(upbeat music) >> Hello and welcome to today's session of the 2021 AWS Global Public Sector Partner Awards for this very important event, the award for best partner transformation, best energy solution. I'm your host, Natalie Erlich for theCUBE and I'm very pleased to welcome our next guests. They are Alan Henson, Senior Principal at Pariveda Solutions and Doug Priedeman, Project Engineering Manager at ExxonMobil Global Projects. Welcome to the program, so glad to have you here. >> Glad to be here. Thank you. >> Yes, thanks for having us. >> Terrific. Well, let's start with you, Doug. Can you give us a brief overview of your subsidiary for some of our audience that may not be familiar with it? And also how are you using AWS now to transform collaboration on major capital projects? >> Certainly and thank you. So as many will know ExxonMobil as a sort of a global energy provider around the world operating on six out of the seven continents. Global Projects, which is the specific subsidiary where I work, we are responsible for delivery of major capital projects to the various business units around the world. So we have the opportunity to, once approved by the business unit, to deliver on the engineering, procurement, and construction activities associated with building a new facility, if you will. And that ranges across oil and gas production, refining and chemical activities. >> Terrific. And I'd love to shift now to Alan. Could you give us an insight on DPH and your collaboration with ExxonMobil? That would be terrific. >> Happy too. We first got involved with Digital Project Home after Doug had reached out to AWS seeking ways to innovate how major capital projects look at collaboration in the engineering, procurement, and construction value chain. And we were brought in as an AWS Premier Partner to help design an uplift, a new way to facilitate that collaboration between ExxonMobil and its EPC companies. And we got involved early on in the design phase where we were in the room together putting up wire frames on the walls, walking through the processes, trying to figure out how do we streamline the process that had quite a bit of toil in it from both the combination of mixed systems to manual processes. And that's where we got involved and really helped to sketch out some of that early vision from Doug. >> Terrific. Now, Doug, how is Digital Project Home facilitating collaboration with your contractors? >> Well, as folks would recognize, some of these projects are quite large, hundreds of millions, billions of dollars, very extensive in terms of the number of people on the owner-operator side as well as the various professional contracting firms that help us to succeed at building out these projects and the decisions, the interactions, the way that we work with one another involves hundreds of millions of hours in some cases, and many, many decisions. What we were looking for is to try to understand how some of those formal interactions, where questions are asked and answered and we need a record of the question that was asked and answered for contractual purposes and for the history, when documents are submitted and need to be reviewed and returned. Some of those formal interactions, historically, had been through platforms and methodologies that were really quite, to use the phrase Alan just did, quite toilsome. And what we were looking to do was to kind of come in to the modern world and use some of the digital tools, methods and programming that are available to help automate in some cases, to help smooth the actual transfer of information, and to bring information to the surface. As practitioners on a project, how do you have information available to you at your fingertips so that you can have better information that allows you to make better decisions and return your answers, not only more quickly with less hours involved in getting to that answer, but also a better answer with a higher confidence that we've answered it the way we need to, we don't have to revisit later. >> Terrific. Well, Alan can you now describe some of the benefits of this cloud native serverless architecture? >> Absolutely. If you remember back what Doug was saying earlier, ExxonMobil operates on six to seven continents around the world. So one of the first things we wanted to do is make sure that we were designing for a solution that could meet any end-user, no matter where they were in the world, whether it was Africa, North America, Australia, Asia, it didn't matter. So we wanted to choose a cloud infrastructure like AWS that had an amazing ability to serve global customers around the world. And more specifically, we knew it was really important to get to a value adding solution as quickly as possible. So by leveraging serverless technology, we got to spend most of our time building the technology that was going to be adding value because AWS infrastructure had already solved many of just the pipe work style issues at hand. So AWS really gave us an accelerated platform to really start diving in to the innovative side of improving collaboration between ExxonMobil and their engineering, procurement and construction vendors. >> Terrific. Now staying with you, Alan. I'd love to hear how is that helping ExxonMobil to build with greater agility and at lower costs? >> There are a couple of things that come to mind with me. First, we led very early on with a modular based design. We knew there were going to be multiple use cases that we had to satisfy and every major capital project does follow rigorous global processes, but often has to adapt them to the environment at hand to what they're particularly constructing, things of that nature. So we wanted to build a solution that would adapt them quickly, so they're not constantly having to go back and build new customizations, new workflows that were specific to one entity or project versus another. So just by making it modular and flexible, we were able to already start to save costs. Additionally, because we're moving into the cloud, we completely take out a lot of the infrastructure maintenance costs that go with that. And that's really where the AWS infrastructure and the cloud based solution really started to help save money as we streamlined this solution. >> Yeah. Well, speaking of flexibility, Doug, why is it so important for your business? >> So, as Alan pointed out, Natalie, we work all over the world with different partners, different EPC contractors, and so we needed the flexibility to be able to use this tool in locations, all around the world. In many cases, the same project has people located around the world. So we had to have that speed and access. We also had to have the flexibility to be able to adjust to specific requirements perhaps of unique relationships between us, our co-venture partners, the countries that host us and so forth. But in addition to that, I'll add to Alan's comment, by structuring it the way Pariveda did, what we ended up with is sort of foundational building blocks that allowed us then to extend in future to additional interactions that we might have with our contractors. So we built out the first couple, and those are available to us today, technical queries and document reviews, but we knew and anticipate that we will continue to have additional workflows, if you will, additional interactions with our partners that we will want to automate and strengthen in the same way. And so having the flexibility of this building block architecture that Pariveda put together allows us to anticipate that in future we can build that out to additional workflows. >> Terrific. Well, now shifting gears. I'd love to hear from Alan a bit here, or actually Doug, excuse me. How do you actually find the system? Do you find that it is intuitive, or do you have to train people really meticulously on this kind of platform? >> Well, design from the beginning to be a very user-friendly. The user experience element of the design work, Pariveda brought that in from the very beginning. And in fact, from our perspective, was one of the key talents that they brought to the design. So we had a problem that we were trying to solve, a platform that we wanted it to work on, but that user interaction, that user experience was so important from the very beginning and is quite frankly, an area where I lacked the experience to have been able to influence it very much, but the Pariveda team and the AWS team as they work together with us built in user experience from the very beginning. That doesn't mean that we don't have to still give some folks a little bit of training to get used to it, but it was designed from the beginning to be quite an intuitive approach, so folks could do their work. We really were after, from my view, from the very beginning, low in toil, rich in information, those were the two things we were trying to accomplish with the entire platform. >> Yeah. And if either one of you want to jump in here. Obviously, you're dealing with a lot of information, what is the data storage like? >> It's surprising not as much as you might think. We designed for optimized data storage from the beginning. We really wanted to make sure we only stored the data that we needed, but also capture as much of it as possible so that we could surface information. That was a goal for us in the beginning, was to not only capture the information that was happening between the collaboration, but design it in a way that we could use technologies like AI and machine learning languages capabilities to surface data out. So from a data storage standpoint, a lot of the data was stored outside of AWS, but we also have a fair amount stored inside of AWS. And because of that footprint, we were able to keep costs quite low. >> Terrific. Well, Alan, again, staying with you, really curious. How is this system addressing the pain points of ExxonMobil global projects specifically? >> One of the main goals from the beginning, like Doug was saying, is to reduce the toil. And a lot of the toil came from the process of an EPC company needing to submit a document over to ExxonMobil and then getting it distributed to the right teams to provide that feedback, or perhaps in reverse, where ExxonMobil needed to send a document over to another EPC companies to get feedback as well. That oftentimes involve multiple people on both sides of that equation. It involved multiple systems that had to be accessed and leveraged to not only capture and trance to document, provide tools for doing markup and providing comments. Digital Project Home unified that entire experience so that the engineers on both sides of the document collaboration process could go into one system and perform all their functions. We automated the routing. We gave them an in tool PDF markup capabilities. So they could just load the document straight into their browser, start doing their work, add their comments, save and submit, and the system would facilitate all of that. So we took out multiple hops in the process and reduce the amount of time people had to spend doing tasks that weren't necessarily a value add. >> And I'll add to that. Natalie, is it okay I'll add to that? >> Oh, please do. >> Both on the EPC contractor side as well as the owner side, we have small teams of what we call document controllers 'cause we handle so many documents. But it's quite a labor intensive or manual type approach, but it didn't need to be. And the DPH approach and the way that it was built out, it's still not completely eliminated all of the intervention of document controllers, but it reduces the burden and even the team size necessary to maneuver those documents back and forth. We in our engagements with our contractors have a contractual obligation to return our comments within a specified period of time. And we were losing 10 to 20% of that time just in the document management side of getting it from the right person to the right person and back. And so when schedules are tight, we have a lot to do, losing 20% of our contractual time to get a document returned with comments, that was a bit painful for us. So eliminating that, or at least drastically reducing it was a big win among others. >> Well, staying with you, Doug, what do you see as the major benefits of creating this platform on AWS? >> Really, to me, it comes down to better decisions. In underpinned by better information at hand to those who are or having to review, answer questions, review documents that are information at hand that allows us then to have the information that's required to get to a good answer and provide that back, whether it's from the contractor to us or the other way around. On either side, surfacing information, because otherwise a practitioner is going off to find an industry standard, going back to find out if we already had a query on that same document, see what we said last time or how that question was different from this question. There was a lot of hunting and pecking, so to speak to find out what information was allied to the question or allied to the document. And what we were really looking for was a solution that would bring that information up, give us live links, allow us to jump across to that information straight away. Not only have the information, but also be able to access it quite quickly. >> Terrific. And Alan, now shifting gears over to you. I'm really curious how this system will improve efficiencies for MCPs for the years to come. >> As Doug mentioned, we designed the system from the beginning to be extendable, to be modular, to think of like Lego blocks, where the Legos themselves represent functionality that we know can serve purposes in multiple different workflows. So as ExxonMobil continues to develop this platform in partnership with feedback from their engineering, procurement, and construction companies, they're going to be able to quickly build new workflows leveraging component based design that we did from day one. So the efficiency is going to come as they or able to add new capabilities to the platform very quickly and using modern technology to ensure that it's relevant and capable and serving the businesses needs. >> Terrific. Now, Doug, as this project scales up, what are some of the other benefits would you expect can be realized? >> Well, Natalie, we're looking to extend it to more projects as is often the case with things like this. We trial it in a few places to get, to build it out, gain the experience. We're looking to extend it to additional users, but we're also looking to do, just what Allan was just mentioning there, folks involved in major projects are familiar with such things as management of change, deviations, issues management. So there are a handful of interactions that happen between between parties and something like this. And so while we've built out two of the workflows as a starting place, and while we've deployed this tool, if you will to a few of our projects, our vision is that we would be able to extend the number of users and be able to build out additional important interactions or workflows that we have so that the Digital Project Home becomes a place that holds even more of a practitioners daily work activities. >> Terrific. And if either one of you would like to jump in here and provide just like a quick snapshot of how much manpower, time, and costs are saved as a result of using this type of platform. >> Well, on our side, Alan, I'll jump in here. We anticipate on a large project, we will transact over thousands of documents. Now, some of them get more review and some of them get less review, but there are thousands of documents that are developed in terms of engineering, procurement, and construction type activities. And to the extent that we can save a small amount of time and get better answers on each one, that really adds up quickly when you consider the number of hours expended in that overall effort. So we're talking thousands upon thousands of hours that we believe can be reduced and what that translates to, not only the ability to execute a project with a smaller team, but we are confident with better information in hand, we'll make better decisions. >> Well, thank you both for your insights. Loved having you on this program. That was Alan Henson, Senior Principal at Pariveda Solutions and Doug Priedeman, Project Engineering Manager at ExxonMobil Global Projects. That's all for this session for the 2021 AWS Global Public Sector Partner Awards, and I'm your host Natalie Erlich for theCUBE. Thanks so much for watching. (bright music)

