and provide the set of capabilities that enterprises are looking for to move their critical workloads across private and public in bit much more assurance and performance and scale, and that's where the work that we are doing with Z, LinuxONE set of as an underpinning to embark on the journey to move those critical workloads to their cloud. So you're absolutely right. When they look at which cloud to go, it's about capabilities, the tools, the management orchestration layers that a cloud provider or a cloud vendor provide and it's not only just about IBM Public Cloud, but it's about enabling the enterprises to provide them the choice and then offer. >> So it's not multicloud for multicloud sake, it's multicloud, that's the reality. Workload drives the functionality. >> Absolutely. We see that as well. >> Validated on theCUBE by the gurus of IBM. The cloud for the job is the best solution. >> So I guess to kind of put a bow on this, the journey we're having is talking about distributed architectures, and you know, we're down on the weeds, we've got micro-services architectures, containerization, and we're working at making those things more secure. Obviously, there's still a little bit more work to do there, but what's next is we look forward, what are the challenges customers have. They live in this, you know, heterogeneous multicloud world. What do we have to do as an industry? Where is IBM making sure that they have a leadership position? >> From my perspective, I think really the next big wave of cloud is going to be looking at those enterprise workloads. It's funny, I was just having a conversation with a very big bank in the Netherlands, and they were, of course, a very big Z client, and asking us about the breadth of our cloud strategy and how they can move forward. Really looking at a private cloud strategy helping them modernize, and then looking at which targeted workloads they could move to public cloud is going to be the next frontier. And those 80 percent of workloads that haven't moved. >> An integration is key, and for you guys competitive strategy-wise, you've got a lot of business applications running on IBM's huge customer base. Focus on those. >> Yes. >> And then give them the path to the cloud. The integration piece is where the linchpin is and OSSI secure. >> Enterprise out guys. >> Love encryption, love to follow up more on the secure container thing, I think that's a great topic. We'll follow-up after this show Raj. Thanks for coming on. theCUBE coverage here. I'm John Furrier, Stu Miniman. Live coverage, day four, here live in San Francisco for IBM Think 2019. Stay with us more. Our next guests will be here right after a short break. (upbeat music)

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and it's ecosystem partners. >> Welcome back to theCUBE. We are continuing our coverage of VMworld 2018 day 3. I'm Lisa Martin, with two very stylish men next to me. I'm quite impressed. Dave Vellante, my esteemed co-host. >> Oh shucks. >> Rocking the salmon, King Salmon Vellante. And The Zog is back, Eric Herzog. Great to have you back. I was looking at you on Twitter and you have been on theCUBE 17 times. Is this 18 or 19? >> You know, I think Dave said I was on one of the very first CUBEs way back in 2010. So I've been on a few. >> That's a whole other criteria of VIP level. Well thank you for coming back. You have been, not only is he, you can't do a CUBE without Eric Herzog. You've been everywhere all over VMworld. I saw you're speaking at IBM booth on VMware and IBM, you're at Cisco, you're giving sessions. How do you fit it all in and still have time for us? >> Well, I always make time for theCUBE. >> Always? Thank you, thanks for that. >> Always make time for you guys. Love talking to CUBE. You guys have been very helpful. We appreciate everything that you do. Love doing shows, love 'em. I may be 60 years old, but I'm really 18 down underneath, so if I only sleep three hours a night, not a problem. >> What do you love about them? I mean, is it? >> Number one is meeting customers. Customers and channel partners, right? Well, all of the employees of all the various companies here get a paycheck from whoever that may be, me, IBM, someone from other companies, people from VMware. That's not who pays your salary. It's the end-users and the channel partners, if they buy through the channel. They're the ones that really pay your salary. So being close to the customers and the partners is number one. Second thing, of course, is seeing all the cool technology. You know, seeing what's going on, what's hot, what can we leverage from our perspective, what can we tie ourselves to. So for example, the hot things, that IBM's really been doing from a storage perspective. Cloud and modern data protection. Those are the two big things we've been focused on for the last couple of years. And how do we integrate our storage solutions and our modern data protection with cloud infrastructure, and then also how do we, if you're not in the cloud, how do we help customers protect their data better in a modern way and reuse their secondary data, instead of making 27,000 copies of the same data. >> So when theCUBE first started at VMworld, modern data protection at the time was dealing with the lack of physical resources, 'cause you went from 10 servers down to one, and you didn't have all that excess capacity to do a run up back up job anymore. Today, modern data protection is all around cloud and multi-cloud and software defined, so I wonder if you can help us sort of paint a picture of what modern data protection is for IBM? >> Sure, I think there's a couple, couple aspects too. So, first of all, you have to support the cloud, and that's two ways. So for us, several of our backup products are used by cloud service providers. In some cases they use our name, and say, "Featuring IBM Spectrum Protect or Spectrum Protect Plus." Other cases, they have their own brand but it's our software underneath the hood so that if the end user is backing up to their cloud, they're actually using our software. So that's item number one. The second thing is you need to make sure that your traditional storage software can TEAR to the cloud, can migrate data to the cloud, can transparently move data to the cloud in an automated fashion using AI. So using artificial intelligent when the data's hot if you connote a target, and that target could be a cloud, and when the data's hot it TEARs the data to the cloud. Sorry, when it's cold. When it's hot it pulls it back in and that needs to be all automated through AI base. So we've done both, we have our backup software which is available from several cloud providers as a backup as a service, we also offer it through the cloud so IBM Cloud actually sells spectrum protect backup as a service solution All of our primary storage software and even our spectrum scale software can automatically TEAR data to a cloud target device. >> Eric I got to ask you so TEARing used to be predominantly, correct me if you disagree but, it used be a one way trip to the bit-bucket. You just described going there and coming back. Has cloud changed that because of big data, analytics? Where people want to pull back data increasingly? >> So I think of a couple of things. So first of all, there's no doubt that the world is data driven. The most valuable asset isn't gold, it's not silver, it is absolutely not oil, it's not diamonds. It is data. And it doesn't matter whether you're one of the largest banks in the world, you're in manufacturing, you're in the government, or whether you're Herzog's barn grill. The data is your most valuable asset. What you do with your customer data, how you manage your business, what you do with your supply chain if your a services company, how are you servicing, what are you charging, what are you billing, all of that is the most critical thing that you have. So in a data driven world, its critical that you use the data. And that also means that because of valued data, when you backup the data or you snapshot or replicate the data, you now created a secondary copy. Well what if you could use it to do tests? What if you could use it to do big data analytics? What if you could use it for DevOps? So instead of making one copy for tests, one copy for disaster recovery, one copy for this, and have basically a plethora of copies all over the place, with what we've provided in modern data protection, you can use a backup, you can use a snap or a replica, and you can use that to do tests or development or to do big data analytics. And using that one copy not making multiple copies. So that's- >> I just want to pick up on something you said there's going to be some folks in our audience like, "yeah yeah we hear that data is more valuable than oil or more valuable than gold, et cetera, more valuable than platinum." There's evidence, if you look at the market value of the top five companies, Apple, Facebook, Microsoft, Google, and Amazon, they've surpassed the banks, they've surpassed the energy companies, and I would argue its cuz of data. People are recognizing that they're data companies, you agree? >> But if you look at that name the only one that actually builds anything of substance, as a fair amount of their volume of revenue, is Apple. >> Is Apple, right. >> Amazon doesn't, they ship stuff. Facebook clearly doesn't, Google has a few things but not really builds stuff its really about the data. Absolutely and if your a more traditional company like a bank or someone building the table. Whoever builds this table if they have their act together and they're using that data right, they're building the table cheaper than anyone else, they're shipping it to theCUBE cheaper than anyone else could ship it to you. They got more colors because they know what their doing. And they ship you the right color table and they don't screw it up and send you a black table when you want it this color table because black won't show up on theCUBE very well. The more you do that the more money you make. Even something as simple as a table manufacturer. And that's all about the data and how you use that data. >> So Eric you love talking with customers which is great as the CMO for IBM storage. Got to talk to those customers. Let's talk about how you're seeing customers take the efficiencies of what IBM is doing with data protection, storage, et cetera. to be able to harness the power of AI, the superpowers that Pat Gelsinger talked about on Monday, and transform their businesses. Give us some of your favorite customer examples where its really revolutionary. >> So we had a great example today, we did a panel with a bunch of end users as part of the show agenda. And one of the customers is a provider of softwares of service to universities and schools. 45,000 customers between the universities, junior colleges, schools districts, et cetera. In North America so Canada and the U.S. And they are doing softwares of service so for them performance is critical, they can't go down. All of the college bookstores, if you go into a college bookstore, all of the infrastructure behind that is them. So they're called Follet. So a couple of things, one because they're doing softwares of service and managing all that. Its critical, can't go down. Got to be available, it's got to be performant, it's got to be resilient, it's got to be reliable. So that's how the storage melds in. From modern data protection the way it melds in is how many books did Dave buy? What did Eric buy? Oh is Dave buying a used book? Or is Eric buying a new book? Okay say we know that the propensity is certain of members of the community. I went to UC Davis, University of California Davis, are going to buy used books, Dave, whereas Herzog's going to buy new. They can figure that out, how many used books they need, how many new books they need, that's all about efficiency and how they make more money. What are the store hours? Certain universities it's this, other universities it's that. What do they do in the winter time? At UC Davis you can go in the winter time, I know you went to school in Boston its probably snowing, no one's going in the bookstore in the wintertime. >> Trend towards book rentals, how do we capitalize on that? >> That's all they do. One of the things they talked about was how they always have to protect that data and back it up. The other thing they talked about was they have to assume a lot of capacity. So what they do is they bought assuming they would have to refresh in 18 months. And because our storage arrays have a ton of different data reduction technology whether that be block, D2, compression, et cetera. And they have petabytes of data. Petabytes. 12 Petabytes. They've actually calculated it out they won't need to buy new storage for 36 months instead of 18 so they just saved on CapX. Through the intelligence of the storage. So in that case you've got both modern data protection and you've got a storage message. One of our other customers who's a public reference, not here at the show, which is a hospital, they were backing up all their data, both cloud and on premise with our backup software, and they went down and their entire system went down and they didn't lose one stitch of data and its a hospital. It's a teaching hospital, think they're in Pennsylvania, and in the public reference in the video he said, "and we went down and off that backup we were able to get all of the data back. We didn't lose any patient data, we didn't lose any research data, we didn't lose any billing data, if you break your arm they do bill you, they didn't lose anything." >> That's not just money, that's lives so that's huge. >> Absolutely. >> I want to ask you about you know that table example you were giving, and we were talking about the big five companies in terms of market cap being data orientated. There seems to be a gap between those sort of traditional companies and those data companies and that gap tends to be the data is often is often in silos its human expertise or expertise around a bottling plant or the manufacturing plant or whatever it is versus a data model with humans who understand how to leverage that data. Do you see, whether its through new data protection techniques or other storage techniques that IBM is working on, ways to help customers break down those data silos so they can become more digital and be able to take advantage of data? >> So I think there's a couple of things. So first of all at the very tactical level we provide this automated IA based data TEARing. We can tear from anything to anything so we can take data from an IBM array and TEAR it to an EMC array. We can take data from an EMC array and TEAR it to a net app array. A net app array to a Tachi array, an HP array back to our array, so we can do this transparent data move based on hot and cold. Not only does that allow you to control CapX and OpX you can move the data from array to array, and once you move that data set it might be working that other array could be hooked up to a different set of servers through the SAN that's running a different workload and then takes that dataset and use it with that other piece of software out on the server side. So that's item number one. Item number two is IBM not just in the storage but overall has a global program where IBM is promoting, through universities all over the world, data scientists. Part of that is training data scientists not only how to do the science of data and analyzing data and mining data and doing it, but to break down those walls. The value is more there. And we also have from a storage perspective some products are spectrum scale products, one of our customers who's one of the largest banks in the world they run 300,000 servers attached to a giant spectrum scale repository, petabytes and petabytes, and they do real time data analytics to see if Dave Vellante or Lisa's credit card was stolen. >> Thank you! >> Oh yes, thank you! >> So that's real world analytics they run but they need petabytes of data. And then with our IBM cloud object storage technology where we have several customers at the exabyte level in production with an exabyte of data, you put the data out when its cold but guess what, if you want to mine it you might want to pull it back and guess what, you can TEAR data from spectrum scale to IBM cloud object storage and then spectrum scale can pull it back in to do the big data analytic workloads. >> And that AI you're using is it heavy open source? Is there a little bit of Watson sprinkled in there? >> It's stuff the storage division developed years ago and then has peppered in the AI based technology into that software to determine when the dataset is hot or cold and then move it back or forth. We also do the old style, so if you go back 10 years ago, the automation of storage was policy based. So we had it way back when which was if the data is 30 days old move it to this array. >> The old HSM kind of... >> Yeah and it was automated so once it hit 30 days, but now what we've done is, we started with that, what I would call automation, and now we've moved that to AI. And by the way, if you still want to do it the old way and say move this data when its 60 days old, you can still do that. But the modern way is let the storage figure out for you and move it back and forth whether it be to the cloud or whether it be on premises. >> So it's intelligent hierarchical storage management? So if the characteristics change the system knows what to do as opposed to- >> So when it's hot it'll pull the data back into flash, for example, when its cold it'll put it out to cloud, it'll put it out to tape or it'll put it out to slow hard drives, either way. >> Alright Eric, so we're almost out of time here. You've been at IBM a long time, IBM's been around a long time, you said you even have customers at exabyte scale. I'm hearing heterogeneity, customer choice, but if I'm a small hospital in the middle of America and I have choice with data protection vendors, storage vendors, some smaller than IBM that might be able to move faster, what are the top three differentiators of why I would want to go with IBM's storage solutions? >> Sure so the first thing is our broad portfolio. Whether it be file block or object, whether it be modern data protection, whether it be archiving if you still want to use tape, we're the number one provider of tape in the world and we sell gobs of it to the web scale guys. >> Of course you do. >> They're the guys that buy it. >> Cuz its cost effective. >> So we've got one throat to choke, all of it talks to each other, and happens to work with all the cloud vendors not just IBM cloud. We work with Amazon, we work with Microsoft, we work with Google, and we work with IBM's own cloud. So we can work with anything. That's out of mind. Second thing, for smaller shops we have a network of business partners all over the world, some of them even deal with the big global Fortune 500 and others deal with small accounts. And then really the third thing is that IBM makes sure that our stuff works with everyone else's stuff. Whether that be cloud, our spectrum tech software which has been around for years and is the leading enterprise backup package, the bulk of what it backs up is not IBM storage. The vast bulk of it is from two of the competitors on the floor of this show, they also back up our stuff too. And we backup everyone's. There's probably 20 storage vendors we backup every one of their data. So if someone buys storage from XYZ, call me, we can back it up. If someone buys it from one of the big competitors we back it up, from us we back it up. So the fact that our software works with everyone's gear is of an advantage for both the small shop and the big shop. We make sure that our software, whether its embedded in our arrays or whether we sell it as just a pieces storage software and we are the number one storage software provider on the planet as well, we can meet the needs of any company big or small because we have this flexibility of working with our stuff and working with everybody else stuff and most of the other guys don't do that. If its a small shop their stuff usually only works with their stuff. >> And from a support perspective, you play with everybody? >> Global network. I mean we're known for our support whether it be IBM direct or what we do with our partners all the partners are certified, its a big certification process, and if they can't certify the product they can't sell IBM's stuff. That's just how we operate. Other people, if they can move a lot of boxes but they don't have anyone pick up the phone or can come out to Dave's house to install, they let them sell, we don't do that at IBM. We don't use those box mover types we go for guys that add value and know how to work with the cloud, know how to do hybrid cloud. One of our resellers designed a Watson based AI system that's used in bottle factories. Packaging. Beer, soda, milk, and it can figure out if its full or not full, if the bottle or can or carton is damaged. And they used Watson to do it. Now they're regular resell. They resell all the storage, they resell our power, they resell mainframe, but they've gone into the software development side using this Watson thing and they're selling a full solution with the software included to bottling plants all over the world. >> Wow, Eric. This has been a super charged conversation. Thanks for stopping by and talking with Dave and me about not just your excitement about talking with customers but really how IBM is really empowering customers of any size worldwide to succeed. We know we'll see you again soon but thanks for stopping by a couple of times this week. >> Great well thank you. Thank you, really appreciate the time. >> And the outfit choices are just on point guys, you blend well too. For Eric, Dave Vellante, I am Lisa Martin, you're watching theCUBE live from VMworld 2018 day 3. Stick around, we'll be back with our next guest after a short break. (electro music)

