(upbeat music) >> From the Bellagio Hotel in Las Vegas, It's theCUBE. Covering UiPath FORWARD IV. Brought to you by UiPath. >> Welcome back to theCUBE's coverage of UiPath FORWARD IV. Live from the Bellagio, in Las Vegas. I'm Lisa Martin with Dave Vellante. We're here all day today and tomorrow. We're going to talk about process mining next. We've got two guests here. Mike Engel is here, intelligent automation and process intelligence leader at PWC. And Ryan McMahon, the SVP of growth at UiPath. Gentlemen, welcome to the program. >> Thank you, Lisa. >> Thank you. >> So Ryan, I'm going to start with you. Talk to us about process mining. How does UiPath do it differently and what are some of the things being unveiled at this event? >> So look, I would tell you it's actually more than process mining and hopefully, not only you but others saw this this morning with Param. It's really about the full capabilities of that discovery suite. In which, obviously, process mining is part of. But it starts with task capture. So, going out and actually working with subject matter experts on a process. Accounts payable, accounts receivable, order to cash, digitally capturing that process or how they believe it should work or execute across one's environment. Right Mike? And then from there, actually validating or verifying with things or capabilities like process mining. Giving you a full digital x-ray of actually how that process is being executed in the enterprise. Showing you process bottlenecks. For things like accounts payable, showing you days outstanding, maverick buying, so you can actually pin point and do a few things. Fix your process, right? Where process should be fixed. Fix your application because it's probably not doing what you think it is, and then third, and where the value comes, is in our platform of which process mining is a capability, our PA platform. Really moving directly to automations, right? And then, having the ability with even task mining to drill into a specific bottleneck. Capturing keystrokes, clicks, and then moving to, with both of those, process mining and task mining, into Automation Hub, as part of our discovery platform as well. Being able to crowdsource, prioritize, all of those potential, if you will, just capabilities of automations, and saying, "Okay, let's go and prioritize these. These deliver to the greatest value," and executing across them. So, as much as it is about process mining, it's actually the whole entire discovery suite of capabilities that differentiates UiPath from other RPA vendors, as the only RPA vendor that delivers process mining, task mining and this discovery suite as part of our enterprise automation platform. >> Such a critical point, Ryan. I mean, it's multi-dimensional. It's not just one component. It's not just process mining or task mining, it's the combination that's really impactful. Agree with you a hundred percent. >> So, one of the things that people who watch our shows know, I'm like a broken record on this, the early days of RPA, I called it paving the cow path. And that was good because somebody knew the process, they just repeat it. But the problem was, the process wasn't necessarily the best process. As you just described. So, when you guys made the acquisition of ProcessGold, I said, "Okay, now I'm starting to connect the dots," and now a couple years on, we're starting to see that come together. This is what I think is most misunderstood about UiPath, and I wonder, from a practitioner's perspective, if you can sort of fill in some of those gaps. It's that, it's different from a point tool, it's different from a productivity tool. Like Power Automate, I'll just say it, that's running in Azure Cloud, that's cool or a vertically integrated part of some ERP Stack. This is a horizontal play that is end to end. Which is a bigger automation agenda, it's bold but it's potentially huge. $60 billion dollar TAM, I think that's understated. Maybe you could, from a practitioner's perspective, share with us the old way, >> Yeah. >> And kind of, the new way. >> Well obviously, we all made a lot of investments in this space, early on, to determine what should we be automating in the first place? We even went so far as, we have platforms that will transcribe these kind of surveys and discussions that we're having with our clients, right. But at the end of the day all we're learning is what they know about the process. What they as individuals know about the process. And that's problematic. Once we get into the next phase of actually developing something, we miss something, right? Because we're trying to do this rapidly. So, I think what we have now is really this opportunity to have data driven insights and our clients are really grabbing onto that idea, that it's good to have a sense of what they think they do but it's more important to have a sense of what they actually do. >> Are you seeing, in the last year in a half we've seen the acceleration of a lot of things, there's some silver linings but we've also seen the acceleration in automation as a mandate. Where is it? In terms of a priority, that you're seeing with customers, and are there any industries that you're seeing that are really leading the edge here? >> Well I do see it as a priority and of course, in the role that I have, obviously everybody I talk to, it's a priority for them. But I think it's kind of changing. People are understanding that it's not just a sense of, as Ryan was pointing out, it's not just a sense of getting an understanding of what we do today, it's really driving it to that next step of actually getting something impactful out the other end. Clients are starting to understand that. I like to categorize them, there's three types of clients, there's starters, there's stall-ers and those that want to scale. >> Right? So we're seeing a lot more on the other ends of this now, where clients are really getting started and they're getting a good sense that this is important for them because they know that identifying the opportunities in the first place is the most difficult part of automation. That's what's stalling the programs. Then on the other end of the spectrum, we've got these clients that are saying, "Hey, I want to do this really at scale, can you help us do that?" >> (Ryan) Right. >> And it's quite a challenge. >> How do I build a pipeline of automations? So I've had success in finance and accounting, fantastic. How do I take this to operations? How do I take this this to supply chain? How do I take this to HR? And when I do that, it all starts with, as Wendy Batchelder, Chief Data Officer at VMware, would say and as a customer, "It starts with data but more importantly, process." So focusing on process and where we can actually deliver automation. So it's not just about those insights, it's about moving from insights to actionable next steps. >> Right. >> And that is where we're seeing this convergence, if you will, take place. As we've seen it many times before. I mentioned I worked at Cisco in the past, we saw this with Voice Over IP converging on the network. We saw this at VMware, who I know you guys have spoken to multiple times. When a move from a hypervisor to including NSX with the network, to including cloud management and also VSAN for storage, and converging in software. We're seeing it too with process, really. Instead of kids and clipboards, as they used to call it, and many Six Sigma and Lean workshops, with whiteboards and sticky papers, to actually showing people within, really, days how a process is being executed within their organization. And then, suggesting here's where there's automation capabilities, go execute against them. >> So Ryan, this is why sometimes I scoff at the TAM analysis. I get you've got to do the TAM analysis, you've got to communicate to Wall Street. But basically what you do is you pull out IDC or Gartner data, which is very stovepipe, and you kind of say, "Okay we're in this market." It's the convergence of these markets. It's cloud, it's containers, it's IS, it's PaaS, it's Saas, it's blockchain, it's automation. They're all coming together to form this, it sound like a buzzword but this digital matrix, if you will. And it's how well you leverage that digital matrix, which defines your digital business. So, talk about the role that automation, generally, RPA specifically, process mining specifically, play in a digital business. >> Do you want to take that Mike or do you want me to take it? >> We can both do it? How about that? >> Yeah, perfect. >> So I'll start with it. I mean all this is about convergence at this point, right? There are a number of platform providers out there, including UiPath, that are kind of teaching us that. Often times led by the software vendors in terms of how we think of it but what we know is that there's no one solution. We went down the RPA path, lots of clients and got a lot of excitement and a lot of impact but if you really want to drive it broader, what clients are looking at now, is what is the ecosystem of tools that we need to have in place to make that happen? And from our perspective, it's got to start with really, process intelligence. >> What I would say too, if you look at digital transformation, it was usually driven from an application. Right? Really. And what I think customers found was that, "Hey," I'm going to name some folks here, "Put everything in SAP and we'll solve all your problems." Larry Ellison will tell you, "Put everything into Oracle and we'll solve all your problems." Salesforce, now, I'm a salesperson, I've never used an out of the box Salesforce dashboard in my life, to run my business because I want to run it the way I want to run it. Having said that though, they would say the same thing, "Put everything into our platform and we'll make sure that we can access it and you can use it everywhere and we'll solve all of your problems." I think what customers