hi everybody this is dave vellante and this is day two of the cube's coverage of falcon 2022 we're live from the aria in las vegas everybody was out last night at the brooklyn bowl awesome band customers were dancing a lot of fun a lot of business going on here todd crosley's here he's to my left he's the senior director of cloud partnerships at crowdstrike and patrick mcdowell is the global technical lead for security partners at aws these guys have been partnering for a long time and we're going to dig into that partnership gents welcome to the cube thanks for having us thanks happy birthday you're very welcome todd talk about the the history of the relationship you guys are kind of bet business on each other but take us back sure thing so you know yesterday or the day before the company turned 11 years old or so i think george talked a lot about that the other day but uh we've actually been working closely with the amazon team for more than five years at this point and it's really evolved into a strategic collaboration really so uh from an executive on down into field alignment channel alignment uh the marketing team and and the build team where we we work with patrick and his extended team on different service integrations and different uh you know effectively positive security outcomes for the customers together i mean patrick if you think about the history of aws it's like you guys realized you had lightning in a bottle and then also realized wow and ecosystem play is the way to go and when you go to re invent it's palpable the the ecosystem innovation and the the flywheel effect that you've created but what's aws's perspective on the partnership with crowdstrike yeah it's essential to us and our customers right so we've been doing deep integrations probably since i think the first big one of crowdstrike was with guard duty amazon guard duty which is our uh easy to use threat detection service in aws one click on and their threat intelligence actually build is built directly into that service so an aws customer turns on guard duty it's automatically uh being uh enhanced and enriched with falcon x threat intelligence uh by default yeah so the cloud has become the first line of defense for a lot of the csos that i talk to you know everybody's cloud first cloud first and it's like okay that's awesome because cloud has really good security but then it's okay but if there's some differences i got there's a shared security model that i have to understand and and so when you guys talk to customers i know it's you know one of the leadership principles is you got to be focused you know insanely focused on customers crowdstrike very customer focused as well that's how you sort of created this company that is doing such innovative things what are customers telling you um about how they want you to work together what kind of feedback are you getting any other examples that you might have in the future yeah sure thing i'll go first so that well so they they depend on uh the like you said this shared security model but there's ample opportunity where vendors like crowdstrike and we've worked with patrick's team extensively to to pinpoint areas where we can provide so examples of that would be like on the in compute so like you recently released the graviton processors we've had a recent success with a customer where uh they've walked down their digital transformation journey they had they were looking to switch over to the graviton processors and we work closely with patrick's team to say okay we're going to certify our sensor uh on that particular area of compute so the customer continue to enjoy crowdstrike in our single-platform cloud-first native platform to say okay you've got skill sets on the on-prem environment your endpoint environment and good news you're switching to graviton no problem we still support that and we've been able to do that by working closely with each other inclusive not just the architects but the product teams work closely together as well yeah in this customer case um you know uh crowdstrike already supported for amazon linux but this customer a very large customer of ours need to move 10 000 ec2 instances to graviton on red hat linux not amazon linux so we got crowdstrike engineering our engineering our architects and we were able to get this customer red hat support for graviton within two months right in production ready to go and unblock this migration so i love the graviton example so what i always default to when somebody says oh we're cloud native i'd say are you running on graviton uh because because graviton is is is uh amazon's custom silicon that complements what you're doing with intel what you're doing with amd and they're all kinds of different instant types but it's based on an arm system and it's delivering new levels of performance and and an energy reduction if i can use that term um and and it's on a new curve yeah and so tremendous cost savings as well right i think out of the box with no change in the application you're getting 20 and that's and i i don't even think you're really driving it as hard as you can is my assessment but you gotta be considerate of these days so but that's an example of of how you're using from a technology standpoint cloud native and then and then sort of partnering does this you know graviton one graviton true graviton three i'm sure there'll be graviton 10 someday no doubt i think it's a good example of us working closely together paying attention to the customer's needs and making sure they don't they don't miss a step and and still stop the breach and pay attention to their security needs so you're part of the apn the amazon partner network yep what do you got to do to be like certified at an elite level there you probably have to go through a lot of hoops and maybe you could describe what you guys do there and how you work together to ensure that a company is adequate and more than adequate for its customers yeah sure thing so we we've participated in and we're certified in for example the security competency area which elevates us amongst other security isvs we're one of the few that have that um we have the well we participate in the well architected program which means that we've demonstrated a common set of criteria and customer references i mean that's a example um another area where we've participated quite a bit is in in the land of digital supply chains notably aws marketplace where we've uh latched on to many of their features and capabilities and participated in strategic programs whether it be um you know including the channel partner or taking a look at traditional private offers or taking a look at like the looping in the entire ecosystem to make sure the customer gets what they need so how do you integrate with things like control tower where where are the seams and how do you make that as seamless as possible for customers or maybe you can explain what control power yeah so uh they have multiple integrations for control tower for their cspm horizon uh it automatically onboards new aws accounts so uh you know as you're vending accounts you're giving to more devops teams horizon is automatically deploying and being protected those accounts so it has those guard rails in place for customers in a nice easy to use deployment model that you don't have to think about right so control tower in general is uh it kind of gives customers guard rails an easy button if you're new to aws i'm migrating hey aws can you just tell me the best practices how should i set up my accounts i need a landing zone i'm doing migration so it's really like a wizard for getting started in aws and crowdstrike integrates that with falcon discover and as well as falcon horizon and your age so yeah you guys really don't compete um you know maybe there's some overlap overlap is better than than gaps but you know when you when you take something like you know network firewalls and things like that amazon brings that to the table and then crowdstrike will build on top of that is that correct yeah i'll take this one uh so george has said it crowdstrike is not a network security company right however they have an integration using their threat intelligence on on our amazon network firewall so aws amazon and crouchstrike coming together actually have a joint offering for customers in a space that crowdstrike has never been in before itself so i think that's very exciting so yeah yeah all those integrations that pat's talking about we've actually cataloged the whole thing on a github page where we find that's where customers go they took a look at the integration and the supporting documentation we're like okay yeah this makes sense this these two companies augment each other well and it turns out to be a good outcome and you check you'll take telemetry data from the aws cloud you can take it from you know any your agents can run anywhere right and then you bring that in to the or i guess you sort of you index it i in my term in in the aws cloud enables that because you've got virtually unlimited scaling capability and that's kind of where you guys started yeah cloud native dogma that's right yeah it's a competitive differentiator for us uh i we think it's nice we're a market leader in our space and amazon's a market leader in their space and and we've got a lot of synergy together where do you guys last question where do you guys respectively want to see the the relationship go if you had to put on your binoculars or even telescope where do you want to see this go well i think we're i think we're all in the business of accelerating positive security outcomes for the customer and the what we're doing is we're spending a lot of time educating our respective fields and respective customers to know that these these integrations do in fact exist uh they absolutely complement each other we were in a meeting uh you know maybe six ten months ago we're in a cio said i didn't know that the two that the two products work so well together speaking about the control tower and horizon particular example had i known that i would have bought it uh a lot quicker this is this is a great outcome and the fact that you're working with amazon together is a bit of a relief so that was nice yeah i'm gonna echo what george kirk said in his keynote yesterday that like security's a journey xdr is a journey and i think the work that we did on the open cyber security schema framework which is an open source common uh security language that all vendors can use including aws and crowdstrike i think that is where we're going to see uh the the industry rally around in the upcoming year there's so much security data there's a common uh now language that all products and clouds could talk to each other that's right tell tell me more about it ocsf is that right where did that come from and yeah so um it's it's a it's an open source framework and you know both crowdstrike aws and other uh you know players in the industry are like there's a common problem none of our products talk together it's all about customer benefit right so what can we do to democratize security data make things talk well play together everyone wants to do more analytics on lots of data lakes so this is where it's all coming together yeah better collaboration in industry obviously is is needed and then the other piece is education you guys both sort of refer to that that's what i when i come to conferences like this and reinforce as well as a lot of it i mean i remember the first reinforcement was like explaining the shared responsibility model now of course a lot of people understood it but a lot of people didn't when you fast forward to 2022 and reinvent it was a lot more focused on how to really exploit the capabilities that aws has and then here at crowdstrike it's like okay helping practitioners really understand how to take advantage of the full platform and and that's to your point patrick the journey all right guys hey we got to go thanks so much you for having us all right keep it right there fast and furious day two from crowdstrike's falcon 2022. you're watching thecube [Music] you

>>Hi everyone, This system A fellow from the University of Tokyo before I thought that would like to thank you she and all the stuff of entity for the invitation and the organization of this online meeting and also would like to say that it has been very exciting to see the growth of this new film lab. And I'm happy to share with you today or some of the recent works that have been done either by me or by character of Hong Kong Noise Group indicating the title of my talk is a neuro more fic in silica simulator for the commenters in machine. And here is the outline I would like to make the case that the simulation in digital Tektronix of the CME can be useful for the better understanding or improving its function principles by new job introducing some ideas from neural networks. This is what I will discuss in the first part and then I will show some proof of concept of the game in performance that can be obtained using dissimulation in the second part and the production of the performance that can be achieved using a very large chaos simulator in the third part and finally talk about future plans. So first, let me start by comparing recently proposed izing machines using this table there is adapted from a recent natural tronics paper from the Village Back hard People. And this comparison shows that there's always a trade off between energy efficiency, speed and scalability that depends on the physical implementation. So in red, here are the limitation of each of the servers hardware on, Interestingly, the F p G, a based systems such as a producer, digital, another uh Toshiba purification machine, or a recently proposed restricted Bozeman machine, FPD eight, by a group in Berkeley. They offer a good compromise between speed and scalability. And this is why, despite the unique advantage that some of these older hardware have trust as the currency proposition influx you beat or the energy efficiency off memory sisters uh P. J. O are still an attractive platform for building large theorizing machines in the near future. The reason for the good performance of Refugee A is not so much that they operate at the high frequency. No, there are particle in use, efficient, but rather that the physical wiring off its elements can be reconfigured in a way that limits the funding human bottleneck, larger, funny and phenols and the long propagation video information within the system in this respect, the f. D. A s. They are interesting from the perspective, off the physics off complex systems, but then the physics of the actions on the photos. So to put the performance of these various hardware and perspective, we can look at the competition of bringing the brain the brain complete, using billions of neurons using only 20 watts of power and operates. It's a very theoretically slow, if we can see. And so this impressive characteristic, they motivate us to try to investigate. What kind of new