>> Live from Orlando, Florida, it's theCUBE, covering Cisco Live 2018. Brought to you by Cisco, NetApp, and theCUBE's ecosystem partners. >> Hello, everyone. Welcome back to theCUBE's live coverage here in Orlando, Florida for Cisco Live 2018. I'm John Furrier with Stu Miniman. Our next guest, Eric Herzog, Chief Marketing Officer and Vice President Global Channel Sales for IBM Storage. CUBE alum, great to see you. Thanks for comin' by. >> Great, we always love comin' and talkin' to theCUBE. >> Love havin' you on. Get the insight, and you get down and dirty in the storage. But I gotta, before we get into the storage impact, the cloud, and all the great performance requirements, and software you guys are building, news is that the CEO of Cisco swung by your booth? >> Yes, Chuck did come by today and asked how-- Chuck Robbins came by today, asked how we're doin'. IBM has a very broad relationship with Cisco, beyond just the storage division. The storage division, the IOT division, the collaboration group. Security's doin' a lot of stuff with them. IBM is one of Cisco's largest resellers through the GTS and GBS teams. So, he came by to see how were doin', and gave him a little plug about the VersaStack, and how it's better than any other converge solutions, but talked about all of IBM, and the strong IBM Cisco relationship. >> I mean, it's not a new relationship. Expand on what you guys are doin'. How does that intersect with division that he put on stage yesterday with the keynote. He laid out, and said publicly, and put the stake in the ground, pretty firmly, "This is the old way." Put an architecture, a firewall, a classic enterprise network diagram. >> Right, right. >> And said, "That's the old way," and put in a big circle, with all these different kinda capabilities with the cloud. It's a software defined world. Clearly Cisco moving up the stack, while maintaining the networking shops. >> Right. >> Networking and storage, always the linchpin of cloud and enterprise computing. What's the connection? Share the touch points. >> Sure, well I think the key thing is everyone's gotta realize that whether you're in a private cloud, a hybrid cloud, or a public cloud configuration, storage is that rock solid foundation. If you don't have a good foundation, the building will fall right over, and it's great that you've got cloud with its flexibility, it's ability to transform, the ability to modernize, move data around, but if what's underneath doesn't work, the whole thing topples over, and storage is a cruel element to that. Now, what we've done at IBM is we have made all of our solutions on the storage side, VersaStack, our all-flash arrays, all of our software defined storage, our modern data protection, everything is what we'll say is cloudified. K, it's, I designed for multiple cloud scenarios, whether it be private, hybrid, or public, or, as you've probably seen, in some the enterprise accounts, they actually use multiple public cloud providers. Whether it be from a price issue, or a legal issues, because they're all over the world, and we're supporting that with all our solutions. And, our VersaStack, specifically, just had a CVD done with Cisco, Cisco Validated Design, with IBM Cloud Private on a VersaStack. >> Talk about the scale piece, because this becomes the key differentiator. We've talked about on theCUBE, many of the times with you around, some of the performance you guys have, and the numbers are pretty good. You might wanna do a quick review on that. I'm not lookin' for speech and feeds. Really, Eric, I'd like to get your reaction, and view, and vision, on how the scale piece is kicking, 'cause clients want scale optionality. They're gonna have a lot of stuff on premise. They have cloud goin' on, multi cloud on the horizon, but they gotta scale. The numbers are off the charts. You're seein' all these security threats. I mean, it's massive. How are you guys addressing the scale question with storage? >> So, we've got a couple things. So first of all, the storage itself is easily scalable. For example, on our A9000 all-flash array, you just put a new one, automatically grows, don't have to do anything, k? With our transparent cloud tiering, you can set it up, whether it be our Spectrum Scale software, whether it be our Spectrum Virtualize software, or whether it be on our all-flash arrays, that you could automatically just move data to whatever your cloud target may be. Whether that be something with an object store, whether that be a block store, and it's all automated. So, the key thing here on scalability is transparency, ease of use, and automation. They wanna automatically join new capacity, wanna automatically move data from cloud to cloud, automatically move data from on premise to cloud, automatically move data from on premise to on premise, and IBM's storage solutions, from a software perspective, are all designed with that data mobility in mind, and that transportability, both on premise, and out to any cloud infrastructure they have. >> What should Cisco customers know about IBM storage, if you get to talk to them directly? We're here at Cisco Live. We've talked many times about what you guys got goin' on with the software. Love the software systems approach. You know we dig that. But a Cisco deployment, they've been blocking and tackling in the enterprise for years, clouds there. What's the pitch? What's the value proposition to Cisco clients? >> So, I think they key thing for us talkin' to a Cisco client is the deep level of integration we have. And, in this case, not just the storage division, but other things. So, for example, a lot of their collaboration stuff uses under pitting software from IBM, and IBM also uses some software from Cisco inside our collaboration package. In our storage package, the fact that we put together the VersaStack with all these Cisco Validated Designs, means that the customer, whether it be a cloud product, for example, on the VersaStack, about 20 of our public references are all small and medium cloud providers that wheel in the VersaStack, connect 'em, and it automatically grows simply and easily. So, in that case, you're looking at a cloud provider customer of Cisco, right? When you're looking at a enterprise customer of Cisco, man, the key thing is the level of integration that we have, and how we work together across the board, and the fact that we have all these Cisco Validated Designs for object storage, for file storage, for block storage, for IBM Cloud Private. All these things mean they know that it's gonna work, right outta the box, and whether they deploy it themselves, whether they use one of our resellers, one of our channel partners, or whether they use IBM services or Cisco service. Bottom line, it works right out of the box, easy to go, and they're up and running quickly. >> So, Eric, you talked a bunch about VersaStack, and you've been involved with Cisco and their UCS since the early days when they came up, and helped drive, really, this wave of converged infrastructure. >> Right. >> One of the biggest changes I've seen in the last couple years, is when you talk to customers, this is really their private cloud platform that they're building. When it first got rolled out, it was virtualization. We kinda added a little bit of management there. What, give us your viewpoint as to kinda high-level, why's this still such an important space, what are the reasons that customers are rolling this out, and how that fits into their overall cloud story? >> Well, I think you hit it, Stu, right on the head. First of all, it's easy to put in and deploy, k? That is a big check box. You're done, ready to go. Second thing that's important is be able to move data around easily, k? In an automated fashion like I said earlier, whether that be to a public cloud if they're gonna tier out. If I'm a private cloud, I got multiple data centers. I'm moving data around all the time. So, the physical infrastructure and data center A is a replica, or a DR center, for data center B, and vice versa. So, you gotta be able to move all this stuff around quickly easy. Part of the reason you're seeing converge infrastructure is it's the wave of what's hit in the server world. Instead of racking and stacking individual servers, and individual pieces of storage, you've got a pre-packed VersaStack. You've got Cisco networking, Cisco server, VMware, all of our storage, our storage software, including the ability to go out to a cloud, or with our ICP IBM Private Cloud, to create a private cloud. And so, that's why you're seeing this move towards converge. Yes, there's some hyperconverged out there in the market, too, but I think the big issue, in certain workloads, hyperconverged is the right way to go. In other workloads, especially if you're creating a giant private cloud, or if you're a cloud provider, that's not the way to go because the real difference is with hyperconverged you cannot scale compute and storage independently, you scale them together, So, if you need more storage, you scale compute, even if you don't need it. With regular converge, you scale them independently, and if you need more storage, you get more storage. If you need more compute-- If you need both, you get both. And that's a big advantage. You wanna keep the capex and opex down as you create this infrastructure for cloud. 'Member, part of the whole idea of cloud are a couple things. A, it's supposed to be agile. B, it's supposed to be super flexible. C, of course, is the modern nomenclature, but D is reduce capex and opex. And you wanna make sure that you can do that simply and easily, and VersaStack, and our relationship with Cisco, even if you're not using a VersaStack config, allows us to do that for the end user. >> And somethin' we're seeing is it's really the first step for customers. I need to quote, as you said, modernize the platform, and then I can really start looking at modernizing my applications on top of that. >> Right. Well, I think, today, it's all about how do you create the new app? What are you doin' with containers? So, for example, all of our arrays, and all of our arrays that go into a VersaStack, have free persistent storage support for any containerize environ, for dockers and kubernetes, and we don't charge for that. You just get it for free. So, when you buy those solutions, you know that as you move to the container world, and I would argue virtualization is still here to stay, but that doesn't mean that containers aren't gonna overtake it. And if I was the CEO of a couple different virtualization companies, I'd be thinkin' about buyin' a container company 'cause that'll be the next wave of the future, and you'll say-- >> Don't fear kubernetes. >> Yeah, all of that. >> Yeah, Eric Herzog's flying over to Dockercon, make a big announcement, I think, so. (laughing) >> Evaluation gonna drop a little bit. I gotta ask you a question. I mean, obviously, we watch the trends that David Floy and our team, NVMe is big topic. What is the NVMe leadership plan for you, on the product side, for you? Can you take a minute to share your vision for what that is gonna be? >> Sure, well we've already publicly announced. We've been shipping an NVMe over fabric solution leveraging InfiniBand since February of this year, and we demoed it, actually, in December at the AI Conference in New York City. So, we've had a fabric solution for NVMe already since December, and then shipping in February. The other thing we're doing is we publicly announced that we'd be supporting the other NVMe over fabric protocols, both fabric channel and ethernet by the end of the year. We publicly already announced that. We also announced that we would have an end to end strategy. In this case, you would be talking about NVMe on the fabric side going out to the switching and the host infrastructure, but also NVMe in a storage sub-system, and we already publicly announced that we'd be doing that this year. >> And how's the progress on that plan? You feel good about it? >> We're getting there. I can't comment yet, but just stay tuned on July 1st, and see what happens. >> So, talk about the Spectrum NAS, and other announcements that you have. What's goin' on? What are the big news? What's happening? >> Well, I think that, yeah, the big thing for us has been all about software. As you know, for the analysts that track the numbers, we are, and ended up in 2017, as tied as the number one storage software company in the world, independent of our system's business. So, one of the key powers there is that our software works with everyone's gear, whether it be a white box through a distributor or reseller, whether it be our direct competitors. Spectrum Protect, which is a, one of the best enterprise backup packages. We backup everybody's gear, our gear, NetApp's gear, HP's gear, Pure's gear, Hitachi's gear, the old Dell stuff, it doesn't matter to us, we backup everything. So, one of the powers that IBM has, from a software perspective, is always being able to support not only our own gear, but supporting all of our competitors as well. And the whole white box market, with things that our partners may put together through the distributors. >> I know somethin' might be obvious to you, but just take me through the benefits to the customer. What's the impact to the customer? Obviously, supporting everything, it sounds like you guys have done that with software, so you're agnostic on hardware. >> Right. >> So, is it a single pane of glass? What's the benefit to the customer with that software capability? >> Yeah, I feel there's a couple things. So, first of all, the same software that we sell as standalone software, we also sell on our arrays. So if you're in a hybrid configuration, and you're using our Flashsystem V9000 in our Storwize family, that software also works with an EMC, or NetApp box. So, one license, one way to do everything, one set of training, which in a small shop is not that important, but in a big shop, you don't have to manage three licenses, right? You don't have to get trained up on three different ways to do things, and you don't have to, by the way, document, which all the big companies would do. So it dramatically simplifies their life from an opex perspective. Makes it easier for them to run their business. >> Eric, we'd love to get your opinion on just how's Cisco doin' out there? It's a big sprawling company. I looked at the opening keynote, the large infrastructure business doing very well in the data center, but they've got collaboration, they do video, they're moving out in the cloud. Wanna see your thoughts as to how are they doing, and still making sure they take care of core networking, while still expanding and going through their own transformation, that they're talkin' very public about. How do we measure Cisco as a software company? >> Well, we see some very good signs there. I mean, we partner with 'em all the time, as I mentioned, for example, in both the security group and our collaboration group, and I'm not talkin' storage now, just IBM in general, we leverage software from them, and they leverage software from us. We deliver joint solutions through our partners, or through each of the two service organizations, but we also have products where we incorporate their software into ours, and they incorporate software in us. So, from our perspective, we've already been doing it beyond their level, now, of expanding into a much greater software play. For us, it's been a strong play for us already because of the joint work we've been doing now for several years on software that they've been selling in the more traditional world, and now pushing out into the broader areas, like cloud, for example. >> Awesome work. Eric, thanks for coming on. I gotta ask you one final, personal, question. >> Sure. >> You got the white shirt on, you usually have a Hawaiian shirt on. >> Well, because Chuck Robbins came by the booth, as we talked about earlier today, felt that I shouldn't have my IBM Hawaiian shirt on, however, now that I've met Chuck, next time, at next Cisco Live, I'll have my IBM Hawaiian shirt on versus my IBM traditional shirt. >> Chuck's a cool guy. Thanks for comin' on. As always, great commentary. You know your stuff. >> Great, thank you. >> Great to have the slicing and dicing, the IBM storage situation, as well as the overall industry landscape. At Cisco Live, we're breakin' it down, here on theCUBE in Orlando. Second day of three days of coverage. I'm John Furrier, Stu Miniman, stay with us for more live coverage after this break.