found is that that's not the case. So they said, "Okay, where are there other ways. Yes, I've got my application doing what it's doing, I've improved my process but hang on. There's things that are repeatable here that I can remove to actually focus on higher level orders." And that's where UiPath comes in. We've kind of had a bottom up swell but I would tell you that as we deliver ROI within days or weeks, versus potentially years and with a heavy, heavy investment up front. We're able to do it. We're able to then work with our partners like PWC, to then demonstrate with business process modeling, the ability to do it across all those, as I call, Silo's of excellence in an organization, to deliver true value, in a timeline, with integrated services from our partner, to execute and deliver on ROI. >> You mentioned some of the great software companies that have been created over the years. One you didn't mention but I want you to comment on it is Service Now. Because essentially McDermott's trying to create the platform of platforms. All about workflow and service management. They bought an RPA company, "Hey we got this too." But it's still a walled garden. It's still the same concept is put everything in here. My question is, how are you different? Yeah look, we're going to integrate with customers who want to integrate because we're an open platform and that's the right approach. We believe there will be some overlap and there'll be some choices to be made. Instead of that top down different approach, which may be a little bit heavy and a large investment up front, with varied results, as far as what that looks like, ours is really a bottoms up. I would tell you too, if you look at our community, which is a million and a half, I believe, strong now and growing, it's really about that practitioner and those people that have embraced it from the bottom up that really change how it gets implemented. And you don't have what I used to call the white blood cells, pushing back when you're trying to say, "Hey, let's take it from this finance and accounting to HR, to the supply chain, to the other sides of the organization," saying, "Hey look, be part of this," instead of, "No, you will do." >> Yeah, there's no, at least that I know of, there's no SAP or Salesforce freemium. You can't try it before you buy. And the entry price is way higher. I mean generally. I guess Salesforce not necessarily but I could taste automation for well under $100,000. I could get in for, I bet you most of your customers started at 25 of $50,000 departmental deployments. >> It's a bottoms up ground swell, that's exactly right. And it's really that approach. Which is much more like an Atlassian, I will tell you and it's really getting to the point where we obviously, and I'm saying this, I work at UiPath, we make really good software. And so, out of the box, it's getting easier and easier to use. It all integrates. Which makes it seamless. The reason people move to RPA first was because they got tired of bouncing between applications to do a task. Now we deliver this enterprise automation platform where you can go from process discovery to crowd sourcing and prioritizing your automations with your pipeline of automations, into Studio, into creating those automations, into testing them and back again, right? We give you the opportunity not to leave the platform and extract the most value out of our, what we call enterprise automation platform. Inclusive of process mining. Inclusive of testing and all those capabilities, document understanding, which is also mine, and it's fantastic. It's very differentiated from others that are out there. >> Well it's about having the right framework in place. >> That's it. From an automation perspective. I think that's a little bit different from what you would expect from the SAP's of the world. Mike, where are you seeing, in the large organizations that you work with, we think of what you describe as the automation pipeline, where are some of the key priorities that you're finding in large organizations? What's in that pipeline and in what order? >> It's interesting because every time we have a conversation whether it's internal or with our clients, we come up with another use case for this type of technology. Obviously, when we're having the initial conversations, what we're talking about is really automation. How do we stuff that pipe with automation. But you know, we have clients that are saying, "Hey listen, I'm trying to carve out of a parent company and what I need to do is document all of my processes in a meaningful way, that I can, at some point, take action on, so there's meaningful outcomes." Whether it be a shared services organization that's looking to outsource, all different types of use cases. So, prioritizing is, I think, it's about impact and the quickest way to impact seems to be automation. >> Is it fair to say, can I look at you UiPath as automation infrastructure? Is that okay or do you guys want to say, "Oh, we're an application." The reason I ask, so then you can answer, is if you look at the great infrastructure plays, they all had a role. The DBA, the CCIE from Cisco, the Cloud Architect, the VMware admin, you've been at all of them, Ryan. So, is there a role emerging here and if it's not plumbing or infrastructure, I know, okay that's cool but course correct me on the infrastructure comment and then, is there a role emerging? >> You know, I think the difference between UiPath and some of the infrastructure companies is, it used to take, Dave, years to give an ROI, really. You'd invest in infrastructure and it's like, if we build it they will come. In fact, we've seen this with Cloud, where we kind of started doing some of that on prem, right? We can do this but then you had Amazon, Azure and others kind of take it and say, "Look, we can do it better, faster and cheaper." It's that simple. So, I would say that we are an application and that we reference it as an enterprise automation platform. It's more than infrastructure. Now, are we going to, as I mentioned, integrate to an open platform, to other capabilities? Absolutely. I think, as you see with our investments and as we continue to build this out, starting in core RPA, buying ProcessGold and getting into our discovery suite of capabilities I covered, getting into, what I see next is, as you start launching many bots into your organization, you're touching multiple applications, so you got to test it. Any time you would launch an application you're going to test it before you go live, right? We see another convergence with testing and I know you had Garrett on and Matt, earlier, with testing, application testing, which has been a legacy, kind of dinosaur market, converging with RPA, where you can deliver automations to do it better, faster and cheaper. >> Thank you for that clarification but now Mike, is that role, I know roles are emerging in RPA and automation but is there, I mean, we're seeing centers of excellence pop up, is there an analogy there or sort of a similar- >> Yeah, I think the new role, if you will, it's not super new but it's really that sense of an automation solution architect. It's a whole different thing. We're talking about now more about recombinant innovation. >> Mike: Yeah. >> Than we are about build it from scratch. Because of the convergence of these low-code, no-code types of solutions. It's a different skill set. >> And we see it at PWC. You have somebody who is potentially a process expert but then also somebody who understands automations. It's the convergences of those two, as well, that's a different skill set. It really is. And it's actually bringing those together to get the most value. And we see this across multiple organizations. It starts with a COE. We've done great with our community, so we have that upswell going and then people are saying, "Hang on, I understand process but I also understand automations. let me put the two together," and that's where we get our true value. >> Bringing in the education and training. >> No question. >> That's a huge thing. >> The traditional components of it still need to exist but I think there are new roles that are emerging, for sure. >> It's a big cultural shift. >> Oh absolutely, yeah. >> How do you guys, how does PWC and UiPath, and maybe you each can answer this in the last minute or so, how do you help facilitate that cultural shift in a business that's growing at warp speed, in a market that is very tumultuous? How do you do that? >> Want to go first or I can go? >> I'll go ahead and go first. It's working with great partners like Mike because they see it and they're converging two different practices within their organization to actually bring this value to customers and also that executive relevance. But even on our side, when we're meeting with customers, just in general, we're actually talking about, how do we deal with, there's what? 13 and a half million job openings, I guess, right now and there's 8500 people that are unemployed, is the last number that I heard. We couldn't even fill all of those jobs if we wanted to. So it's like, okay, what is it that we could potentially automate so maybe we don't need all those jobs. And that's not a negative, it's just saying, we couldn't fill them anyway. So let's focus on where we can and where, there again, can extract the most value in working with our partners but create this new domain that's not networking or virtualization but it's actually, potentially, process and automation. It's testing and automation. It might even be security and automation. Which, I will tell you, is probably coming next, having come out of the security space. You know, I sit there and listen to all these threats and I see these people chasing, really, automated threats. It's like, guys a threat hunter that's really good goes through the same 15 steps that they would when they're chasing a false positive, as if