inspired principles be useful for designing better izing machines? The idea of this research project in the future collaboration it's to temporary alleviates the limitations that are intrinsic to the realization of an optical cortex in machine shown in the top panel here. By designing a large care simulator in silicone in the bottom here that can be used for suggesting the better organization principles of the CIA and this talk, I will talk about three neuro inspired principles that are the symmetry of connections, neural dynamics. Orphan, chaotic because of symmetry, is interconnectivity. The infrastructure. No neck talks are not composed of the reputation of always the same types of non environments of the neurons, but there is a local structure that is repeated. So here's a schematic of the micro column in the cortex. And lastly, the Iraqi co organization of connectivity connectivity is organizing a tree structure in the brain. So here you see a representation of the Iraqi and organization of the monkey cerebral cortex. So how can these principles we used to improve the performance of the icing machines? And it's in sequence stimulation. So, first about the two of principles of the estimate Trian Rico structure. We know that the classical approximation of the Cortes in machine, which is a growing toe the rate based on your networks. So in the case of the icing machines, uh, the okay, Scott approximation can be obtained using the trump active in your position, for example, so the times of both of the system they are, they can be described by the following ordinary differential equations on in which, in case of see, I am the X, I represent the in phase component of one GOP Oh, Theo F represents the monitor optical parts, the district optical parametric amplification and some of the good I JoJo extra represent the coupling, which is done in the case of the measure of feedback cooking cm using oh, more than detection and refugee A then injection off the cooking time and eso this dynamics in both cases of CME in your networks, they can be written as the grand set of a potential function V, and this written here, and this potential functionally includes the rising Maccagnan. So this is why it's natural to use this type of, uh, dynamics to solve the icing problem in which the Omega I J or the Eyes in coping and the H is the extension of the rising and attorney in India and expect so. >>Not that this potential function can only be defined if the Omega I j. R. A. Symmetric. So the well known problem of >>this approach is that this potential function V that we obtain is very non convicts at low temperature, and also one strategy is to gradually deformed this landscape, using so many in process. But there is no theorem. Unfortunately, that granted convergence to the global minimum of there's even 20 and using this approach. And so this is >>why we propose toe introduce a macro structure the system or where one analog spin or one D o. P. O is replaced by a pair off one and knock spin and one error on cutting. Viable. And the addition of this chemical structure introduces a symmetry in the system, which in terms induces chaotic dynamics, a chaotic search rather than a >>learning process for searching for the ground state of the icing. Every 20 >>within this massacre structure the role of the ER variable eyes to control the amplitude off the analog spins to force the amplitude of the expense toe, become equal to certain target amplitude. A Andi. This is known by moderating the strength off the icing complaints or see the the error variable e I multiply the icing complain here in the dynamics off UH, D o p o on Then the dynamics. The whole dynamics described by this coupled equations because the e I do not necessarily take away the same value for the different, I think introduces a >>symmetry in the system, which in turn creates chaotic dynamics, which I'm showing here for solving certain current size off, um, escape problem, Uh, in which the exiled from here in the i r. From here and the value of the icing energy is shown in the bottom plots. And you see this Celtics search that visit various local minima of the as Newtonian and eventually finds the local minima Um, >>it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing hamiltonian so that we're gonna do not get stuck in any of them. On more over the other types of attractors, I can eventually appear, such as the limits of contractors or quality contractors. They can also be destabilized using a moderation of the target amplitude. And so we have proposed in the past two different motivation of the target constitute the first one is a moderation that ensure the 100 >>reproduction rate of the system to become positive on this forbids the creation of any non tree retractors. And but in this work I will talk about another modulation or Uresti moderation, which is given here that works, uh, as well as this first, uh, moderation, but is easy to be implemented on refugee. >>So this couple of the question that represent the current the stimulation of the cortex in machine with some error correction, they can be implemented especially efficiently on an F B G. And here I show the time that it takes to simulate three system and eso in red. You see, at the time that it takes to simulate the X, I term the EI term, the dot product and the rising everything. Yet for a system with 500 spins analog Spain's equivalent to 500 g. O. P. S. So in f b d a. The nonlinear dynamics which, according to the digital optical Parametric amplification that the Opa off the CME can be computed in only 13 clock cycles at 300 yards. So which corresponds to about 0.1 microseconds. And this is Toby, uh, compared to what can be achieved in the measurements tobacco cm in which, if we want to get 500 timer chip Xia Pios with the one she got repetition rate through the obstacle nine narrative. Uh, then way would require 0.5 microseconds toe do this so the submission in F B J can be at least as fast as, ah one gear repression to replicate the post phaser CIA. Um, then the DOT product that appears in this differential equation can be completed in 43 clock cycles. That's to say, one microseconds at 15 years. So I pieced for pouring sizes that are larger than 500 speeds. The dot product becomes clearly the bottleneck, and this can be seen by looking at the the skating off the time the numbers of clock cycles a text to compute either the non in your optical parts, all the dog products, respect to the problem size. And and if we had a new infinite amount of resources and PGA to simulate the dynamics, then the non in optical post can could be done in the old one. On the mattress Vector product could be done in the low carrot off, located off scales as a low carrot off end and while the kite off end. Because computing the dot product involves the summing, all the terms in the products, which is done by a nephew, Jay by another tree, which heights scares a logarithmic any with the size of the system. But this is in the case if we had an infinite amount of resources on the LPGA food but for dealing for larger problems off more than 100 spins, usually we need to decompose the metrics into ah smaller blocks with the block side that are not you here. And then the scaling becomes funny non inner parts linear in the and over you and for the products in the end of you square eso typically for low NF pdf cheap P a. You know you the block size off this matrix is typically about 100. So clearly way want to make you as large as possible in order to maintain this scanning in a log event for the numbers of clock cycles needed to compute the product rather than this and square that occurs if we decompose the metrics into smaller blocks. But the difficulty in, uh, having this larger blocks eyes that having another tree very large Haider tree introduces a large finding and finance and long distance started path within the refugee. So the solution to get higher performance for a simulator of the contest in machine eyes to get rid of this bottleneck for the dot product. By increasing the size of this at the tree and this can be done by organizing Yeah, click the extra co components within the F p G A in order which is shown here in this right panel here in order to minimize the finding finance of the system and to minimize the long distance that the path in the in the fpt So I'm not going to the details of how this is implemented the PGA. But just to give you a new idea off why the Iraqi Yahiko organization off the system becomes extremely important toe get good performance for simulator organizing mission. So instead of instead of getting into the details of the mpg implementation, I would like to give some few benchmark results off this simulator, uh, off the that that was used as a proof of concept for this idea which is can be found in this archive paper here and here. I should result for solving escape problems, free connected person, randomly person minus one, spin last problems and we sure, as we use as a metric the numbers >>of the mattress Victor products since it's the bottleneck of the computation, uh, to get the optimal solution of this escape problem with Nina successful BT against the problem size here and and in red here there's propose F B J implementation and in ah blue is the numbers of retrospective product that are necessary for the C. I am without error correction to solve this escape programs and in green here for noisy means in an evening which is, uh, behavior. It's similar to the car testing machine >>and security. You see that the scaling off the numbers of metrics victor product necessary to solve this problem scales with a better exponents than this other approaches. So so So that's interesting feature of the system and next we can see what is the real time to solution. To solve this, SK instances eso in the last six years, the time institution in seconds >>to find a grand state of risk. Instances remain answers is possibility for different state of the art hardware. So in red is the F B G. A presentation proposing this paper and then the other curve represent ah, brick, a local search in in orange and center dining in purple, for example, and So you see that the scaring off this purpose simulator is is rather good and that for larger politicizes, we can get orders of magnitude faster than the state of the other approaches. >>Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FBT implementation would be faster than risk Other recently proposed izing machine, such as the Hope you know network implemented on Memory Sisters. That is very fast for small problem size in blue here, which is very fast for small problem size. But which scanning is not good on the same thing for the >>restricted Bosman machine implemented a PGA proposed by some group in Brooklyn recently again, which is very fast for small promise sizes. But which canning is bad So that, uh, this worse than the purpose approach so that we can expect that for promise sizes larger than, let's say, 1000 spins. The purpose, of course, would be the faster one. >>Let me jump toe this other slide and another confirmation that the scheme scales well that you can find the maximum cut values off benchmark sets. The G sets better cut values that have been previously found by any other >>algorithms. So they are the best known could values to best of our knowledge. And, um, or so which is shown in this paper table here in particular, the instances, Uh, 14 and 15 of this G set can be We can find better converse than previously >>known, and we can find this can vary is 100 times >>faster than the state of the art algorithm and cp to do this which is a recount. Kasich, it s not that getting this a good result on the G sets, they do not require ah, particular hard tuning of the parameters. So the tuning issuing here is very simple. It it just depends on the degree off connectivity within each graph. And so this good results on the set indicate that the proposed approach would be a good not only at solving escape problems in this problems, but all the types off graph sizing problems on Mexican province in communities. >>So given that the performance off the design depends on the height of this other tree, we can try to maximize the height of this other tree on a large F p g A onda and carefully routing the trickle components within the P G A. And and we can draw some projections of what type of performance we can achieve in >>the near future based on the, uh, implementation that we are currently working. So here you see projection for the time to solution way, then next property for solving this escape problems respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital and, you know, free to is shown in the green here, the green >>line without that's and, uh and we should two different, uh, prosthesis for this productions either that the time to solution scales as exponential off n or that >>the time of social skills as expression of square root off. So it seems according to the data, that time solution scares more as an expression of square root of and also we can be sure >>on this and this production showed that we probably can solve Prime Escape Program of Science 2000 spins to find the rial ground state of this problem with 99 success ability in about 10 seconds, which is much faster than all the other proposed approaches. So one of the future plans for this current is in machine simulator. So the first thing is that we would like to make dissimulation closer to the rial, uh, GOP or optical system in particular for a first step to get closer to the system of a measurement back. See, I am. And to do this, what is, uh, simulate Herbal on the p a is this quantum, uh, condoms Goshen model that is proposed described in this paper and proposed by people in the in the Entity group. And so the idea of this model is that instead of having the very simple or these and have shown previously, it includes paired all these that take into account out on me the mean off the awesome leverage off the, uh, European face component, but also their violence s so that we can take into account more quantum effects off the g o p. O, such as the squeezing. And then we plan toe, make the simulator open access for the members to run their instances on the system. There will be a first version in September that will >>be just based on the simple common line access for the simulator and in which will have just a classical approximation of the system. We don't know Sturm, binary weights and Museum in >>term, but then will propose a second version that would extend the current arising machine to Iraq off eight f p g. A. In which we will add the more refined models truncated bigger in the bottom question model that just talked about on the supports in which he valued waits for the rising problems and support the cement. So we will announce >>later when this is available, and Farah is working hard to get the first version available sometime in September. Thank you all, and we'll be happy to answer any questions that you have.