>> Announcer: Live from Nice, France, it's The Cube covering Dot Next Conference 2017, Europe. Brought to you by Nutanix. (techno music) >> Welcome back, I'm Stu Miniman happy to welcome back to our program, from the IBM Cognitive Systems Group, we have Bob Picciano and Stefanie Chiras. Bob, fresh off the keynote, uh speech. Went a little bit long but glad we could get you in. Um, I think when the, when the IBM Power announcement with Nutanix got out there, a lot of people were trying to put the pieces together and understand. You know, we with The Cube we've, we've been tracking, you know, Power for quite a while, Open Power, all the things but, but I have to admit that even myself, it was like, okay, I understand cognitive systems. We got all this AI things and everything but on the stage this morning, you kind of talked a little bit about the chipset and the bandwidth. You know, things like GPUs and utilization, you know, explain to us, you know, what is resonating with customers and, you know, where, you know, what's different about this because a lot of the other ones it's like, oh well, you know, software runs a lot of places and it doesn't matter that much. What's important about cognitive systems for Nutanix? >> Yeah, so, first off, thanks Stu. And, as always, thanks for, you know, you for following us and understanding what we're doing. You mentioned not just Power but you mentioned Open Power, and I think that's important. It shows, actually, the deeper understanding. You know, we've come a long way in a very short amount of time with what we've done with Open Power. Open Power was very much at it's core about really making Power a natural choice for industry standard Linux, right? The Linuxes that used to run on Power a couple of generations ago were more proprietary Linuxes. They were Big Endian Linux but Open Power was about making all that industry standard software run on top of Power where we knew our value proposition would shine based on how much optimization we put into our cores and how much optimization we put into IO bandwidth and memory bandwidth. And boy, you know, have we been right. In fact, when we take an industry standard workload like a no sequel database or Enterprise DB, or a Mongoloid DB, Hadoop, and put it on top of Linux, an industry standard Linux, on top of Power, we typically see that run about 2X to 3X better price performance on Linux on Power than it would on Linux on Intel. This is a repeating pattern. And so, what we're trying to do here is uh, really enable that same efficiency and economics to the Nutanix Hyper Converged Space. And remember, all these things about insight based applications, artificial intelligence, are all about data intensive workloads. Data intensive workloads and that's what we do best. So we're bringing the best of what we do and the optionality now for these AI workloads and cognitive systems right into the heart of what Nutanix is pivoting to as well. Which is really at the, at the core of the enterprise for data intensive workloads. Not just, you know, edge related VDI based workloads. Stefanie will you, you want to comment on that a little bit as well. >> Yeah, we are so focused on being prioritized and what space we go after in the Linux market around these data centric and AI workloads. And at the end of the day, you know, Nutanix has Nutanix states. It's about invisible infrastructure, but the infrastructure underneath matters. And now with the simplicity of what Nutanix brings you can choose the best infrastructure for the workloads that you decide to run, all with single pane of glass management. So it allows us to bring our capabilities at the infrastructure levels for those workloads, into a very simplest, simple deployment model under a Nutanix private cloud. >> Yeah, I, I think back when, you know, we had things like, when Hadoop came out, you know, we got all these new modern databases, >> Right. >> You know, I wanted to change the infrastructure but simplicity sure wasn't there. >> Yep. >> Uh-huh. >> It was a couple of servers sitting under the desk, okay, but when you needed to scale, when you needed to manage the environment, um, it was challenging. We, we saw, when, you know, Wikibon for years was doing, you know, research on big data and it was like, ah, you know, half the deployments are failing because, you know, it wasn't what they expected. >> Right. >> The performance wasn't there, the cost was challenging. So it feels like we're kind of, you know, turn the corner on, you know, making, putting the pieces together to make these solutions workable. >> I think we are. I think Dheeraj and his team, Sunil, they've done a wonderful job on making the one click simplicity, ease of deployment, ease of manageability. We saw today, creation of availability zones. High availability infrastructure. Very very simplistic. So, you know, as, you know, I've had other segments with Dave and John in the past, we've always talked about, it's not about big data, it's about really creating the ability to get fast actionable insights. So it's a confluence of that date environment, the processed based workflow environment, and then making that all simple. And this feels like a very natural way to accomplish that. >> I want to understand, if I caught right, it's not Power or x86 but it's really putting the right workloads in the, in the right place. >> That's right. >> Did I get that right? >> That's right. >> What, what are the customer deployments, you know? >> Heterogeneity is key. >> How do I then manage those environments because, you know, I, I want kind of homogeneity of, of management, even if I have heterogeneity, you know, in, in my environment, you know. What, what are you hearing from your customers? >> I think how we've looked at Linux evolved. The set of workloads that are being run on Linux have evolved so dramatically from where they started to running companies and being much more aggressive on compute intensive. So it's about when you bring total cost of ownership which requires the ability to simply manage your operations in a data center. Now the best of Prism capabilities along with the Acropolis stack allows simplicity of single pane of glass management for you to run your Power node, set of nodes, side by side with your x86 set of nodes. So what you want to run on x86 or Windows can now be run seamlessly and compatible with your data centric workloads and data driven workloads, or AI workloads on your Power nodes. It really is about bringing total cost of ownership down. And that really requires accessibility and it requires simplicity of management. And that's what this partnership really brings. It's a new age for hyper converged. >> Yeah. >> What should we be looking for, for the partnership, kind of over the next 12 years, 12, 12 months. (laughs) >> 12 years? (laughs) (laughter) >> 12 years might be a little tough to predict, but over the next year, what, what should we be looking for the partnership? You know, I think back you talked about, Open Powered Google is, you know, a big partner there. Is there a connection? Am I drawing lines between, you know, Nutanix and Google and what you're doing? >> I won't comment on that yet but, you know, but, as you know we have a big rollout coming up as we're getting ready to launch Power Nine. So there'll be more news on some of those fronts as we go through the coming weeks. And I hope to see you down in Dallas at our Cloud or Cognitive event. Or at one of the other events we'll be jointly at where we do some of these announcements. But if you think about where this naturally takes us, Sunil talked about mode one and mode two applications. So what we want to see is increasing that catalog for mode one applications. So things that I'd like to see is an expanded set of relationships around what we both do in the SAP space. I'd like to see that catalog of support enriched for what's out there on top of the Linux on Power space, where we know our value proposition will continue to be demonstrated both in total cost of acquisition as well as total cost of ownership. >> Yeah. >> I mean, we're really, you know, seeing some great results on our Linux base. As you know, it's now about 20 percent of the power revenue base is from Linux. >> Uh-huh. >> And that's grown from a very small amount just a few years ago. So, I look to see that and then I would look at more heterogeneity in terms of the support of what we do, both in Linux and maybe, in the future, also what we do to support the AIX workloads, uh, with Nutanix as well. Because I do think our clients are asking about that optionality. They have big investments, mission critical workloads around AIX and the want to start to bring those worlds together. >> Alright and Stefanie, want to give you the final word, you know, anything kind of learnings that you've had, of the relationships as you've been getting out and getting into those customer environments. >> I have to say the excitement coming in from the sales team, from our clients, and from the business partners have been incredible. It really is about the coming together of, not only two spaces of simple, and absolutely the best infrastructure and being able to optimize from bottom to top, but it's about taking hyper converge to a new set of workloads. A new space. Um, so the excitement is just incredible. I am thrilled to be here at Dot Next and be able to talk to our clients and partners about it. >> Alright well Stefanie and Bob thank you so much for joining us. >> Thanks Stu. >> Thank you Stu. >> Sorry we had to do a short segment but we'll be catching ya up at many more. Alright so we'll be back with lots more coverage here from Nutanix Dot Next in Nice, France. I'm Stu Miniman, you're watching The Cube. (techno music)

>> Man: Let me check. >> Announcer: Live from Las Vegas, it's The Cube. Covering InterConnect 20 17. Brought to you by IBM. >> Okay, welcome back everyone. Day two, we are here live in Las Vegas for IBM InterConnect. This is Silicon Angle's The Cube coverage of IBM's cloud event. The CEO, Ginni Rometty, was just on stage. We're kickin' off wall to wall coverage for three days. I'm John Furrier, my co-host, Dave Vellante, here for all three days. >> And, our next guest is Andy Lin, who's the VP of (mumbles) Mark Three Systems. A, 20 plus year IBM platinum partner. Doin' some real cutting edge work with cognitive as Ginny Rometty said cognitive to the core, is IBM's core strategy. Data first, enterprise strong is kind of the buzz words. Andy, welcome to The Cube. Appreciate you comin' on. >> Thanks for havin' me. >> So, obviously, enterprise strong, you know, it's, it's a kind of whole nother, you know, conversation that we can go deep on, but data first and cognitive to the core is really kind of the things that you guys are really getting into. All kinds of data types. Automating it and making it almost frictionless to move insights out. So, take a minute to explain what Mark Three's doing and what your role is with the company. >> Sure. Absolutely. So, I'm Vice President of strategy in Mark Three, so I work sort of across all our initiatives, especially areas that are emerging. Just a little bit about Mark Three, just historically for background purposes. So, we're a 22 year IBM platinum partner, as you pointed out. We actually started in the mid 90's, actually doing IT infrastructure around the IBM stack at that time. So, we sort of been with IBM over the last 20 years since the beginning. We've sort of grown up throughout the stack as IBM's evolved over the last two decades. About two and a half years ago, we started a digital development unit, called BlueChasm. And what BlueChasm does, is it basically builds open digital and cognitive platforms on the IBM cloud that are around a lot of services you pointed out. And, we basically designed it based on use cases that the ecosystem and our clients talk about. And, to give you a couple examples, one of the, one of the big ones that we're seeing a lot of interest around is called video recon. Video recon is a video analytics platform that's API enabled and open at it's core. So, regardless of where the video comes from, if it's a content management system, if it's a camera, we're able to basically take in that video, basically watch and listen to the video using Watson and some elements of our own intellectual property. And, then basically return insights based on what it sees and hears along with time stamps, back to the user to actually take action. >> Yeah. I love the name BlueChasm. It brings up, you know, Jeffrey Moore's Crossing the Chasm. Blue, IBM, big blue, so you know, it's a nice clever play. The BlueChasm opportunity. So, in your mind, for people watching, squint through some of the trends and extract out where you see these opportunities. Because if you're talkin' about new opportunities are emerging because of cloud horsepower and compute and storage and all the greatness of cloud, and you got real time analytics kind of really hittin' the main stream. That's going to, that's highlighted by internet of things is you can't go anywhere these days without hearing about autonomous vehicles, industrial (mumbles) things, AI, Mark Benioff was sayin', you know, we've seen the movies like Terminator and we've all dreamed about AI, so we can kind of get excited about the prospects. But, the chasm you're talkin' about, this is where these things that were ungettable before, unreachable new things, what are some of those things that you guys are doin' in that chasm? >> Yeah, so I think some of the things that we're doing are basically enabling, like I'll use video recon as an example, right, we're enabling a class to be able to get new insights using basically computer vision, but in an open and accessible way, that they've never had been able to do before. Vision itself, I don't think is new or revolutionary. You know, a lot of folks are doing it, self driving cars, etcetera. >> John: Yeah. >> But, I think what is new is being able to make it open and easily accessible to the normal enterprise, the normal service provider. Up to now, it's been, you know you've had, really had to have your own team of, you know, really, really deep AI develops or PHD's to be able to produce it for your own platform. What we're trying to do is basically demarketize that. >> John: Yeah. >> So, to give you an example, some use cases that we're, we're sort of working on today, the ability to do things like read meters and gages, as an example, with a camera. That way you can avoid a situation where somebody has to walk around all the time, you know, look at different things that could be dangerous. That there could be issues actually looking at what you see from a metering perspective. Or to be able to, for instance, for in the media entertainment industry or the video production industry, be able to do things like identify shot types, be able to more quickly allow our enterprise users in that particular space to be able to create video content quickly. And, the underlying theme with all this, I think it's really about speed to market. And, how quickly can you iterate and please whatever your customers in that particular space that you're in. >> So with the video recon, so your, your videos are searchable, essentially. >> (Andy) Correct. >> So, so what do you do? Use Watson, natural language processing to sort of translate them? Now (mumbles), of course, you know, NLP is maybe I don't know 75, 80 percent accurate, how do you close that gap? >> Yeah, so video recon does both visual and audio. So, the audio portion you are correct. There is some degree of trade off in accuracy relative to what I think the average human can do today. Assuming the human is focused and able to really tag these videos accurately. So, we are able to train it based on things like proper words and things that are enterprise focused. Because I know there, there are a lot of different ways that I think you can maybe attack this today from a video analytics perspective, where we're focused primarily just on the enterprise, solving business problems with, with video analytics. So, you know, taking advantage of if Watson improves, cause we do use (mumbles) tech at it's core from, on the audio perspective. Applying some of our own techniques to basically improve the accuracy of certain words that matter most to the enterprise. One of the things we've noticed is it's an entirely collaborative relationship with our, with our, with our enterprise clients but really partners. Because what works well for one, may not work well for another. One thing about cognitive is it really depends on the end user as to if this is a good idea or not. Or if this will work for their use case, just based on error, as you pointed out. >> So, to your point, you're identifying enterprise use cases and then tuning the system. Building solutions, essentially, for those use cases. >> Andy: Absolutely. >> Now, you said 22 year IBM platinum partner, so you obviously started well before this so-called digital transformation. >> Andy: Yes. >> You see digital transformation as, you know, revolutionary, or is it more of an evolution of your business? >> I'd definitely say it's an evolution. I think, you know, a lot of the industry buzz words out there are all around, you know, transformation or transition, but for us it's been completely additive. You know, at the end of the day we're just doing what our clients want, you know. And, we're still continuing the core part of our business around modernizing and optimizing IT infrastructure, tech sacks in the data center, also infrastructure service in the cloud. Also, up through the middle where it's still really as strong as ever. I mean, in fact that business has actually been very much reinforced by some of these capabilities that we brought in on the digital development side. Because, at the end of the day, you know, clients may have a digital unit and they may have, you know, IT, but they're really viewed sort of all in the same. A lot of people try to put 'em in two different buckets bimodal or whatever you want to use. But, you know, inevitably, you know, clients just see a business problem they want to address. >> Yep. >> And, they're saying how can I address it the fastest and the most effectively as relative to what their stakeholders want. And, we just realized early on that we had to have that development capability, be able to build platforms, but also guide out clients. If they don't want one of our platforms, if they don't want video recon or cognitive call center platform, that's perfectly fine. We're more than happy to guide them on how to build something similar for their developers with our developers relative to their tech stack, you know, hopefully on the IBM cloud. >> Andy, one of the things you were pointing out that I think is worth highlighting is the digital transformation buzz word, which has been around for a few years now, really is in main stream right now. >> Andy: Yes. >> People are really working hard to figure this out. We're seeing the disruption on the business model side. You mentioned speed and time to market, that's agility. That's not just a technical development term anymore. It's actually business model. It's business related. >> Andy: Yes. >> But there's two axes of things going on. There's the under the hood, heavy lifting stuff that goes on around getting stuff digitally to work. That's IT, security, and you know, Ginni Rometty talks about a lot of that on stage. That's being enterprise grade or enterprise strong. The other one is this digitization of the real world, right? So, that's creative. That requires insights. That requires kind of a different, it's actually probably maybe more fun for some people, but I mean it depends on who your profile is, but you have kind of two spectrums. Cool and relevant and exciting and intoxicating, creative, user experience driven. You mentioned reading meters. >> Andy: Yeah. >> That's the analog world. >> Andy: Yes. >> That's actually space. That's the world. That's like, you got the sky you got the meter. >> Andy: Yeah. >> You got physical impressions. This is the digitization of our world. What's your perspective? How do you talk to customers when they say, "Hey I want to digitize my business." >> Andy: Mm hmm. >> How does it go? What do you say? I mean, do you break it down into those axes? Do you go, did they see it that way? Can you share some color on this digital transformation of digitizing business? >> Yeah, so I mean it really depends on, I think, it normally it has to do with interacting with some other stakeholders in a certain way, you know. I think from our perspective it really is about, you know, how they want to interface. And, most of the time you pointed out speed. Speed I think is the number one reason why people are doing the digital transformation. It's not really about cost or these other factors. It's how quickly can I adjust my business model so I can win in the market place? And, you know, I think I pointed this earlier, but like, you know IOT is huge now. It covers what I call three out of the five senses in my mind. It covers basically touch, smell and taste in many