(upbeat music) >> Hey everyone, and welcome back to theCUBEs continuing coverage of AWS re:invent 2021 live in Las Vegas. Lisa Martin here, with David Nicholson. We are running one of the industry's largest, most important hybrid tech events this year with AWS and its enormous ecosystem of partners. We've been talking yesterday and today about the next decade and cloud innovation. We're pleased to welcome back one of our CUBE alumni, Alan Henson, the Vice President of Pariveda Solutions. Welcome back to the program. >> Thank you, glad to be here. >> So talk to us about what's going on at Pariveda. What are some of the things that you're focused on in the energy space? >> So for us, specifically, we're looking at energy as it's redefining itself, right? It's no longer just oil and gas. It's no longer just coal. It's renewable energies, it's carbon capture, it's retail energy, it's power generation. We're trying to understand as this energy industry redefines itself, how companies are starting to participate in there and how technologies are really helping them as they redefine their business models and go through their digital transformations. >> I was doing some reading that Amazon is already the largest purchaser of renewable energy in the world and will be 100% renewable energy by 2025. Talk to me about the partnership with AWS. >> So our partnership goes back quite a while. We were one of their early partners. We saw the early potential of AWS, jumped in both feet in the deep end, and we've had a wonderful partnership ever since. More recently over the last couple of three years, as they've really matured their definition of energy, we've been right there with them, partnering with them on a number of different projects across multiple industries and really getting excited about how they define their journey going forward in the energy industry. >> We're in such a state of flux right now. We have been for quite a while, but talk about the energy transition. What is that? Why now? Are we all ready? >> Ooh, great question. So the energy transition is really about us as a society, looking to new sources of energy over fossil fuels. 83% of the world's energy today comes from fossil fuels, about 30% from coal, a little over 50% from oil and gas itself. We as a world are looking at this as this is energy that can't continue to be our primary source. It has been a pivot-able source of energy getting us here. It is cheap, it is reliable, it is abundant. It's very good at what it does today. However, it's causing harm. So we need to address that. So what we're doing looking forward is helping companies understand what does it mean to be net zero? What does it mean to monitor and capture your carbon? What does it mean to transition your business model from a pure oil and gas play to one that's looking at new energies like carbon capture, like wind, like solar. So we're helping all of these companies go through that journey as they figure out those next steps. >> So where does Pariveda come into the picture? Take this down to the level of an engagement with an energy company. Who are the people that you parachute in? >> Sure. >> To engage with the customer? Well let's talk about oil and gas first. The most near-term best solution that we're seeing is really about operational excellence. How can I better run my business so I reduce my footprint? Am I having better maintenance to reduce accidental spills? Am I controlling my unexpected emissions, like flaring? How can I use technology to help me run my business better? Then we have companies in the retail energy, who are looking at their customer base who are purchasing large amounts of energy, who they themselves are striving to be net zero by 2050, 2060 and creating solutions for them so they can begin to capture their carbon solutions. So we typically parachute in a couple of different types of groups. Pariveda is both an advisory services firm and a technology services firm. So based upon where a company is in their journey, we may start more in the strategy space, working with the C-Suite. What does it mean to build and structure an organization to strategically go after this new energy space or perhaps they're focusing more on operational excellence. They're trying to figure out how to leverage technology and process, to run their business better, more cost effectively. More importantly, more ESG friendly. >> ESG is a big buzzword these days. You were talking about conversations at the C-Suite level? Has it always been there or is that something that with climate change and all the things going on, you think of, you know, Hurricane Ida, the drought in California and the fires, the flooding in Washington, is that something that is now more of a focus of the C-suite level? >> I think it has to be. Global warming first became mainstream back in the seventies, when we first started realizing there was going to be an impact from our use of fossil fuels. Originally, it wasn't quite sure the scientific data wasn't there necessarily to support it. But now we're starting to see that there is a climate change. Whether or not it's caused by fossil fuels is a debate for another day. But we are starting to see that. As a result, we're also starting to see a lot of pressures coming from various different areas of our world, the financial industry, wanting to become a lot more transparent about their investment holdings. Which means they're looking at their portfolio and choosing whether or not to put investment into capital projects, which is the heart of oil and gas companies. We're seeing social pressers, not just with campaigns and protests, but where people are choosing to work, the products they're choosing to buy, the brand that they're using to associate their identity. And that's also creating pressures for the C-Suite to start to pay attention because that impacts their whole pipeline of talent. So I think we're starting to see that because of those impacts becoming much more far reaching than just some scientific publications. >> Well, the focus on people is critical. You know, we talk about often people process technology, but the people focus is critical, especially since this has such, from an optics perspective, global visibility. >> Yes, people is critically important, not just from a talent acquisition, but also from a talent development perspective. These organizations are going to be going through some pretty dramatic changes. They're going to be leveraging technology they're already familiar with, perhaps some processes they're already familiar with, but they're ultimately moving into new industries, new competitive markets. So you need to not only be able to recruit the top talent by promoting an image that people can align to, but also be able to build that talent internally so that you can make them effective as you go through these business model transformations. >> You know, there's been a theme that we've seen just in the first full day today here at AWS re:invent. And that theme is that the AWS ecosystem is thriving and critical to the success of what AWS is developing. You've given a great example of an organization, your organization, that connects or bridges the divide between technology and the value that technology can bring. You said it at the outset, you're not going in and talking technology first, typically. It's, let's talk about strategy. Let's talk about people and culture, and then let's find the tools that are best suited to leverage to achieve the goals. Because you started talking about energy, and it's like, well, so which compute instance do I need for that, exactly? Somebody has to connect those dots. >> Absolutely. That's what I love about AWS. They offer a broad suite of services in their overall cloud infrastructure that allow you to start in multiple areas. Let's start with one of the very first projects that we got into that really focused on operational excellence and improving how the organization ran its business. This is a public reference, I'm going to go ahead and say it, we did work with AWS, partnering with them at ExxonMobil to help them redefine how they collaborate with their engineering procurement and construction companies. So this was a cloud platform that allowed them to change the way they interface with those vendors as they took on these large capital projects. We were able to take time out of the system, help that organization run more profitably, which allows them to invest in that new energy technology. Then we moved to retail energy where we've been looking at a large adoption in IOT technologies. That IOT capability of AWS allows organizations to monitor their infrastructure, understand how their equipment is performing, where carbon emissions might be occurring, or other greenhouse gases might be occurring, and bringing that in. Then you bring in the AL and ML stack capabilities. One of the leading ways of detecting emissions right now is image machine learning around emissions, looking at satellite photos to see if there are changes in the atmosphere where there might be a methane leak. So all these technologies work together to help us derive better answers for how to be a better energy company and how to be a more environmentally friendly corporation. >> What's the customer flywheel like? You know, often we talk with AWS there, they talk about really-- we start backwards. We start from the customer, we work forward, our customer obsession. We saw the NASCAR slides this morning of all the logos and I'm sure many more that didn't fit. But talk to me about the alignment between Pariveda, your focus on the customers, how they help you guys innovate and create new solutions, I imagine similar culturally to AWS. >> That's one of my favorite aspects about being a premier partner with AWS is the cultural alignment. We have a process that we call right to left faking. It's beginning with business outcomes before we ever look at the technology, ever start to design the solution, ever start to build that solution. Are we meeting the end user's needs, and where that culturally aligns with AWS is it aligns with their working backwards process where they sit with their primary end users and pick some point in the future and say, if I were to do a press release today, announcing the solution that we just built, what would it say? And then if I had questions, I wanted people to be able to find answers to the frequently asked questions. What would be in those frequently asked questions and what would those answers look like? So those two approaches to starting with the right to left business outcome focus helps us begin with the most important thing that we call "jobs to be done". So we're not working on a symptom, we're working on the actual problem. And that's where we've really aligned with AWS and our cultures have helped us focus on the most critical issues at hand. >> So we've talked a lot about energy and your affiliation with AWS in these efforts, but tell us a little more about Pariveda in terms of in a more broad sense. What's the history? >> Sure. >> Give us the pitch. >> Yeah, absolutely. Pariveda has been around for over 18 years. It started with a vision that our mission should be about developing people to their fullest potential. Start there and everything else will come. Since then, we've developed into both a strategy services firm and a technology services firm where we want to bring together what we consider to be the three primary components of an enterprise architecture. Basically business, product, technology, all wrapped around strategy. And so we want to focus on those areas when we use those to help deliver projects. So whether it's technology, whether we're helping travel and hospitality companies that you probably would recognize, or we're working with sports leagues to help rebrand, we're working in the agricultural industry to change how they capture data from equipment in the field. To working in the medical industry, redefining the way that doctors work with your patients by capturing your entire conversation for them. So they're spending less time translating their notes and instead evaluating their notes to ensure top quality health care, to working energy. So we're based in North America. We have ten offices in the U.S., one in Toronto. We're about 750 strong. And we are really focused on deliberate growth versus just exponential growth. >> Well the outcomes focus is absolutely critical, as you talked about earlier. For every organization, you know, one of the things that we learned during the last 22 months is that real-time data access is no longer a "nice to have". It's absolutely essential. But we're also seeing every company's becoming a data company, but they have to learn how. How can we work with technology partners like AWS, like Pariveda, to be able to capture the value that it -- unlock it quickly so that we can iterate and be able to deliver, especially in this interesting climate that we're in and pivot and pivot and pivot. So that outcomes focus that Pariveda has, is really critical for enabling businesses in every industry to be able to survive and thrive these days. >> You said it well, we agree with you completely. What we've designed at Pariveda is what we call the modern data enterprise, where it looks at the holistic vision of becoming a data company, everything from governance to technology choices, to how I structure my organization to have the right roles, the right leadership, the right executive support, and thinking about the full picture of delivering a successful data platform so that we can really focus on something that one of my mentees calls "data liquidity". It's the ability of a company to convert their data to value as quickly as possible. In order to do that, you have to come at it from multiple angles. >> You do, and that's a competitive differentiator these days. >> Yes, absolutely. It's more than just "Let me bring you a data link and hookup some data pipelines". Again, if that's where you start, you're probably not starting in the right place. We want to start with the end users. What questions are they answering? What jobs they trying to get done? And then moving back and say, well, what data do we need? And what form do we need and how do we present it to them so they can do their job extremely well and create their own competitive differentiation. >> Right. That's really critical. Last question is -- we have just a few seconds left here, Alan -- is so much announced today alone. This is, like David said, the first full day of coverage at re:invent, but from a visionary perspective, what are some of the things that we can expect to see from Pariveda as we finish the year 2021 and enter 2022? >> So let me speak a little selfishly to the energy. What you are going to see is us as an organization are going to work side-by-side with AWS energy to help shape the picture. What does it mean to be an energy company? As these industries start to converge, we're going to build more holistic platforms and more holistic approaches so organizations can figure out "How do I still do the business I need to do today to fund the business I need to so tomorrow?" And you're going to start to see us bringing better messaging to that on both strategy, technology, and product approaches. >> Awesome. Alan, thank you for joining David and me, talking about what's going on with power data, awesome approach. I love the people focus. Great stuff. >> Lisa, David, thank you for having me. >> Oh, our pleasure. For David Nicholson, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (upbeat 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)