>> Male's Voice: From around the globe, its theCUBE. With digital coverage of a special announcement, brought to you by Nutanix. (soft music) >> Hi, I'm Stu Miniman. And welcome to this special announcement for Nutanix, about some new product releases in the public cloud. To help us kick this off for the Asia Pacific and Japan region. Happy to welcome to the program Jordan Reizes, who's the vice president of marketing, for APJ and Nutanix. Jordan, help us introduce it. Thanks Stu. So today we're really pleased to announce Nutanix Clusters, availability in Asia Pacific and Japan, at the same time as the rest of the world. And we think this technology is really important to our geographically dispersed customers, all across the region, in terms of helping them, On-Ramp to the cloud. So, we're really excited about this launch today. And Stu, I can't wait to see the rest of the program. And make sure you stay tuned at the end, for our interview with our CTO, Justin Hurst. Who's going to be answering a bunch of questions that are really specific to the APJ region. >> All right, thank you so much Jordan, for helping us kick this off. We're now going to cut over to my interview with Monica and Tarkan, with the news. >> Hi, I'm Stu Miniman. And I want to welcome you to this special event that we are doing with Nutanix. Of course, in 2020 many things have changed. And that has changed some of the priorities, for many companies out there. Acceleration of cloud adoption, absolutely have been there. I've talked to many companies that were dipping their toe, or thinking about, where they were going to cloud. And of course it's rapidly moved to accelerate to be able to leverage work from home, remote contact centers, and the like. So, we have to think about how we can accelerate what's happening, and make sure that our workforce, and our customers are all taken care of. So, one of the front seats of this, is of course, companies working to help modernize customers out there. And, Nutanix is part of that discussion. So, I want to welcome to join us for this special discussion of cloud and Nutanix. I have two of our CUBE alumnus. First of all, we have Monica Kumar. She's the senior vice president of product, with Nutanix. And Tarkan Maner, who's a relative newcomer. Second time on theCUBE, in his new role many time guests. Previously, Tarkan is the chief commercial officer with Nutanix. Monica and Tarkan, thank you so much for joining us. >> Thank you so much. So happy to be back on theCUBE. >> Yeah, thank you. >> All right. So, Tarkan as I was teeing up, we know that, IT staffs in general, CIO specifically, and companies overall, are under a lot of pressure in general. But in 2020, there are new pressures on them. So, why don't you explain to us, the special cloud announcement. Tell us, what's Nutanix launching, and why it's so important today. >> So, Stu first of all, thank you. And glad to be here with Monica. And basically you and I, spend some time with a few customers in the past few weeks and months. I'll tell you, the things in our industry are changing at a pace that we never seen before. Especially with this pandemic backdrop, as we're going through. And obviously, all the economic challenges that creates beyond the obviously, health challenges and across the world, all the pain it creates. But also it creates some opportunities for our customers and partners to deliver solutions to our enterprise customers, and commercial customers, and in a public sector customers, in multiple industries. From healthcare, obviously very importantly, to manufacturing, to supply chains, and to all the other industries, including financial services and public sector again. So in that context, Monica knows as well as she's our leader. You know, our strategy, we're putting lots of effort in this new multi-class strategy as a company. As you know, is too well, Nutanix wrote the book, in digital infrastructures with its own private, (mumbles) infrastructure story. Now they're taking that next level, via our data center solutions, via DevOps solutions, and end user computer solutions. Now, the multicloud fashion, working with partners like AWS. So, in this launch, we have our new, hybrid cloud infrastructure, Nutanix Clusters product now available in the AWS. We are super excited. We have more than 20 tech firms, and customers, and partners at sealable executive level support in this big launch. Timing is usually important, because of this pandemic backdrop. And the goal is obviously to help our customers save money, focus what's important for them, save money for them, and making sure they streamlined their IT operation. So it's a huge launch for us. And we're super excited about it. >> Yeah. And the one thing I would add too, what Tarkan said too is, look, we talk to a lot of customers, and obviously cloud is the constant, in terms of enabling innovation. But I think more with COVID, what's on top of mind is also how do we use cloud for innovation? But really be intelligent about cost optimization. So with this new announcement, what we are excited about is we're bringing, making really a hybrid cloud reality, across public and private cloud. But also making sure customers, get the cost efficiency they need, when they're deploying the solution. So we are super excited to bring true hybrid cloud offering with AWS to the market today. >> Well, I can tell you Nutanix cluster is absolutely one of the exciting technologies I've enjoyed, watching and getting ready for. And of course, a partnership with the largest public cloud player out there AWS, is really important. When I think about Nutanix from the earliest days, the word that we always used for the HI Space and Nutanix specifically, was simplicity. Anybody in the tech space know that, true simplicity is really hard to do. When I think about cloud, when I think about multicloud, simplicity is not the first thing that I think of. So, Tarkan has helped us connect, how is Nutanix going to extend the simplicity that it's done, for so long now in the data center, into places like AWS with this solution? >> So, Stu you're spot on. Look, Monica and I spend a lot of time with our customers. One thing about Nutanix executive team, you're very customer-driven. And I'm not just saying this to make a point. We really spent tons of time with them because our solutions are basically so critical for them to run their businesses. So, just recently I was with a senior executive, C level executive of an airline. Right before that, Monica and I spent actually with one of the largest banks in the world in France, in Paris. Right before the pandemic, we were actually traveling. Talking to, not all the CIO, the chief operating officer on one of these huge banks. And the biggest issue was, how these companies are trying to basically adjust their plans, business plans. I'm not talking about tech plans, IT plans, the business plans around this backdrop with the economic stress. And obviously, now pandemic is in a big way. One of the CIOs told me, he was an airline executive. "Look Tarkan, in the next four months, my business might be half of what it is today. And I need to do more with less, in so many different ways, while I'm cutting costs." So it's a tough time. So, in that context is to... Your actually right. Multicloud is in a difficult proposition, but it's critical, for these companies to manage their cost structures across multiple operating models. Cloud to us, is not a destination, it's a means to an ends. It is an operating model. At the end of the day, the differentiation is still the software. The unique software that we provide from digital infrastructures, to deliver, end to end discreet data center solutions, DevOps solutions for developers, as well as for end user computing individuals, to making sure to take advantage of, these VDI decibels service topic capability. So in that context, what we are providing now to this CIOs who are going through, this difficult time is, a platform, in which they can move their workloads from cloud to cloud, based on their needs, with freedom of choice. Look, one of these big banks that Monica and I visited in France, huge global bank. They have a workloads on AWS, they have workload on Azure, they have workloads on Google, workloads on (indistinct), the local XP, they have workloads in Germany. They have workloads providers in Asia, in Taiwan, and other locations. On top of that, they're also using Nutanix on-prem as well as Nutanix cloud, our own cloud services for VR. And then, this is not just in this nation. This is an operating model. So the biggest request from them is, look, can you guys make this cost effective? Can we use, all these operating models and move our data, and applications from cloud to cloud? In simple terms, can we get, some kind of a flexibility with commits as well as we pay credits they paid for so far? And, those are things we're working on. And I'm sure Monica is going to get a little bit more into detail, as we talk to this. You are super excited, to start this journey with AWS, with this launch, but you're not going to stop there. Our goal is, we just kind of discussed with Monica earlier, provide freedom of choice across multiple clouds, both on-prem and off-prem, for our customers to cut costs, and to focus on what's important for them. >> Yeah, and I would just add, to sum it up, we are really simplifying the multicloud complexity for our customers. And I can go into more detail, but that's really the gist of it. Is what Nutanix is doing with this announcement, and more coming up in the future. >> Well, Monica, when I think about customers, and how do they decide, what stays in their data center, what goes into the public cloud? It's really their application portfolio. I need to look at my workloads, I need to look at my skillset. So, when I look at the cluster solution, what are some of the key use cases? What workloads are going to be the first ones that you expect, or you're having customers use with it today? >> Sure. And as we talk to customers too, this clearly few key use cases that they've been trying to, build a hybrid strategy around. The first few ones are bursting into cloud, right? In case of, a demand of sudden demand, how do I burst and scale my, let's say a VDI environment. or database environment into the cloud? So that's clearly one that many of our customers want to be able to do simply, and without having to incur this extreme complexity of managing these environments. Number two, it's about DR, and we saw with COVID, right? Business continuity became a big deal for many organizations. They weren't prepared for it. So the ability to actually spin up your applications and data in the cloud seamlessly, in case of a disaster, that's another big use case. The third one, of which many customers talk about is, can I lift and shift my applications as is, into the cloud? Without having to rewrite a single line of code, or without having to rewrite all of it, right? That's another one. And last but not least, the one that we're also hearing a lot about is, how do I extend my current applications by using cloud native services, that's available on public cloud? So those are four, there's many more, of course. But in terms of workloads, I mentioned two examples, right? VDI, which is Virtual Desktop Infrastructure, and is a computing, and also databases. More and more of our customers, don't want to invest in again having, on-premises data center assets sitting there idly. And, wait for when the capacity surges, the demand for capacity surges, they want to be able to do that in the cloud. So I'd say those are the few use cases and workloads. One thing I want to go back to what Tarkan was talking about, really their three key reasons, why the current hybrid cloud solutions, haven't really panned out for customers. Number one, it's having a unified management environment across public and private cloud. There's a few solutions out there, but none of them have proved to be simple