ways. And, for us, I think we're basically trying to help them even get beyond IOT with video. Video really covers, you know, sight and hearing as well. It covers all the five senses. And, then you take that and figure out how do I digitize that experience and be able to allow you to interact with your stakeholders. Whether it be your customers, your suppliers or your partners out in the market place. And, then based on that we'll take these building blocks on how we, you know, extend the experience, and work with them on their specific use case. >> So, you got to ingest the data, which is the, you know, the images or data coming in. >> Correct. >> Then you got to prep it available for insights. >> Correct. >> And, produce them in, like really fast. >> Andy: Yep. >> That's hard. >> Andy: It is, yeah. >> It's not trivial. >> No it is not, it's not a trivial problem. Yeah, absolutely. And, I think, you know, there's a lot of opportunity here in the space over the next I think two to two to five years. But you're absolutely right. >> John: Yeah. >> I mean it is, it is a challenging. >> And, I want to get your thoughts too, and if you can share your reaction to some of the trends around machine learning, for instance. It's really kind of fueling this democratization. >> Andy: Yeah. >> You mention in the old days it was really hard, there was kind of a black art to, to machine learning or unique special, specialties. And, even data science that's at one level was really, really hard. Now you have common people doing things with visualization. What's the same with machine learning? I mean, you got more data sets coming in. Do you see that trend relevant to what you guys are working on in BlueChasm? >> Absolutely. I think at the core of it, and this wasn't our plan initially three years ago, we didn't realize that this was happen, but every single one of the platforms or prototypes or apps we've built, they all incorporate some degree of machine learning, deep learning within it's core. And, this is primarily just driven by I think what, to give a client a unique platform or a unique service on the market. Because, much of the base digitization, I mean Ginny likes to talk a lot about, you know, the key to being, differentiating yourself from digital world is being cognitive. And, we've seen this really play out in practice. And, I think what's changed, as you pointed out is, that it's easily accessible now to sort of the common man, as I put it. In years past, you really had to have people that are highly specialized. You build your own product. But now through open source- >> There's building blocks out there. >> Absolutely. >> You can just take an open source library and say hey, and then tweak the machine learning. >> Absolutely. And, the ramp up time has come down, you know, dramatically, even for our developers. Just watching them work. I mean, the prototype to video recon was built over the course of a weekend by one of our developers. He just came in one Monday and said, you know, is this, is this interesting? >> He's fired. >> Exactly. And, we were like, yes I think this is interesting. >> Well this is the whole inspiration thing that I talk about, the creativity. This is the two axes, right? >> You try to do that in the old days, I got to get a server provision. >> Andy: Yeah. >> I'm done. >> Andy: Right. >> You know, I'm going to go have a a beer. Whatever. I mean, there's almost an abandonment going on. We talked to Indiegogo yesterday about how they're funding companies. >> Andy: Yeah. >> You have this new creative action. >> Andy: Mm hmm. >> So you guys are seeing that. Any other examples you can share in terms of color around this kind of innovation? >> Yeah, so we, at BlueChasm we try to let our developers sort of have free reign over what they like to create. So video recon was spawned literally by a, on a side project, you know as with a lot of companies. It was, you know, a platform that sort of evolved into a commercial product, almost by accident, right? And, we've had others that have been anchored by like what clients had done, but like around the cognitive call center, which basically takes phone calls that are recorded and then basically transcribes and makes them easily searchable for audit reasons, training reasons, etcetera. Same kind of idea. We built things around like cognitive drones. A lot of folks are trying to do things with drones. Drones themselves aren't really not novel anymore, but being able to utilize them to collect data in unique ways, I think that industry is definitely evolving. We've built other things like, what I call the minority report board, after the scene in the movie where the board sort of looks at you and then based on what it sees of you, of different data points, it shows you an ad or shows you a piece of visual content to allow you to interact. >> John: Yeah. >> I mean, these are, these are examples. You know, we have others. But, you know we've just seen like in this organization if we allow creativity to sort of reign, you know, have free reign. We're able to sort of bring it back in along with some of the strengths of core Mark Three about being (mumbles). >> I mean the cognitive is really interesting. It's a programmatic approach to life. And, if you think about it, it's like if you have this collective intelligence with the data, you could offer an augmented reality experience- >> Andy: Yes. >> To anybody now, based upon what you're doin'. >> Absolutely. So I mean, I think that the toughest part I think right now is figuring out which of the opportunities to pursue. Because, there are so many out there and everyone has some interest in some degree, you know. You have to figure out how to prioritize about, you know, which, which of the ones you want to address first. >> John: Yeah. >> And, in what order. Because, what we've noticed is that a lot of these are building blocks that lead to other greater and greater platform concepts, and part of the challenge is figuring out what order you want to actually build these into. And, through you know, microservices through retainerization all these, you know, awesome evolutions as far as like with cloud and infrastructure technology, you're really able to piece together these pieces to build amazing (mumbles) quickly. >> The cloud native stuff is booming right now. >> Yeah. >> It's really fun to watch. Microservices, (mumbles), this orchestration, composability is just kickin' ass. >> Absolutely. >> And, all your clients are basically becoming software companies. They're takin' your services and building out their own sas capabilities. >> Andy: Right. >> Right? >> Without a doubt. I mean, you know the cloud (mumbles), container revolution's been significant for us. I mean we, we added the audio component to video recon based on some of the work we've been doing on the call center side. It was almost by accident. And, we were able to really put them together in a day because we were able to basically easily compose the overall platform at that time, or the prototype of the platform at that time just by linking together those services. So, we see this as a pattern moving forward. >> Andy, thanks for coming on The Cube. Really appreciate it. In the quick 30 seconds, what are you doin' here at the show? What are you guys talkin' about? What's some of the activity? Coolest thing you're seeing? Share some insight, what's going on here in Las Vegas. Share some perspective. >> Yeah, absolutely. So, we have a booth here in Vegas. We're demoing some of the platforms we talked about: video recon, cognitive call center. We're at booth six 87, which is toward the center back of the expo center. We have four break outs that we'll be doing as well. Talking about some of these concepts, as well as some of our projects that involve, you know, modernization of the data center as well. So, the true what I call IBM full stack. >> And, for the folks that aren't here watching, is there, the website address? Where can they go to get more information? >> Yeah, absolutely. You can go to Mark Three sys. M A R K triple I S Y S dot com, which is our website. If you want to learn a little bit more about video recon you can go to video recon dot I O. We have a very simple demo page, but you know, if you're interested in learning more or you want to explore if we can accommodate your specific use case, please feel free to reach out to me. Also, Mark Three systems, M A R K triple I systems at Twitter as well, and I can get back to you. >> Well, you know we're going to follow up with you. Going to get all of our Cube videos into the cognitive era. You'll be seeing us, pinging you online for that. >> Yeah. >> Love the video recon, just great. BlueChasm, great, great initiative. Congratulations on that. >> Thank you. >> Thanks for comin' on. Its The Cube live here in Las Vegas. Day two of coverage, wall to wall. I'm John Furrier with Dave Vellante. Stay with us. More great interviews after this short break.

>> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

(bright music) >> Narrator: From around the globe, it's the CUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Welcome back to IBM Think 2021, the virtual edition. This is the CUBEs, continuous, deep dive coverage of the people, processes and technologies that are really changing our world. Right now, we're going to talk about modernization and what's beyond with Jamie Thomas, general manager, strategy and development, IBM Enterprise Security. Jamie, always a pleasure. Great to see you again. Thanks for coming on. >> It's great to see you, Dave. And thanks for having me on the CUBE is always a pleasure. >> Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM is focused on hybrid cloud, Arvind Krishna says we must win the architectural battle for hybrid cloud. I love that. We've been hearing a lot about AI. And I wonder if you could talk about IBM Systems and how it plays into that strategy? >> Sure, well, it's a great time to have this discussion Dave. As you all know, IBM Systems Technology is used widely around the world, by many, many 1000s of clients in the context of our IBM System Z, our power systems and storage. And what we have seen is really an uptake of monetization around those workloads, if you will, driven by hybrid cloud, the hybrid cloud agenda, as well as an uptake of Red Hat OpenShift, as a vehicle for this modernization. So it's pretty exciting stuff, what we see as many clients taking advantage of OpenShift on Linux, to really modernize these environments, and then stay close, if you will, to that systems of record database and the transactions associated with it. So they're seeing a definite performance advantage to taking advantage of OpenShift. And it's really fascinating to see the things that they're doing. So if you look at financial services, for instance, there's a lot of focus on risk analytics. So things like fraud, anti money laundering, mortgage risk, types of applications being done in this context, when you look at our retail industry clients, you see also a lot of customer centricity solutions, if you will, being deployed on OpenShift. And once again, having Linux close to those traditional LPARs of AIX, I-Series, or in the context of z/OS. So those are some of the things we see happening. And it's quite real. >> Now, you didn't mention power, but I want to come back and ask you about power. Because a few weeks ago, we were prompted to dig in a little bit with the when Arvind was on with Pat Kessinger at Intel and talking about the relationship you guys have. And so we dug in a little bit, we thought originally, we said, oh, it's about quantum. But we dug in. And we realized that the POWER10 is actually the best out there and the highest performance in terms of disaggregating memory. And we see that as a future architecture for systems and actually really quite excited about it about the potential that brings not only to build beyond system on a chip and system on a package, but to start doing interesting things at the Edge. You know, what do you what's going on with power? >> Well, of course, when I talked about OpenShift, we're doing OpenShift on power Linux, as well as Z Linux, but you're exactly right in the context for a POWER10 processor. We couldn't be more we're so excited about this processor. First of all, it's our first delivery with our partner Samsung with a seven nanometer form factor. The processor itself has only 18 billion transistors. So it's got a few transistors there. But one of the cool inventions, if you will, that we have created is this expansive memory region as part of this design point, which we call memory inception, it gives us the ability to reach memory across servers, up to two petabytes of memory. Aside from that, this processor has generational improvements and core and thread performance, improved energy efficiency. And all of this, Dave is going to give us a lot of opportunity with new workloads, particularly around artificial intelligence and inferencing around artificial intelligence. I mean, that's going to be that's another critical innovation that we see here in this POWER10 processor. >> Yeah, processor performance is just exploding. We're blowing away the historical norms. I think many people don't realize that. Let's talk about some of the key announcements that you've made in quantum last time we spoke on the qubit for last year, I think we did a deeper dive on quantum. You've made some announcements around hardware and software roadmaps. Give us the update on quantum please. >> Well, there is so much that has happened since we last spoke on the quantum landscape. And the key thing that we focused on in the last six months is really an articulation of our roadmaps, so the roadmap around hardware, the roadmap around software, and we've also done quite a bit of ecosystem development. So in terms of the roadmap around hardware, we put ourselves out there we've said we were going to get to over 1000 qubit machine and in 2023, so that's our milestone. And we've got a number of steps we've outlined along that way, of course, we have to make progress, frankly, every six months in terms of innovating around the processor, the electronics and the fridge associated with these machines. So lots of exciting innovation across the board. We've also published a software roadmap, where we're articulating how we improve a circuit execution speeds. So we hope, our plan to show shortly a 100 times improvement in circuit execution speeds. And as we go forward in the future, we're modifying our Qiskit programming model to not only allow a easily easy use by all types of developers, but to improve the fidelity of the entire machine, if you will. So all of our innovations go hand in hand, our hardware roadmap, our software roadmap, are all very critical in driving the technical outcomes that we think are so important for quantum to become a reality. We've deployed, I would say, in our quantum cloud over, you know, over 20 machines over time, we never quite identify the precise number because frankly, as we put up a new generation machine, we often retire when it's older. So we're constantly updating them out there, and every machine that comes on online, and that cloud, in fact, represents a sea change and hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. >> That's key, the developer angle you got redshift running on quantum yet? >> Okay, I mean, that's a really good question, you know, as part of that software roadmap in terms of the evolution and the speed of that circuit execution is really this interesting marriage between classical processing and quantum processing and bring those closer together. And in the context of our classical operations that are interfacing with that quantum processor, we're taking advantage of OpenShift, running on that classical machine to achieve that. And once again, if, as you can imagine, that'll give us a lot of flexibility in terms of where that classical machine resides and how we continue the evolution the great marriage, I think that's going to that will exist that does exist and will exist between classical computing and quantum computing. >> I'm glad I asked it was kind of tongue in cheek. But that's a key thread to the ecosystem, which is critical to obviously, you know, such a new technology. How are you thinking about the ecosystem evolution? >> Well, the ecosystem here for quantum is infinitely important. We started day one, on this journey with free access to our systems for that reason, because we wanted to create easy entry for anyone that really wanted to participate in this quantum journey. And I can tell you, it really fascinates everyone, from high school students, to college students, to those that are PhDs. But during this journey, we have reached over 300,000 unique users, we have now over 500,000 unique downloads of our Qiskit programming model. But to really achieve that is his back plane by this ongoing educational thrust that we have. So we've created an open source textbook, around Qiskit that allows organizations around the world to take advantage of it from a curriculum perspective. We have over 200 organizations that are using our open source textbook. Last year, when we realized we couldn't do our in person programming camps, which were so exciting around the world, you can imagine doing an in person programming camp and South Africa and Asia and all those things we did in 2019. Well, we had just like you all, we had to go completely virtual, right. And we thought that we would have a few 100 people sign up for our summer school, we had over 4000 people sign up for our summer school. And so one of the things we had to do is really pedal fast to be able to support that many students in this summer school that kind of grew out of our proportions. The neat thing was once again, seeing all the kids and students around the world taking advantage of this and learning about quantum computing. And then I guess that the end of last year, Dave, to really top this off, we did something really fundamentally important. And we set up a quantum center for historically black colleges and universities, with Howard University being the anchor of this quantum center. And we're serving 23 HBCUs now, to be able to reach a new set of students, if you will, with STEM technologies, and most importantly, with quantum. And I find, you know, the neat thing about quantum is is very interdisciplinary. So we have quantum physicist, we have electrical engineers, we have engineers on the team, we have computer scientists, we have people with biology and chemistry and financial services backgrounds. So I'm pretty excited about the reach that we have with quantum into HBCUs and even beyond right I think we can do some we can have some phenomenal results and help a lot of people on this journey to quantum and you know, obviously help ourselves but help these students as well. >> What do you see in people do with quantum and maybe some of the use cases. I mean you mentioned there's sort of a connection to traditional workloads, but obviously some new territory what's exciting out there? >> Well, there's been a really a number of use cases that I think are top of mind right now. So one of the most interesting to me has been one that showed us a few months ago that we talked about in the press actually a few months ago, which is with Exxon Mobil. And they really started looking at logistics in the context of Maritime shipping, using quantum. And if you think of logistics, logistics are really, really complicated. Logistics in the face of a pandemic are even more complicated and logistics when things like the Suez Canal shuts down, are even more complicated. So think about, you know, when the Suez Canal shut down, it's kind of like the equivalent of several major airports around the world shutting down and then you have to reroute all the traffic, and that traffic and maritime shipping is has to be very precise, has to be planned the stops are plan, the routes are plan. And the interest that ExxonMobil has had in this journey is not just more effective logistics, but how do they get natural gas shipped around the world more effectively, because their goal is to bring energy to organizations into countries while reducing CO2 emissions. So they have a very grand vision that they're trying to accomplish. And this logistics operation is just one of many, then we can think of logistics, though being a being applicable to anyone that has a supply chain. So to other shipping organizations, not just Maritime shipping. And a lot of the optimization logic that we're learning from that set of work also applies to financial services. So if we look at optimization, around portfolio pricing, and everything, a lot of the similar characteristics will also go be applicable to the financial services industry. So that's one big example. And I guess our latest partnership that we announced with some fanfare, about two weeks ago, was with the Cleveland Clinic, and we're doing a special discovery acceleration activity with the Cleveland Clinic, which starts prominently with artificial intelligence, looking at chemistry and genomics, and improve