(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 around the globe, it's theCUBE with digital coverage of AnsibleFest 2020, brought to you by Red Hat. >> The ascendancy of massive clouds underscored the limits of human labor. People, they simply don't scale at the pace of today's technology. And this trend created an automation mandate for IT which has been further accentuated by the pandemic. The world is witnessing the build-out of a massively distributed system that comprises on-prem apps, public clouds and edge computing. The challenge we face is how to go from managing things you can see and touch to cost effectively managing, securing and scaling these vast systems. It requires an automation first mindset. Hello, everyone. This is Dave Vellante and welcome back to AnsibleFest 2020. We have a great panel to wrap up this show. With me are our three excellent guests and CUBE alums. Ashesh Badani is the Senior Vice President of Cloud Platforms at Red Hat. Ashesh, good to see you again. Thanks for coming on. >> Yeah, likewise. Thanks for having me on again, Dave. >> Stefanie Chiras is Vice President and General Manager of the RHEL Business Unit and my sports buddy. Stefanie, glad to see you back in the New England area. I knew you'd be back. >> Yeah, good to see you, Dave. Thanks for having us today. >> You're very welcome. And then finally, Joe Fitzgerald, longtime CUBE alum, Vice President and General Manager of the Management Business Unit at Red Hat. Joe, good to see you. >> Hey, Dave, good to be here with you. >> Ashesh, I'm going to start with you. Lay out the big picture for us. So how do you see this evolution to what we sometimes talk about as hybrid cloud, but really truly a hybrid cloud environment across these three platforms that I just talked about? >> Yeah, let me start off by echoing something that most of your viewers have probably heard in the past. There's always this notion about developers, developers, developers. And you know, that still holds true. We aren't going away from that anymore. Developers are the new kingmakers. But increasingly, as the scope and complexity of applications and services that are deployed in this heterogeneous environment increases, it's more and more about automation, automation, automation. In the times we live in today, even, you know, before dealing with the crises that, you know, we have, just the sheer magnitude of requirements that are being placed on enterprises and expectations from customers require us to be more and more focused on automating tasks which humans just can't keep up with. So you know, as we look forward, this conversation here today, you know, what Ansible's doing, you know, is squarely aimed at dealing with this complexity that we all face. >> So Stefanie, I wonder if you could talk about what it's going to take to implement what I call this true hybrid cloud, this connection and management of this environment. RHEL is obviously a key piece of that. That's going to be your business unit, but take us through your thoughts there. >> Yeah, so I'm kind of building on what Ashesh said. When we look at this hybrid cloud world, right, which now hybrid is much more than it was considered five years ago. It used to be hybrid was on-prem versus off-prem. Now, hybrid translates to many layers in the stack. It can be VMs hybrid with containers. It can be on-prem with off-prem and clearly with edge involved, as well. Whenever you start to require the ability to bridge across these, that's where we focus on having a platform that allows you to access sort of all of those and be able to deploy your applications in a simple way. When I look at what customers require, it's all about speed of deploying applications, right, build, deploy and run your applications. It's about stability, which is clearly where we're focused on RHEL being able to provide that stability across multiple types of hybrid deployment models. And third is all about scale. It is absolutely all about scale and that's across multiple ranges in hybrid, be it on-prem, off-prem, edge and that's where all of this automation comes in, so to me, it's really about where do you make those strategic decisions that allow you to choose, right, for the flexibility that you need and still be able to deploy applications with speed, have that stability, resiliency, and be able to scale. >> So Joe, let's talk about your swim lane and it's weird to even use that term, right? 'Cause as Stefanie just said, we're kind of breaking down all these silos that we talk in terms of platform, but how do you see this evolving, and specifically, what's the contribution from a management perspective? >> Right, so Stefanie and Ashesh talked about sort of speed, scale and complexity. Right, people are trying to deploy things faster or larger scale, and oh, by the way, keep everything highly available and secure. That's a challenge, right? And so, you know, interestingly enough, Red Hat, about five years ago, we recognized that automation was going to be a problem as people were moving into open hybrid clouds, which we've been working with our customers for years on. And so we acquired this small company called Ansible, which had some really early emerging technology, all open source, right, to do automation. And what we've done over the past five years is we've really amplified that automation and amplified the innovation in that community to be able to provide automation across a wide array of domains that you need to automate, right, and to be able to plug that in to all the different processes that people need in order to be able to go faster, but to track, manage, secure and govern these kind of environments. So we made this bet years ago and it's paying off for Red Hat in very big ways. >> I mean, no doubt about it. I mean, when you guys bought Ansible, so it wasn't clear that it was going to be the clear leader. It is now. I mean, it's pulled ahead of Chef, Puppet. You saw, you know, VMware bought Salt, but I mean, Ansible very clearly has, based on our surveys, the greatest market momentum. We're going to talk about that. I know some of the other analysts have chimed in on this, but let me come back to this notion of on-prem and cloud and edge and this is complicated. I mean, the edge, it's kind of its own island, isn't it? I mean, you got the IT and the OT schism, so maybe you could talk a little bit about how you see those worlds coming together, the cloud, the on-prem, the edge. Maybe Stefanie, you can start. >> Yeah, I think the magic, Dave, is going to happen when it's not its own island, right, as we start to see this world driven by data cause the spread of a data center to be really dis-aggregated and allow that compute to move out closer to the data, the magic happens when it doesn't feel like an island, right, that's the beauty and the promise of hybrid. So when you start to look at what can you provide that is consistent that serves as a single language that you can talk to from on-prem, off-prem and edge, you know, it all comes down to, for us, having a platform that you can build once and deploy across all of those, but the real delicacy with edge is there are some different deployment models. I think that comes into deployment space and we're clearly getting feedback from customers. We're working on some capabilities where edge requires some different deployment models in the ways you update, et cetera, and thanks to all of you out there who are working with us upstream in order to deliver that. And I think the second place where it's unique is in this ability to manage and automate out at the edge, but our goal is certainly at our platform levels, whether it be on RHEL, whether it be on OpenShift to provide that consistent platform that allows you that ease of deployment, then you got to manage and automate it and that's where the whole Ansible and the ecosystem really plays in. You need that ecosystem and that's always what I love about AnsibleFest is this community comes together and it's a vibrant community, for sure. >> Well, I mean, Ashesh, you guys are betting big on this and I often think of the cloud is just this one big cloud. You got the on-prem cloud, you got the public clouds. Edge becomes just an extension of that cloud. Is that how you think about it and what is it actually going to take to make that edge not an island? >> Yeah, great point, Dave, and that's exactly how we think about it. We've always thought about our vision of the cloud as being a platform and abstraction that spans all the underlying infrastructure that the user can take advantage of, so if it happens to reside in a data center, some in a private cloud running off a data center, more increasingly in the public cloud setting, and as Stefanie called out, we're also starting to see edge deployments come in. We're seeing, you know, big build-outs in the work we're doing with telecom providers from a 5G perspective that's helping drive that. We're seeing, if you will, IOT-like opportunities with, let's say, the automotive sector or some in the retail sector, as well. And so this fabric, if you will, needs to span this entire set of deployment that a customer will take advantage of. And Joe started touching on this a little bit, right, with this notion of the speed, scale and complexity, so we see this platform needing to expand to all these footprints that customers are using. At the same time, the requirements that they have, even when they're going out the edge, is the same with regard to what they see in the data center and the public cloud, so putting all that together really is our sweet spot. That's our focus. And to the point you're making, Dave, that's where we're making a huge bet across all of Red Hat. >> So I mentioned, you know, some of our research and I do these breaking analysis segments every week and recently I was digging into cloud and specifically was interested in hybrid and multi. And you know, hybrid been I think pretty well understood for awhile. Multi I think was a lot of, you know, a lot of talk, but it's becoming real and the data really shows that. It shows OpenShift and Ansible have momentum. I mentioned that before. Yeah, you know, obviously VMware is there, but clearly Red Hat is well positioned specifically in multicloud and hybrid. And I know some of the other analyst firms have picked up on this. What are you guys seeing in the market? Maybe Joe, you can chime in and Ashesh, you can maybe add some color. >> Yeah, so you know, there's a lot of fashion, right, around hybrid and multicloud today, so every vendor is jumping on with multicloud storing. And you know, a lot of the vendors' strategies are, pick my solution and vertically use my stuff in the public cloud on-premise, maybe even at the edge, right, and you'll be fine. And you know, obviously customers don't like lock-in. They like to be able to take advantage of the best services, availability, security, different things that are available in each of these different clouds, right? So there is a strong preference for hybrid and multicloud. Red Hat is sort of the Switzerland of hybrid and multicloud because we enable you to run your workloads across all these different substrates, whether it's in public clouds, multiple, right, into the data center and physical, virtual, bare metal, out to the edge and edge is not a single homogeneous, you know, set of hardware or even implementation. It varies a lot by vertical, so you have a lot of diversity, right? And so Red Hat is really good at helping provide the platforms like OpenShift and RHEL that are going to provide that consistency across those different environments or also in the case of Ansible to provide automation that's going to match the physics of management and automation that are required across each of those different environments. Trust me, managing or automating something at the edge and with very small footprint of some device across the constraint network is very, very different than managing things in a public cloud or in a data center and that's where I think Red Hat is really focused and that's our sweet spot, helping people manage those environments. >> And Ashesh, you guys have obviously put a lot of effort there. If you could maybe comment. >> Yeah, I was just going to say, Dave, I'll add just really quickly to what Joe said. He said it well. But the thing I will add is the way for us to succeed here is to follow the user, follow the customer. Right, instead of us just coming out with regard to what we believe the path to be, you know, we're really kind of working closely with the actual customers that we have. So for example, recently been working with a large water utility in Italy, but they're thinking about, you know, the world that they live in and how can they go off and, you know, have kiosks that are spread throughout Italy, able to provide reports with regard to the quality of the water that's available, as well as other services to all their citizens. But it's really interesting use case for us to go off and pursue because in some sense, you can ask yourself, well, is that public cloud? Are they going to take advantage of those services? Is that, you know, private cloud? Is that data center, is that IOT, is that edge? At a certain point in time, what you've got to think about is, well, we've got to provide integrated end-to-end solution that spans all of these different worlds, and so as long as I think we keep that focus, as long as we make sure our North Star is really what the user's trying to do, what problem they're trying to solve, I think we'll come out just fine on the other side of this. >> So I'd love to get all your thoughts, all three of you, on just what's going on in containers, generally, Kubernetes, specifically. I mean, everybody knows it's a hot space and the data shows that it is maturing, but it's amazing to me how much momentum it still has. I mean, it's like the new shiny toy, but it's everywhere and so it's able to sort of maintain that velocity and it's really becoming the go-to cloud native development platform, so the question is how is Red Hat, you know, helping your customers connect OpenShift to the rest of their IT infrastructure, platforms, their processes, the tools. I mean, who wants to start? I'd love to hear from all three of you. Ashesh, why don't you kick it off and then we'll just go left to right. >> So Dave, we've spoken to you and to folks the CUBE, as well, other for many years on this. We've made a huge investment in the Kubernetes market and been one of the earliest to do that and we continue to believe in the promise that it delivers to users, this notion of being able to have an environment that customers can use regardless of the underlying choices that they make. Here's an extremely powerful one, it's truly an open source, right? This is key to, you know, what we do. Increasingly, what we're working on is to ensure that one, if you make a commitment to Kubernetes and increasingly we see lots of customers around the world doing that, that we ensure that we're working closely, that our entire portfolio helps support that. So if you're going to make a choice with regard to Kubernetes base deployment, we help support you running it yourself wherever it is that you choose to run it, we help support you whether you choose to have us manage on your behalf and then also make sure we're providing an entire portfolio of services, both within Red Hat as well as from third parties so that you have the most productive, integrated experience possible. >> Okay, and Stefanie, loved your point of view on this, and Joe, I'd love to understand how you're bridging kind of the Ansible and Kubernetes communities, but Stefanie, why don't you chime in first? >> Yeah, I'll quickly add to what Ashesh said and talked about well on really the promise and the value of containers, but particularly from a RHEL perspective, we have taken all our capabilities and knowledge in the Linux space and we have taken that to apply it to OpenShift, right, because Kubernetes and containers is just another way to deploy Linux, so making sure that that underpinning is stable, secure and resilient and tied to an ecosystem, right? An ecosystem of various architectures, an ecosystem of ISVs and tooling, right? We've pulled that together and everything we've done in Linux for, you know, over decades now at Red Hat and we've put that into that customer experience around OpenShift to deploy containers, so we've really built, it has been a portfolio-wide effort, as Ashesh alluded to, and of course, it passes over to Ansible as well with Joe's portfolio. >> Yeah, we talked about this upfront, Joe. The communities are so crucial, so how are you bridging those Ansible and Kubernetes communities? What's your thought on that? >> Well, a quick note about those communities. So you know, OpenShift is built on Kubernetes and a number of other projects. Kubernetes is number seven in the top 10 open source projects based on the number of contributors. Turns out Ansible is number nine, right? So if you think about it, these are two incredibly robust communities, right? On the one hand, building the container platform in Kubernetes and in the other around Ansible and automation. It turns out that as the need for this digital acceleration and building these container-based applications comes along, there's a lot of other things that have to be done when you deploy container-based applications, whether it's infrastructure automation, right, to expand and manage and automate the infrastructure that you're running your container-based applications on, creating more clusters, you know, configuring storage, network, you know, counts, things like that, but also connecting to other systems in the environment that need to be integrated with around, you know, ITSM or systems of record, change management, inventory, cost, things like that, so what we've done is we've integrated Ansible, right, in a very powerful way with OpenShift through our advanced cluster management capability, which allows us to provide an easy way to instrument Ansible during critical points, whether it's you're deploying new clusters out there or you're deploying a new version of an application or a new application for the first time, whether you're checking policy, right, to ensure that, you know, the thing is secure and that, you know, you can govern these environments, right, that you're relying on. So we've really now tied together two sort of de facto standards, OpenShift built on Kubernetes and a number of other projects and then Ansible, or Red Hat, has taken this innovation in the community and created these certified content collections, platforms