a bot would do that for them. >> I mean, I've written about the productivity declines over the past several decades in western countries, it's not universal around the world and maybe we have a productivity boost because of Covid but it's like this perpetual workday now. That's not sustainable. So we're not going to be able to solve the worlds great problems. Whether it's climate change, diversity, massive deaths, on and on and on, unless we deal with that labor gap. >> That's right. >> And the only way to do that is automation. It's so clear to me that that's the answer. Part of the answer. >> It is part of the answer and I think, to your point Lisa, it's a cultural shift that's going to happen whether we want it to or not. When you think about people that are coming into the work force, it's an expectation now. So if you want to retain or you know, attract and retain the right people, you'd better be prepared for it as an organization. >> Yeah, remember the old, proficient in Word and Excel. Makes it almost trivial. It's trivial compared to that. I think if you don't have automation chops, going forward, it's going to be an issue. Hey, we have whatever, 5000 bots running at our company, how could you help? Huh? What's a bot? >> That's right. You're right. We see this too. I'll give you an example at Cisco. One of their financial analysts, junior starter, he says, "Part of our training program, is creating automations. Why? Because it's not just about finance anymore. It's about what can I automate in my role to actually focus on higher level orders and this for me, is just amazing." And you know, it's Rajiv Ramaswamy's son who's over there at Cisco now as a financial analyst. I was sitting on my couch on a Saturday, no kidding, right Dave? And I get a text from Rajiv, who's now CEO at Nutanix, and he says, "I can't believe I just created a bot." And I said, "I'm at the right place." Really. >> That's cool, I mean hey, you're right too. You want to work for Amazon, you got to know how to provision a EC2 instance or you don't get the job. >> Yeah. >> You got to train for that. And these are the types of skills that are expected- >> That's right. >> For the future. >> Awesome. Guys- >> I'm glad I'm older. >> Are you no longer proficient in Word is the question. >> Guys, thanks for joining us, talking about what you guys are doing together, how you're really facilitating this massive growth trajectory. It's great to be back in person and we look forward to hearing from some of your customers later today. >> Terrific. >> Great. >> Thank you for the opportunity. >> Thank you for having us. >> Thank you guys. >> Our pleasure. For Dave Vellante, I'm Lisa Martin, you're watching theCUBE live from the Bellagio in Las Vegas, at UiPath FORWARD IV. Stick around. We'll be back after a short break. (upbeat music)

>> My name is Franco Nori. Is a great pleasure to be here and I thank you for attending this meeting and I'll be talking about some of the work we are doing within the NTT-PHI group. I would like to thank the organizers for putting together this very interesting event. The topics studied by NTT-PHI are very exciting and I'm glad to be part of this great team. Let me first start with a brief overview of just a few interactions between our team and other groups within NTT-PHI. After this brief overview or these interactions then I'm going to start talking about machine learning and neural networks applied to computationally difficult problems in quantum physics. The first one I would like to raise is the following. Is it possible to have decoherence free interaction between qubits? And the proposed solution was a postdoc and a visitor and myself some years ago was to study decoherence free interaction between giant atoms made of superconducting qubits in the context of waveguide quantum electrodynamics. The theoretical prediction was confirmed by a very nice experiment performed by Will Oliver's group at MIT was probably so a few months ago in nature and it's called waveguide quantum electrodynamics with superconducting artificial giant atoms. And this is the first joint MIT Michigan nature paper during this NTT-PHI grand period. And we're very pleased with this. And I look forward to having additional collaborations like this one also with other NTT-PHI groups, Another collaboration inside NTT-PHI regards the quantum hall effects in a rapidly rotating polarity and condensates. And this work is mainly driven by two people, a Michael Fraser and Yoshihisa Yamamoto. They are the main driving forces of this project and this has been a great fun. We're also interacting inside the NTT-PHI environment with the groups of marandI Caltech, like McMahon Cornell, Oliver MIT, and as I mentioned before, Fraser Yamamoto NTT and others at NTT-PHI are also very welcome to interact with us. NTT-PHI is interested in various topics including how to use neural networks to solve computationally difficult and important problems. Let us now look at one example of using neural networks to study computationally difficult and hard problems. Everything we'll be talking today is mostly working progress to be extended and improve in the future. So the first example I would like to discuss is topological quantum phase transition retrieved through manifold learning, which is a variety of version of machine learning. This work is done in collaboration with Che, Gneiting and Liu all members of the group. preprint is available in the archive. Some groups are studying a quantum enhanced machine learning where machine learning is supposed to be used in actual quantum computers to use exponential speed-up and using quantum error correction we're not working on these kind of things we're doing something different. We're studying how to apply machine learning applied to quantum problems. For example how to identify quantum phases and phase transitions. We shall be talking about right now. How to achieve, how to perform quantum state tomography in a more efficient manner. That's another work of ours which I'll be showing later on. And how to assist the experimental data analysis which is a separate project which we recently published. But I will not discuss today because the experiments can produce massive amounts of data and machine learning can help to understand these huge tsunami of data provided by these experiments. Machine learning can be either supervised or unsupervised. Supervised is requires human labeled data. So we have here the blue dots have a label. The red dots have a different label. And the question is the new data corresponds to either the blue category or the red category. And many of these problems in machine learning they use the example of identifying cats and dogs but this is typical example. However, there are the cases which are also provides with there are no labels. So you're looking at the cluster structure and you need to define a metric, a distance between the different points to be able to correlate them together to create these clusters. And you can manifold learning is ideally suited to look at problems we just did our non-linearities and unsupervised. Once you're using the principle component analysis along this green axis here which are the principal axis here. You can actually identify a simple structure with linear projection when you increase the axis here, you get the red dots in one area, and the blue dots down here. But in general you could get red green, yellow, blue dots in a complicated manner and the correlations are better seen when you do an nonlinear embedding. And in unsupervised learning the colors represent similarities are not labels because there are no prior labels here. So we are interested on using machine learning to identify topological quantum phases. And this requires looking at the actual phases and their boundaries. And you start from a set of Hamiltonians or wave functions. And recall that this is difficult to do because there is no symmetry breaking, there is no local order parameters and in complicated cases you can not compute the topological properties analytically and numerically is very hard. So therefore machine learning is enriching the toolbox for studying topological quantum phase transitions. And before our work, there were quite a few groups looking at supervised machine learning. The shortcomings that you need to have prior knowledge of the system and the data must be labeled for each phase. This is needed in order to train the neural networks . More recently in the past few years, there has been increased push on looking at all supervised and Nonlinear embeddings. One of the shortcomings we have seen is that they all use the Euclidean distance which is a natural way to construct the similarity matrix. But we have proven that it is suboptimal. It is not the optimal way to look at distance. The Chebyshev distances provides better performance. So therefore the difficulty here is how to detect topological quantifies transition is a challenge because there is no local order parameters. Few years ago we thought well, three or so years ago machine learning may provide effective methods for identifying topological Features needed in the past few years. The past two years several groups are moving this direction. And we have shown that one type of machine learning called manifold learning can successfully retrieve topological quantum phase transitions in momentum and real spaces. We have also Shown that if you use the Chebyshev distance between data points are supposed to Euclidean distance, you sharpen the characteristic features of these topological quantum phases in momentum space and the afterwards we do so-called diffusion map, Isometric map can be applied to implement the dimensionality reduction and to learn about these phases and phase transition in an unsupervised manner. So this is a summary of this work on how to characterize and study topological phases. And the