speed around machine learning for all of the the critical healthcare operations that the Cleveland Clinic has embarked on but as part of that journey, they like many clients are evolving from artificial intelligence, and then learning how they can apply quantum as an accelerator in the future. And so they also indicated that they will buy the first commercial on premise quantum computer for their operations and place that in Ohio, in the the the years to come. So it's a pretty exciting relationship. These relationships show the power of the combination, once again, of classical computing, using that intelligently to solve very difficult problems. And then taking advantage of quantum for what it can uniquely do in a lot of these use cases. >> That's great description, because it is a strong connection to things that we do today. It's just going to do them better, but then it's going to open up a whole new set of opportunities. Everybody wants to know, when, you know, it's all over the place. Because some people say, oh, not for decades, other people say I think it's going to be sooner than you think. What are you guys saying about timeframe? >> We're certainly determined to make it sooner than later. Our roadmaps if you note go through 2023. And we think the 2023 is going to will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kind of use cases and this intense working with these clients, 'cause when they work with us, they're giving us feedback on everything that we've done, how does this programming model really help me solve these problems? What do we need to do differently? In the case of Exxon Mobil, they've given us a lot of really great feedback on how we can better fine tune all elements of the system to improve that system. It's really allowed us to chart a course for how we think about the programming model in particular in the context of users. Just last week, in fact, we announced some new machine learning applications, which these applications are really to allow artificial intelligence users and programmers to get take advantage of quantum without being a quantum physicist or expert, right. So it's really an encapsulation of a composable elements so that they can start to use, using an interface allows them to access through PyTorch into the quantum computer, take advantage of some of the things we're doing around neural networks and things like that, once again, without having to be experts in quantum. So I think those are the kind of things we're learning how to do better, fundamentally through this co-creation and development with our quantum network. And our quantum network now is over 140 unique organizations and those are commercial, academic, national laboratories and startups that we're working with. >> The picture started become more clear, we're seeing emerging AI applications, a lot of work today in AI is in modeling. Over time, it's going to shift toward inference and real time and practical applications. Everybody talks about Moore's law being dead. Well, in fact, the yes, I guess, technically speaking, but the premise or the outcome of Moore's law is actually accelerating, we're seeing processor performance, quadrupling every two years now, when you include the GPU along with the CPU, the DSPs, the accelerators. And so that's going to take us through this decade, and then then quantum is going to power us, you know, well beyond who can even predict that. It's a very, very exciting time. Jamie, I always love talking to you. Thank you so much for coming back on the CUBE. >> Well, I appreciate the time. And I think you're exactly right, Dave, you know, we talked about POWER10, just for a few minutes there. But one of the things we've done in POWER10, as well as we've embedded AI into every core that processor, so you reduce that latency, we've got a 10 to 20 times improvement over the last generation in terms of artificial intelligence, you think about the evolution of a classical machine like that state of the art, and then combine that with quantum and what we can do in the future, I think is a really exciting time to be in computing. And I really appreciate your time today to have this dialogue with you. >> Yeah, it's always fun and it's of national importance as well. Jamie Thomas, thanks so much. This is Dave Vellante with the CUBE keep it right there our continuous coverage of IBM Think 2021 will be right back. (gentle music) (bright music)

Narrator: From theCUBE studios in Palo Alto and Boston, it's theCUBE, covering IBM Think, brought to you by IBM. >> We're back. You're watching theCUBE and our coverage of IBM Think 2020, the digital IBM thinking. We're here with Jamie Thomas, who's the general manager of strategy and development for IBM Systems. Jamie, great to see you. >> It's great to see you as always. >> You have been knee deep in qubits, the last couple years. And we're going to talk quantum. We've talked quantum a lot in the past, but it's a really interesting field. We spoke to you last year at IBM Think about this topic. And a year in this industry is a long time, but so give us the update what's new in quantum land? >> Well, Dave first of all, I'd like to say that in this environment we find ourselves in, I think we can all appreciate why innovation of this nature is perhaps more important going forward, right? If we look at some of the opportunities to solve some of the unsolvable problems, or solve problems much more quickly, in the case of pharmaceutical research. But for us in IBM, it's been a really busy year. First of all, we worked to advance the technology, which is first and foremost in terms of this journey to quantum. We just brought online our 53 qubit computer, which also has a quantum volume of 32, which we can talk about. And we've continued to advance the software stack that's attached to the technology because you have to have both the software and the hardware thing, right rate and pace. We've advanced our new network, which you and I have spoken about, which are those individuals across the commercial enterprises, academic and startups, who are working with us to co-create around quantum to help us understand the use cases that really can be solved in the future with quantum. And we've also continued to advance our community, which is serving as well in this new digital world that we're finding ourselves in, in terms of reaching out to developers. Now, we have over 300,000 unique downloads of the programming model that represents the developers that we're touching out there every day with quantum. These developers have, in the last year, have run over 140 billion quantum circuits. So, our machines in the cloud are quite active, and the cloud model, of course, is serving us well. The data's, in addition, to all the other things that I mentioned. >> So Jamie, what metrics are you trying to optimize on? You mentioned 53 qubits I saw that actually came online, I think, last fall. So you're nearly six months in now, which is awesome. But what are you measuring? Are you measuring stability or coherence or error rates? Number of qubits? What are the things that you're trying to optimize on to measure progress? >> Well, that's a good question. So we have this metric that we've defined over the last year or two called quantum volume. And quantum volume 32, which is the capacity of our current machine really is a representation of many of the things that you mentioned. It represents the power of the quantum machine, if you will. It includes a definition of our ability to provide error correction, to maintain states, to really accomplish workloads with the computer. So there's a number of factors that go into quantum volume, which we think are important. Now, qubits and the number of qubits is just one such metric. It really depends on the coherence and the effect of error correction, to really get the value out of the machine, and that's a very important metric. >> Yeah, we love to boil things down to a single metric. It's more complicated than that >> Yeah, yeah. >> specifically with quantum. So, talk a little bit more about what clients are doing and I'm particularly interested in the ecosystem that you're forming around quantum. >> Well, as I said, the ecosystem is both the network, which are those that are really intently working with us to co-create because we found, through our long history in IBM, that co-creation is really important. And also these researchers and developers realize that some of our developers today are really researchers, but as you as you go forward you get many different types of developers that are part of this mix. But in terms of our ecosystem, we're really fundamentally focused on key problems around chemistry, material science, financial services. And over the last year, there's over 200 papers that have been written out there from our network that really embody their work with us on this journey. So we're looking at things like quadratic speed up of things like Monte Carlo simulation, which is used in the financial services arena today to quantify risk. There's papers out there around topics like trade settlements, which in the world today trade settlements is a very complex domain with very interconnected complex rules and trillions of dollars in the purview of trade settlement. So, it's just an example. Options pricing, so you see examples around options pricing from corporations like JPMC in the area of financial services. And likewise in chemistry, there's a lot of research out there focused on batteries. As you can imagine, getting everything to electric powered batteries is an important topic. But today, the way we manufacture batteries can in fact create air pollution, in terms of the process, as well as we want batteries to have more retention in life to be more effective in energy conservation. So, how do we create batteries and still protect our environment, as we all would like to do? And so we've had a lot of research around things like the next generation of electric batteries, which is a key topic. But if you can think, you know Dave, there's so many topics here around chemistry, also pharmaceuticals that could be advanced with a quantum computer. Obviously, if you look at the COVID-19 news, our supercomputer that we installed at Oak Ridge National Laboratory for instance, is being used to analyze 8000 different compounds for specifically around COVID-19 and the possibilities of using those compounds to solve COVID-19, or influence it in a positive manner. You can think of the quantum computer when it comes online as an accelerator to a supercomputer like that, helping speed up this kind of research even faster than what we're able to do with something like the Summit supercomputer. Oak Ridge is one of our prominent clients with the quantum technology, and they certainly see it that way, right, as an accelerator to the capacity they already have. So a great example that I think is very germane in the time that we find ourselves in. >> How 'about startups in this ecosystem? Are you able to-- I mean there must be startups popping up all over the place for this opportunity. Are you working with any startups or incubating any startups? Can you talk about that? >> Oh yep. Absolutely. There's about a third of our network are in VC startups and there's a long list of them out there. They're focused on many different aspects of quantum computing. Many of 'em are focused on what I would call loosely, the programming model, looking at improving algorithms across different industries, making it easier for those that are, perhaps more skilled in domains, whether that is chemistry or financial services or mathematics, to use the power of the quantum computer. Many of those startups are leveraging our Qiskit, our quantum information science open programming model that we put out there so it's open. Many of the startups are using that programming model and then adding their own secret sauce, if you will, to understand how they can help bring on users in different ways. So it depends on their domain. You see some startups that are focused on the hardware as well, of course, looking at different hardware technologies that can be used to solve quantum. I would say I feel like more of them are focused on the software programming model. >> Well Jamie, it was interesting hear you talk about what some of the clients are doing. I mean obviously in pharmaceuticals, and battery manufacturers do a lot of advanced R and D, but you mentioned financial services, you know JPMC. It's almost like they're now doing advanced R and D trying to figure out how they can apply quantum to their business down the road. >> Absolutely, and we have a number of financial institutions that we've announced as part of the network. JPMC is just one of our premiere references who have written papers about it. But I would tell you that in the world of Monte Carlo simulation, options pricing, risk management, a small change can make a big difference in dollars. So we're talking about operations that in many cases they could achieve, but not achieve in the right amount of time. The ability to use quantum as an accelerator for these kind of operations is very important. And I can tell you, even in the last few weeks, we've had a number of briefings with financial companies for five hours on this topic. Looking at what could they do and learning from the work that's already done out there. I think this kind of advanced research is going to be very important. We also had new members that we announced at the beginning of the year at the CES show. Delta Airlines joined. First Transportation Company, Amgen joined, a pharmaceutical, an example of pharmaceuticals, as well as a number of other research organizations. Georgia Tech, University of New Mexico, Anthem Insurance, just an example of the industries that are looking to take advantage of this kind of technology as it matures. >> Well, and it strikes me too, that as you start to bring machine intelligence into the equation, it's a game changer. I mean, I've been saying that it's not Moore's Law driving the industry anymore, it's this combination of data, AI, and cloud for scale, but now-- Of course there are alternative processors going on, we're seeing that, but now as you bring in quantum that actually adds to that innovation cocktail, doesn't it? >> Yes, and as you recall when you and I spoke last year about this, there are certain domains today where you really cannot get as much effective gain out of classical computing. And clearly, chemistry is one of those domains because today, with classical computers, we're really unable to model even something as simple as a caffeine molecule, which we're all so very familiar with. I have my caffeine here with me today. (laughs) But you know, clearly, to the degree we can actually apply molecular modeling and the advantages that quantum brings to those fields, we'll be able to understand so much more about materials that affect all of us around the world, about energy, how to explore energy, and create energy without creating the carbon footprint and the bad outcomes associated with energy creation, and how to obviously deal with pharmaceutical creation much more effectively. There's a real promise in a lot of these different areas. >> I wonder if you could talk a little bit about some of the landscape and I'm really interested in what IBM brings to the table that's sort of different. You're seeing a lot of companies enter this space, some big and many small, what's the unique aspect that IBM brings to the table? You've mentioned co-creating before. Are you co-creating, coopertating with some of the other big guys? Maybe you could address that. >> Well, obviously this is a very hot topic, both within the technology industry and across government entities. I think that some of the key values we bring to the table is we are the only vendor right now that has a fleet of systems available in the cloud, and we've been out there for several years, enabling clients to take advantage of our capacity. We have both free access and premium access, which is what the network is paying for because they get access to the highest fidelity machines. Clearly, we understand intently, classical computing and the ability to leverage classical with quantum for advantage across many of these different industries, which I think is unique. We understand the cloud experience that we're bringing to play here with quantum since day one, and most importantly, I think we have strong relationships. We have, in many cases, we're still running the world. I see it every day coming through my clients' port vantage point. We understand financial services. We understand healthcare. We understand many of these important domains, and we're used to solving tough problems. So, we'll bring that experience with our clients and those industries to the table here and help them on this journey. >> You mentioned your experience in sort of traditional computing, basically if I understand it correctly, you're still using traditional silicon microprocessors to read and write the data that's coming out of quantum. I don't know if they're sitting physically side by side, but you've got this big cryogenic unit, cables coming in. That's the sort of standard for some time. It reminds me, can it go back to ENIAC? And now, which is really excites me because you look at the potential to miniaturize this over the next several decades, but is that right, you're sort of side by side with traditional computing approaches? >> Right, effectively what we do with quantum today does not happen without classical computers. The front end, you're coming in on classical computers. You're storing your data on classical computers, so that is the model that we're in today, and that will continue to happen. In terms of the quantum processor itself, it is a silicon based processor, but it's a superconducting technology, in our case, that runs inside that cryogenics unit at a very cold temperature. It is powered by next-generation electronics that we in IBM have innovated around and created our own electronic stack that actually sends microwave pulses into the processor that resides in the cryogenics unit. So when you think about the components of the system, you have to be innovating around the processor, the cryogenics unit, the custom electronic stack, and the software all at the same time. And yes, we're doing that in terms of being surrounded by this classical backplane that allows our Q network, as well as the developers around the world to actually communicate with these systems. >> The other thing that I really like about this conversation is it's not just R and D for the sake of R and D, you've actually, you're working with partners to, like you said, co-create, customers, financial services, airlines, manufacturing, et cetera. I wonder if you could maybe kind of address some of the things that you see happening in the sort of near to midterm, specifically as it relates to where people start. If I'm interested in this, what do I do? Do I need new skills? Do I need-- It's in the cloud, right? >> Yeah. >> So I can spit it up there, but where do people get started? >> Well they can certainly come to the Quantum Experience, which is our cloud experience and start to try out the system. So, we have both easy ways to get started with visual composition of circuits, as well as using the programming model that I mentioned, the Qiskit programming model. We've provided extensive YouTube videos out there already. So, developers who are interested in starting to learn about quantum can go out there and subscribe to our YouTube channel. We've got over 40 assets already recorded out there, and we continue to do those. We did one last week on quantum circuits for those that are more interested in that particular domain, but I think that's a part of this journey is making sure that we have all the assets out there digitally available for those around the world that want to interact with us. We have tremendous amount of education. We're also providing education to our business partners. One of our key network members, who I'll be speaking with later, I think today, is from Accenture. Accenture's an example of an organization that's helping their clients understand this quantum journey, and of course they're providing their own assets, if you will, but once again, taking advantage of the education that we're providing to them as a business partner. >> People talk about quantum being a decade away, but I think that's the wrong way to think about it, and I'd love your thoughts on this. It feels like, almost like the return coming out of COVID-19, it's going to come in waves, and there's parts that are going to be commercialized thoroughly and it's not binary. It's not like all of a sudden one day we're going to wake, "Hey, quantum is here!" It's really going to come in layers. Your thoughts? >> Yeah, I definitely agree with that. It's very important, that thought process because if you want to be competitive in your industry, you should think about getting started now. And that's why you see so many financial services, industrial firms, and others joining to really start