and capabilities that people can actually build and rely on and know that it's going to work. >> Ashesh, I mean, Red Hat has earned the right, really, to play in both the cloud native world and of course the traditional infrastructure world, but I'm interested in what you're seeing there, how you're bringing those two worlds together. Are they still, you know, largely separate? Are you seeing traditional IT? I mean, you're certainly seeing them lean in to more and more cloud native, but what are you guys doing specifically to kind of bring those worlds together? >> Yeah, increasingly it's really hard to be able to separate out those worlds, right? So in the past, we used to call it shadow IT. There really is no shadow IT anymore, right? This is IT. So we've embraced that completely. You know, our take on that is to say there are certain applications that are going to be appropriate for being run in a data center a certain way. There are certain other workloads that'll find their way appropriate for the public cloud. We want to make sure we're meeting them across, but what we want to do is constantly introduce technologies to help support the choices customers make. What do I mean by that? Let me give a couple examples. One is, you know, we can say customers have VMs that are based out in specific environments and they can only run as VMs. That code can't be containerized for a variety of reasons, right? You know, hard to re-architect that, don't have the funds, you know, have certain security compliance reasons. Well, what if we could take those VMs and then have them be run in containers in a native fashion? Wouldn't that be extremely powerful value proposition to run containers and then VMs as containers sort of side by side with Kubernetes orchestrating them all. So that's a capability we call open source virtualization. We've introduced that and made that generally available within our platform. Another one, which I think Joe starting to touch on a little bit here, is both around this notion of Ansible, as well as advanced cluster management. And say, once technologies like Ansible are familiar to our customers, how about if we find ways to introduce things like the operator framework to help support people's use of Ansible and introduce technologies like advanced cluster management, which allows for us to say, well, regardless of where you run your clusters, whether you run your Kubernetes clusters on premise, you run them in the cloud, right, we can imagine a consistent fashion and manage, you know, health and policy and compliance of applications across that entire state. So David, question's extremely good one, right, but what we are trying to do is try to be able to say, you know, we are going to just span those two worlds and provide as many tools as possible to ensure that customers feel like, you know, the shift, if you will, or the move between traditional enterprise software application development and the more modern cloud native can be bridged as seamlessly as possible. >> Yeah, Joe, we heard a lot of this at AnsibleFest, so the ACM as a key component of your innovation, and frankly, your competitive posture. Anything you would add to what Ashesh just shared? >> Well, I think that one of the things that Red Hat is really good at is we take management and automation as sort of an intrinsic part of what needs to go on. It's not an afterthought. You just don't go build something, go, "Oh I need management," go out and, you know, go get something, right, so we've been working on, sort of automation and management for many, many years, right, so we build it in concert with these platforms, right, and we understand the physics of these different environments, so we're very focused on that from inception, as opposed to an afterthought when people sort of paint themselves into a corner or have management challenges they can't deal with. >> There's a lot of analogs in our business, isn't there? Management is a bolt-on and security is a bolt-on. It just doesn't work that well and certainly doesn't scale. Stefanie, I want to come back to you and I want to come back to the edge. We hear a lot of people talking about extending their deployments to the edge in the future. I mean, you look at what IBM's doing. They're essentially betting its business on RHEL and OpenShift and betting that its customers are going to do the same as well are you. Maybe talk about, you know, what you're doing to specifically extend RHEL to the edge. >> Yeah, Dave, so we've been looking at this space consistent with our strategy, as Ashesh talked about, right? Our goal is to make sure that it all looks and feels the same and provides one single Linux experience. We've been building on a number of those aspects for quite some time, things like being able to deal with heterogeneous architectures, as an example, being able to deal with, you know, having Arm components and x86 components and power components and being able to leverage all of that from multiple vendors and being able to deploy. Those are things we've been focused on for a long time and now when you move into the space of the edge, certainly we're seeing, you know, essentially data center level hardware move out to be dis-aggregated and dispersed as they move it closer to the data and where that's coming in and where the analysis needs to be done, but some of those foundational things that we've been working on for years starts to pay off because the edge tends to be more heterogeneous all the way from an architecture level to an application level, so now we're seeing some asks. We've been working upstream in order to pull in some features that drive capabilities around specifically updating, deploying those updates, doing rollbacks and things like that, so we're focused on that. But really, it's about pulling together the capabilities of having multiple architectures, dealing with heterogeneous infrastructure out there at the edge, being able to reliably deploy it even when, for example, we have customers who they deploy their hardware and they can't touch it for years. How do they make sure that that's out there in a stable environment that they can count on? And then, you know, adding in things like containerization. We talked about the magic of that, being able to deploy an application consistently and being able to deploy a single container out there to the edge. We're thinking about it all the way from the architecture up to how the application gets deployed and it's going to take the whole portfolio to do that as you need to manage it, as you need to deploy containers, so it's a focus across the company for how we deal with that. >> And as we were talking about before, you know, it takes a village. You know that bromide, but it does, requires an ecosystem of jobs. I mean, there's some real technical challenges in R&D that has to happen. I mean, you've got to be, you know, you're talking about cloud native in all three different clouds, and you know, and not just the big three, but other clouds and then bringing that to the edge, so there's some clear technical challenges, but there's also some business challenges out there. So you know, what are you seeing in that regard? You know, what are some of those things that you hope to solve by bridging that gap? >> Well, I think one of the things we're trying to do and I'm focused on the management and automation side is to provide a common set of management tooling of automation, right, and I think Ansible fits that quite well. So for the past five years since Ansible's been part of Red Hat, we've expanded from, you know, they started off initially doing configuration management, right? We've expanded to include, you know, network and storage and security, now edge. At AnsibleFest, we demonstrated things like serverless event-driven automation, right, building an OpenShift serverless in Knative. We're trying to expand the use cases for Ansible so that there's a simplicity, there's a tool reduction, right, across all these environments and you don't have to go deal with nine vendors, and you know, 17 different tools to try to manage each element here to be able to provide a common set. It reduces complexity, cost and allows skills to be able to be reused across these different areas. It's going to all be about digital acceleration, right, and reducing that complexity. And one last comment. One of the reasons we bought Ansible years ago is the architecture, it's agent-less. Many of our competitors that you hear, the first thing they want to do is go deploy an agent somewhere and that creates its own ongoing burden of, do I have the latest version of the agent? Is it secure? Does it fit on the device? As Stefanie mentioned, is there a version that fits on the architecture the device is running on? It starts getting really, really complicated. So Ansible is just simple, elegant, agent-less. We've expanded the domains we can automate with it and we've expanded sort of the modality. How can I call it? User, driven by an event, as part of some life cycle management, app deployment, Ansible plugs right in. >> Well, Joe, you can tell you're a management guy, right? Agents, another thing that has to be managed. You just laundry list of stuff. (laughs) I want to come back to this notion Joe just touched on, this digital transformation. They say, "If it ain't broke, don't fix it." Well, COVID broke everything. And I got to say, I mean, all the talk about digital transformation over the last, you know, several years, yes, it was certainly happening, but there was also a lot of lip service going on and now if you're not digital, you're out of business. And so, you know, given everything that we've seen in the last, you know, whatever, 150, 200 days or so, what's the impact that you're seeing on customers' digital transformation initiatives, and you know, what is Red Hat doing to respond? Maybe Ashesh, you could start and we can get feedback from the others. >> Yeah, David, it's an unfortunate thing to say, right, but there's that meme going around with regard to who's responsible for digital transformation and it's a little bit of I guess gallows humor to call it COVID, but we're increasingly seeing that customers and the journey that they're on is one that they haven't really gotten off, even with this, if you will, change of environment that's come about. So projects that we've seen in play, you know, are still underway. We've seen acceleration, actually, in some places with regard to making services more easily accessible. Anyone who's invested in hybrid cloud or public cloud is seeing huge value with regard to being able to consume services remotely, being able to do this on demand and that's a big part of the value proposition, you know, that comes forward. And increasingly what we're trying to do is try to say, how can we engage and assist you in these times, right? So our services team, for example, has transformed to be able to help customers remotely. Our support team has gone off and work more and more with customers. For a company like Red Hat, that hasn't been completely, if you will, difficult thing to do mostly because we've been so used to working in a distributed fashion, working remotely with our customers, so that's not a challenge in itself, but making sure customers understand that this is really a critical journey for them to go on and how we can kind of help them, you know, walk through that has been good and we're finding that that message really resonates. Right, so both Stefanie and Joe talked a little bit about, you know, how essentially our entire portfolio is now built around, you know, ensuring that if you'd like to consume on demand, we can help support you, if you'd like to consume in a traditional fashion, we can help you. That amount of flexibility that we provide to customers is really coming to bear at this point in time. >> So maybe we could wrap with, we haven't really dropped any customer names. Stefanie and Joe and Ashesh, I wonder if you have any stories you can share or, you know, customer examples that we could close on that are exciting to you this year. >> So I can start, if that's okay. >> Please. >> So an area that I find super interesting from a customer perspective that we're increasingly seeing more and more customers go down is sheer interest in, if you will, kind of diversity of use cases that we're seeing, right? So we see this, for example, in automotive, right? So whether it's a BMW or a Volkswagen, we see this now in health care with the ACA, in we'll say a little bit more traditional industries like energy with Exxon or Schlumberger around increasingly embrace of AIML, right? So artificial machine learning, if you will, advanced analytics being much more proactive with regard to how they can take data that's coming in, adjust it, be able to make sense of the patterns and then be able to, you know, have some action that has real business impact. So this whole trend towards, you know, AIML workloads that they can run is extremely powerful. We work very closely with Nvidia, as well, and we're seeing a lot of interest, for example, in being able to run a Kubernetes-based platform, support Nvidia GPUs for specific class workloads. There's a whole bunch of customers, people in financial services that, you know, this is a rich area of interest. You know, we've seen great use cases for example around grid with Deutsche Bank. And so, to me, I'm personally really excited to see kind of that embrace the PC from our customers regard to saying there's a whole lot of data that's out there. You know, how can we essentially use all of these tools that we have in place? You know, we talk about containers, microservices, DevOps, you know, all of this and then put it to bear to really put to work and get business value. >> Great, thank you for that, Ashesh. Stefanie, Joe, Stefanie, anything you want to add or final thoughts? >> Yeah, just one thing to add and I think Ashesh talked to a whole number across industry verticals and customers. But I think the one thing that I've seen through COVID is that if nothing else, it's taught us that change is the only constant and I think, you know, our whole vision of open hybrid cloud is how to enable customers to be flexible and do what they need to do when they need to do it, wherever they want to deploy, however they want to build. We provide them some consistency, right, across that as they make those changes and I think as I've worked with customers here through since the beginning of COVID, it's been amazing to me the diversity of how they've had to respond. Some have doubled down in the data center, some have doubled down on going public cloud and to me, this is the proof of the strategy that we're on, right, that open hybrid cloud is about delivering flexibility, and boy, nothing's taught us the need for flexibility like COVID has recently, so I think there's a lot more to do. I think pulling together the platforms and the automation is what is going to enable the ability to do that in a simple fashion. >> So Joe, you get the final word. I mean, AnsibleFest 2020, I mean, it's weird, right? But that's the way these events are, all virtual. Hopefully, next year we got a shot at being face to face, but bring us home, please. >> Yeah, I got to tell ya, having, you know, 20,000 or so of your closest friends get together to talk about automation for a couple of days is just amazing. That just shows you sort of the power of it. You know, we have a lot of customers this week at AnsibleFest telling you their story, you know, CarMax and ExxonMobil, you know, BlueCross BlueShield. I mean, there's a number across all different verticals, globally, Cepsa from Europe. I mean, just an incredibly, you know, diverse array of customers and use cases. I would encourage people to look at some of the customer presentations that were on at AnsibleFest, listen to the customer telling you what they're doing with Ansible, deploying their networks, deploying their apps, managing their infrastructure, container apps, traditional apps, connecting it, moving faster. They have amazing stories. I encourage people to go look. >> Well, guys, thanks so much for helping us wrap up AnsibleFest 2020. It was really a great discussion. You guys have always been awesome CUBE guests. Really appreciate the partnership and so thank you. >> Thanks a lot, Dave. Appreciate it. >> Yeah, thanks, Dave. >> Thanks for having us. >> All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE and we'll see you next time. (calm music)