enough, to actually put into real execution. You know, with Nutanix, the one thing you can do is literally build a hybrid cloud within, under an hour. Under an hour, you can spin up Nutanix Clusters, which you have on-premises, the same exact cluster in Amazon, under one hour. There you go. And you have the same exact management plan, that we offer on-prem, that now can manage your AWS Nutanix Clusters. It's that easy, right? And then, you can easily move your data and applications across, if you choose to. You want to move and burst into public cloud? Do it. You want to keep some stuff on-prem? Do it. If you're going to develop in the cloud, do it. Want to keep production on-prem, do it. Single management plan, seamless mobility. And the third point is about cost. Simplicity of managing the costs, making sure you know, how you're going to incur costs. How about, if you can hibernate your AWS cluster when you're not using it? We allow the... We have the capability now in our software to do that. How about knowing, where to place which workload. Which workload goes into public cloud, which stays on-premises. We have an amazing tool called beam, that gives the customers that ability to assess, which is the right cloud for the right workload. So I can go on and on about this. You know, we've talked to so many customers, but this is in a nutshell. You know, the use cases and workloads that we are delivering to customers right out the gate. >> Well, Monica, I'd love to hear a little bit about the customers that have had early access to this. What customer stories can you share? Understand of course? You're probably going to need to anonymize. But, I'd like to understand, how they've been leveraging clusters, the value that they're getting from it. >> Absolutely. We've been working with a number of customers. And I'll give you a few examples. There's a customer in Australia, I'll start with that. And they basically run a big event that happens every five years for them. And that they have to scale something to 24 million people. Now imagine, if they have to keep capacity on site, anticipating the needs for five years in a row, well, they can't do that. And the big event is going to happen next year for them. So they are getting ready with now clusters, to really expand the VDI environments into the cloud, in a big way with AWS. So from Nutanix on-prem to AWS, and expand VDI and burst into the cloud. So that's one example. That's obviously when you have an event-driven capacity bursting into the cloud. Another customer, who is in the insurance business. For them, DR is of course very important. I mean, DR is important for every industry in every business. But for them, they realize that they need to be able to, transparently run the applications in the case of a disaster on the cloud. So they've been using non Nutanix Clusters with AWS to do that. Another customer is looking at lifting and shifting some of the database applications into, AWS with Nutanix, for example. And then we have yet another customer who's looking at retiring, their a part of the data center estate, and moving that completely to AWS, with Nutanix as a backbone, Nutanix Clusters as a backbone. I mean, and we have tons of examples of customers who during COVID, for example, were able to burst capacity, and spin up hundreds and thousands of remote employees, using clusters into AWS cloud. Using Citrix also by the way, as the desktop provider. So again, I can go on, we have tons of customers. There's obviously a big demand for the solution. Because now it's so easy to use. We have customers, really surprised going, "Wait, I now have built a whole hybrid card within an hour. And I was able to scale from, six nodes, to 60 nodes, just like that, on AWS cloud from on-prem six nodes, to 16 in AWS cloud. Our customers are really, really pleasantly surprised with the ease of use, and how quickly they can scale, using clusters in AWS. >> Yeah. Tarkan I have to imagine that, this is a real change for the conversation you have with customers. I mean, Nutanix has been partner with AWS for a number of years. I remember the first time that I saw Nutanix, at the reinvent show. But, cloud is definitely front and center, in a lot of your customer's conversations. So, with your partners, with your customers, has to be just a whole different aspect, to the conversations that you can have. >> Actually Stu, as you heard from Monica too. As I mentioned earlier, this is not just a destination for the customers, right? I know you using these buzzwords, at the end of day, there's an open end model. If it's an open end model they want to take advantage of, to cut costs and do more with less. So in that context, as you heard, even in this conversation, there is many pinpoint in this. Like again, being able to move the workloads from location to location, cost optimize those things, provide a streamlined operations. Again, as Monica suggested, making the apps, and the data relating those apps mobile, and obviously provide built-in networking capabilities. All those capabilities make it easier for them to cut costs. So we're hearing constantly, from the enterprises is small and large, private sector and public sector, nothing different. Clearly they have options. They want to have the freedom of choice. Some of these workloads are going to run on-prem, some of them off prem. And off prem is going to have, tons of different radiations. So in that context, as I mentioned earlier, we have our own cloud as well. We provide 20 plus skews to 17,000 customers around the world. It's a $2 billion software business run rate is as you know. And, a lot of those questions on-prem customers now, also coming to our own cloud services. With cloud partners, we have our own cloud services, with our own billing, payments, logistics, and service capabilities. With a credit card, you can actually, you can do DR. (mumbles) a service to Nutanix itself. But some of these customers also want to go be able to go to AWS, or Azure, or to a local service provider. Sometimes it's US companies, we think US only. But think about this, this is a global phenomenon. I have customers in India. We have customers in Australia as Monica talked about. In China, in Japan, in Germany. And some of these enterprise customers, public sector customers, they want to DR, Disaster Recovery as a service to a local service provider, within the country. Because of the new data governance, laws and security concerns, they don't want the data and us, to go outside of the boundaries of the country. In some cases, in the same continent, if you're in Switzerland, not even forget about the country, the same city. So we want to make sure, we give capabilities for customers, use the cloud as an operating model the way they want. And as part of this, just you know Stu, you're not alone in this, we can not do this alone. We have, tremendous level of partner support as you're going to see in the new announcements. From HP as one of our key partners, Lenovo, AMD, Intel, Fujitsu, Citrix for end user computing. You're partnering with Palo Alto networks for security, Azure partners, as you know we support (indistinct). We have partners like Red Hat, whose in tons of work in the Linux front. We partnered with IBM, we partner with Dell. So, the ecosystem makes it so much easier for our customers, especially with this pandemic backdrop. And I think what you're going to see from Nutanix, more partners, more customer proof points, to help the customers innovate the cut costs, in this difficult backdrop. Especially for the next 24 months, I think what you're going to see is, tremendous so to speak adoption, of this multicloud approach that you're focusing on right now. >> Yeah, and let me add, I know our partner list is long. So Tarkan also, we have the global size, of course. The WebPros, and HCL, and TCS, and Capgemini, and Zensar, you name it all. We're working with all of them to bring clusters based solutions to market. And, for the entire Nutanix stack, also partners like Equinix and Yoda. So it's a long list of partnerships. The one thing I did want to bring up Stu, which I forgot to mention earlier, and Tarkan reminded me is a superior architecture. So why is it that Nutanix can deliver this now to customers, right? I mean, our customers have been trying to build hybrid cloud for a little while now, and work across multiple clouds. And, we know it's been complex. The reason why we are able to deliver this in the way we are, is because of our architecture. The way we've architected clusters with AWS is, it's built in native network integration. And what that means is, if your customer and end user who's a practitioner, you can literally see the Nutanix VMs, in the same space as Amazon VMs. So for a customer, it's in the exact same space, it's really easy to then use other AWS services. And we bypass any, complex and latency issues with networking, because we are exactly part of AWS VPC for the customer. And also, the customers can use by the way, the Amazon credits, with the way we've architected this. And we allow for bringing your own license, by the way. That's the other true part about simplicity is, same license that our customers use on-premises today for Nutanix, can be brought exactly the same way to AWS, if they choose to. And now of course, we do also offer other licensing models that are cloud only. But I want to point out that DVIOL is something that we are very proud of. It's truly enabling, bring your own license to AWS cloud in this case. >> Well, it's interesting, Monica. Of course, one of the things everybody's watched of Nutanix over the last few years is that move, from an appliance primarily to a software model. And, as an industry as a whole, it's much more moving to the cloud model for pricing. And it sounds like, that's the primary model with some flexibility and options that you have, when you're talking about the cluster solution here, is that correct? >> Yeah, we also offer the pay as you go model of course, and cloud as popular. So, customers can decide they just want to pay for the amount they use, that's fine. Or they can bring their existing on-prem license, to AWS. Or we also have a commit model, where they commit for a certain capacity for the year, and they go with that. So we have two or three different kinds of models. Again, going with the freedom of choice for our customers. We offer them different models they can choose from. But to me, the best part is to bring your own license model. That's again, a true hybrid pricing model here. They can choose to use Nutanix where they want to. >> Yeah. Well, and Monica, I'm glad you brought up some of the architectural pieces here. 