experimentation around some of these domain areas to understand jointly how we evolve these algorithms to solve these problems. I think that the production level characteristics will curate the rate and pace of the industry. The industry, as we know, can drive things together faster. So together, we can make this a reality faster, and certainly none of us want to say it's going to be a decade, right. I mean, we're getting advantage today, in terms of the experimentation and the understanding of these problems, and we have to expedite that, I think, in the next few years. And certainly, with this arms race that we see, that's going to continue. One of the things I didn't mention is that IBM is also working with certain countries and we have significant agreements now with the countries of Germany and Japan to put quantum computers in an IBM facility in those countries. It's in collaboration with Fraunhofer Institute or miR Scientific Organization in Germany and with the University of Tokyo in Japan. So you can see that it's not only being pushed by industry, but it's also being pushed from the vantage of countries and bringing this research and technology to their countries. >> All right, Jamie, we're going to have to leave it there. Thanks so much for coming on theCUBE and give us the update. It's always great to see you. Hopefully, next time I see you, it'll be face to face. >> That's right, I hope so too. It's great to see you guys, thank you. Bye. >> All right, you're welcome. Keep it right there everybody. This is Dave Vellante for theCUBE. Be back right after this short break. (gentle music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum, World 2019 brought to you by the M Wear and its ecosystem partners. >> Welcome back to San Francisco. Day three of our coverage here on the Cube Of'em world 2019. I'm John Wall's Glad to have you here aboard for our continuing coverage here Day Volonte is also joining me, as is the sartorially resplendent Eric Herzog, cm of and vice president. Global storage channels that IBM storage. Eric, good to see you and love the shirt. Very >> nice. Thank you. Well, always have a wine shirts when I'm on the Cube >> I love in a long time Cuba to we might say, I'm sure he's got the record. Yeah, might pay. Well, >> you and pattern, neck and neck. We'll go to >> the vault. And well, >> since Pat used to be my boss, you know, couch out a path. >> Well, okay. Let the little show what IBM think. Maybe. Well, that's OK. Let's just start off a big picture. We're in all this, you know. Hybrid. Multilingual. This discussion went on this week. Obviously, just your thoughts about general trends and where the business is going now supposed to wear? Maybe we're 23 years ago. Well, the >> good thing is for IBM storage, and we actually came to your partner and titty wiki Bond when our new general manager, Ed Walsh, joined. And we came and we saw Dave and John at the old office are at your offices, and we did a pitch about hybrid multi cloud. Remember that gave us some feedback of how to create a new slide. So we created a slide based on Dave's input, and we were doing that two and 1/2 years ago. So we're running around telling the storage analyst Storage Press about hybrid multi cloud based on IBM storage. How weaken transparently move data, things we do with backup, Of course. An archive. You've got about 450 small and medium cloud providers. Their backup is a service engine. Is our spectrum protect? And so we talked about that. So Dave helped us craft the slide to make it better, because he said, we left a couple things >> out that Eric >> owes you. There were a few other analysts I'm sure you talked to and got input, but but us really were the first toe to combine those things in your in your marketing presentations. But >> let's I'd love to get >> an update on the business. Yes, help people understand the IBM storage organization. You guys created the storage business, you know, years and years and years ago. It's a it's a you know you've got your core business, which is column arms dealers. But there's a lot of Regent IBM, the Cloud Division. You've got the service's division, but so help us understand this sort of organizational structure. So >> the IBM story division's part of IBM Systems, which includes both the mainframe products Z and the Power Server entities. So it's a server in storage division. Um, the Easy guys in particular, have a lots of software that they sell and not just mainframe. So they have a very, very large software business, as do we. As you know, from looking at people that do the numbers, We're the second largest storage software company in the world, and the bulk of that software's not running on IBM gear. So, for example, spectrum protect will back up anyone's array spectrum scale and our IBM Cloud Object storage are sold this software only software defined as the spectrum virtualized. You could basically create a J. Bader Jabo after your favorite distributor or reseller and create your honor. Rates are software, but the all of the infrastructure would actually not be ours, not branded by us. And you call us for tech support for the software side. But if you had a bad power supplier fan, you'd have to call, you know, the reseller distributor said this very robust storage software business. Obviously you make sure that was compatible with the other server elements of IBM systems. But the bulk of our storage is actually sitting connect to some server that doesn't have an IBM logo on it. So that's the bulk of our business connected to Intel servers of all types that used to include, of course, IBM Intel Server division, which was sold off to Lenovo. So we still have a very robust business in the array space that has nothing to do with working on a power machine are working on a Z machine, although we clearly worked very heavily with them and have a number of things going with him, including something that's coming very shortly in the middle of September on some new high end products that we're going to dio >> went 90 Sea Counts All this stuff. Do they >> count to give IBM credit for all the storage that lives inside of the IBM Cloud? Do you get you get credit for that or >> not get credit for that? So when they count our number, it's only the systems that we sell and the storage software that we sell. So if you look at if we were a standalone company, which would include support service made everything, some of which we don't get credit for, right, the support and service is a different entity at IBM that does that, UM, the service's group, the tech support that all goes to someone else. We don't have a new credit >> so hypothetical I don't I don't think this is the case, but let's say hypothetically, if pure storage sold an array into IBM Cloud, they would get credit for it. But if you're array and I'm sure this happens is inside of the IBM, you don't get credit for it. >> That's true interesting, so it's somewhat undercounts. Part of that is the >> way we internally count because we're selling it to ourselves. >> But that's it. >> It's not. It's more of an accounting thing, but it's different when we sell the anybody else. So, for example, we sell the hundreds of cloud providers who in theory compete with the IBM Cloud Division >> to you Get credit for that. You get credit for your own away. That's way work. But if we were standing >> on coming for, say, government, we were Zog in store and I bought the company away, we would be about a $6.3 billion standalone storage software company. That's what we would be if we were all in because support service manes. If we were our own company with our own right legal entity, just like net app or the other guys, we'd be Stanley would be in that, you know, low $6 billion range, counting everything all in. When we do report publicly, we only report our storage system because we don't report our storage software business. And as you notice a few times, our CFO has made comments. If we did count, the storage software visit would be ex, and he's publicly stated that price at least two times. Since I've been an idea when he talks about the software on, but legally we only talk about IBM storage systems. When he publicly state our numbers out onto Wall Street, that's all >> we publicly report. So, um, you're like, you're like a walking sheet of knowledge here, but I wonder if you could take the audience through the portfolio. Oh, it's vast. How should we think about it? And the names have changed. You talk about, you know, 250 a raise, whatever it is the old sand volume control. And now it's a spectrum virtualized, >> right? So take us to the portfolio. What's the current? It's free straight for. >> We have really three elements in the portfolio, all built around, if you will, solution plays. But the three real elements in the portfolio our storage arrays, storage systems, we have entry mid range and high end, just like our competitors do. We lead with all flash, but we still sell hybrid and obviously, for backup, an archive. We still sell all hard drive right for those workloads. So and we have filed blocking object just like most other guys do, Um, for an array, then we have a business built around software, and we have two key elements. Their software defined storage, and we saw that software completely stand alone. It happens, too, by the way, be embedded on the arrays. So, for example, Dave, you mentioned Spectrum virtualized that ship's on flash systems and store wise. But if you don't want our raise, we will sell you just spectrum virtualized alone for block spectrum scale for Big Big Data A. I file Workloads and IBM caught object storage, which could all of them could be bought on an array. But they also could be bought. Itjust Standalone component. Yes, there's a software so part of the advantage we feel that delivers. It's some of the people that have software defined storage, that air raid guys. It's not the same software, so for us, it's easier for us to support and service. It's easier for a stack developing have leading it. Features is not running two different pieces of software running, one that happens to have a software on Lee version or an array embedded version. So we've got that, and then the third is around modern data protection, and that's really it. So a modern data protection portfolio built around spectrum, protect and Protect Plus and some other elements. A software to find storage where we sell the software only, and then arrays. That's it. It's really three things and not show. Now they're all kinds components underneath the hood. But what we really do is we sell. We don't really run around and talk about off last race. We talk about hybrid multi cloud. Now all of our flash raise and a lot of our software defined storage will automatically tear data out, too. Hybrid multi cloud configurations. We just So we lead with that same thing. We have one around cyber resiliency. Now, the one thing that spans the whole portfolio of cyber resiliency way have cyber rebellion see and a raise. We have some softer on the mainframe called Safeguarded Copy that creates immutable copies and has extra extra security for the management rights. You've got management control, and if you have a malware ransomware attack, you couldn't recover to these known good copies. So that's a piece of software that we sell on the mainframe on >> how much growth have you seen in that in? Because he's never reveals if you've got it resonating pervasive, right, Pervasive. So >> we've got, for example, malware and ransomware detection. Also, Inspector protect. So it's taken example. So I'm going to steal from the Cube and I'm gonna ask Dave and for you, I want a billion dollars and Dave's gonna laugh at me because he used a spectrum protect. He's gonna start laughing. But if I'm the ransomware guy, what do I do? I go after your snapshots, your replicas and your backup data sets. First, I make sure I've got those under control. And then when I tell you I'm holding you for ransom, you can't go back to a known good copy. So Ransomware goes after backup snaps and replicas first. Then it goes half your primary storage. So what we do, inspector protect, for example, is we know that at Weeki Bond and the Cube, you back up every night from 11 32 1 30 takes two hours to back you up every night. It's noon. There's tons of activity in the backup data sets. What the heck is going on? We send it out to the admin, So the admin for the Cube wicky bond takes a look and says, No server failure. So you can't be doing a lot of recovery because of a bad server. No storage failures. What the heck is going on? It could be a possible mount where ransomware attack. So that type of technology, we encrypt it, rest on all of our store to raise. We have both tape and tape and cloud air gapping. I'm gonna ask you about that. We've got both types of air gapped >> used to hate tape. Now he loves my love, right? No, I used to hate it, But now I love it because it's like the last resort, just in case. And you do air gapping when you do a WR gapping with customers, Do you kind of rotate the You know, it's like, uh, you know, the Yasser Arafat used to move every night. You sleep in a different place, right? You gonna rotate the >> weird analogy? You do >> some stuff. There's a whole strategy >> of how we outlined how you would do a tape air gap, you a cloud air gap. Of course you're replicating or snapping out to the cloud anyway, so they can't get to that. So if you have a failure, we haven't known good copy, depending on what time that is, right. And then you just recover. Cover back to that and even something simple. We have data rest, encryption. Okay. A lot of people don't use it or won't use it on storage because it's often software based, and so is permanent. Well, in our D s platform on the mainframe, we can encrypt with no performance hit on our flash system products we can encrypt with no performance it on our high end store. Wise, we have four models on the two high end stores models we could encrypt with no performance penalty. So why would you not encrypt all your debt? When there's a performance penalty, you have to sort of pick and choose. My God, I got to encrypt this valuable financial data, but, boy, I really wish it wasn't so slow with us. There is no performance it when you encrypt. So we have encryption at rest, encryption at flight malware and ran somewhere detection. We've got worm, which is important, obviously, doesn't mean I can't steal from wicked Bond Cube, but I certainly can't go change all your account numbers for all your vendors. For sake. of argument, right? So and there's obviously heavily regulated industries that still require worm technology, right? Immutable on the fine, by the way, you could always if it's wormed, you could encrypt it if you want to write. Because Worm just means it's immutable. It doesn't. It's not a different data type. It's just a mutable version of that data. >> So the cyber resiliency is interesting, and it leads me to another question I have around just are, indeed so A lot of companies in this industry do a lot of D developing next generation products. I think, you know, look a t m c when you were there, you know, this >> was a lot of there. Wasn't a ton, >> of course, are a lot of patents and stuff like that. IBM does corps are a lot of research and research facilities, brainiac scientists, I want if you could talk about how the storage division takes advantage of that, either specifically, is it relates to cyber resiliency. But generally, >> yes, so as you know, IBM has got, I think it's like 12 12 or 15 research on Lee sites that that's all they do, and everyone there is, in fact, my office had to be. Akiyama didn't labs, and there's two labs actually hear. The AMA didn't research lab and the Silicon Valley lab, which is very close about five miles away. Beautiful. Almost everything. There is research. There's a few product management guys I happen, Navid desk there every once. Well, see a sales guy or two. But essentially, they're all Richard with PhDs from the leading inverse now at Al Madden and many sites, all the divisions have their own research teams there. There's a heavy storage contingent at Al Midan as an example. Same thing in Zurich. So, for example, we just announced last week, as you know, stuff that will work with Quantum on the tape side. So you don't have to worry about because one of things, obviously, that people complain about quantum computing, whether it's us or anyone else, the quantum computing you can crack basically any encryption. Well, guess what? IBM research has developed tape that can be encrypted. So if using quantum computer, whether it be IBM or someone else's when you go with quantum computing, you can have secured data because the quantum computer can't actually cracked the encryption that we just put into that new tape that was done at IBM Research. How >> far away are we from From Quantum, actually being ableto be deployed and even minor use cases. >> Well, we've got available right now in ibm dot com for Betas. So we've got several 1000 people who have been accidents in it. And entities, we've been talking publicly in the 3 to 7 year timeframe for quantum computer crap out. Should it? Well, no, because if you do the right sort of security, you don't but the power. So if you're envisioning one of my favorite movies, I robot, right where she's doing her talking and that's that would really be quantum in all honesty. But at the same time, you know, the key thing IBM is all about ethics and all about how we do things, whether it be what we do with our diversity programs and hiring. And IBM is always, you know, at the forefront of doing and promoting ethical this and ethical. Then >> you do a customer data is huge. >> Yeah, and what we do with the customer data sets right, we do. GDP are, for example, all over the world were not required by law to do it really Only in Europe we do it everywhere. And so if you're not, if you're in California, if you happen to be in Zimbabwe or you're in Brazil, you get the same protection of GDP are even though we're not legally required to do it. And why are we doing that? Because they're always concerned about customers data, and we know they're paranoid about it. We want to make sure people feel comfortable with IBM. We do. Quantum computing will end up in that same vein. >> But you know, I don't worry about you guys. I were about the guys on the other side of the fence, the ones that I worry about, the same thing Capabilities knew that was >> on, of course. And you know, he talked about it in his speech, and he talked about action on the Cube yesterday about some of his comments on the point, and he mentioned that was based on Blockchain. What he said was Blockchain is a great technology. They've got Blockchain is no. IBM is a big believer in Blockchain. We promoted all over the place and in fact we've done all kinds of different Blockchain things we just did. One announced it last week with Australia with the Australian. I think it is with their equivalent of Wall Street. We've done some stuff with Merrick, the big shipping container thing, and it's a big consortium. That's all legal stuff that was really talking about someone using it the wrong way. And he's very specific point out that Blockchain is a great technology if used ethically, and IBM is all about how we do it. So we make sure whether be quantum computing, Blockchain, et cetera, that everything we do at IBM is about helping the end users, making sure that we're making, for example, open source. As you know. Well, the number one provider of open source technology pre read had acquisition is IBM. We submit Maur into the open community. Renounce Now are we able to make some money off of that? Sure we are, but we do it for a reason, because IBM believes as day point out in this core research. Open computing is court research, and we just join the Open Foundation last week as well. So we're really big on making sure that what we do ourselves is Ethel now We try to make sure that what happens in the hands of people who buy our technology, which we can always track, is also done ethically. And we go out of our way to join the right industry. Associations work with governments, work with whatever we need to do to help make sure that technology could really be iRobot. Anyone who thinks that's not true. If you talk to your grandparent's goto, go to the moon. What are you talking about? >> What Star Trek. It's always >> come to me. Oh, yeah, >> I mean, if you're your iPhone is basically the old community. Transport is the only thing I wish I could have the transfer. Aziz. You know, >> David has the same frame us up. I'm afraid of flying, and I I felt like two million miles on United and David. He's laughs about flowers, so I'm waiting for the transport. I know that's why anymore there's a cone over here. Go stand. Or maybe maybe with a little bit of like, I'm selling my Bitcoin. No, hang on, just hold on. There's always a comeback. Not always. There could be a comeback because Derek always enjoy it as always. Thanks for the good seeing you. All right, Back with more Veum. World 2019 The Cube live in San Francisco.