example we used is to look at the canonical famous models like the SSH model, the QWZ model, the quenched SSH model. We look at this momentous space and the real space, and we found that the metal works very well in all of these models. And moreover provides a implications and demonstrations for learning also in real space where the topological invariants could be either or known or hard to compute. So it provides insight on both momentum space and real space and its the capability of manifold learning is very good especially when you have the suitable metric in exploring topological quantum phase transition. So this is one area we would like to keep working on topological faces and how to detect them. Of course there are other problems where neural networks can be useful to solve computationally hard and important problems in quantum physics. And one of them is quantum state tomography which is important to evaluate the quality of state production experiments. The problem is quantum state tomography scales really bad. It is impossible to perform it for six and a half 20 qubits. If you have 2000 or more forget it, it's not going to work. So now we're seeing a very important process which is one here tomography which cannot be done because there is a computationally hard bottleneck. So machine learning is designed to efficiently handle big data. So the question we're asking a few years ago is chemistry learning help us to solve this bottleneck which is quantum state tomography. And this is a project called Eigenstate extraction with neural network tomography with a student Melkani , research scientists of the group Clemens Gneiting and I'll be brief in summarizing this now. The specific machine learning paradigm is the standard artificial neural networks. They have been recently shown in the past couple of years to be successful for tomography of pure States. Our approach will be to carry this over to mixed States. And this is done by successively reconstructing the eigenStates or the mixed states. So it is an iterative procedure where you can slowly slowly get into the desired target state. If you wish to see more details, this has been recently published in phys rev A and has been selected as a editor suggestion. I mean like some of the referees liked it. So tomography is very hard to do but it's important and machine learning can help us to do that using neural networks and these to achieve mixed state tomography using an iterative eigenstate reconstruction. So why it is so challenging? Because you're trying to reconstruct the quantum States from measurements. You have a single qubit, you have a few Pauli matrices there are very few measurements to make when you have N qubits then the N appears in the exponent. So the number of measurements grows exponentially and this exponential scaling makes the computation to be very difficult. It's prohibitively expensive for large system sizes. So this is the bottleneck is these exponential dependence on the number of qubits. So by the time you get to 20 or 24 it is impossible. It gets even worst. Experimental data is noisy and therefore you need to consider maximum-likelihood estimation in order to reconstruct the quantum state that kind of fits the measurements best. And again these are expensive. There was a seminal work sometime ago on ion-traps. The post-processing for eight qubits took them an entire week. There were different ideas proposed regarding compressed sensing to reduce measurements, linear regression, et cetera. But they all have problems and you quickly hit a wall. There's no way to avoid it. Indeed the initial estimate is that to do tomography for 14 qubits state, you will take centuries and you cannot support a graduate student for a century because you need to pay your retirement benefits and it is simply complicated. So therefore a team here sometime ago we're looking at the question of how to do a full reconstruction of 14-qubit States with in four hours. Actually it was three point three hours Though sometime ago and many experimental groups were telling us that was very popular paper to read and study because they wanted to do fast quantum state tomography. They could not support the student for one or two centuries. They wanted to get the results quickly. And then because we need to get these density matrices and then they need to do these measurements here. But we have N qubits the number of expectation values go like four to the N to the Pauli matrices becomes much bigger. A maximum likelihood makes it even more time consuming. And this is the paper by the group in Inns brook, where they go this one week post-processing and they will speed-up done by different groups and hours. Also how to do 14 qubit tomography in four hours, using linear regression. But the next question is can machine learning help with quantum state tomography? Can allow us to give us the tools to do the next step to improve it even further. And then the standard one is this one here. Therefore for neural networks there are some inputs here, X1, X2 X3. There are some weighting factors when you get an output function PHI we just call Nonlinear activation function that could be heavy side Sigmon piecewise, linear logistic hyperbolic. And this creates a decision boundary and input space where you get let's say the red one, the red dots on the left and the blue dots on the right. Some separation between them. And you could have either two layers or three layers or any number layers can do either shallow or deep. This cannot allow you to approximate any continuous function. You can train data via some cost function minimization. And then there are different varieties of neural nets. We're looking at some sequel restricted Boltzmann machine. Restricted means that the input layer speeds are not talking to each other. The output layers means are not talking to each other. And we got reasonably good results with the input layer, output layer, no hidden layer and the probability of finding a spin configuration called the Boltzmann factor. So we try to leverage Pure-state tomography for mixed-state tomography. By doing an iterative process where you start here. So there are the mixed States in the blue area the pure States boundary here. And then the initial state is here with the iterative process you get closer and closer to the actual mixed state. And then eventually once you get here, you do the final jump inside. So you're looking at a dominant eigenstate which is closest pure state and then computer some measurements and then do an iterative algorithm that to make you approach this desire state. And after you do that then you can essentially compare results with some data. We got some data for four to eight trapped-ion qubits approximate W States were produced and they were looking at let's say the dominant eigenstate is reliably recorded for any equal four, five six, seven, eight for the ion-state, for the eigenvalues we're still working because we're getting some results which are not as accurate as we would like to. So this is still work in progress, but for the States is working really well. So there is some cost scaling which is beneficial, goes like NR as opposed to N squared. And then the most relevant information on the quality of the state production is retrieved directly. This works for flexible rank. And so it is possible to extract the ion-state within network tomography. It is cost-effective and scalable and delivers the most relevant information about state generation. And it's an interesting and viable use case for machine learning in quantum physics. We're also now more recently working on how to do quantum state tomography using Conditional Generative Adversarial Networks. Usually the masters student are analyzed in PhD and then two former postdocs. So this CGANs refers to this Conditional Generative Adversarial Networks. In this framework you have two neural networks which are essentially having a dual, they're competing with each other. And one of them is called generator another one is called discriminator. And there they're learning multi-modal models from the data. And then we improved these by adding a cost of neural network layers that enable the conversion of outputs from any standard neural network into physical density matrix. So therefore to reconstruct the density matrix, the generator layer and the discriminator networks So the two networks, they must train each other on data using standard gradient-based methods. So we demonstrate that our quantum state tomography and the adversarial network can reconstruct the optical quantum state with very high fidelity which is orders of magnitude faster and from less data than a standard maximum likelihood metals. So we're excited about this. We also show that this quantum state tomography with these adversarial networks can reconstruct a quantum state in a single evolution of the generator network. If it has been pre-trained on similar quantum States. so requires some additional training. And all of these is still work in progress where some preliminary results written up but we're continuing. And I would like to thank all of you for attending this talk. And thanks again for the invitation.