'Cause you talked about all the partners that you have out there. If I'm sitting in the partner world, I've been heard nothing over the last few years, but I've been inundated by all of the hybrid solutions. So, every public cloud provider, including AWS now, is talking about hybrid solutions. You've got virtualization players, infrastructure players, all talking out there. So, architecture you talked a bit about. Anything else, key differentiators that you want people to understand, as what sets Nutanix apart from the crowd, when it comes to hybrid cloud. >> Well, like I said, it's because of our architecture, you can build a hybrid cloud in under an hour. I mean, prove to me if you can do with other providers. And again, I don't mean that, having that ego. But really, I mean, honestly for our customers, it's all about how can we, speed up a customer's experience to cloud. So, building a cloud under an hour, being able to truly manage it with a single plan, being able to move apps and data, with one click in many cases. And last but not least, the license portability. All of that together. I think the way, (indistinct) I've talked about this as, we may not have been the first to market, but we believe they are the best to market in this space today. That's what I would say. >> Tarkan and I'd love to hear a little bit of the vision. So, with Monica kind of alluded to, anybody that kind of digs underneath the covers is, it's bare metal offerings from the cloud providers that are enabling this technology. There was a certain partnership that AWS had, that enabled this, and now you're taking advantage of it. What do you feel when you look at clusters going forward, give us a little bit what should we be looking for, when it comes to AWS and maybe even beyond. >> Thank you Stu. Actually, is spot on question. Most companies in the space, they follow these buzzwords, right? (indistinct) multicloud. And when you killed on, you and you find out, okay, you support two cloud services, and you actually own some kind of a marketplace. And you're one of the 19,000 services. We don't see this as a multicloud. Our view is, complete freedom of choice. So our vision includes a couple of our private clouds, government clouds success with our customers. We've got enterprise commercial and public sector customers. Also delivered to them choice, with Nutanix is own cloud as I mentioned earlier. With our own billing payment, we're just as capable starting with DR as a service, Disaster Recovery as a service. But take that to next level, the database as a service, with VDI based up as a service, and other services that we deliver. But on top of that also, as Monica talked about earlier, partnerships we have, with service providers, like Yoda in India, a lot going on with SoftBank in Japan, Brooklyn going on with OBH in France. And multiple countries that we are building this XSP (indistinct) telco relationships, give those international customers, choice within that own local region, in their own country, in some cases in their city, where they are, making sure the network latency is not an issue. Security, data governance, is not an issue. And obviously, third leg of this multilayer stool is, hyperscalers themselves like AWS. AWS has been a phenomenal partner, working with Doug (indistinct), Matt Garmin, the executive team under Andy Jassy and Jeff Bezos, biggest super partners. Obviously, that bare metal service capability, is huge differentiator. And with the typical AWS simplicity. And obviously, with Nutanix simplicity coming together. But given choice to our customers as we move forward obviously, our customer set a multicloud strategy. So I'm reading an amazing book called Silk Roads. It's an amazing book. I strongly suggest you all read it. It's all talking about partnerships. Throughout the history, those empires, those countries who have been successful, partnered well, connect the dots well. So that's what we're trying to learn from our own history. Connecting dots with the customers and partners as we talked about earlier. Working with companies that with Wipro. And we over deliver to the end user computer service called, best of a service door to desk. Database as a service, digital data services get that VA to other new services started in HCL and others. So all these things come together as a complete end to end strategy with our partners. So we want to make sure, as we move forward in upcoming weeks and months, you're going to see, these announcements coming up, one partner at a time. And obviously we are going to measure success, one customer at a time as we more forward with the strategy. >> All right. So Monica, you mentioned that if you were an existing Nutanix customer, you can spin up in the public cloud, in under an hour. I guess final question I have for you is, number one, if I'm not yet a Nutanix customer, is this something I could start in the public cloud. and leverage some capabilities? And, whether I'm an existing customer or a prospect, how do I get started with Nutanix Clusters? >> Absolutely. We are all about making it easy for our customers to get started. So in fact, I know seeing is believing. So if you go to nutanix.com today, you'll see we have a link there for something called a test drive. So we are giving our prospects, and customers the ability to go try this out. Either just take a tour, or even do a 30 day free trial today. So they can try it out. They can just get spun up in the cloud completely, and then connect to on-premises if they choose to. Or just, if they choose to stay in public cloud only with Nutanix, that's absolutely the customer choice. And I would say this is really, only the beginning for us as Tarkan was saying. I mean, I'm just really super excited about our future, and how we are going to enable customers, to use cloud for innovation going forward. In a really simple, manner that's cost efficient for our customers. >> All right. Well, Monica and Tarkan, thank you so much for sharing the updates. Congratulations to the team on bringing this solution out. And as you said, just the beginning. So, we look forward to, talking to you, your partners, and your customers going forward. >> Thank you so much. >> Thank you Stu. Thank you, Monica. >> Hi, and welcome back. We've just heard Nutanix's announcement about Nutanix Clusters on AWS, from Monica and Tarkan, And, to help understand some of the specific implications for the Asia Pacific and Japan region. Happy to welcome Justin Hurst, who is the CTO, for APJ with Nutanix. Justin, thanks for joining us. >> Well, thanks Stu. Thanks for having me. >> Absolutely. So, we know Justin of course, 2020, has had a lot of changes, for everyone globally. Heard some exciting news from your team. And, wondering if you can bring us inside the APJ region. And what will the impact specifically be for your customers in your region? >> Yeah, let's say, that's a great question. And, it has been a tremendously unusual year, of course, for everyone. We're all trying, to figure out how we can adapt. And how we can take this opportunity, to not only respond to the situation, but actually build our businesses in a way, that we can be more agile going forward. So, we're very excited about this announcement. And, the new capabilities it's going to bring to our customers in the region. >> Justin, one of the things we talk about is, right now, there's actually been an acceleration of how customers are looking to On-Ramp to the cloud. So when you look at the solution, what's the operational impact of Nutanix Clusters? And that acceleration to the cloud? >> Well, sure. And I think that, is really what we're trying to accomplish here, with this new technology is to take away a lot of the pain, in onboarding to the public cloud. For many customers I talk to, the cloud is aspirational at this point. They may be experimenting. They may have a few applications they've, spun up in the cloud or using a SaaS service. But really getting those core applications, into the public cloud, has been something they've struggled with. And so, by harmonizing the control plan and the data plan, between on-premises and the public cloud, we just completely remove that barrier, and allow that mobility, that's been, something people have really been looking forward to. >> All right, well, Justin, of course, the announcement being with AWS, is the global leader in public cloud. But we've seen the cluster solution, when has been discussed in earlier days, isn't necessarily only for AWS. So, what can you tell us about your customer's adoption with AWS, and maybe what we should look at down the road for clusters with other solutions? >> Yeah, for sure. Now of course, AWS is the global market leader, which is why we're so happy to have this launch event today of clusters on AWS. But with many of our customers, depending on their region, or their regulatory requirements, they may want to work as well, with other providers. And so when we built the Nutanix cluster solution, we were careful not to lock in, to any specific provider. Which gives us options going forward, to meet our customer demands, wherever they might be. >> All right. Well, when we look at cloud, of course, the implications are one of the things we need to think about. We've seen a number of hybrid solutions out there, that haven't necessarily been the most economical. So, what are the financial considerations, when we look at this solution? >> Yeah, definitely. I think when we look at using the public cloud, it's important not to bring along, the same operational mindset, as traditional on-premise infrastructure. And that's the power of the cloud, is the elasticity. And the ability to burst workloads, to grow and to shrink as needed. And so, to really help contain those costs, we've built in this amazing ability, to hibernate workloads. So that customers can run them, when they need them. Whether it's a seasonal business, whether it's something in education, where students are coming and going, for different terms. We've built this functionality, that allows you to take traditional applications that would normally run on-premises 24/7. And give them that elasticity of the public cloud, really combining the best of both worlds. And then, building tooling and automation around that. So it's not just guesswork. We can actually tell you, when to spin up a workload, or where to place a workload, to get the best financial impact. >> All right, Justin, final question for you is, this has been the works on Nutanix working on the cluster solution world for a bit now. What's exciting you, that you're going to be able to bring this to your customers? >> Yeah. There's a lot of new capabilities, that get unlocked by this new technology. I think about a customer I was talking to recently, that's expanding their business geographically. And, what they didn't want to do, was invest capital in building up a new data center, in a new region. Because here in APJ, the region is geographically vast, and connectivity can vary tremendously. And so for this company, to be able to spin up, a new data center effectively, in any AWS region around the world, really enables them to bring the data and the applications, to where they're expanding their business, without that capital outlay. And so, that's just one capability, that we're really excited about. And we think we'll have a big impact, in how people do business. And keeping those applications and data, close to where they're doing that business. >> All right. Well, Justin, thank you so much for giving us a look inside the APJ region. And congratulations to you and the team, on the Nutanix Clusters announcement. >> Thanks so much for having me Stu. >> All right. And thank you for watching I'm Stu Miniman. Thank you for watching theCUBE. (soft music)

>> connecting with thought leaders all around the world, this is a CUBE Conversation. Hi, everybody this is Dave Vellante of theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SEER model, the most popular SEER model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O our open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these great Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

>> Starting the record, Dave in five, four, three. Hi, everybody this is Dave Vellante, theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SaaS model, the most popular SaaS model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O or open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these Greek Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

>> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Okay, welcome back everyone, it's theCUBE's virtual coverage of AWS Summit Online, they're virtual. Then I'm John Furrier, your host of theCUBE. We're here in our Palo Alto studios for theCUBE virtual. We're remotely doing interviews during this COVID crisis. We have our quarantine crew, we're doing our best now for two and a half months getting those stories out, and today is AWS Summit. It's going to continue online, it never ends. It's virtual, it's asynchronous, but more importantly, let's get to great content. Our next guest Jimmy Chen, CEO of Propel. Great entrepreneur, vision with real impact and this is a story that is super important in my opinion, because it's a tech story and it's a social impact story. And you don't have to do one or the other, you can do both these days. This is going to be great. Jimmy, thanks for spending the time with us today. >> Yeah John, thanks for having me on the show. >> So, I want to get into the broader entrepreneurship and social impact as an entrepreneurial thing, which I think is a total awesome opportunity. But, you guys are using AWS for good, Propel, Take a minute to explain Propel the company, the things you're working and what you're passionate about. >> So Propel, we're a tech company based in Brooklyn that build software to help people navigate safety net programs like the food stamp program. There are about 40 million Americans who get their food stamp benefits on a debit card, called an EBT card, which looks kind of like a debit card or a credit card you get from a bank. But, when we spent time talking to people who use these cards to buy groceries, we actually found that it has kind of a weird quirk, which is that everyone who goes grocery shopping with an EBT card has to call the 1-800 number on the back of the card first, because that's how they can check the balance. And if you try to check-out at the grocery store you don't have enough left on your card, you get into this really embarrassing experience of having to decide, do you want three apples or two, and trying to figure out how to get your balance to be appropriate for the amount of food they're trying to buy. And so, we actually found that this pain point of needing to call the 1-800 number to go check your balance on your EBT card is a really common one that's felt by all 40 million of these Americans who use the food stamp program to put food on the table. So, what be built at Propel is really simple, it's a mobile banking app for the EBT card, the same way that you have a mobile banking app or your banking product, that we've created a digital free app that allows someone who gets their food stamp benefit on an EBT card to check their balance, to see their transaction history and more broadly actually to improve their overall financial help. >> And mends also the quality of life, knowing confidence whether whatever they're going through, that's something they're going to feel about as well. Talk about the tech piece of it. Obviously, this is a good example of something that I've been really riffing on for many years now, and just trying to get people's attention to is that cloud computing changes the game on social impact, because the time to get to the value, which is well talked about in entrepreneurial circles, later got funded, I got product market fit, applies to anything. And this is really spawning a new generation of entrepreneurship. This is a real thing and Amazon does that. What's your experience with AWS in this area? >> Well, our experience over the last month and a half in the middle of the COVID crisis I think has really driven home the value of AWS for our business, which is that, you know, at the start of COVID we had about 2 million people who used the Fresh EBT app on a monthly basis to manage their existing SNAP benefits. Unfortunately, as the economy has worsen and people's usage of safety net services as has increased, so has our userbase. And AWS has been really key to us, being able to scale our services, to be able to help an extra million people start using the Fresh EBT app essentially over the last few weeks. And so, you know, to your point about infrastructure and scale and technology, for us it's really been about, what are the best practices in the consumer tech worlds? And how do we apply those to help people that are lower-income and generally deal with experiences that are less good. >> You know, I've talked about though is something that I've been really talking a lot about, and maybe I'm a little bit older, but the younger entrepreneurs, they love to be agile and everything else. But what you're doing and what you've done is really have agility, but when you have these hard times everyone uses the word pivot. Which I hate that word pivot, it means to me like, it didn't work out, I'm going to pivot to something else. But to me, I think what's available when you're using the cloud, like what new position you're in, you built an app for a use case, you had product market fit. This COVID crisis becomes a tailwind for you, because actually your app helps people that are in need, but it also might give you an opportunity to do other things really fast, which means jump on an opportunity, not necessarily pivot. I mean is that tacking, pivot? It's kind of semantics, but it's a cultural mindset. And I want to get your thoughts Jimmy on how you see your business changing where you can actually take what you've built on the trajectory in the climbs of scale, the steep learnings. And then also take new territory down, whether it's a new service, helping people in need, 'cause that's the mission. Now you have flexibility. >> Jimmy: That's right. >> Talk about how you think about that, and what are some of your opportunities that you see. >> Jimmy: Well, the reality is that financial life for people who are low-income and using safety net services changes rapid. And there's no better example of this over the last, you know, few decades than the COVID crisis. Over the past few months, people who are using food stamp benefits have had really an unprecedented challenge over the last few months. It's been tough for everyone, but our survey data shows that for people who were getting food stamp benefits and working in early March, 86% of them have now lost some source of income, or have had their hours cut. And so I think one of the things we're starting to hear from our users is just the unprecedented type of need that they're facing and that they're turning to apps like the Fresh EBT app, to help them to navigate this particular crisis. To answer questions like, "What are the nutrition programs "through the government that are available to me? "How do I get a stimulus check? "What about the unemployment program? "And just, what are the full set of safety net resources "that are available to help someone like me "to get back on my feet and to make it through "this unprecedented financial hardship?" So, to your point about pivoting, you know, it's not necessarily, I don't think of it as pivoting, I think of it as like as responding to the real changes in user need. >> Yeah, ceasing opportunity on your position of your value proposition. Jimmy talk about the company, that your company launched a new service, Project 100. What is that about? Can you take a minute to explain that? >> Project 100 is a partnership between Propel, Stand for Children and the GiveDirectly team, which is the other two are nonprofits that are focused on different aspects of serving people that are in financial need. And it is a partnership that we've created to raise a $100 million to be able to make cash transfers to a 100,000 people who use the Fresh EBT app and are in financial need. So, Propel's role in this is that we, because our app helps people that are getting their food stamp benefits, we can certify that this is a person who is in financial need and uses, essentially, the status on the food stamp program as a proxy for, this is a family who really needs help to get through this crisis. We've been fortunate to have a lot of donors who are very generous and interested in finding ways to support, you know, people that are going through these types of financial hardships. And so, we've been fortunate to raise already about $70 million through this program. But, I think we still have a ways to go to reach this $100 million goal, where we really think that, that was a material impact on helping low-income Americans weather this financial shock. >> Well, I really appreciate what you're doing and thanks for what you're doing, it's great, and I think it's a great opportunity. Got great product market fit and you got a lot of horizontal opportunities to go after as you're more successful. I also want to get your thoughts real quick on tech entrepreneurship. It's been very glamorous over the past couple decades, to be an entrepreneur, but ultimately it's about creating value. I think, you're seeing with the cloud a lot of opportunities that aren't the traditional, you know, go public, built, raise a bunch of money, really either for profit or nonprofit, really in highly social impact situations. This is a growing field and you're doing it. Can you share what you're seeing and what advice you could give folks who are really thinking about having a mission driven opportunity. >> Jimmy: Well, I think that people solve the problems that they understand, and that traditionally tech entrepreneurs understand the very specific set of challenges, because the demographics of tech entrepreneurs are a smaller set than the overall population in the United States, right? Tech entrepreneurs tend to be male, they tend to have a college education, they tend to live in cities like San Francisco or New York City, and they tend to have a lot of money. But the reality is, that's not the demographic of people who use technology in the United States and so if people solve the problems that they understand, whose going to solve the problems that people on food stamps understand, if there are not a lot of people who are on food stamps that are starting their own software companies? And so I think the power of tools like Amazon Web Services and the cloud that allow people to be able to create new technology in a record amount of time and scale that, is the ability to democratize who gets to build the technology that people use, right? It means, both being able to help people who traditionally would not have the resources to start a new type of organization, to start a new one, but it also means being able to help companies like mine identify these types of challenges, to learn about the needs that people who are low-income have and be able to scale a product. >> Phenomenal mission Propel. Jimmy Chen, CEO of Propel. If you're designing a product, or art, or anything, you got to know who you're designing it for. And great point, and people solve problems that they understand. Thank you for what you're doing. Congratulations and continue success. We'll keep in touch. Thanks for coming on the virtual CUBE, thank you. >> Jimmy: Thank you so much for having me John. >> I'm John Furrier here on theCUBE for theCUBE virtual coverage of AWS Summit Online. A virtual conference has gone a way to virtual, so is theCUBE. Until further notice, we're going to do our part in our studio in Palo Alto, the studio in Boston. Checking in with folks and getting the updates. We're all in this together, and I'm John Furrier with theCUBE. Thanks for watching. (bright music)