>> Live from San Francisco. Its The Cube. Covering IBM Think 2019. Brought to you by, IBM. >> Okay, welcome back everyone, live here in The Cube here in San Francisco, exclusive coverage of IBM Think 2019. I'm John Furrier and Stu meeting next guest is Calline Sanchez, Vice President of IBM Systems Labs Services. New role for you, welcome back to the cube. >> Yes. Thank you for asking me back. >> So the new role, Vice President of the Systems Lab Services. Sounds super cool, sounds like you got a little lab in there, a little experimentation >> yeah think of it as a sandbox for geeks worldwide. And what that means is we enable high performance computing deployments as well as what we do with blockchain and also artificial intelligence. >> So its a play ground for people that want to do some big things, solve big problems, what are some of the things that you offer, just take us through how it works. Do I just jump in online, is it a physical location? What's it like ? In 2018 9000 plus engagements worldwide in 123 countries. So to net it out is, it's not necessarily a single lab or a single garage, we have multiple locations and skills worldwide to enable these engagements. >> How big is the organization roughly? Its over a thousand folks, consultants who are smart and capable. >> We had a conversation yesterday with Jamie Thomas, talking about, from a super computer stand point, now IBM's reclaimed the top couple of positions there and from a research stand point, David Floyer from our team has been talking for years about how HPC architectures are really going to permeate what happens in the industry and I think about distributed architectures, it all seems to go back to what people in the HPC environment lived in. You've got background in that, you worked for one of the big labs, explain how this has come from something some government lab used to do to something that now many more companies around the globe are leveraging. >> Before IBM I worked at Sandia National Laboratories and the reason why I chose to work with these awesome skills worldwide in lab services is that I wanted to be part of the cool group, so to speak. So they were doing work in deployments with Oak Ridge National Laboratories and also Laurence Lilvermore. So you'll hear (inaudible) with Laurence Livermore speak on stage about some of the relevance associated with high performance computing and why were number 1. So, to get to our question it's cool to be back online with what I could say, high performance computing deployment. We are the mechanics so to speak in this organization. Similar to what we do with formula 1, people who put on the tires, add the air and also enable the cars to move around. Well without them, guess what? Things don't move around. >> So you guys work on the high performance systems, you got quantum coming around the corner, you got AI front and center so you guys are like the hot shots. You come in, you build solutions with what's in the tool chest, if you will with IBM, is that right ? >> correct You're 100% correct. I will say it in my mind, we make things real. We deploy and implement strategic technologies worldwide for the benefit of our end users and we do that also with our partners. >> Give an example of an engagement you guys have had that's notable, that's worth sharing. >> Recently, this was a really exciting area a Smarter Cities with Kazakhstan. And so heres this independent city that works on basically AI for filming things whether its a security thing recognizing certain faces, deployments associated with weapons etc. And they were able to secure safety based on the film, films that they've taken, those assets. Now the other aspect is managing safer traffic. So even the president of Kazakhstan felt it was extremely relevant that we helped him deploy and he comes back to one of our European leaders saying, hey we need more of this and we want it to be extensive, we want to scale this opportunity. >> Talk about the philosophy's you guys are deploying because it sounds like its a... you said sandbox, when I think sandbox I think you do prototypes, I'm thinking about cool stuff, building solutions and that kind of brings this whole entrepreneurial creation mindset. Do you guys have like a design thinking methodology, is there things you're bringing to the table what else is involved besides the sandbox? >> You are correct. We have a very key component of design thinking. There's a CTO that reports to me directly who leads our overall design thinking and so that's a key component of what we do worldwide. Now as far as... We also enable incubation of technologies. So it's like what we intend to do with IBM Cube, What we intend to do with blockchain on system Z. So with these things we have garages worldwide to deploy or incubate the technology. >> What's the coolest thing you've worked on so far? Or the team's worked on? >> That's really hard to say 'cause there's so much. >> It's like picking a favorite child. >> Yeah, it's like I have way too many. So I was - >> You mention blockchain. I like blockchain. Blockchain, are you in healthcare, is it more, is there certain industries that are popping out for you guys? >> So healthcare is an example but I have seen it in the telecom area as well as other industries in general. So we have 11 industries in which we serve. >> How about AI? We're always trying to understand where customers are, how they're really moving things forward, to understand that that HPC architecture is a foundational layer for many customers to help deploy AI. Where are customers starting to make progress ? Give us some of the vibe you're feeling from customers out there. >> So its exciting with AI right now because we have Power Vision that allows us as any of us to actually exploit, utilize and play with, so to speak. So from my perspective that is what's nice, is that you can enable opportunities with the consumer market and learn. Similar to what we do with, and for instance, I am jumping around here, IMB Cube. Where users can actually become a user and start evaluating algorithms in order to enable this really amazing technology as in IB Cube. >> That was always the promise of big date, is that we should be able to leverage our data and get the average business user to do it. So it sounds like AI will continue that trend. >> Correct. So in prior rule, I talked to all of you about big data storage, right and replication. So now what's amazing about the conversations is that they've transcended. Its like, here you're looking to manage these large data warehouses, when, what do you do with the data? How's it monetized, how is it used in order to solution what's possible. >> What is the goal of the organization, next 6 months, year, what's the charter, what's your key performance indicators, how do you guys measure success, client engagements, onboarding people, what is the business objectives? >> So we look at the number of engagements, we also look at educational services worldwide for instance I will be in Cairo, Egypt next week to work on specific things that are going on in Mia in order to enable this next growth market so to speak. What in addition we do to measure ourselves, utilization, classic services organization view of the world. So we also evaluate what we can do with revenue, profit and our understanding of growth and we really believe the focus is these growth technologies. >> Is there a criteria if I wanted to get involved, just say I am a customer, prospect, wow, I really want to get into this design thinking, got these labs, coolest labs services, I want to play with the cutting edge technologies, how do I get involved? Is there a criteria open to all or how does it work? >> In addition to IBM Systems Labs Services, I have technical universities and we actually run technical universities worldwide for end users, clients as well as what we do with partners and IBMers. And this is important because we're able to then discuss, talk, collaborate with SME's across multiple areas of technology. So its a very good question and very important that I mention the technical universities. >> Are there certifications along that line? What are some of the hot skill sets that people are looking to learn about ? >> It circles right back to your last question, AI. With regards to how we certify folks as well as we, in essence, they get enough training in boot camps in order to get badges. >> So their certification, they just pass the touring test and then they're okay. >> correct. Well. (laughs) I don't know about the touring test so to speak. >> So is there a website on IBM.com, is there like a URL as in like labservices.ibm.com? >> I personally like the look at twitter where you can do a search on IBM Lab Services or Tech U. >> Tech U. And screening, how big is that focus, used a lot of video, is it collaborative tooling is it face to face, virtual, how do you guys do the training, all the above? >> Unfair, I was going to say all of the above. (laughs) It depends. (laughs) Giving that classic response, our favorite is video blogs. What we can do in social media with the YouTube channels etc. to get our opinions or our voice out with regards to key technologies. >> Well great, make sure you let us know what those channels are and we'll promote them, get that metadata out there, of course The Cube loves to collaborate. And thanks for coming on and sharing. >> I appreciate it and I will definitely take a sticker and put it on my laptop. >> Calline Sanchez, Vice President of the new IBM Systems Lab Services. A lot of opportunities to get in the worldwide sandbox and put the sluices together from blockchain to cutting edge AI. Your live coverage here at San Francisco at IBM Think, I'm (inaudible) stay with us for more coverage after this short break. (lively music)

>> Live from San Francisco. It's theCube covering IBM Think 2019. Brought to you by IBM. >> Welcome back to Moscone Center everybody. The new, improved Moscone Center. We're at Moscone North, stop by and see us. I'm Dave Vellante, he's Stu Miniman and Lisa Martin is here as well, John Furrier will be up tomorrow. You're watching theCube, the leader in live tech coverage. This is day zero essentially, Stu, of IBM Think. Day one, the big keynotes, start tomorrow. Chairman's keynote in the afternoon. Jamie Thomas is here. She's the general manager of IBM's Systems Strategy and Development at IBM. Great to see you again Jamie, thanks for coming on. >> Great to see you guys as usual and thanks for coming back to Think this year. >> You're very welcome. So, I love your new role. You get to put on the binoculars sometimes the telescope. Look at the road map. You have your fingers in a lot of different areas and you get some advanced visibility on some of the things that are coming down the road. So we're really excited about that. But give us the update from a year ago. You guys have been busy. >> We have been busy, and it was a phenomenal year, Dave and Stu. Last year, I guess one of the pinnacles we reached is that we were named with our technology, our technology received the number one and two supercomputer ratings in the world and this was a significant accomplishment. Rolling out the number one supercomputer in Oakridge National Laboratory and the number two supercomputer in Lawrence Livermore Laboratory. And Summit as it's called in Oakridge is really a cool system. Over 9000 CPUs about 27,000 GPUs. It does 200 petaflops at peak capacity. It has about 250 petabytes of storage attached to it at scale and to cool this guy, Summit, I guess it's a guy. I'm not sure of the denomination actually it takes about 4,000 gallons of water per minute to cool the supercomputer. So we're really pleased with the engineering that we worked on for so many years and achieving these World records, if you will, for both Summit and Sierra. >> Well it's not just bragging rights either, right, Jamie? I mean, it underscores the technical competency and the challenge that you guys face I mean, you're number one and number two, that's not easy. Not easy to sustain of course, you got to do it again. >> Right, right, it's not easy. But the good thing is the design point of these systems is that we're able to take what we created here from a technology perspective around POWER9 and of course the patnership we did with Invidia in this case and the software storage. And we're able to downsize that significantly for commercial clients. So this is the world's largest artificial intlligence supercomputer and basically we are able to take that technology that we invented in this case 'cause they ended up being one of our first clients albeit a very large client, and use that across industries to serve the needs of artificial intelligence work loads. So I think that was one of the most significant elements of what we actually did here. >> And IBM has maintained, despite you guys selling off your microelectronics division years ago, you've maintained a lot of IP in the core processing and the design. You've also reached out certainly with open power, for example, to folks. You mentioned Invidia. But having that, sort of embracing that alternative processor mode as opposed to trying to jam everything in the die. Different philosophy that IBM is taking. >> Yeah we think that the workload specific processing is still very much in demand. Workloads are going to have different dimensions and that's what we really have focused on here. I don't think that this has really changed over the last decades of computing and so we're really focused on specialized computing purpose-built computing, if you will. Obviously using that on premise and also using that in our hybrid cloud strategies for clients that want to do that as well. >> What are some of the other cool things that you guys are working on that you can talk about. >> Well I would say last year was quite an interesting year in that from a mainframe perspective we delivered our first 19 inch form factor which allows us to fit nicely on a floor tile. Obviously allows clients to scale more effectively from a data center planning perspective. Allows us to have a cloud footprint, but with all the characteristics of security that you would normally expect in a mainframe system. But really tailored toward new workloads once again. So Linux form factor and going after the new workloads that a lot of these cloud data centers really need. One of our first and foremost focus areas continues to be security around that system and tomorrow there will be some announcements that will happen around Z security. I can't say what they are right now but you'll see that we are extending security in new ways to support more of these hybrid cloud scenarios. >> It's so funny. We were talking in one of our earlier segments talking about how the path of virtualization and trying to get lots of workloads into something and goes back to the device that could manage all workloads which was the Mainframe. So we've watched for many years system Z lots of Linux on there if you want to do some cool container, you know global Z that's an option, so it's interesting to watch while the pendulum swings in IT have happened the Z system has kept up with a lot of these innovations that have been going on in the industry. >> And you're right, one of our big focuses for the platform for Z and power of course is a container-based strategy. So we've created, you know last year we talked about secure container technology and we continue to evolve secure container technology but the idea is we want to eliminate any kind of friction from a developer's perspective. So if you want to design in a container-based environment then you're more easily able to port that technology or your applications, if you will to a Z mainframe environment if that's really what your target environment is. So that's been a huge focus. The other of course major invention that we announced at the Consumer Electronics show is our Quantum System One. And this represented an evolution of our Quantum system over the last year where we now have the world's really first self-contained universal quantum computer in a single form factor where we were able to combine the Quantum processor which is living in the dilution refrigerator. You guys remember the beautiful chandelier from last year. I think it's back this year. But this is all self-contained with it's electronics in a single form factor. And that really represents the evolution of the electronics in particular over the last year where we were able to miniaturize those electronics and get them into this differentiated form factor. >> What should people know about Quantum? When you see the demos, they explain it's not a binary one or zero, it could be either, a virtually infinite set of possibilities, but what should the lay person know about Quantum and try to understand? >> Well I think really the fundamental aspect of it is in today's world with traditional computers they're very powerful but they cannot solve certain problems. So when you look at areas like material science, areas like chemistry even some financial trading scenarios, the problems can either not be solved at all or they cannot be completed in the right amount of time. Particularly in the world of financial services. But in the area of chemistry for instance molecular modeling. Today we can model simple molecules but we cannot model something even as complex as caffeine. We simply don't have the traditional compute capacity to do that. A quantum computer will allow us once it comes to maturity allow us to solve these problems that are not solvable today and you can think about all the things that we could do if were able to have more sophisticated molecular modeling. All the kinds of problems we could solve probably in the world of pharmacology, material science which affects many, many industries right? People that are developing automobiles, people that are exploring for oil. All kinds of opportunities here in this space. The technology is a little bit spooky, I guess, that's what Einstein said when he first solved some of this, right? But it really represents the state of the universe, right? How the universe behaves today. It really is happening around us but that's what quantum mechanics helps us capture and when combined with IT technology the quantum computer can bring this to life over time. >> So one of the things that people point to is potentially a new security paradigm because Quantum can flip the way in which we do security on it's head so you got to be thinking around that as well. I know security is something that is very important to IBM's Systems division. >> Right, absolutely. So the first thing that happens when someone hears about quantum computing is they ask about quantum security. And as you can imagine there's a lot of clients here that are concerned about security. So in IBM research we're also working on quantum-safe encryption. So you got one team working on a quantum computer, you got another team ensuring that the data will be protected from the quantum computer. So we do believe we can construct quantum-safe encryption algorithms based on lattice-based technology that will allow us to encrypt data today and in the future when the quantum computer does reach that kind of capacity the data will be protected. So the idea is that we would start using these new algorithms far earlier than the computer could actually achieve this result but it would mean that data created today would be quantum safe in the future. >> You're kind of in your own arm's race internally. >> But it's very important. Both aspects are very important. To be able to solve these problems that we can't solve today, which is really amazing, right? And to also be able to protect our data should it be used in inappropriate ways, right? >> Now we had Ed Bausch on earlier today. Used to run the storage division. What's going on in that world? I know you've got your hands in that pie as well. What can you tell us about what's going on there? >> Well I believe that Ed and the team have made some phenomenal innovations in the past year around flash MVME technology and fusing that across product lines state-of-the-art. The other area that I think is particularly interesting of course is their data management strategy around things like Spectrum Discover. So, today we all know that many of our clients have just huge amounts of data. I visited a client last year that interesting enough had 1 million tapes, and of course we sell tapes so that's a good thing but then how do you deal and manage all the data that is on 1 million tapes. So one of the inventions that the team has worked on is a metadata tagging capability that they've now shipped in a product called spectrum discover. And that allows a client to have a better way to have a profile of their data, data governance and understand for different use cases like data governance or compliance how do they pull back the right data and what does this data really mean to them. So have a better lexicon of their data, if you will than what they can do in today's world. So I think that's very important technology. >> That's interesting. I would imagine that metadata could sit in Flash somewhere and then inform the serial technology to maybe find stuff faster. I mean, everybody thinks tape is slow because it's sequential. But actually if you do some interesting things with metadata you can-- >> There's all kinds of things you can do I mean it's one thing to have a data ocean if you will, but then how do you really get value out of that data over a long period of time and I think we're just the tip of the spear in understanding the use cases that we can use this technology for. >> Jamie, how does IBM manage that pipeline of innovation. I think we heard very specific examples of how the super computers drive HPC architectures which everybody is going to use for their AI infrastructure. Something like quantum computing is a little bit more out there. So how do you balance kind of the research through the product and what's going to be more useful to users today. >> Yeah, well, that's an interesting question. So IBM is one of the few organizations in the world really that have an applied research organization still. And Dario Gil is here this week he manages our research organization now under Arvind Krishna. An organization like IBM Systems has a great relationship with research. Research are the folks that had people working on Quantum for decades, right? And they're the reason that we are in a position now to be able to apply this in the way that we are. The great news is that along the way we're always working on a pipeline of this next generation set of technologies and innovations. Some of them succeed and some of them don't. But without doing that we would not have things like Quantum. We would not have advanced encryption capability that we pushed all the way down into our chips. We would not have quantum-safe encryption. Things like the metadata tagging that I talked about came out of IBM research. So it's working with them on problems that we see coming down the pipe, if you will that will affect our clients and then working with them to make sure we get those into the product lines at the right amount of time. I would say that Quantum is the ultimate partnership between IBM Systems and IBM research. We have one team in this case that are working jointly on this product. Bringing the skills to bear that each of us have on this case with them having the quantum physics experts and us having the electronics experts and of course the software stacks spanning both organizations is really a great partnership. >> Is there anything you could tell us about what's going on at the edge. The edge computing you hear a lot about that today. IBM's got some activities going on there? You haven't made huge splashes there but anything going on in research that you can share with us, or any directions. >> Well I believe the edge is going to be a practical endeavor for us and what I mean by that is there are certain use cases that I think we can serve very well. So if we look at the edge as perhaps a factory environment, we are seeing opportunities for our storaging compute solutions around the data management out in some of these areas. If you look at the self-driving automobile for instance, just design something like that can easily take over a hundred petabytes of data. So being able to manage the data at the edge, being able to then to provide insight appropriately using AI technologies is something we think we can do and we see that. I own factories based on what I do and I'm starting to use AI technology. I use Power AI technology in my factories for visual inspection. Think about a lot of the challenges around provenance of parts as well as making sure that they're finally put together in the right way. Using these kind of technologies in factories is just really an easy use case that we can see. And so what we anticipate is we will work with the other parts of IBM that are focused on edge as well and understand which areas we think our technology can best serve. >> That's interesting you mention visual inspection. That's an analog use case which now you're transforming into digital. >> Yeah well Power AI vision has been very successful in the last year . So we had this power AI package of open source software that we pulled together but we drastically simplified the use of this software, if you will the ability to use it deploy it and we've added vision capability to it in the last year. And there's many use cases for this vision capability. If you think about even the case where you have a patient that is in an MRI. If you're able to decrease the amount of time they stay in the MRI in some cases by less fidelity of the picture but then you've got to be able to interpret it. So this kind of AI and then extensions of AI to vision is really important. Another example for Power AI vision is we're actually seeing use cases in advertising so the use case of maybe you're at a sporting event or even a busy place like this where you're able to use visual inspection techniques to understand the use of certain products. In the case of a sporting event it's how many times did my logo show up in this sporting event, right? Particularly our favorite one is Formula One which we usually feature the Formula One folks here a little bit at the events. So you can see how that kind of technology can be used to help advertisers understand the benefits in these cases. >> Got it. Well Jamie we always love having you on because you have visibility into so many different areas. Really thank you for coming and sharing a little taste of what's to come. Appreciate it. >> Well thank you. It's always good to see you and I know it will be an exciting week here. >> Yeah, we're very excited. Day zero here, day one and we're kicking off four days of coverage with theCube. Jamie Thomas of IBM. I'm Dave Vellante, he's Stu Miniman. We'll be right back right after this short break from IBM Think in Moscone. (upbeat music)