>>From the cube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cute conversation. Welcome to this cube conversation. I'm Lisa Martin pleased to be joined once again by the co CEO of mem sequel, Raj Verma, Raj, welcome back to the program. >>Thank you very much, Lisa. Great to see you as always. >>It's great to see you as well. I always enjoy our conversations. So why don't you start off because something that's been in the news the last couple of months besides COVID is one of your competitors, snowflake confidentially filed IPO documents with the sec a couple months ago. Just wanted to get your perspective on from a market standpoint. What does that signify? >>Yeah. Firstly, congratulations to the snowflake team. Uh, you know, I've, I have a bunch of friends there, you know, John McMahon, my explosives on the board. And I remember having a conversation with him about seven years ago and it was just starting off and I'm just so glad for him and Bob Mobileye. And, and as I said, a bunch of my friends who are there, um, they're executed brilliantly and, uh, I'm thrilled for that. So, um, we are hearing as to what the outcomes are likely to be. And, uh, it just seems like, uh, you know, it's going to be a great help. Um, and I think what it signifies is firstly, if you have a bit technology and if you execute well, good things happen and there's enough room for innovation here. So that is one, the second aspect is I think, and I think more importantly, what it signifies is a change of thought in the database market. >>If you really see, um, and know if my memory serves me right in the last two decades or probably two and a half buckets, we just had one company go public in the database space and that was Mongo. And, um, and that was in, I think October, 2017 and then, uh, two and a half years. So three years we've seen on other ones and uh, from the industry that we know, um, you know, there are going to be a couple that are going to go out in the next 18 months, 24 months as well. So the fact is that we had a, the iron grip on the database market for almost, you know, more than two decades. It was Oracle, IBM that a bit of Sybase and SAP HANA. And now there are a bunch of companies which are helping solve the problems of tomorrow with the technology of the month. >>And, uh, and that is, um, that is snowflake is a primary example of that. Um, so that's a, that's good change. God is good. I do think the incumbents are gonna find it harder and harder going forward. And also if you really see the evolution of the database market, the first sort of workloads that moved to the cloud with the developer workloads and the big benefactor that that was the no secret movement and one company that executed in my opinion, the best was Mongol. And they were the big benefactor of that, that sort of movement to the cloud. The second was the very large, but Moisey database data warehouse market, and a big benefactor of that has been snowflake big queries, the other one as well. However, the biggest set of tsunami of data that's we are seeing move to the cloud is the operational data, which is the marriage of historical data with real time data to give you real time insights as, or what we call the now are now. >>And that's going to be much, much bigger than, uh, than both the, you know, sequel or the developer data movement and the data warehouse. And we hope to be a benefactor of that. And then the shake up that happens in the database market and the change that's happening there, isn't a vendor take on market anymore, and that's good because you don't then have the stranglehold that Oracle had and you know, some of the ways that are treated as customers and help them to run some, et cetera, um, yeah. And giving customers choice so that they can choose what's best for the business is going to be, it's going to be great. And me are going to see seven to 10 really good database companies in large, in the next decade. And we surely hope them secret as one of them of, we definitely have the, have the potential to be one of them. >>You have the market, we have the product, we have the customers. So, you know, as I tell my team, it's up to us as to what we make of it. And, um, you know, we don't worry that much about competition. You did mention snowflake being advantage station. We, yeah, sure. You know, we do compete on certain opportunities. However, their value proposition is a little more single-threaded than ours. So they are more than the Datavail house space are. Our vision of the board is that, uh, you know, you should have a single store for data, whether it's database house, whether it's developer data or whether it's operational data or DP data. And, uh, you know, watch this space from orders. We make somebody exciting announcements. >>So dig into that a little bit more because some of the news and the commentary Raj in the last, maybe six weeks since the snowflake, um, IPO confidential information was released was, is the enterprise data warehouse dead. And you just had a couple of interesting things we're talking about now, we're seeing this momentum, huge second database to go public in two and a half bigots. That's huge, but that's also signifying to a point you made earlier. There's, there's a shift. So memes SQL isn't, we're not talking about an EDW. We're talking about operational real time. How do you see that if you're not looking in the rear view mirror, those competitors, how do you see that market and the opportunities? >>Yeah, I, I don't think the data warehouse market is dead at thought. I think the very fact that, you know, smoke makers going out at whatever valuation they go out, which is, you know, tens of billions of dollars is, um, is a testimony to the fact that, you know, it's a fancy ad master. This is what it is. I mean, data warehouses have existed for decades and, uh, there is a better way of doing it. So it's a fancy of mousetrap and, and that's great. I mean, that's way to money and it's clearly been demonstrated. Now what we are saying is that I think that is a better way to manage the organization's data rather than having them categorized in buckets of, you know, data warehouse, data developer, data DP, or transactional data, you know, uh, analytical data. Is there a way to imagine the future where there is one single database that you can quit eat, or data warehouse workloads for operational workloads, for OLTB work acknowledge and gain insights. And that's not a fancier mousetrap that is a data strategy reimagine. And, uh, and that's our mission. That's our purpose in life right now and are very excited about it's going to be hard. It's not, it's not a given it's a hard problem to solve. Otherwise, if you can solve it before we have the, uh, we have the goods to deliver and the talent, the deliberate, and, um, we are, we are trying it out with some very, very marquee customers. So we've been very excited about, >>Well, changing of the guard, as you mentioned, is hard. The opposite is easy, the opposite, you know, ignoring and not wanting to get out of that comfort zone. That's taken the easy route in my opinion. So it seems like we've got in the market, this, this significant changing of the guard, not just in, you know, what some of your competition is doing, but also from a customer's perspective, how do you help customers, especially institutions that have been around for decades and decades and decades pivot quickly so that the changing of the guard doesn't wipe them out. >>Yeah. Um, I actually think slightly differently. I think changing of the guard, um, wiping out a customer is if they stick or are resistant to the fact that there is a change of God, you know, and if they, if they hold on to, as we said in our previous conversation, if you stick onto the decisions of yesterday, you will not see the Sundays of tomorrow. So I do think that, uh, you know, change, you have a, God is a, is a symbolism, not even a symbolism as a statement to our customers to say, there is a better way of doing, uh, what you are doing to solve tomorrow's problem. And then doesn't have to be the Oracles and the BB tools and the psychosis of the world. So that's, that's one aspect of it. The second thing is, as I've always said, you're not really that obsessed about, uh, competition. >>The competition will do what they do. Uh, we are really very focused on having an impact in the shortest period of time on our customers and, uh, hopefully a positive impact. And if you can't do it, then, you know, I've had conversations with a few of them saying, maybe be not the company for you. Uh, it's not as if I have to sort of, software's a good one. I supply to the successful customers in the bag to do the unsuccessful with customers. The fact is that, you know, in certain, certain places there isn't an organizational alignment and you don't succeed. However, we do have young, we have in the last 14 months or so made tremendous investments into really ease of use of flexibility of architecture, which is hybrid and tactile, and that shrinking the total time to value for our customers. Because if I, if I believe you, if you do these three things, you will have an impact, a positive impact on the customer, in the sharpest, uh, amount of time and your Lindy or yourself. And I think that is more important than worrying needlessly about competition. And then the competition will do what they do. But if you keep your customers happy by having a positive impact, um, successes, only amount of time, >>Customers and employees are essential to that. But I like that you talked about customer obsession because you see it all over the place. Many people use it as descriptors of themselves and their LinkedIn profiles, for example, but for it actually to be meaningful, you talked about the whole objective is to make an impact for your customers. How do you define that? So that it's not just, I don't want to say marketing term, but something that everyone says they're customer obsessed showing it right within the pudding. >>It's easy to say we are customer obsessed. I mean, this organization is going to say we don't care about our customer. So, you know, of course we all want our customers to be successful. How do you, that's easy, you know, having a cultural value that we put our customers first is, was easy, but we didn't choose to do that. What we said is how do you have an impact on your customer in the shortest amount of time, right? That is, that is what you have. I'm sequel and Lee have now designed every process in mem sequel to align with that word. If, if that is a decision that we have to make a B essentially lenses through