Hi, I'm Hideo Mabuchi from Stanford University. This is my presentation on coherent nonlinear dynamics, and combinatorial optimization. This is going to be a talk, to introduce an approach, we are taking to the analysis, of the performance of Coherent Ising Machines. So let me start with a brief introduction, to ising optimization. The ising model, represents a set of interacting magnetic moments or spins, with total energy given by the expression, shown at the bottom left of the slide. Here the cigna variables are meant to take binary values. The matrix element jij, represents the interaction, strength and sign, between any pair of spins ij, and hi represents a possible local magnetic field, acting on each thing. The ising ground state problem, is defined in an assignment of binary spin values, that achieves the lowest possible value of total energy. And an instance of the easing problem, is specified by given numerical values, for the matrix j and vector h, although the ising model originates in physics, we understand the ground state problem, to correspond to what would be called, quadratic binary optimization, in the field of operations research. And in fact, in terms of computational complexity theory, it can be established that the, ising ground state problem is NP complete. Qualitatively speaking, this makes the ising problem, a representative sort of hard optimization problem, for which it is expected, that the runtime required by any computational algorithm, to find exact solutions, should asyntonically scale, exponentially with the number of spins, and four worst case instances at each end. Of course, there's no reason to believe that, the problem instances that actually arise, in practical optimization scenarios, are going to be worst case instances. And it's also not generally the case, in practical optimization scenarios, that we demand absolute optimum solutions. Usually we're more interested in, just getting the best solution we can, within an affordable cost, where costs may be measured in terms of time, service fees and or energy required for computation. This focus is great interest on, so-called heuristic algorithms, for the ising problem and other NP complete problems, which generally get very good, but not guaranteed optimum solutions, and run much faster than algorithms, that are designed to find absolute Optima. To get some feeling for present day numbers, we can consider the famous traveling salesman problem, for which extensive compilations, of benchmarking data may be found online. A recent study found that, the best known TSP solver required median runtimes, across a library of problem instances, that scaled as a very steep route exponential, for an up to approximately 4,500. This gives some indication of the change, in runtime scaling for generic, as opposed to worst case problem instances. Some of the instances considered in this study, were taken from a public library of TSPs, derived from real world VLSI design data. This VLSI TSP library, includes instances within ranging from 131 to 744,710, instances from this library within between 6,880 and 13,584, were first solved just a few years ago, in 2017 requiring days of runtime, and a 48 core two gigahertz cluster, all instances with n greater than or equal to 14,233, remain unsolved exactly by any means. Approximate solutions however, have been found by heuristic methods, for all instances in the VLSI TSP library, with, for example, a solution within 0.014% of a known lower bound, having been discovered for an instance, with n equal 19,289, requiring approximately two days of runtime, on a single quarter at 2.4 gigahertz. Now, if we simple-minded the extrapolate, the route exponential scaling, from the study yet to n equal 4,500, we might expect that an exact solver, would require something more like a year of runtime, on the 48 core cluster, used for the n equals 13,580 for instance, which shows how much, a very small concession on the quality of the solution, makes it possible to tackle much larger instances, with much lower costs, at the extreme end, the largest TSP ever solved exactly has n equal 85,900. This is an instance derived from 1980s VLSI design, and this required 136 CPU years of computation, normalized to a single core, 2.4 gigahertz. But the 20 fold larger, so-called world TSP benchmark instance, with n equals 1,904,711, has been solved approximately, with an optimality gap bounded below 0.0474%. Coming back to the general practical concerns, of applied optimization. We may note that a recent meta study, analyze the performance of no fewer than, 37 heuristic algorithms for MaxCut, and quadratic binary optimization problems. And find the performance... Sorry, and found that a different heuristics, work best for different problem instances, selected from a large scale heterogeneous test bed, with some evidence, the cryptic structure, in terms of what types of problem instances, were best solved by any given heuristic. Indeed, there are reasons to believe, that these results for MaxCut, and quadratic binary optimization, reflect to general principle, of a performance complementarity, among heuristic optimization algorithms, and the practice of solving hard optimization problems. There thus arises the critical pre processing issue, of trying to guess, which of a number of available, good heuristic algorithms should be chosen, to tackle a given problem instance. Assuming that any one of them, would incur high cost to run, on a large problem of incidents, making an astute choice of heuristic, is a crucial part of maximizing overall performance. Unfortunately, we still have very little conceptual insight, about what makes a specific problem instance, good or bad for any given heuristic optimization algorithm. This is certainly pinpointed by researchers in the field, as a circumstance and must be addressed. So adding this all up, we see that a critical frontier, for cutting edge academic research involves, both the development of novel heuristic algorithms, that deliver better performance with lower costs, on classes of problem instances, that are underserved by existing approaches, as well as fundamental research, to provide deep conceptual insight, into what makes a given problem instance, easy or hard for such algorithms. In fact, these days, as we talk about the end of Moore's law, and speculate about a so-called second quantum revolution, it's natural to talk not only about novel algorithms, for conventional CPUs, but also about highly customized, special purpose hardware architectures, on which we may run entirely unconventional algorithms, for common tutorial optimizations, such as ising problem. So against that backdrop, I'd like to use my remaining time, to introduce our work on, analysis of coherent using machine architectures, and associated optimization algorithms. Ising machines in general, are a novel class of information processing architectures, for solving combinatorial optimization problems, by embedding them in the dynamics, of analog, physical, or a cyber-physical systems. In contrast to both more traditional engineering approaches, that build ising machines using conventional electronics, and more radical proposals, that would require large scale quantum entanglement the emerging paradigm of coherent ising machines, leverages coherent nominal dynamics, in photonic or optical electronic platforms, to enable near term construction, of large scale prototypes, that leverage posting as information dynamics. The general structure of current of current CIM systems, as shown in the figure on the right, the role of the easing spins, is played by a train of optical pulses, circulating around a fiber optical storage ring, that beam splitter inserted in the ring, is used to periodically sample, the amplitude of every optical pulse. And the measurement results, are continually read into an FPGA, which uses then to compute perturbations, to be applied to each pulse, by a synchronized optical injections. These perturbations are engineered to implement, the spin-spin coupling and local magnetic field terms, of the ising hamiltonian, corresponding to a linear part of the CIM dynamics. Asynchronously pumped parametric amplifier, denoted here as PPL and wave guide, adds a crucial nonlinear component, to the CIM dynamics as well. And the basic CIM algorithm, the pump power starts very low, and is gradually increased, at low pump powers, the amplitudes of the easing spin pulses, behave as continuous complex variables, whose real parts which can be positive or negative, by the role of soft or perhaps mean field spins. Once the pump power crosses the threshold, for perimetric self oscillation in the optical fiber ring, however, the amplitudes of the easing spin pulses, become effectively quantized into binary values, while the pump power is being ramped up, the FPGA subsystem continuously applies, its measurement based feedback implementation, of the using hamiltonian terms. The interplay of the linearized easing dynamics, implemented by the FPGA , and the thresholds quantization dynamics, provided by the sink pumped parametric amplifier, result in a final state, of the optical plus amplitudes, at the end of the pump ramp, that can be read as a binary strain, giving a proposed solution, of the ising ground state problem. This method of solving ising problems, seems quite different from a conventional algorithm, that runs entirely on a digital computer. As a crucial aspect, of the computation is performed physically, by the analog continuous coherent nonlinear dynamics, of the optical degrees of freedom, in our efforts to analyze CA and performance. We have therefore turn to dynamical systems theory. Namely a study of bifurcations, the evolution of critical points, and typologies of heteroclitic orbits, and basins of attraction. We conjecture that such analysis, can provide fundamental insight, into what makes certain optimization instances, hard or easy for coherent ising machines, and hope that our approach, can lead to both improvements of the course CIM algorithm, and the pre processing rubric, for rapidly assessing the CIM insuibility of the instances. To provide a bit of intuition about how this all works. It may help to consider the threshold dynamics, of just one or two optical parametric oscillators, in the CIM architecture just described. We can think of each of the pulse time slots, circulating around the fiber ring, as are presenting an independent OPO. We can think of a single OPO degree of freedom, as a single resonant optical mode, that experiences linear dissipation, due to coupling loss, and gain in a pump near crystal, as shown in the diagram on the upper left of the slide, as the pump power is increased from zero. As in the CIM algorithm, the non-linear gain is initially too low, to overcome linear dissipation. And the OPO field remains in a near vacuum state, at a critical threshold value, gain equals dissipation, and the OPO undergoes a sort of lasing transition. And the steady States of the OPO, above this threshold are essentially coherent States. There are actually two possible values, of the OPO coherent amplitude, and any given above threshold pump power, which are equal in magnitude, but opposite in phase, when the OPO cross this threshold, it basically chooses one of the two possible phases, randomly, resulting in the generation, of a single bit of information. If we consider two uncoupled OPOs, as shown in the upper right diagram, pumped at exactly the same power at all times, then as the pump power is increased through threshold, each OPO will independently choose a phase, and thus two random bits are generated, for any number of uncoupled OPOs, the threshold power per OPOs is unchanged, from the single OPO case. Now, however, consider a scenario, in which the two appeals are coupled to each other, by a mutual injection of their out coupled fields, as shown in the diagram on the lower right. One can imagine that, depending on the sign of the coupling parameter alpha, when one OPO is lasing, it will inject a perturbation into the other, that may interfere either constructively or destructively, with the field that it is trying to generate, via its own lasing process. As a result, when can easily show that for alpha positive, there's an effective ferromagnetic coupling, between the two OPO fields, and their collective oscillation threshold, is lowered from that of the independent OPO case, but only for the two collective oscillation modes, in which the two OPO phases are the same. For alpha negative, the collective oscillation threshold, is lowered only for the configurations, in which the OPO phases are opposite. So then looking at how alpha is related to the jij matrix, of the ising spin coupling hamilitonian, it follows the, we could use this simplistic to OPO CIM, to solve the ground state problem, of the ferromagnetic or antiferromagnetic angles, to ising model, simply by increasing the pump power, from zero and observing what phase relation occurs, as the two appeals first start to lase. Clearly we can imagine generalizing the story to larger, and, however, the story doesn't stay as clean and simple, for all larger problem instances. And to find a more complicated example, we only need to go to n equals four, for some choices of jij for n equals four, the story remains simple, like the n equals two case. The figure on the upper left of this slide, shows the energy of various critical points, for a non frustrated n equals for instance, in which the first bifurcated critical point, that is the one that, by forgets of the lowest pump value a, this first bifurcated critical point, flows asyntonically into the lowest energy using solution, and the figure on the upper right, however, the first bifurcated critical point, flows to a very good, but suboptimal minimum at large pump power. The global minimum is actually given, by a distinct critical point. The first appears at a higher pump power, and is not needed radically connected to the origin. The basic CIM algorithm, is this not able to find this global minimum, such non-ideal behavior, seems to become more common at margin end, for the n equals 20 instance show in the lower plots, where the lower right pod is just a zoom into, a region of the lower left block. It can be seen that the global minimum, corresponds to a critical point, that first appears that of pump parameter a around 0.16, at some distance from the adriatic trajectory of the origin. That's curious to note that, in both of these small and examples, however, the critical point corresponding to the global minimum, appears relatively close, to the adiabatic trajectory of the origin, as compared to the most of the other, local minimum that appear. We're currently working to characterise, the face portrait typology, between the global minimum, and the adiabatic trajectory of the origin, taking clues as to how the basic CIM algorithm, could be generalized, to search for non-adiabatic trajectories, that jumped to the global minimum, during the pump up, of course, n equals 20 is still too small, to be of interest for practical optimization applications. But the advantage of beginning, with the study of small instances, is that we're able to reliably to determine, their global minima, and to see how they relate to the idea, that trajectory of the origin, and the basic CIM algorithm. And the small land limit, We can also analyze, for the quantum mechanical models of CAM dynamics, but that's a topic for future talks. Existing large-scale prototypes, are pushing into the range of, n equals, 10 to the four, 10 to the five, 10 to the six. So our ultimate objective in theoretical analysis, really has to be, to try to say something about CAM dynamics, and regime of much larger in. Our initial approach to characterizing CAM behavior, in the large end regime, relies on the use of random matrix theory. And this connects to prior research on spin classes, SK models, and the tap equations, et cetera, at present we're focusing on, statistical characterization, of the CIM gradient descent landscape, including the evolution of critical points, And their value spectra, as the pump powers gradually increase. We're investigating, for example, whether there could be some way, to explain differences in the relative stability, of the global minimum versus other local minima. We're also working to understand the deleterious, or potentially beneficial effects, of non-ideologies such as asymmetry, in the implemented using couplings, looking one step ahead, we plan to move next into the direction, of considering more realistic classes of problem instances, such as quadratic binary optimization with constraints. So in closing I should acknowledge, people who did the hard work, on these things that I've shown. So my group, including graduate students, Edwin Ng, Daniel Wennberg, Ryatatsu Yanagimoto, and Atsushi Yamamura have been working, in close collaboration with, Surya Ganguli, Marty Fejer and Amir Safavi-Naeini. All of us within the department of applied physics, at Stanford university and also in collaboration with Yoshihisa Yamamoto, over at NTT-PHI research labs. And I should acknowledge funding support, from the NSF by the Coherent Ising Machines, expedition in computing, also from NTT-PHI research labs, army research office, and ExxonMobil. That's it. Thanks very much.