>> Announcer: From theCUBE studios in Palo Alto and Boston. It's theCUBE. Covering IBM Think. Brought to you by IBM. >> Hi everybody, we're back this is Dave Vellante from theCUBE and you're watching our wall-to-wall coverage of IBM's Digital Think 2020 event and we are really pleased to have Guillermo Miranda here. He's the Vice President of Corporate and Social Responsibility. Guillermo thanks for coming on theCUBE. >> Absolutely, good afternoon to you. Good evening, wherever you are. >> So, you know this notion of corporate responsibility, it really has gained steam lately and of course with COVID-19, companies like IBM really have to take the lead on this. The tech industry actually has been one of those industries that has been less hard hit and IBM as a leader along with some other companies are really being looked at to step up. So talk a little bit about social responsibility in the context of the current COVID climate. >> Absolutely. Now thank you for the question. Look, first our responsibility is with the safety of our employees and the continuity of business for our clients. In this frame what we have done is see what is the most adequate areas to respond to the emergency of the pandemic and using what we know in terms of expertise and the talent that we have is why we decided to work first with high performance computing. IBM design and produce the fastest computers in the world. So Summit and a consortium of providers of high performance computing is helping on the discovery of vaccinations and drugs for the pandemic. The second thing that we are doing is related with data and insights. We own The Weather Company which is at 80 million people connected to check the weather every morning, every afternoon. So through The Weather Company, we are providing insights and data about county level information on COVID-19. Another thing that we are doing is we are offering some of our products for free. Watson, it is a chatbot to inform about what is adequate, what is needed in the middle of a pandemic if you are a consumer. We are also helping with our volunteers. IBM volunteers are helping teachers and school districts to rapidly flip into remote learning and get used to the tools of working on a remote environment. And finally we have a micro volunteering opportunity for anybody that has a computer or an android phone. So with the world community grid, you can help with the discovery also of drugs and vaccinations for COVID-19. >> Wow that's great, those are four awesome initiatives. They can't get the vaccine fast enough. Getting good quality information in the hands of people in this era of fake news also very very important. Students missing out on some of the key parts of their learning so remote learning is key. I love this idea of kind of micro crowd sourcing solutions. Really kind of opening that up and hopefully we'll have some big wins there Guillermo. Thank you for that. I want to ask you people talk about blue collar jobs, they talk about white collar jobs, you guys talk about new collar jobs. You and others. What are new collar jobs and why are they important? >> Look, in this data, digital, artificial intelligence driven economy, it's important not to have a digital divide between the haves and the have nots on the foundational skills to be operational in a digital economy. So new collar jobs are precisely the intersection of the skills that you need to operate in this digital driven economy with the basic knowledge to be a user of technology. So think about a cyber security analyst. You don't need a masters degree in industrial engineering to be a cyber security analyst. You just need the basic things about operating an environment on a security control center for instance. Or talk about blockchain or talk about software engineering, full stack developer. There are many roles that you can do in this economy where you don't need to have a full four-year degree in a university to have a decent paying job for the digital economy. These are the new collar jobs and what we are attempting to do with the new collar job definition is to get rid of the paradigm that the university degree is the only passport to a successful career in the marketplace. You can start in different, having the opportunity to have a job in a high tech area. Not necessarily with a PhD in engineering as I said, it's something important for us, for our clients and for the community. >> Yeah, so that's a very interesting concept that a lot of us can relate to. To go back to our university days, many of the courses that we took, we shook our heads and said, "okay, why do I have to take this?" Okay, I get it, well rounded liberal arts experience, that's all good but it's almost like you're implying that the notion of specialization that we've known for years like for instance, in vocations, auto-mechanic, woodworking, etc. Planning that have really critical aspect of the economy. Applying that to the technology business. It's genius and very simple. >> Absolutely. Look, this is the reinvention of vocational education for the 21st century where you continue to need the plumber, you continue to need the hairdresser but also you need people that operate the digital platforms and are comfortable with this environment and they don't need to pass at the beginning through full university. And it's also the concept that we have divided the secondary education, high school from college, university etc., like a Chinese wall. Here is high school, here is college. No! There can be a clear integration because you can start to get ready without finishing high school yet. So there are several paradigms that we have evolved in the previous century that now we need to change and be ready for this 21st century digital driven economy. >> Yeah, very refreshing. Really about time that this thinking came into practice. Talk about P-Tech. How does P-Tech fit into acquiring these skills? And maybe you could give us a sense as to the sort of profile of the folks and there backgrounds and give us a sense as to and add some color to how that's all working. >> Absolutely, so look, the P-Tech model started 10 years ago in a high school in New York City, in Brooklyn. And the whole idea is to go to an under-served area and create a ramp onto success that will help you to first finish high school. Finishing high school is very important and has a lot connotations for your future. And then at the same time, they start getting an associate degree in an area of high growth. The third component is the industry partner. An industry partner that works with the school district and the community college in order to bring the knowledge of what is needed in that community in order to create real job opportunities and we will send you the people and then you will use it. No! We need to work together in order to train the talent for the future. And you just go to the middle age and the guilds were the ones that were preparing the workers. So the industry was preparing the workforce. Why in the 20th century we renounced to that? Having real, relevant skills starting in high school, helping the kids to graduate with a dual diploma. High school, college and practice in real life what it is to be in a workplace environment. So we have more than 220 schools. In this school year, we have more than 150,000 kids in 24 countries already working through the P-Tech model. >> Love it and really scaling that up. So let's say I'm an individual. I'm a young person, I'm from a diverse background, maybe my parents came to this country and I'm a first generation American. Of course, it's not just the United States, it's global but let's say I'm from a background that's less advantaged, how do I take advantage? How hard is it for me to tap in to something like P-Tech and get these skills? >> Well, first one of the characteristics of the model is this is free admission. So there is not a barrier fence. If your school district offers P-Tech, you can apply to P-Tech and get into the P-Tech model education without any barrier without any account. And the second thing that you need to have is curiosity. Because it's not going to be the typical high school where you have math, science, gym, whatever. This is more of an integration of how the look of a career will be in the future and how you have to start understanding that there are drivers into the economy that are fast tracks into well paid jobs. So curiosity on top of being ready to join a P-Tech school in the school district where you live in. >> That's great Guillermo, thank you for sharing that. Now of course corporate responsibility, that's a wide net. This is one of your passions. I'll give you the last word to kind of, where do you see this whole corporate responsibility movement going generally and specifically within IBM? >> I think that this whole pandemic will just accelerate some of the clear trends in the marketplace. Corporate responsibility cannot be an afterthought as before in the '80s or '90s. I will put a foundation. I have a little of profits that are left and then I will distribute grants and that's my whole corporate responsibility approach. Corporate responsibility needs to be within the fabric of how do you do business. It has to be embedded into the values of your company and your value proposition and you have to serve those projects with the same kind of skills and technology, in the case of IBM, that you do for your commercial engagements. And this is what we do in IBM. We help IBMers to be helpful to their communities with the same kind of quality and platforms that we offer to our clients. And we help to solve one of the most complicated problems in society through technology, innovation, time. >> Love it. Guillermo thanks so much, you're doing great work. Really appreciate you coming on theCUBE and sharing with our audience. Congratulations. >> Absolutely. Thank you for very much for having me. >> You're very welcome and thank you for watching everybody. This is Dave Vellante from theCUBE. You're watching our continuous coverage of IBM Think 2020, the digital version. Keep it right there, we'll be right back after this short break. (bright music)

>> Narrator: Live from Washington D.C. it's the Cube covering AWS Public Sector Summit. Brought to you by Amazon Web Services. >> Welcome back everyone to the Cube's live coverage of the AWS Public Sector Summit here in our nation's capital, I'm your host Rebecca Knight. We are joined by Aileen Gemma Smith, the CEO and co-founder of Vizalytics Technology. Thank you so much for coming on the cube. >> Thank you for having me, it's a pleasure to be here. >> Let's start by telling our viewers a little bit about Vizalytics, there's a story there about how you founded it. >> Thank you, the mission of Vizalytics is enabling change with data and we saw tremendous opportunity in open and public available data to say, let's make a difference for communities and the whole reason why we started was in 2012 Hurricane Sandy hit my home town of Staten Island and I saw firsthand digital divide, people need access to information, it's not put together in a format that they can use, but it actually is there, so I said, we've got to do something to make a difference. Our first product was a mobile app for shopkeepers. We had thousands of users throughout New York City and then that led on to out first enterprise client being the City of New York. >> The mobile app for shopkeepers could do what? What did it do? >> It let you know everything that was going on outside and around your business that could make a difference to your bottom line, so imagine all you had to do is business name, business address, I'm going to tell you here's your risk for fines, here's when there's going to be public works, here's when someone's filed for a different permit, et cetera, and shopkeepers loved it because we didn't have to do anything to get that information, you told me exactly what I needed to know and you made it really easy to share. >> And now you are a woman founder, a female founder with a she builds t-shirt on and an AWS Hero medallion. Tell me more about this. >> Absolutely, it is a distinct privilege to be an AWS Community Hero. Community Heroes are evangelists for the community where we're talking about how can we build and create more diverse and inclusive communities. I'm privileged and honored to be the only female hero in the Australia and New Zealand region, so I'm determined to say, how can we support more women, how can we support more underestimated founders and tech developers? We have this whole series called She Builds on AWS. We've got events in Sydney, Melbourne, soon to be in Perth, et cetera and that's how we're doing more for our community and as a Community Hero how can I find more voices who aren't me, give them a platform to say, we need to hear what you're building and what you're doing and how can we all support one another as we want to build on on AWS. >> What is it to be like at event like this, where as you said you're the only female Community Hero here, how often are you getting together, collaborating, learning, and how are best practices emerging and what are those best practices? >> First off I want to mention that we have the first ever developer's lounge