the fact of what is in the best interest of our customer and what will get us to have an impact, a positive impact on the customer in the shortest amount of time, that is a decision, which is a buy decision for us to make. >>A lot of times it's more expensive. It's a, a lot duffel. It stresses the, um, the, the, the organization, um, and the people in it. But that's, uh, that's what you have to do if you are. Um, if you are, you know, as, as they say, customer obsessed, um, it is, it's just a term which is easy to use, but very difficult to put here too. And we want to be a tactic. It right to be, we are going to continue to learn. It's a, it's not a destination, it's a journey. And we continue to take decisions and refine our processes do, as I said, huh, impact on our customers in the shortest amount of time. Now, obsessiveness, a lot of times is seen as a negative in the current society that we live in. And there's a reason for that because the, they view view obsession, but I view obsession and aggression is that is a punishing expression, which is really akin to just being cruel, you know, leading by fear and all the rest of it, which is as no place in any organization. >>And I actually think that in society at large, nothing, I believe that doesn't have any place in society. And then there's something which I dumb as instrumentalists, which is, this is where we were. This is where we are. This is where we are going and how do we track our progress on a daily, weekly, monthly basis? And if we, aren't sort of getting to that level that we believe we should get to, if our customers, aren't seeing the value of dramas in the shortest amount of time, what is it that we need to do better? Um, is that obsession, our instrumental aggression is, is, is what we are all about. And that brings with it a level of intensity, which is not what everyone, but then when you are, you know, challenging the institutions which have, uh, you know, the also has to speak for naked, it's gonna take a Herculean effort to ask them. And, uh, you know, the, the basically believed that instrumental aggression in terms of the, uh, you know, having an impact on customer in the shop to smile at time is gonna get us there. And a, and B are glad to have people who actually believe in that. And, uh, and that's why we've made tremendous progress over the course of last, uh, two years. >>So instrumental aggression. Interesting. How you talked about that, it's a provocative statement, but the way that you talk about it almost seems it's a prescriptive, very strategic, well thought out type of moving the business forward, busting through the old guard. Cause let's face it, you know, the big guys, the Oracles they're there, they're not easy for customers to rip and replace, but instrumental aggression seems to kind of go hand in hand with the changing of the guard. You've got to embrace one to be able to deliver the other, right. >>Yeah. So ducks, I think even a fever inventing something new. Um, I mean, yeah, it just requires instrumental aggression, I believe is a, uh, uh, anchor core to most successful organizations, whether in IP or anywhere else. That is a, that is a site to that obsession. And not, I'm not talking about instrumental aggression here, but I'm really talking about the obsession to succeed, uh, which, uh, you know, gave rise to what I think someone called us brilliant jerks and all the rest of it, because that is the sort of negative side of off obsession. And I think the challenge of leadership in our times is how do you foster the positivity of obsession, which needs to change a garden? And that's the instrumental aggression as a, as a tool to, to go there. And how do you prevent the negative side of it, which says that the end justifies the means and, and that's just not true. >>Uh, there is, there is something that's right, and there's something that's wrong. And, uh, and if that is made very clear that the end does not justify the meanings, it creates a lot of trust between, um, Austin, our customers, also not employees. And when their inherent trust, um, happens, then you foster, as I said, the positive side of obsession and, um, get away from the negative side of obsession that you've seen in certain very, very large companies. Now, the one thing that instrumental aggression and obsession brings to a company is that, uh, it makes a lot of people uncomfortable, and this is what I continue to tell. Um, our, our employees and my audience is, um, you know, be comfortable being uncomfortable because what you're trying to do is odd. And it's going to take a, as I say, a Herculean effort. So let's, uh, let's be comfortable being uncomfortable, uh, and have fun doing it. If there's, uh, how many people get a chance to change, uh, industry, which was dominated by a few bears and have such a positive impact, not only on our estimates, but society at large. And, uh, I think it's a privilege. Pressure is a privilege. And, uh, I'm grateful for the opportunity that's been afforded to me and to my colleagues. And, uh, >>It's a great way. Sorry. That's a great way of looking at it. Pressure is a privilege. If you think about, I love what you said, I always say, get, you know, get comfortably uncomfortable. It is a heart in any aspect, whether it's your workouts or your discipline, you know, working from home, it's a hard thing to do to your point. There's a lot of positivity that can come from it. If we think of what's happening this week alone and the U S political climate changing of the old guard, we've got Kamala Harris as our first female VP nominee and how many years, but also from a diversity angle, from a women leadership perspective, blowing the door wide open. >>It's great to see that, um, you know, we have someone that my daughter's going to look up to and say that, uh, you know, yes, there is, there is a place for us in society and we can have a meaningful contribution to society. So I actually think that San Antonio versus nomination is, um, you know, it's a simple ism of change of God, for sure. Um, I have no political agendas, um, at all. Then you can see how it pans out in November, but the one thing is for sure, but it's going to make a lot of people uncomfortable, a change of God, or this makes a lot of people. And, and, uh, and you know, I was reflecting back on something else and in everything that I've actually achieved, which is, is something I'm proud of. I had to go through a zone, but I was extremely uncomfortable. >>Uh, Gould only happens when you have uncomfortable, um, girl to happens in your conference room. And, um, whether it's, um, you know, running them sequel, uh, or are having a society change, uh, if you stick to your comfort zone, you stick to your prejudices and viruses because it's just comfortable there, there's a, uh, wanting to be awkward. And, uh, and, and I think that that's that essential change of God. As I said, at the cost of repeating myself will make a lot of people uncomfortable, but I honestly believe will move the society forward. And, uh, yeah, I, um, I couldn't be more proud of, uh, having a California San Diego would be nominated and it's a, she brings diversity multicultural. And what I loved about it was, you know, we talk about culture and all the rest of it. And she, she was talking about how our parents who were both, uh, uh, at the Berkeley when she was growing up, we were picking up from and she be, you know, in our, in our prime going to protests and Valley. >>And so it was just, uh, it was ingrained in her to be able to challenge the status school and move the society forward. And, uh, you know, she was comfortable being uncomfortable when she was in that, you know, added that. And that's good. Maybe not. I think we sort of, uh, yeah, I, yeah, let's see, let's see what November brings to us, but, um, I think just a nomination has, uh, exchanged a lot of things and, uh, if it's not this time, it can be the next time, but at the time off the bat, but you're going to have a woman by woman president in my lifetime. Um, that's um, I minced about them, uh, and that's just great. >>Well, I should hope so too. And there's so many, I know we've got to wrap here, but so many different data points that show that that technology company actually, companies, excuse me, with women in leadership position are significantly 10, 20% more profitable. So the changing of the guard is hard as you said, but it's time to get uncomfortable. And this is a great example of that as well as the culture that you have at mem sequel Raja. It's always a pleasure and a philosophical time talking with you. I thank you for joining me on the cube today. >>Thank you me since I'm just stay safe, though. >>You as well for my guest, Raj Burma, I'm Lisa Martin. Thank you for watching this cube conversation.

