 From around the globe, it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. Welcome back to IBM Think 2021, the virtual edition. This is theCUBE's continuous deep dive coverage of the people, processes and technologies that are really changing our world. And 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 theCUBE. It's always a pleasure. Yeah, it is our pleasure. And listen, we've been hearing a lot about IBM's focus on hybrid cloud, Arvin 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 can 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, our IBM systems technology is used widely around the world by many, many thousands 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 modernization 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 is 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 closer to those traditional LPARs of AIX, iSeries, or in the context of ZOS. 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 Gelsinger 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 power, the power 10 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 are you, what's going on with power? Well, of course, when I talked about OpenShift, we're doing OpenShift on PowerLinux as well as Zlinux. But you're exactly right in the context for our power 10 processor. We could be more, we're so excited about this process. Our 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 reach 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 in 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 power 10 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 theCUBE, for last year's 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're going to get to over a thousand qubit machine 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 circuit execution speeds. So we hope, or 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 easily easy use by all types of developers, but to improve the fidelity in the entire machine, if you will. 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 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 online in that cloud, in fact, represents a sea change in hardware and a sea change in software. So they're all the latest and greatest that our clients can have access to. Yeah, that's key, the developer angle. You got Redshift running on quantum yet? I mean, it's a really good question. 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 bringing 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, 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 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 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 backplained 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 in 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 hundred people sign up for our summer school. We had over 4,000 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 all 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 the neat thing about quantum is it's very interdisciplinary. So we have quantum physicists, 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 obviously help ourselves but help these students as well. What are some of the, what do you see in people do with quantum? Maybe some of the use case, 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 up a few months ago that we've talked about in the press, actually a few months ago, which is with Exxon Mobile. 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 of the traffic. And that traffic in maritime shipping has to be very precise, has to be planned, the stops are planned, the routes are planned. And the interest that Exxon Mobile 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 and to 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. And we can think of logistics though, 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 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 improved speed around machine learning for all of the critical healthcare operations that 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 and as 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 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 play of people. 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 know, go through 2023 and we think that 2023 is going to, will be a pivotal year for us in terms of delivery around those roadmaps. But it's these kinds of use cases and this intense working with these clients because 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 ExxonMobil, 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 composable elements that they can start to use using an interface to allow 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 to 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, yes, I guess technically speaking, but the premise or the outcome of Moore's law is actually accelerating. We're seeing processes of performance quadrupling every two years now when you include the GPU along with the CPU, the DSPs, the accelerators, and then so that's going to take us through this decade and then quantum is going to power us well beyond who can even predict that. It's a very, very exciting time, Jim. I always love talking to you. Thank you so much for coming back on theCUBE. Well, I appreciate the time and I think you're exactly right, Dave. We've talked about power 10 just for a few minutes there, but one of the things we've done in power 10 as well is we've embedded AI into every core of 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 it's 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 for theCUBE. Keep it right there, our continuous coverage of IBM Think 2021. Very back.