>> from Cambridge, Massachusetts. It's three Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Hi already. We're back in Cambridge, Massachusetts at the M I t. Chief data officer Information quality event. Hashtag m i t cdo i Q. And I'm David Dante. He's Paul Gillen. Day one of our two day coverage of this event. This is the Cube, the leader in live tech coverage. Joe Caserta is here is the president of Caserta and Doug Laney, who is principal data strategist at Caserta, both Cube alarm guys. Great to see you again, Joe. What? Did you pick up this guy? How did that all came on here a couple of years ago? We had a great conversation. I read the book, Loved it. So congratulations. A nice pickup. >> We're very fortunate to have. >> Thanks. So I'm fortunate to be here, >> so Okay, well, what attracted you to Cassard? Oh, >> it's Joe's got a tremendous reputation. His his team of consultants has a great reputation. We both felt there was an opportunity to build some data strategy competency on top of that and leverage some of those in Phanom. Its ideas that I've been working on over the years. >> Great. Well, congratulations. And so, Joe, you and I have talked many times. And the reason I like talking because you know what's going on in the market place? You could you could siphon. What's riel? What's hype? So what do you see? It is the big trends in this data space, and then we'll get into it. Yeah, sure. Um, trends >> are chief data officer has been evolving over the last couple of years. You know, when we started doing this several years ago, there was just a handful of people, maybe 30 40 people. Now, there's 450 people here today, and it's been evolving. People are still trying to find their feet. Exactly what the chief date officers should be doing where they are in the hierarchy. Should they report to the c e o the C I O u the other CDO, which is a digital officer. So I think you know, hierarchically. That's still figuring it out politically. They're figuring it out, but technically also, they're still trying to figure it out. You know what's been happening over the past three years is the evolution of data going from traditional data warehousing and business intelligence. To get inside out of data just isn't working anymore. Eso evolving that moving it forward to more modern data engineering we've been doing for the past couple of years with quote unquote big data on That's not working anymore either, right? Because it's been evolving so fast. So now we're on, like, maybe Data three dato. And now we're talking about just pure automate everything. We have to automate everything. And we have to change your mindset from from having output of a data solution to an outcome to date a solution. And that's why I hired Doug, because way have to figure out not only had to get this data and look at it and analyze really had to monetize it, right? It's becoming a revenue stream for your business if you're doing it right and Doug is the leader in the industry, how to figure that >> you keep keep premise of your book was you gotta start valuing data and its fundamental you put forth a number of approaches and techniques and examples of companies doing that. Since you've published in phenomena Microsoft Apple, Amazon, Google and Facebook. Of the top five market value cos they've surpassed all the financial service is guys all ExxonMobil's and any manufacturer? Automobile makers? And what of a data companies, right? Absolutely. But intrinsically we know there's value their way any closer to the prescription that you put forth. >> Yeah, it's really no surprise and extra. We found that data companies have, ah, market to book value. That's nearly 33 times the market average, so Apple and others are much higher than that. But on average, if you look at the data product companies, they're valued much higher than other companies, probably because data can be reused in multiple ways. That's one of the core tenets of intra nomics is that Data's is non depleted ble regenerative, reusable asset and that companies that get that an architect of businesses based on those economics of information, um, can really perform well and not just data companies, but >> any company. That was a key takeaway of the book. The data doesn't conform to the laws of scarcity. Every says data is the new oil. It's like, No, it's not more valuable. So what are some examples in writing your book and customers that you work with. Where do you see Cos outside of these big data driven firms, breaking new ground and uses of data? I >> think the biggest opportunity is really not with the big giant Cos it's really with. Most of our most valuable clients are small companies with large volumes of data. You know if and the reason why they can remain small companies with large volumes of data is the thing that holds back the big giant enterprises is they have so much technical. Dad, it's very hard. They're like trying to, you know, raise the Titanic, right? You can't really. It's not agile enough. You need something that small and agile in order to pivot because it is changing so fast every time there's a solution created, it's obsolete. We have to greet the new solution on dhe when you have a big old processes. Big old technologies, big old mind sets on big old cultures. It's very hard to be agile. >> So is there no hope? I mean, the reason I ask the question was, What hope can you give some of these smokestack companies that they can become data centric? Yeah, What you >> see is that there was a There was a move to build big, monolithic data warehouses years ago and even Data Lakes. And what we find is that through the wealth of examples of companies that have benefited in significant ways from data and analytics, most of those solutions are very vocational. They're very functionally specific. They're not enterprise class, yada, yada, kind of kind of projects. They're focused on a particular business problem or monetizing or leveraging data in a very specific way, and they're generating millions of dollars of value. But again they tend to be very, very functionally specific. >> The other trend that we're seeing is also that the technology and the and the end result of what you're doing with your data is one thing. But really, in order to make that shift, if your big enterprises culture to really change all of the people within the organization to migrate from being a conventional wisdom run company to be a data really analytics driven company, and that takes a lot of change management, a lot of what we call data therapy way actually launched a new practice within the organization that Doug is actually and I are collaborating on to really mature because that is the next wave is really we figured out the data part. We figured out the technology part, but now it's the people part people. Part is really why we're not way ahead of where we even though we're way ahead of where we were a couple of years ago, we should be even further. Culturally, it's very, very challenging, and we need to address that head on. >> And that zeta skills issue that they're sort of locked into their existing skill sets and processes. Or is it? It's fear of the unknown what we're doing, you know? What about foam? Oh, yeah, Well, I mean, there are people >> jumping into bed to do this, right? So there is that part in an exciting part of it. But there's also just fear, you know, and fear of the unknown and, you know, part of what we're trying to do. And why were you trying Thio push Doug's book not for sales, but really just to share the knowledge and remove the mystery and let people see what they can actually do with this data? >> Yeah, it's more >> than just date illiteracy. So there's a lot of talk of the industry about data literacy programs and educating business people on the data and educating data people on the business. And that's obviously important. But what Joe is talking about is something bigger than that. It's really cultural, and it's something that is changed to the company's DNA. >> So where do you attack that problem? It doesn't have to go from the top down. You go into the middle. It has to >> be from the top down. It has to be. It has to be because my boss said to do it all right. >> Well, otherwise they well, they might do it. But the organization's because if you do, it >> is a grassroots movement on Lee. The folks who are excited, right? The foam of people, right? They're the ones who are gonna be excited. But they're going to evolve in adopt anyway, right? But it's the rest of the organization, and that needs to be a top down, Um, approach. >> It was interesting hearing this morning keynote speakers. You scored a throw on top down under the bus, but I had the same reaction is you can't do it without that executive buying. And of course, we defined, I guess in the session what that was. Amazon has an interesting concept for for any initiative, like every initiative that's funded has to have what they call a threaded leader. Another was some kind of And if they don't, if they don't have a threat of leader, there's like an incentive system tau dime on initiative. Kill it. It kind of forces top down. Yeah, you know, So >> when we interview our clients, we have a litmus test and the limits. It's kind of a ready in this test. Do you have the executive leadership to actually make this project successful? And in a lot of cases, they don't And you know, we'll have to say will call us when you're ready, you know, or because one of the challenges another part of the litmus test is this IittIe driven. If it's I t driven is gonna be very tough to get embraced by the rest of the business. So way need to really be able to have that executive leadership from the business to say this is something that we need >> to do to survive. Yeah, and, you know, with without the top down support. You could play small ball. But if you're playing the Yankees, you're gonna win one >> of the reasons why when it's I t driven, it's very challenging is because the people part right is a different budget from the i T budget. And when we start talking about data therapy, right and human resource is and training and education of just culture and data literacy, which is not necessary technical, that that becomes a challenge internally figuring out, like how to pay for Andi how to get it done with a corporate politics. >> So So the CDO crowd definitely parts of your book that they should be adopting because to me, there their main job is okay. How does data support the monetization of my organization? Raising revenue, cutting costs, improving productivity, saving lives. You call it value. And so that seems to be the starting point. At the same time. In this conference, you grew out of the ashes of back room information quality of the big data height, but exploded and have kind of gone full circle. So But I wonder, I mean, is the CDO crowd still focused on that monetization? Certainly I think we all agree they should be, but they're getting sucked back into a governance role. Can they do both, I guess, is >> my question. Well, governance has been, has been a big issue the past few years with all of the new compliance regulation and focus on on on ensuring compliance with them. But there's often a just a pendulum swing back, and I think there's a swing back to adding business value. And so we're seeing a lot of opportunities to help companies monetize their data broadly in a variety of ways. A CZ you mentioned not just in one way and, um, again those you need to be driven from the top. We have a process that we go through to generate ideas, and that's wonderful. Generating ideas. No is fairly straightforward enough. But then running them through kind of a feasibility government, starting with you have the executive support for that is a technology technologically feasible, managerially feasible, ethically feasible and so forth. So we kind of run them through that gauntlet next. >> One of my concerns is that chief data officer, the level of involvement that year he has in these digital initiatives again is digital initiative of Field of Dreams. Maybe it is. But everywhere you go the CEO is trying to get digital right, and it seems like the chief data officer is not necessarily front and center in those. Certainly a I projects, which are skunk works. But it's the chief digital officer that's driving it. So how how do you see in those roles playoff >> In the less panel that I've just spoken, very similar question was asked. And again, we're trying to figure out the hierarchy of where the CDO should live in an organization. Um, I find that the biggest place it fails typically is if it rolls up to a C I. O. Right. If you think the data is a technical issue, you're wrong, Right? Data is a business issue, Andi. I also think for any company to survive today, they have to have a digital presence. And so digital presence is so tightly coupled to data that I find the best success is when the chief date officer reports directly to the chief digital officer. Chief Digital officer has a vision for the user experience for the customer customers Ella to figure out. How do we get that customer engaged and that directly is dependent on insight. Right on analytics. You know, if the four of us were to open up, any application on our phone, even for the same product, would have four different experiences based on who we are, who are peers are what we bought in the past, that's all based on analytics. So the business application of the digital presence is tightly couple tow Analytics, which is driven by the chief state officer. >> That's the first time I've heard that. I think that's the right organizational structure. Did see did. JJ is going to be sort of the driver, right? The strategy. That's where the budget's gonna go and the chief date office is gonna have that supporting role that's vital. The enabler. Yeah, I think the chief data officer is a long term play. Well, we have a lot of cheap date officers. Still, 10 years from now, I think that >> data is not a fad. I think Data's just become more and more important. And will they ultimately leapfrog the chief digital officer and report to the CEO? Maybe someday, but for now, I think that's where they belong. >> You know what's company started managing their labor and workforce is as an actual asset, even though it's not a balance sheet. Asked for obvious reasons in the 19 sixties that gave rise to the chief human resource officer, which we still see today and his company start to recognize information as an asset, you need an executive leader to oversee and be responsible for that asset. >> Conceptually, it's always been data is an asset and a liability. And, you know, we've always thought about balancing terms. Your book sort of put forth a formula for actually formalizing. That's right. Do you think it's gonna happen our lifetime? What exactly clear on it, what you put forth in your book in terms of organizations actually valuing data specifically on the balance sheet. So that's >> an accounting question and one that you know that you leave to the accounting professionals. But there have been discussion papers published by the accounting standards bodies to discuss that issue. We're probably at least 10 years away, but I think respective weather data is that about what she'd asked or not. It's an imperative organizations to behave as if it is one >> that was your point it's probably not gonna happen, but you got a finger in terms that you can understand the value because it comes >> back to you can't manage what you don't measure and measuring the value of potential value or quality of your information. Or what day do you have your in a poor position to manage it like one. And if you're not manage like an asset, then you're really not probably able to leverage it like one. >> Give us a little commercial for I do want to say that I do >> think in our lifetime we will see it become an asset. There are lots of intangible assets that are on the books, intellectual property contracts. I think data that supports both of those things are equally is important. And they will they will see the light. >> Why are those five companies huge market cap winners, where they've surpassed all the evaluation >> of a business that the data that they have is considered right? So it should be part of >> the assets in the books. All right, we gotta wraps, But give us Give us the The Caserta Commercial. Well, concert is >> a consultancy that does essentially three things. We do data advisory work, which, which Doug is heading up. We do data architecture and strategy, and we also do just implementation of solutions. Everything from data engineering gate architecture and data science. >> Well, you made a good bet on data. Thanks for coming on, you guys. Great to see you again. Thank you. That's a wrap on day one, Paul. And I'll be back tomorrow for day two with the M I t cdo m I t cdo like you. Thanks for watching. We'll see them all.