>>Fly from San Francisco. It's the cube covering RSA conference 2020 San Francisco brought to you by Silicon angled medias >>live in. Welcome to the cube coverage here in San Francisco at Moscone hall for RSA 2020 I'm John furrier, host of the cube. We're here breaking down all the actions in cyber security. I'll say three days of wall-to-wall cube coverage. You got two great guests here, experts in the cybersecurity enterprise security space. Over 25 years. We've got two gurus and experts. We've got Bob Mindell, executive vice president of North America cyber practice for cap Gemini and Joe McMahon, head of North America cyber strategy, even a practitioner in the intelligence community. Langley, you've been in the business for 25 years. You've seen the waves guys, welcome to the cube. Thank you John. Thanks for having us. So first let's just take a step back. A cyber certainly on the number one agenda kind of already kind of broken out of it in terms of status, board level conversation, every CSO, risk management and a lot of moving parts. >>Now, cyber is not just a segment in the industry. It is the industry. Bob, this is a big part of business challenge today. What's your view? What was going on? So John has a great point. It's actually a business challenge and that's one of the reasons why it's now the top challenge. It's been a tech challenge for a long time. It wasn't always a business challenge for you as was still considered an it challenge and once it started impacting business and got into a board level discussion, it's now top of mind as a business challenge and how it can really impact the business continuity. Joe is talking before we came on camera about you know CEOs can have good days here and there and bad days then but sees us all have bad days all the time because there's so much, it's so hard. You're on the operations side. >>You see a day to day in the trenches as well as the strategy. This is really an operations operationalizing model. As new technology comes out, the challenge is operationalizing them for not only a business benefit but business risk management. It's like changing an airplane engine out at 35,000 feet. It's really hard. What are you seeing as the core challenge? This is not easy. It's a really complex industry. I mean, you take the word cybersecurity, right? Ready? Cybersecurity conference. I see technology, I see a multitude of different challenges that are trying to be solved. It means something different to everybody, and that's part of the problem is it's a really broad ecosystem that we're in. If you meet one person that says, I know all of cyber, they're lying, right? It's just like saying, I know active directory and GRC and I know DNS and I know how to, how to code, right? >>Those people don't exist and cyber is a little bit the same way. So for me, it's just recognizing the intricacies. It's figuring out the complexities, how people processing technology really fit together and it's an operation. It is an ongoing, and during operation, this isn't a program that you can run. You run it for a year, you install and you're done. There's ebbs and flows. You talked about the CISOs and the bad days. There's wins and there's losses. Yeah. And I think part of that is just having the conversation with businesses. Just like in it, you have bad days and good days wins and losses. It's the same thing in cybersecurity and we've got to set that expectation. Yeah, you didn't bring up a good point. I've been saying this on the cube and we've been having conversations around this. It used to be security as part of it, right? >>But now that it's part of the business, the things that you're mentioning around people, process, technology, the class, that kind of transformational formula, it is business issues, organizational behavior. Not everyone's an expert specialism versus generalists. So this is like not just a secure thing, it's the business model of a company is changing. So that's clear. There's no doubt. And then you've got the completion of the cloud coming, public cloud, hybrid multi-cloud. Bob, this is a number one architectural challenge. So outside of the blocking and tackling basics, right, there's now the future business is at risk. What does cap Gemini do? And because you guys are well known, great brand, helping companies be successful, how do you guys go to customers and say, Hey, here's what you do. What's the, what's the cap Gemini story? >>So the cat termini stories is really about increasing your cybersecurity maturity, right? As Joe said, starting out at the basics. If you look at a lot of the breaches that have occurred today have occurred because we got away from the basics and the fundamentals, right? Shiny new ball syndrome. Really. Exactly exasperates that getting away from the basics. So the technology is an enabler, but it's not the be all and end all right, go into the cloud is absolutely a major issue. That's increasing the perimeter, right? We've gone through multiple ways as we talked about, right? So now cloud is is another way, cloud, mobile, social. How do you deal with those from on prem, off prem. But ultimately it's about increasing your cyber cyber security maturity and using the cloud as just increasing the perimeter, right? So you need to, you really need to understand, you have your first line defense and then your maturity is in place. Whether the data resides in your organization, in the cloud, on a mobile device, in a social media, you're responsible for it all. And if you don't have the basics, then you're, you're really, and you guys bring a playbook, is that what you guys come in and do? Correct. Correct. Right. So our goal is to coordinate people, process technology and leverage playbooks, leverage the run books that we had been using for many years. >>I want to get down to you on this one because of what happens when you take that to the, into the practitioner mode or at implementation. Customers want the best technology possible. They go for the shiny new choice. Bob just laid out. There's also risks too because it may or may not be big. So you've got to balance out. I got to get an edge technically because the perimeters becoming huge surface area now or some say has gone. Now you've got edge, just all one big exposed environment, surface area for vulnerabilities is massive. So I need better tech. How do you balance and obtain the best tech and making sure it works and it's in production and secure. So there's a couple of things, right, and this is not, it's not just our, and you'll hear it from other people that have been around a long time, but a lot of organizations that we see have built themselves so that their cybersecurity organization is supporting all these tools that we see. >>That's the wrong way to do it. The tools should support the mission of the organization, right? If my mission is to defend my enterprise, there are certain things that I need to do, right? There's questions I need to be able to ask and get answers to. There's data I need visibility into. There's protections and controls I need to be able to implement. If I can lay those out in some coordinated strategic fashion and say, here's all the things I'm trying to accomplish, here's who's going to do it. Here's my really good team, here's my skilled resources, here's my workflows, my processes, all that type of stuff. Then I can go find the right technology to put into that. And I can actually measure if that technology is effective in supporting my mission. But too often we start with the technology and then we hammer against it and we run into CISOs and they say, I bought all this stuff and it's not working and come hell yeah. >>And that's backing into it the wrong. So I've heard from CSOs, I'd like they buying all these tools. It's like a tool shed. Don't be the fool with the wrong tool as they I say. But that brings up the question of, okay, as you guys go to customers, what are some of the main pain points or issues that they're trying to overcome that that are opportunities that you guys are helping with? Uh, on the business side and on the technical side, what are some of the things? So on the business side, you know, one is depending on their level of maturity and the maturity of the organization and the board of directors and their belief in, in how they need to help fund this. We can start there. We can start by helping draw out the threat landscape within that organization where they are maturity-wise and where they need to go and help them craft that message to the board of directors and get executive sponsorship from the board down in order to take them from baby, a very immature organization or you know, a reactive organization to an adaptive organization, right. >>And really become defenders. So from a business perspective, we can help them there. From the technology perspective, Joe, uh, you know, or an implementation perspective. I think, you know, it's been a really interesting road like being in this a long time, you know, late two thousands when nation States were first really starting to become a thing. All the industries we were talking to, every customer is like, I want to be the best in my industry. I want to be the shining example. And boards in leadership were throwing money at it and everybody was on this really aggressive path to get there. The conversation is shifted a little bit with a lot of the leadership we talked to. It's, I just want to be good enough, maybe a little bit better than good enough, but my, my objective anymore is it to leave the industry. Cause that's really expensive and there's only one of those. >>My objective is to complete my mission maybe a little bit above and beyond, but I need the right size and right. So we spent a lot of time helping organizations, I would say optimize, right? It's what is the right level of people, what is the right amount of resources, what's the right spend, what's the right investment, the right allocation of technology and mix of everything, right? And sometimes it's finding the right partner. Sometimes it's doing certain things in house. It's, there's no one way to solve this problem, but you've got to go look at the business challenges. Look at the operational realities of the customer, their budgets, all those, their geographies mattered, right? Some places it's easy to hire talent. Some places it's not so easy to hire talent. And that's a good point, right? Some organizations, >>they just need to understand what does good look like and we can, we have so many years of experience. We have so many customers use skates is we've been there and we've done that. We can bring the band and show them this is what good looks like and this is sustainable >>of what good looks like. I want to get your reactions to, I was talking to Keith Alexander, general Keith Alexander, a former cyber command had last night and we were talking about officers, his defense and that kind of reaction. How the Sony hack was was just was just, they just went after him as an example. Everyone