>> Narrator: Live from Las Vegas, it's TheCUBE! Covering IBM Think 2018. Brought to you by IBM. >> Hello everyone I'm John Furrier, we're here inside TheCUBE Studios at Think 2018. We're extracting the scene, even though it's actually our live event coverage leader, covering IBM Think. The big tent event taking six shows down to one. Big tent event. Everyone's here; the customers, developers, all the action. My next guest is Jamie Thomas, General Manager of IBM's Systems Strategy and Development. Good to see you Cube alumni, thanks for coming by. >> Good to see you, it's always one of the highlights of my parts of these meetings is getting a chance to talk with you all about what we're doing. >> We've had, I can't even remember how many, it's like eight years now, but you've been on pretty much every year, giving the update. I was just riffing on the opening about blockchain the innovation sandwich at IBM. I'm calling it the innovation sandwich, that's not what you guys are calling it. It really is about the data, and then blockchain and AI, that's the main thing with Cloud as the foundational element. You're in strategy. Systems. So you have all the underlying enabling technology with IBM and looking at that direction. Part of the innovation sandwich is systems. >> Absolutely, I think it fundamentally what we're seeing is all of the work and innovation we've invested in over the last few years is finally culminating in a really nice conclusion for us, if you will. Because if you look at the trajectory of those forces you spoke about right? Which is how do we harness the power of data? Of course, to harness that data we have to apply techniques like artificial intelligence, machine learning, deep learning to really get the value out of the data. And then we have to underpin that with a multi-cloud architecture. So we really do feel that all the innovations that we've been working on for the last few years are now coming to bear to help our clients solve these problems in really unique ways. >> We've had many conversations, we've gone down in the weeds, we've been under the hood, we've talked about business value. But I think that what I'm seeing and what TheCube is reporting over the past year and more recently is, there's now a clear line of sight for the customers. The interesting thing is the model's flipped around as we've always been seeing, but it's clear, dev ops enabled cloud to be successful where we have a programmable infrastructure. You guys have been doing software defined systems for a long time. But now with blockchain, cryptocurrency and decentralized application developers, you have inefficiencies being disrupted by making things more efficient. We're seeing the business logic be the intellectual property. So users, business users, business decision makers are looking at the business model of token economics. It's kind of at the top of the business stack that have to manage technology now. So the risk is flipped around. It used to be that technology was the risk. Technology purchase, payback period over ten plus years, more longevity to the cycle. Now you've got Agile now going real-time, this requires everything to be programmable. The data's got to be programmable, the systems have to be programmable. What's the IBM solution there? How do you guys fit that formula? Do you agree with it? Your thoughts. >> Well absolutely, I think that fundamentally you have infrastructure that can really meet the needs and characteristics of the next generation killer applications, right? So whether that's blockchain, or whether we're talking about artificial intelligence across numerous industries and every industry is looking at applying those techniques. You have to ensure that you have an architectural approach with your infrastructure that allows you to actually get the result from a client perspective. When we look at the things that we've invested in we're really investing in infrastructure that we feel allow clients to achieve those goals. If you look at what we've done with things like Power9, the ability to create a high speed interconnect with things like GPU acceleration using our partner NVIDIA's technology as an example. Those are really important characteristics of the infrastructure to be able to enable clients to then achieve the goals of something like artificial intelligence. >> What's different for the people that are now getting this, coming in, how do you summarize the past few years of strategy and development around the systems piece? Because systems programming is all about making things smaller, faster, cheaper, Moore's Law. But also having a network effect in supply chains or value chains, blockchain or whatever that is, that's the business side. What's new, how do you talk about that to the first time to someone who's now for the first time going, okay, I get it. It's clear. What's the system equation? How do you explain that to someone? >> Well I think it's a combination of focusing on both economics, but also having a keen eye on where the puck is going. In the world of hardware development, you have to have that understanding at least a year and a half, two years back, to actually culminate in a product offering that can serve the needs at the right time. So I think we've looked at both of those combinations. It's not just about economics. Is is about also being specialized, being able to serve the needs of the next generation of killer applications and therefore the programmers that support those applications. >> What's the big bet that you guys have made? If you could look back of the past three, four years, in the trials and tribulations of storage, compute, cloud, and it's been a lot of zigging and zagging. Not pivoting, because you guys have been innovating. What's the one thing, a few things you can point to, one thing or a few things and saying that was a good bet, that's now fruits coming off the tree in this new equation. >> Well, I think there's a few things and all of these things were done with a context that we believe that artificial intelligence and cloud architectures were here to stay. But if you look at the bets we made around the architecture of Power9, which was really how do we make this the best architecture in the world for artificial intelligence execution? All of those design points, all of the thought about the ecosystem around the partners, OpenPOWER, the connectivity between the GPU and the CPU that I mentioned. All of that and the software stack the investments we've made in things like PowerAI to allow developers to easily use the platform for that have been fundamentally important. Then if you look at what we did in the Z platform, it's really about this notion about pervasive encryption. Allowing developers to use encryption without forethought. Ensuring that performance would always be on. They would not have to change their applications. That's really fundamentally important for applications like blockchain. To be able to have encryption in the cloud, the kind of services we announced yesterday. So these bets of understanding that it's not just about the short term, it's about the long term and this next generation of applications. As we all know, as you and I know, you can't serve those kind of applications without having an understanding of the data map. How are you going to manage the just huge amounts of data that these organizations are dealing with? So our investments, for years now, in software defined storage, our Spectrum Storage family, and our Flash have served us well. Because now we have the mechanisms, if you will, at our fingertips to manage storage and data in these multi-cloud architectures as well as improve data latency. Access to data through the things we've done. >> So the performance is critical there? >> Yeah, absolutely, the things we've done with Flash, and the things we've done with our high end storage with the mainframe, the zHyperlink capability we've built in there between the KEK and the storage device, those are really, really important in this new world order of these kinds of next generation applications. >> Yeah, skating where the puck is is great and then sometimes you're just near there and the puck comes to you, however, whatever way you want to look at it. Take a minute to explain your role now, what specifically does systems mean? Where does it begin and where does it stop? You mentioned software stack, software defined storage, we get that piece. What's the system portfolio look like? >> We're focused on the modern infrastructure of the future. And of course that infrastructure involves hardware. It involves systems and storage. But it also fundamentally involves infrastructure-related hardware, software stacks. So we own and manage critical software stacks. The creation of things like PowerAI that work with the IBM Cloud team to ensure that IBM Cloud Private can support our platforms, Power and Z out of the box. Those are all fundamentally important initiatives. We of course still own all of the operating systems everybody loves, whether it's Linux, AIX, Z/OS, as well as the work around all the transactional systems. But first and foremost, there's a really tight tie as we all know, between hardware and then the software that needs to be brought to bear to execute against that hardware, the two have to be together, right? >> What about R&D? What's the priority on R&D? It's the continuation of some of the things you just mentioned, but is there anything on the radar that you can share in R&D that's worth noting? >> Well I think, clearly we're working on the next evolution of these systems already. The next series of Power9's we have new machines rolling out this month from a Power9 perspective. We're always working on the next generation of the mainframe of course. But I'd say that our project that's gotten a lot of note at the conferences is our Quantum project. So IBM Systems is partnering with IBM Research to create the Quantum computer. That would be the most leading edge effort that we have going on right now, so that's pretty exciting. >> Yeah, and that's always good stuff coming out. Smaller, how big is this Quantum, can you put it on your finger? Was that the big news? A lot of great action there. >> Well the Quantum computer is a very different form factor. It's truly an evolutionary, revolutionary event, if you will, from a hardware perspective, right? Because the qubit itself has to run at absolute zero. So it has to run in a very cold environment. And then we speak to it through a wave-based communications, if you will, coming in from an electronic stack. It's fundamentally a huge change in hardware architecture. >> What's that going to enable for the folks watching? Is it more throughput? More data? New things, what kind of enablement do you guys envision? >> Well first of all the Quantum computer will never replace classical computers because they're very different in terms of what they can process. There's many problems today in the world that are really not solvable. Problems around chemistry, material science, molecular modeling. There's certainly certain financial equations that really are processable but not processable in the right amount of time. So when you look at what we can do with Quantum, I think there will be problems that we can solve today that we can't even solve. As well as it will be an accelerator to a lot of the existing traditional systems if you will, to allow us to accelerate certain operations. If we think about the creation of more intelligent training models for instance, to apply against artificial intelligence problems, we could anticipate that the Quantum computer could help speed up the evolution and development of these models. There is a lot of interest in working on this evolution of hardware because it's somewhat like the 1940's era of the mainframe. We're at the very beginning stages and we all know that when we evolve the mainframe it was through significant partnerships. Helping the man get to the moon. Working with airlines on the airline's reservation system. It was these partnerships that really enabled us to understand what the power of the machine could be. I think it will be the same way with Quantum as we work with our partners on that endeavor. >> Talk about the, because performance is critical, and you know blockchain has been criticized as having performance problems, writing to the chain, if you will. So clearly there's a problem opportunity basis you can work on there. What are the problems in blockchain, is that your area? Do you work on that? Are you vectoring into blockchain? >> Well of course we're very involved in the blockchain efforts because IBM secure blockchain is running on our z14 processor. One of the things we want to take advantage there is not only the performance of the system, but also, once again, the security characteristics. The ability to just encrypt on the fly. The exploitation of the fast encryption, the cryptology module, all of that, is really key fundamental in our journey on blockchain. I also think that we have a unique perspective in IBM on blockchain because we're a consumer of blockchain. We're already using it in our CFO office. I've spoken to you guys before about supply chains, I own the supply chain manufacturing for IBM and we're also running a shadow process for blockchain where we're working on customs declarations just like Maersk was talking about yesterday. Because customs declarations is a very difficult process. Very manual, labor intensive, a lot of paper. So we're doing that as well, and we'll be a test case for IBM's blockchain work. >> And I've heard from last night that you have 100 customers already. You've heard my opening, I was ranting on the opportunity that blockchain has which is to take away inefficiencies. And supply chain, you guys no stranger to supply chain, you've been bringing technology to solve supply chain problems for generations at IBM. Blockchain brings a new opportunity. >> It does, and my team fundamentally realizes this of course, as a supply chain organization. We ship over five million pieces of stuff every year. We're shipping into 170 countries. We have a tight but dispersed manufacturing operations, so we see this everyday. We have to ship products into every country in the world. We have to work with a very dispersed network through our partners of logistics. So we see the opportunity in blockchain for things like customs declarations as a first priority, but obviously, the logistics network, there's just huge opportunities here where far too much of this is really done manually. >> You guys could really run the table on this area. I mean blockchain, supply chain, chain I mean similar concept it's just decentralized and distributed. >> Well I think supply chain is such an area ripe for this kind of application. Something that's really going to breakthrough what has been so labor intensive from a manual perspective. Even if you look at how ports are managed and Maersk talked about that yesterday. >> So you're long on blockchain? >> Well, I'm excited about it because I'm a customer of blockchain. I see the issues that occur in supply chains everyday and I fundamentally think it will be a game changer. >> Yeah, I'm biased, I mean we're trying to move our media business to the blockchain because everything's decentralized. I'm excited about the application developer movement that's starting now. You're starting to see with crytocurrency, token economics come into play around the business model innovations. Do you guys talk about that internally when you do R&D? You have to cross-connect the business model logic token economics with the technology? >> Well of course you know that's a fundamental part of what the blockchain focus on right? It's just like any new project that we embarked on. You've got to get the underlying technology right but you've always have to do that in the context of the business execution, the business deployment. So we're learning from all the engagements we're doing. And then that shapes the direction that we take the underlying technology into. >> Jamie, talk about the IBM Think 2018, it's a big event. I mean you can't multiply yourself times six. You go to all the events. This is a big event. You must be super busy. What's the focus? What's your reaction, what have you been talking about? >> Well it's kind of nice to talk to you kind of towards the end of the event. Sometimes I talk to you guys at the very beginning of the event so they all kind of have a retrospective of the things that have happened. I think it was a great event in terms of showcasing our innovation, but also having a number of key CEO's from various firms talk to us about how they're really using this technology. Great examples from RBC, from Maersk, from Verizon, from the NVIDIA CEO yesterday. And also some really pointed discussions around looking into the future. So we had a research talk about, Arvind Krishna spoke about, the next five big plays. Which are artificial intelligence, blockchain, Quantum were on that list certainly. As well as now we'll be having a Quantum keynote later today so we'll dive into Quantum a little bit more in terms of how the future will be shaped by that technology. But I think it was a nice mix of hearing about the realization of deploying some of the things that we've done in IBM, but combined with where are things going and stimulating thought with the client which is always important in these kind of meetings. It is having that strategic discussion about how we can really partner with them. >> Real conversations. >> Yeah, real conversations about how we can partner with them to be successful as they leave this conference and go back to their home offices. >> Well congratulations on a great strategy, you've been running strategy. I know we've talked in the past. You've kind of had to bring it all together into one package, into one message, but still have the ability and flexibility to manage the tech. So my final question for you is where's the puck going next? Where are you skating now strategy wise to catch that next puck? >> Well I think that what we'll see is a continued progression, if you will, and speed around some of the things that we've already talked about here. I think there's been a lot of discussion for instance, around multi-cloud architectures. But I really think we're still at the tip of the spear in fundamentally getting the value out of those architectures. That real deployment of some of those architectures as clients modernize their applications and really take advantage of Cloud, I think will drive a different utilization of storage, and it will require different characteristics out of our systems as we go forward. So I think that we're at the tip of a journey here that will inform us. >> The modernization and business model innovation, technology enablement all coming together. >> Right, we were talking about that right? So think about the primary use case of IBM Cloud Private right now is modernization of those applications. So as those clients modernize those applications and then start to deploy these new techniques in combination with that; around artificial intelligence and blockchain, there's just a huge opportunity for us to continue this infrastructure innovation journey. >> International Business Machines. The name of the company obviously, and you know my opinion on this, we're reporting that the real critical intellectual property for customers is going to be the business innovation, the business model opportunities in blockchain, AI, really accelerate that piece. >> And as Ginni said yesterday, we're here to serve our clients, to make sure that they're successful in moving from where they have been and the continuation of this journey. And so that will be where we keep our focus as we go forward. >> Well looking forward to talking about token economics. I think that's going to be a continued conversation as you guys create more speed, more performance, the business model innovations around token economics. And then decentralized application developers will probably impact IoT, will probably impact a lot of these fringe, emerging, use cases that need compute, that need power. They need network effect, they need data. >> Absolutely, so I mean there's been a lot of discussion this week about making sure that we move the processing to the data, not the data to the processing because obviously you can't move all that data around. That's why I think these and Fungible architecture and Agile architecture will give clients the ability to do that more effectively. And as you said, we always have to worry about those developers. We have to make sure that they have the modern tools and techniques that allow them to move with speed and still take advantage of a lot of those. >> And educate the business users . >> Exactly, exactly. >> Are you having fun? >> I'm having great fun, this has been a great conference. It's always great to talk with you guys. >> We really appreciate your friendship and always coming on TheCube and sharing your insights. Always great to get the data out there. Again, we're data driven, this data driven interview with Jamie Thomas, General Manager of System Strategy and Development here at IBM Think inside TheCube studios we're on the floor here in Las Vegas. I'm John Furrier. We'll be back with more after this short break.