from New York it's the cube covering blockchain week now here's John furries hello and welcome back I'm John Fourier we're here on the ground actually on the water on the majesty bow to New York City as decentral has their big unveiling Anthony do you Arielle cube alumni a good friend of the cube is having a massive event here in New York City celebrating the new releases of their new platform their new hardware product actually called the cube to talk about that with Anthony but moreover it's part of a big holistic blockchain week in New York City exciting new projects from new financial products that Kryptos enabling technology innovation a lot of personal people going doing deals so what's going on with you you look great we are at the party looking good people are going crazy out out there we're in a boat I think this kind of environment is very friendly to the kind of community that is created by blockchain naturally so I really commend decentral and Anthony and all of their efforts around this in that they're now creating an environment where I can't walk five feet down the hallway without seeing somebody else that I know and the important thing about that is that now we're really creating this big digital conglomerate we're creating a network of people where I was just speaking to someone outside and he said that it's amazing to see people sharing all kinds of information about their new projects they're they're they're recognizing that there really is enough pie for everyone there's not it is a competition game but really that we should really compete on the application layer and that we should collaborate on the codebase we should collaborate on security and we should collaborate on these really big issues like regulation and privacy so it's amazing to see all these people and that's important that's the open source ethos right there really work together on a project not product because there's a difference between a project and a product and open source is that's languish it's important yeah that's the ethos I love that what's going on in the bug will share some anecdotes what's happening here people who didn't make it couldn't make the boat they you know ate some cars Aston Martin bracelet here what's some of the hallway conversations on the bow what are you hearing here during blockchain week well first of all blockchain week has been has been an amazing opportunity for the blockchain Research Institute to really showcase the work that we are doing to express our interest in enterprise blockchain but really also to support the growing community that is happening in the world and more so in Canada we believe that Canada has an amazing opportunity to to be a leader in blockchain and they are already really a significant amount of the people here our Canadian you know Anthony is a proud Canadian lots of different companies are and one of the major initiatives that we had at consensus was the Canadian Pavilion so we gathered together 23 Canadian blockchain companies and by the way you need a bigger room we did because so many there was a lot yeah open your own conference but the key part with that is that we really wanted to showcase the amazing Canadian innovations that are happening so that people recognize that you know Canada and the more specifically the Toronto Waterloo corridor is is the next Silicon Valley the next hub of blockchain and of quantum computing and of AI and so if you take those three together really those are done taps got an Allen snaps got our two co-founders they authored a report for the World Economic Forum and they argued that that blockchain really is the third leg of the stool that we need to provide an atmosphere for innovation and this was a really good way for us to do that and certainly it's got money tied to its the applications now have a financial component token economics a real key enabler in this to us certainly blockchain check great we love it everyone loves blockchain but it's the token economics that kick in that are starting to see money things applications tying into tokens and coins and yeah I think but that really creates a lot of it creates a lot of confusion it creates a lot of noise suddenly you know in that in the first generation of the internet we we said you know government hands off we want to you know we want to regulate this ourselves this is our thing it's the age of information like like that Tapscott said you know we're entering the internet of value but in entering the internet of value we're now we're now no longer dealing with just information we're dealing with things that matter to people we're dealing with identity and privacy and physical assets and you know real estate and all kinds of different things that are really foundations of the economy and in this case we really need the community to come together and support a regulatory environment because if we don't then the regulator's will and it won't work in the in our messengers it's got to be open open always be proprietary I'm so convinced that open source software which I have lived that generation when it was we were fighting for you know UNIX versus Xenu copyright with AT&T and then was a tea or two citizen now it runs the world's Tier one source one and the model is proven it's coming to crypto and yeah you see that do you see that coming clearly or did that I think as as platforms like you know obviously aetherium but as platforms like hyper ledger and r3s Corte and the forum platform from JPMorgan as these platforms grow in size and grow in membership and grow in in collaboration people will see that the the way to collaborate it's all about this I don't know if you've seen the graphs about fad protocols yes now we're in trusting our payments and our identities and our you know the things that really matter to us we're not giving them to the application layer anymore we're giving them to the protocol layer and if we're giving them to the protocol layer then we really need to collaborate to ensure that all that information is correct all the time and the only way we're going to be able to do that is to be able to create open source platforms and open source activities where everyone is able to participate that's the only way we can create something and if you want to take the code and do something downstream for that liberation please so we have lots of enterprise clients like Procter & Gamble and ExxonMobil and and PepsiCo and others where they're very interested in in enterprise blockchain but at the same time they want to be able to leverage the security of the public chain right it's um Matt spoke at a a Onix had a really really interesting comment about two weeks ago he said I think and he apologized in advance like this might be controversial but but I really think he's right in that he said you know five ten twenty years down the road we won't know the difference between an enterprise blockchain and a public chain right like we're gonna be up we will be a choice right I do you think we'll be able to have it we'll get to a point where it will be dumb not to use the public chain it will be dumb not to be able to leverage the security of it because if you and I enter into you know if we build our own blockchain together I mean that's great one of interesting things too you missed the panel because you might have seen Jimmy song's debate with I did yes that was very provocative so he's got a point on it's just two sides of the coin you know no pun intended right one is what you're saying that enterprises can come in Jimmy was saying is that it's a waste to use the public chain now because some inefficiencies he's technically accurate but that's gonna get better so I wouldn't throw the baby out with the bathwater sometime no I agree but but I think there's a lot of solutions to come in the next year or two or three around interoperability and I think at the end of the day everyone should be able to use whatever blockchain that they think best fits their features but that they should integrate with it with a company like a on or icon or metronome or all these other interesting interoperability projects where you're able to to leverage the security of the public chain but also be able to continue to have your own ecosystem together yeah son of Don Tapscott about this one you interview them at an IBM event and and I'm old enough that I've seen a couple although some of these waves and I lived and I hear the same arguments all the time oh the performance is not there compared to this and easily but these are waves these are shifts right so PC oh no one's having anything with that you know Delta goes on on on web oh it's the so it's slow to dial-up and load a webpage but all of them who were shifts in growth growth was coming behind it yeah so that's the wrong conversations are happening the growth is coming so you guys really nail it with your analysis I think I had your team because it is the shift it is about not necessarily getting in the weeds over did this one thing is it good now yeah great work or well will something really move forward I think that so don actually said in 1992 i in paradigm shift he said that leaders of old paradigms often have trouble embracing the new and so for us at the blockchain research institute we really exist to bridge that knowledge gap between top-tier executives like fred smith and rob carter from FedEx like you know internally at PepsiCo we aim to bridge that knowledge gap so that they just better know how to flow funds within their own company just doing great one is doing great work well to get me to give a plug real quick love your work explaining some of the things you guys are doing you're on the right track I can say I love what you're doing I looked at it it's right on but you're open you're not like you know down on your fist on the table yeah you guys are cool with the work you guys are doing so we're doing 80 projects on the strategic applications of blockchain technology in a variety of industries so our research fits in three categories we have verticals where financial services is obviously our largest vertical but we're also looking into projects in in retail and manufacturing in supply chain in healthcare in government in media and telecommunications in resources and mining and you know you know pickaxe mining not real mining mining old-school mining yeah and then we're also looking at a lot of the management applications of blockchain so you know the first generation of the internet didn't really do a lot to change the structure of the corporation it allows that it allowed us to find people all over the world I can find people to do anything but I still have to negotiate a contract with them myself to enter into an agreement I sell to establish trust but if we now have this amazingly fluid technology that allows us to lower the cost of search the cost of negotiating contracts the cost of contracting and the cost of establishing trust then that blows the windows and the walls of the corporation wide open and in that we are really driving to help our member organizations understand the nature of the firm is changing economic theory of yesteryear being disrupted really fast way yeah vodka Jane thanks for coming up here one more question yes this week what did you hear in the out there in the city what's your observation for the people didn't make it to New York a lot of great face to face a lot of great engagement good networking good contacts growing ecosystem but still a tight-knit community people know each other they're sharing information what did you hear share some data some insights that that folks couldn't get if they didn't come I think for us a lot of the reason that we are here is that it's a you know peril if you don't show up it's being part of a community if if we are going to show a leadership role in this community then we need to show up for our colors we need to show up for companies that that you know may not be able to advocate for themselves I've met so many interesting companies this week that either do not have the resources or they're trying to raise money or they're trying to be investors and and the life of an entrepreneur obviously is is a tough one and for us we we have a growing pioneer membership at the blockchain Research Institute where we aim to connect large corporations who are looking for or looking to invest in different in different watching platforms but don't know where to start and so we run essentially a white listing service where we are partnered with lots of amazing companies like pay case and shift and Collider X and a on and all these different companies where they're they're really working to move the ball forward as well as make an impact so yeah it was for us it was it was looking for more innovative companies but also you know doing our part showing our role this was a one of the first times that I actually saw Don Tapscott a now except thought actively you know taking meanings and participating in the conversation and and being present and being there so so for us it was a lot of it was presence he was a lot of presidents we're some fun you having fun I am yes yes behind us is a boat we're on it we're in the front part we're in the anthony o diario private suite lounge here's where he can relax it gets kind of a green room behind us awesome DJ four stories of boat going down to your just past the Statue of Liberty a lot of action let's get back to the partying what are you saying alright I'm jump for it thanks for watching we're on the boat New York City thank you for watching

(uptempo orchestral music) >> Hello and welcome to a special exclusive conversation here in the studios of Palo Alto, California. I'm John Furrier, your co-host and theCube co-founder of Silicon Angle Media. We have exclusive, breaking launch here from a Cube alumni Al Burgio, who's the founder and CEO of Fusechain, a hot start up going after the blockchain, a little bit of open source. This is a launch. This is new information coming out. You still (indistinct talking) for the first time talking about your project again Cube alumni. Welcome to the theCube conversation. >> Thank you for having me John. >> You're the founder and CEO of Fusechain. >> That's correct. >> So you're just in Miami, 5000 people at these blockchain conferences which are exploded the biggest wave. Crypto and Blockchain in tandem are creating a very attractive and intoxicating market. It's the biggest wave we've seen in all the alpha entrepreneurs going out there. Some scammers too are trying to get into this market. We've documented that on theCube. But it's the biggest wave we've seen in a long time. You're out there. Talk about what is Fusechain? What's the story? Gives us the update. >> Sure. So Fusechain is a blockchain technology company, really founded to support a new open source project that is also coming out of stealth mode called the digital bits project. It's focused on disrupting the coalition loyalty industry. What we refer to as let's say one dot of loyalty in rewards. We feel that that market is ripe for disruption. A lot of frictions, others I'm happy to talk about in that space and we feel that blockchain in a decentralized model with the right partners and coalition could change the game. >> So you've got a T-shirt for us. I appreciate it called digital bits. New open source project. What I like about what you're doing, first of all you got a great track record. You have a ton of start ups you've done in the past and again great exits and you always have a good eye for where there's disruption and certainly crypto is dislocating industries, not just disrupting. Radically changing the makeup so before I dig into that. I want to get into digital bit. It's a little bit open source. So you have an open source project combined with what you guys do, so it sounds like you're what Red Hat was for Linux. You're for digital bits, is that? >> That's right so we are. So Fusechain is focused on building applications that are interoperable with that blockchain to support enterprises which is merchants, retailers, hotels so forth that would be working with the digital bits project. And so we feel that there is an opportunity to monetize that building let's say SAS type models around these applications and supporting and helping make digital events very successful. >> So it's interesting, I was observing when I was in New York last fall and I walked into a funds conversation with a bunch of guys. And people were trying to grop where the action was and I raised my hand and said, you can tell a good deal by the ones that are going to take down and incumbent industry, not just the player. You're taking a similar approach which I like about what your deal is. What is it about your approach and what is the target and how are you going to attack that? >> Sure, sure. First and foremost, really focused on blockchain and what was important for us characteristics wise and we felt that it needed to rapid transaction in terms of nature. Seconds as opposed to blocks, let's say every 10 minutes like a bitcoin for example. Because we are focused ultimately let's say on the consumer space. So we first and foremost on how our approach to developing this protocol and supporting the digital bits project. From there it was what industry did we feel would be best suited for this and this is how we gravitate into the loyalty industry. There is already a learned behavior in loyalty. People look at points as let's say a form of currency. They know how to go join one earn and what have you. It's like human mining, if you will and so we wanted to fit let's blockchain technology loyalty as opposed to fitting loyalty into blockchain. The other thing that I liked in terms of us going in this direction was really looking at. There was a lot of different ICOs, blockchain projects out there and so forth. We're the first to market with this. We're the first to market with that, but what's the incumbent doing in corporate America? Let's say, they're probably sitting and