knows about that hack, but he really was getting at the idea of human efficiency, the human equation, which is if you have someone working on something that here, but their counterpart might be working on it maybe from a different company or in the same company, they're redundant. So there's a lot of burnout, a lot of people putting out fires. So reactive is clearly, I see as a big trend that the conversation's shifting towards let's be proactive, let's get more efficient in the collaboration as well as the technology. What you, how do you guys react to that? What's your view on that statement? So >>people is the number one issue, in my opinion. In this space, there's a shortage of people. The people that are in it are working very long hours. They're burnt out. So we constantly need to be training and bringing more people into the industry. Then there's the scenario around information sharing, right? Threat information sharing, and then what levels are you comfortable with as an organization to share that information? How can you share best practices? So that's where the ice sacks come into play. That's also where us as a practitioner and we have communities, we have customers, we bring them together to really information, share, share, best practice. It's in all of our best interests. We all have the same goal and the goal is to protect our assets, especially in the United States. We have to protect our assets. So we need, the good thing is that it's a pretty open community in that regards and sharing the information, training people, getting people more mature in their people, process technology, how they can go execute it. >>Yeah. What's your take on the whole human equation piece? Right? So sharing day, you probably heard a word and the word goes back to where I came from, from my heritage as well, but I'm sure general Alexander used the word mission at some point, right? So to me, that's the single biggest rallying point for all of the people in this. If you're in this for the right reasons, it's because you care about the mission. The mission is to defend us. Stop the bad guys from doing days, right? Whether you're defending the government, whether you're defending a commercial enterprise, whether you're defending the general public, right? Whatever the case is, if you're concerned, you know, if you believe in the mission, if you're committed to the mission, that's where the energy comes from. You know, there's a lot of, there's a lot of talk about the skill gap and the talent gap and all of those types of things. >>To me, it's more of a mindset issue than anything. Right? The skill sets can be taught. They can be picked up over time. I was a philosophy major. All right? Somehow I ended up here. I have no idea how, um, but it's because I cared about the mission and everybody has a part to play. If you build that peer network, uh, both at an individual level and at an organizational and a company level, that's really important in this. Nobody's, nobody's an expert at everything. Like we said, you brought a philosophy. I think one of the things I have observed in interviewing and talking to people is that the world's changed so much that you almost need those fresh perspectives because the problems are new problems, statements, technology is just a part of the problem set back to the culture. The customer problem, Bob, is that they got to get all this work done. >>And so what are some of the use cases that you guys are working on that that is a low hanging fruit in the industry or our customer base? How do you guys engage with customers? So our target market is fortune 500 global 1000 so the biggest of the big enterprises in the world, right? And because of that, we've seen a lot of a complex environments, multinational companies as our customers. Right? We don't go at it from a pure vertical base scenario or a vertical base solution. We believe that horizontal cybersecurity can it be applied to most verticals. Right. And there's some tweaking along the way. Like in financial services, there's regulars and FFIC that you need to be sure you adapt to. But for the most part the fundamentals are applicable. All right. With that said, you know, large multinational manufacturing organization, right? They have a major challenge in that they have manufacturing sites all over the world. >>They building something that is, you know, unique. It has significant IP to it, but it's not secure. Historically they would have said, well, nobody's really gonna just deal steal what we do because it's really not differentiated in the world, but it is differentiated and it's a large corporation making a lot of money. Unfortunately ransomware, that'd be a photographer. Ransomware immediately, right? Like exact down their operations and their network, right? So their network goes down. They can have, they can, they can not have zero downtown and their manufacturing plants around the world. So for us, we're implementing solutions and it's an SLA for them is less than six seconds downtime by two that help secure these global manufacturing environment. That's classic naive when they are it. Oh wow. We've got to think about security on a much broader level. I guess the question I have for you guys, Joe, you talk about when do you guys get called in? >>I mean what's your main value proposition that you guys, cause you guys got a broad view of the industry, that expertise. Why do, why are customers calling you guys and what do you guys deliver? They need something that actually works, right? It's, it's you mentioned earlier, I think when we were talking how important experiences, right? And it's, Bob said it too, having been there, done that I think is really important. The fact that we're not chasing hype, we're not selling widgets. That we have an idea of what good looks like and we can help an organization kind of, you know, navigate that path to get there is really important. So, uh, you know, one of our other customers, large logistics company, been operating for a very long time. You know, very, very mature in terms of their, it operations, those types of things. But they've also grown through merger and acquisition. >>That's a challenge, uh, cause you're taking on somebody else's problem set and they just realize, simply put that their existing security operations wasn't meeting their needs. So we didn't come in and do anything fancy necessarily. It's put a strategic plan in place, figure out where they are today, what are the gaps, what do they need to do to overcome those gaps? Let's go look at their daily operations, their concept of operations, their mission, their vision, all of that stuff down to the individual analysts. Like we talked about the mindset and skillset. But then frankly it's putting in the hard work, right? And nobody wants to put in the heart. I don't want to say nobody wants to put in the hard work. That's fun. There's a lot of words that's gets done I guess by the questions that you guys getting called in on from CSOs chief and Mason security officers. >>Guess who calls you? So usually we're in talking to the Cisco, right? We're having the strategic level conversation with the Cisco because the Cisco either has come in new or has been there. They may have had a breach. Then whatever that compelling event may be, they've come to the realization that they're not where they need to be from a maturity perspective and their cyber defense needs revamping. So that's our opportunity for us to help them really increase the maturity and help them become defenders. Guys, great for the insight. Thanks for coming on the cube. Really appreciate you sharing the insights. Guys. Give a quick plug for what you guys are doing. Cap Gemini, you guys are growing. What do you guys look to do? What are some of the things that's going on? Give the company plug. Thanks Sean show. It's been a very interesting journey. >>You know this business started out from Lockheed Martin to Leidos cyber. We were acquired by cap Gemini a year ago last week. It's a very exciting time. We're growing the business significantly. We have huge growth targets for 2020 and beyond, right? We're now over 800 practitioners in North America, over 2,500 practitioners globally, and we believe that we have some very unique differentiated skill sets that can help large enterprises increase their maturity and capabilities plug there. Yeah, I mean, look, nothing makes us happier than getting wins when we're working with an organization and we get to watch a mid level analyst brief the so that they just found this particular attack and Oh by the way, because we're mature and we're effective, that we were able to stop it and prevent any impact to the company. That's what makes me proud. That's what makes it so it makes it fun. >>Final question. We got a lot of CSOs in our community. They're watching. What's the pitch to the CSO? Why, why you guys, we'd love to come in to understand what are their goals, how can we help them, but ultimately where do they believe they think they are and where do they need to go and we can help them walk that journey. Whether it's six months, a year, three years, five years. We can take them along that journey and increase the cyber defense maturity. Joe, speak to the CSO. What are they getting? They're getting confidence. They're getting execution. They're getting commitment to delivery. They're getting basically a, a partner in this whole engagement. We're not a vendor. We're not a service provider. We are a partner. A trusted partner. Yeah, partnerships is key. Building out in real time. A lot new threats. Got to be on offense and defense going on. A lot of new tech to deal with. I mean, it's a board level for a long time. Guys, thanks for coming on. Cap Gemini here inside the cube, bringing their practices, cybersecurity, years of experience with big growth targets. Check them out. I'm John with the cube. Thanks for watching.