waiting and there's nothing preventing them copycatting and doing the same when there's enough of an established market. What I liked about loyalty more specifically the coalition models. We didn't feel that with a decentralized model. Putting into the market a decentralized model that they could replicate that the same way, It's like if you look at Netflix and what they did to Blockbuster. Blockbuster could not pivot quite the same way. We feel that loyalty dot one, specifically the coalition programs, will have a challenges in adopting blockchain in a similar manner. And so we feel that for that reason what we're up to here with this plain venture it's going to be highly disruptive. >> Let's get to the business model after we talk a little bit about the actual tech and the products. So you have digit bits and I notice you guys have a trade mark on that going on. But it's going to be open source. So what is digital bits? Is that the coin? Is it a utility token? How does it work? What are you actually doing? >> So digital bits is the name of the open source project. It's the name of the blockchain protocol. It will be the name of the cryptocurrency, so all the name of that cryptocurrency to that blockchain once it's put in circulation. And the project itself, we will ultimately see that spun into a foundation so it's the name of all of the above in terms of what digital bits is. Fusechain is a contributor to that project and we obviously like what it stands for. We're building parallel management platforms and so forth. Others are free to do this as well and have begun to do so. That will help make that project successful. >> So in other words, it creates a code from digital bits and apply it but you're going to be a token in the project. >> Yeah, if you think of, use Red Hat as an example. So there was open source project out there, various Linux type projects back in the day and big enterprises wanted to take advantage of that. But who was going to support them doing that? So Red Hat obviously established a very successful market in doing that so in a similar manner. We want to support digital bits in a very big way. We're building applications that businesses are going to need so they don't have to go build them themselves, and it will bring those markets. >> Who are you targeting? You're targeting existing businesses that have loyalty. You're trying to take that business away from them. Isn't that new? What the-- >> So coalition loyalty industry is fairly well established. >> John: What does that mean coalition? >> Coalition is multi merchant so in the United States, a brand known as Punti, that happens to be owned by American Express, but you can go to Macy's earn Punti, ExxonMobil and so forth. Canada is very big market for this as well so you have air miles, major grocery chains. >> John: They're always expiring, I hate these programs. >> Well that's the other issue with them. So there's tremendous friction and frustration now with these programs that exists. We're looking to disrupt that as well and provide-- >> So how do they work with you? Give an example of the use case that (indistinct talking). >> Ultimately we feel that, from a coalition standpoint often times the merchant is paying a reoccurring fee to support that program. So let's say big grocery store or hotel or what have you and in order for the privilege of their customers to be able to earn let's say, while shopping online at their store or in that facility just for the privilege of their users to be able to earn, the merchant is having to pay the operator that program, before the consumer has done anything with those points and so it's a big cost to them and we basically just to quantify, it can be as much of an 80% savings verses what the merchant would have to pay the support. One dot to support this decentralized blockchain base solution. >> So you guys are a decentralized application or are you a decentralized platform or you an infrastructure protocol? How do you categorically define yourself? >> So digital bits is definitely an infrastructure protocol but focus specifically on loyalty rewards and so just to, it's really opened in that sense that various businesses can join and support this. In a number of different ways whether it's pre-existing products, platforms that they have. They want it to be inoperable or they simply want their users to be able to now earn this form of loyalty. And we have in the coming weeks, you'll see announcements from other brands, some let's say blue chipish and others up and coming early stage companies with doing loyalty in a different way, joining the digital bits project to take advantage of the tokenize economy. >> I like this Red Hat to Linux in metaphor because I think no one's actually seen that yet happen. I see a lot of (indistinct talking) happen certainly the (indistinct talking) a decentralized apps or de-apps as they are called is huge growth market. We see a big tsunami coming with de-apps, decentralized applications. So will I be writing decentralized apps on your platform infrastructure? Is that they're doing? How are they implementing in your mind the Fusechain and the digital bits? >> So I mean there's basic examples of the products in market already, let's say multi-coin wallets. If they wanted to list digital bits as another cryptocurrency that their app supports then they can support the project in that way. So there's a number of different ways that the developers are established. >> I can build my own wall. I could integrate it into a pre-existing coin wallet. So you're pretty flexible, you're agnostic on how to gets done. >> Exactly, exactly. And this is why ultimately digital bits will be spun into a foundation. >> It will establish some policies around this so it's not completely naked but some governance. >> It's always tricky, you got to be careful. >> Well, governance from the standpoint of I'm looking at it from the perspective of how merchants, the terms by which they would disseminate digital bits to their consumers. >> So some lightweight governance. Is it hardcore governance or lightweight? >> No, I would say lightweight. So it's making sure that there's no bad actors at least at the time of-- >> (indistinct talking) a non-profit apart of the Fusechain? >> No, no, non-profit. >> Okay, okay so let's get into some of your journey. I see entrepreneurial journeys are happening all the time. A lot of people are jumping into the ICO and our crypto blockchain as a start. A lot of my alpha friends are doing it. It's just like wow. This is a big trend. It's disruptive. >> Al: Oh highly. >> Where there's disruption, you're going to have entrepreneurs but also scammers. We'll get that in a second but talk about your journey. ICO, you got to get formed. Get a little form, it could be expensive. We've documented theCube with Goodwin, a law firm in the valley that's doing a lot of ICOs. It could be expensive. There's tax consequences so how are you looking as an entrepreneur? You have opportunity recognition, check. Now you got to put it together. Utility token, are you raising money, are you doing the ICO? Can you give us some details? >> So it's utility token. We are raising money Fusechain initially is focused on raising capital, let's call it the old fashioned way. So Fusechain itself is taking in equity investment not involving any cryptocurrency. >> So no token sales on that simply. >> Is to date but a digital bits itself will be partaking and raising capital for the project. >> With Fusechain's ICO or their own ICO? >> No, no, it will be the digital bits projects. >> So will the ICO go through Fusechain or will go through digital bits? >> It will go through digital bits. >> Okay so you got a utility so that involves a token sales. So you're going to do a private, that's equity for Fusechain and then a token sale for digital bits. >> Al: Correct. >> Okay, that's nice-- >> Call it the pre-presale in advance of it actually being widely disseminated. >> What is the utility of the platform because that's the how we test? >> Yeah, yeah so we're keeping it really simple to start. We feel that we'll be able to demonstrate other utilities with this project, but similar to other projects out there if you're familiar with Ripple and Stellar and so forth. Some basic utility, you need to have some of the coin to be able to send coin. And so we're keeping it relatively simple from that perspective. There's security benefits. >> So the utility you're going after at launch is token sharing. >> Correct. >> Okay, and the activity is loyalty based for the merchants? >> Yes, and consumers so ultimately, digital bits stands for all these sort things I've just mentioned integrated together in this decentralized model really focused on giving back to users. So first and foremost, users being consumers that use these programs and the merchants that have historically supported these types of programs. In addition to that, digital bits is also focused on giving back to society. More specifically aligning itself with charitable organization worldwide that the project itself will be able to give back to. >> You're the (indistinct talking) guy. Your last (indistinct talking) you successfully sold it and exit pairing and networking. One big global network now. So I want to get your perspectives on entrepreneurs and how you've been traveling. We tried to get you last week here on theCube to talk about you're project and getting out there now but you've seen a lot of the events you're out in the field, you're own in the trenches. What's the landscape like in crypto and blockchain? Can you offer any observations? Good, bad and ugly, what's it take? >> I was for example recently last week I attended the North American Bitcoin Blockchain conference down in Miami, nearly 5000 people. Tremendous buzz, great pedigree among speakers. Both domestic speakers worldwide and people I would say from all walks of life. A lot of people are interested in either in the space or very interested in the space and I don't have the numbers in terms what the attendance was last year at that conference. But I wouldn't be surprised if it's 10x-- >> Are these new in tech? Are they tech gurus? What's the makeup and profile of folks in here? >> Overstock.com CEO. One of the keynote speakers of this and obviously a very well established company heavy in blockchain with their subsidiary t0 as well as some of the up and comers. Great pedigree, more specifically associated with the blockchain space but really supporting a lot of these events and being great evangelists for all things blockchain. >> So I get your perspective again. You see many ways of innovation, we're talking before we came on camera. I've been saying and when we talk privately in the valley here and in other places that this is like a dot com bubble, but it's accelerated. Everyone's getting their surf boards and jumping on those big waves. Some think there will be a crash. I think they'll be a probably a reset. There's just too much action happening and again the dot com bubble. Everything actually happens. >> Al: Yeah. >> So a little anecdote there but the point is there's some scammers. >> Al: Yes. >> There's some bubble activity. How are you sorting through that noise? What should people look through? Because when people are like, "Well I'm skeptical. "You're riding a hype wave right now. "What's the real deal?" >> The reality is with anything super exciting, there's always scammers. You have to take traditional stocks. There's always the penny stock scammers let's say and so this is not necessarily something exclusive to blockchain tokens or what have you. We see this in the traditional capital market systems and equities that are out there today. I'd say that this is very much mid 90s internet in terms of equivalent. The benefit of blockchain is that the internet exists so social network and Facebook. The ability to get news out there, widely disseminated, The internet existed. That infrastructure is helping to support the rapid growth trend that we're seeing with blockchain. So I would say that it is a bigger phenomenon than the internet was in the 90, by virtue the internet now existing. >> I got to ask you so one of the things I always is that there's no value being created. It's really a mirage right? So this thing about blockchain is there's a lot of value creation opportunities. As an entrepreneur, you get to see that and certainly see it from the Fusechain and digital bits. If someone said to, "Al, this thing is a bunch of hype. "Where's the value?" Where's the value? Why is crypto and blockchain attracting all these entrepreneurs? Why is it so intoxicating? Why is it attracting all walks of life? What's the value creation opportunity? >> Put cryptocurrencies aside for a moment and just focus on blockchain as a technology and really what it stands for. It is truly revolutionary. This is something with capability to have distributed ledgers solving the double spend issue. All of these things that historically could not be done with the internet or other forms of technology. And so it's very powerful in terms of its applications in areas of let's say even supply chain and how businesses can have this trusted collaborative platform or technology where you don't have to trust any centralized corporation, other institution or what have you, and it just works. So that is the technology itself is highly powerful and it's already evident that it's touching a number of different industries. So outside of the cryptocurrencies, let's say craze. Blockchain is definitely here. It's here to stay and it's just going to continue-- >> That's a fundamental infrastructure shift. >> Absolutely. >> Alright, so let me give you the little snarky comment that get on Facebook all the time. "Ah John crypto, this blockchain. "Have you seen a distributed database before, lol?" That's some snarky comments. So the naysayers will be like, "It's just a distributed database ledger." And then some people will be like, "I just don't see the business case. "Why do people actually need blockchain?" What's your take on those two points? >> I think that, that's a great way to look at it. Can you solve that problem with just using regular database? And probably often times the answer is yes, so blockchain shouldn't necessarily be used for everything, but there is certain things that historically, and again-- >> (indistinct talking) is one. >> Exactly, yeah. >> (indistinct talking) attracts. >> Absolutely, and so there's a number of industries where having it be blockchain based is definitely better than dealing with distributed databases. >> I've been commenting. I'm pro-blockchain as you know. Pretty bias, people know that. However what I say to folks is look, there's a dynamic going on here that's revolutionary at the infrastructure level. I think that's true. That will play out and then I think immutability and then the decentralized nature of apps. It will be a whole another genre of software development whether it's media (indistinct talking) to software. But ultimately it's these communities, if you look at in the media business. I was just at Sundance. There's new artist coming on that have their own audiences. >> Al: Right. >> So those are crushing the elites. So you have a revolution where the common person or group of people could get together in an unstructured way, a decentralized way to take on elite or huge industry incombantants or industries themselves. That's a phenomenon. That's kind of nuance. >> Al: Absolutely. >> It's real. >> It's absolutely real. Think of open source traditionally. You needed your employer to sponsor you. Hey if work for you, can I spend 10% of my time on a open source project? The open source project itself never really had a mechanism to provide support form of remuneration. Now by tokenising and so forth these native currencies an idea can provide a potential for reward and we're seeing that happen, and so it no different than any other great idea. 90 plus % of start ups don't necessarily make it. 90 plus % of blockchain ideas may not make it but the reality is, a community with a great idea can kick off a project on their own and stand the test of time. >> Well Red Hat became popular from Linux which was a second tier citizen in an open source. Now it's tier one also open source is running things so I got to ask you a final question on the business model. How are you guys planning on making money? Is it from support in the open source projects specifically, more services on the coin side. Is it managing the coins? Do you have visibility yet into that model? >> Yes, so I would say yes to what you just said. So Fusechain will create shareholder value in a few different ways. One, obviously being one of the first supporters to the digital bit project. We obviously want to see that project wildly successful, coin appreciation and the asset appreciation that potential could occur there will create shareholder value for Fusechain. In addition to that, Fusechain is building applications that will be SAS like in model. We'll be able to derive a reoccurring revenue. (indistinct talking) models but we'll derive reoccurring revenues. >> For the ecosystem of saving the digital bits actually it evolves. >> Right, merchants, you can go build softwares yourself or here's a subscription based platform that you can use and we'll provide support as well. >> Having fun? >> I'm having a blast. It's the 90s all over again. >> It the twinkle of the eye. I got to say, it's super intoxicating. I'll take hit of that blockchain in next segment with you. Appreciate it, it's really awesome. Blockchain and crypto, really amazing revolution. We're doing our part to unpack it, analyze it and also look at the good deals out there. This is SiliconANGLE theCube here in Palo Alto. I'm John Furrier. Special exclusive to you conversation with Fusechain coming out, talking about their project for the first time digital bits with Al Burgio, the founder and CEO. Thanks for watching. (uptempo orchestral music)