here in the main hall which is great because we need to see that here in public sector and having those opportunities to meet and greet and talk with folks, hey, you're working on this as well? Tell me more about what you're doing, let me surface out what kind of solutions you're doing, that's where all of the energy and the excitement happens because then you start to discover, oh, I didn't know. Folks are working on this and this, hey we've got the same problem and especially in public sector where folks so often have the challenge of different siloes. I didn't know what I didn't know, how can we bring them all together, so seeing that here in public sector where we can champion, you've got all of these different folks who are working together, it's just a wonderful opportunity. >> And what are you hearing? The big theme here is about IT modernization in the public sector, the public sector, for better or for worse has a reputation of being a little slow or a little more antiquated, there's certain divisions of the government in particular and educational institutions that are incredibly innovative. >> Absolutely. >> Rebecca: Where do you think things stand right now? >> There's absolutely positive change and I like to celebrate here are the leaders and here are the folks that are doing more, yes, public sector does, for good reasons in some cases take a long time to say, how do we want to change, do we feel safe for this change, et cetera, but then you see pockets of excellence. I'm currently based in Sydney, Australia. Transport for New South Wales is one of our clients and I am honored and excited by all that they're doing where at the executive level you have buy-in and you have support. You have support for saying we need organizational change. You have support for saying, let's do proof of concept, let's do these explorations, let's actually have a startup accelerator hub so we as public sector can interact with startups and early-stage founders or university students to make that kind of a difference. When you see that, that's part of why, okay great, we're in Australia now because there's this energy and action and a willingness to move so that's where I think look to those centers of excellence and say, how can we do that within our organization and what can we do better. >> But not saying that we're not seeing quite that energy in the US or how did you think about the differences? >> Again, it depends district by district. Different municipalities have different challenges, different size, et cetera. When you look at this, for example, in San Francisco where you have the Startup in Residence program, started off small, cohort, five or six companies, great, now how can we scale that program and make it national where they had something like 700 applications for maybe a cohort of 50 or 60 companies that are working. That's where you start to see there's an energy that's flowing through, so I think the opportunity for change comes in that kind of cross collaboration and if you have an event like this where you've got public sector folks from all over the world saying, really interesting, you feel my pain, how can we work together on this, what's your team doing, how can I learn from that, how can I take that back to my teams or where can we think about some of the harder problems of organizational change and what do we do if we don't have that executive champion, how can we start to get there? I think that's the kind of energy and opportunity of all the things we're seeing here at Public Sector Summit. >> But as you said, it's also looking for the rest of us, looking at these centers of excellence, see what they're doing, see how they're experimenting, getting those proofs of concept and then saying, hey, we've got something there, let's see if we can replicate this. >> Absolutely, and within public sector, when you have that opportunity to say, and look at how we're doing this in London, look at how we're doing this in Toronto, look at how we're doing this in Sydney and how we're doing this in Melbourne then you can suddenly go back to New York and say, okay great, we do have these other examples, it is being done so we can use that as a guide for what we wanted to do as we continue to innovate. >> What are some of the most exciting things that you're seeing here, some new public sector initiatives, technology, services that you think are really going to be game changers. >> How much time do we have? (laughing) First off, the energy to we want to collaborate, we want to be more agile, we want to make a difference. The sense that this event has grown from just a small cohort to 1,000, couple of thousand, now I believe there's something like 15,000 attendees. >> 18,000 according to Theresa Carlson. >> Think about the fact that we're all willing to be here together, that's a line in the sand that we need to be able to do more, so it's not about a particular technology per se, but willingness to say, we need to be here, we need to face these problems. We've got this challenge of should we bring these legacy systems over, should we think about how we want to work together in public product partnerships that we can all come together and start to work at this and also think about, we've got Public Sector Summits throughout the world, please join us at Canberra Summit that's going to be going on in late August. We've got Tokyo Summit going on right now, so it's not just all here in D.C., you're starting to see these clusters move out and that's really wonderful and exciting for us. >> It's wonderful and exciting on the one hand and yet this summit is taking place against a backdrop where we're seeing a real backlash against technology. The public sentiment has really soured, regulators and lawmakers are sharpening their blades and saying, hey, maybe we should pay attention more to what these technology companies are doing and just how powerful they've become in all of our daily lives. What's the sentiment that you're hearing on the ground, particularly as the founder yourself. >> I think that's where knowledge can be powerful. Can we empathize with some of the challenges? I hope that all companies choose to act with integrity, not necessarily that they do, but there are a lot of folks saying, we need to be able to do more. From a policy perspective, how can tech companies partner with policymakers who may not understand how all of these technologies work and what they're capable of or not capable of, we need more clarity on that because I think that's where it becomes a black box of conflict and if you can change it to say, this is challenges that you have with facial recognition or sentiment analysis or what have you, let's really think about do the systems today do, what are the guard rails that we need to put in and how can we work as partners with policymakers so it's not just driven by lobbyists but there's actually an understanding of, this is the implication of these systems. >> Here are the unintended consequences. >> Absolutely and if I can come back to New York for a second, New York City has one of the strongest open data logs in the nation. Part of that is because Gale Brewer, the Borough President of Manhattan said we need to formalize this. How do we put this together? She didn't come from a tech background, but she saw a problem that needed to be solved and she said, how do we put this together and how do we get the right folks to the table to think about doing this in a really scalable, meaningful way, so the more that we see those opportunities in that backdrop of tensions and concerns, that's how we move forward, facing those hard questions. It's not Rome was built in a day, it's not. It's going to take us a lot of time and there's a lot of unanswered ethical questions as well that we have to start really thinking deeply about. >> But it starts, as you said, with making the data visible and then getting more voices who-- >> Making it visible and also understanding what's not included in the data. Coming back to when I started my company, there was a lot of, but this isn't being counted and what happens when you're saying, I'm making a bias based on this particular dataset that leaves out this whole community over here. Can we think about what's not included in that data or how the data collection itself or the organization itself is changing things, so that's why, coming back to, you need more female founders, you need more underrepresented populations to have those voices of have you considered this, have you given representation to this particular group, to this population. Without doing that, then you're just reinforcing the same siloes and the same biases and we have an obligation to our community and to one another to change that. >> I know you have a keen interest in diversity issues and, as you're talking about, bringing in more women and more underrepresented minorities to lend their perspective to these very important issues that are shaping our lives. How do we solve this problem? Technology has such a bro culture and we're seeing the problems with that. >> First off, from a founder's point of view, you have to know when not to listen, you have to know when not to let someone shut you down because they'll say-- >> The noise. >> Oh my goodness, the noise of, we've got ageism, we've got sexism, we've got racism, we've got elitism. I went to Brooklyn College, I'm very proud of that fact. I had venture capitalists say, I don't want to invest in you, you're too old and you didn't go to a pedigree school, well guess what, my company's still here, some of the folks you've invested in, they folded a long time ago, so part of it is a willingness to drive forward but it's also building networks of support. Coming back to being the community hero, how can I elevate these voices and say, we need to give them an opportunity to be here, we need to change this, so part of it is we want more seats at the table, but if that table's not going to welcome me, I'm creating a whole 'nother table over here where we can start to have that cluster effect and that's where the dedication, the tenacity and you see things like we power tech, where we're really looking to elevate those voices. That change can't happen unless we keep doing that and unless the folks who are like, but this is how we've always done it, are willing to say, actually, shortcoming here, let's think about changing this and broadening the conversation. >> Is that changing though? >> We were talking a lot about how there's a new generation of workers coming up who do think differently and they do grow up with this stuff and they say, we don't need this red tape, why is this taking so long? They're impatient and maybe a more willingness to listen to other voices, are you seeing a difference? >> Absolutely, I'm seeing a difference for sure. That doesn't mean sexism, ageism, elitism has gone away. It has not, but you're starting to see, again, clusters of excellence and I think if you really want to make change you focus on where that traction is, use that as your foothold to build and scale and then start to be able to do more because that's the only way. We've got some barriers that for other founders I empathize with how insurmountable it can be, but if you've got that dedication, if you refuse to be defined by what someone else says you are or what your company is capable of being and then you find those great partners to say, let's do this together, the whole conversation changes. >> Aileen Gemma Smith those are great words to end on. Thank you so much for coming on the Cube. >> Absolute pleasure, thank you. >> I'm Rebecca Knight, we will have much more of the Cube's live coverage of the AWS Public Sector Summit here in Washington D.C. coming up in just a bit. (techno music)

>> Narrator: Live. From Atlanta Georgia. It's theCUBE. Covering, Citrix Synergy, Atlanta 2019. Brought to you by Citrix. >> Hey, Welcome back to theCUBE. Lisa Martin with Keith Townsend and we're comin' to you Live from Atlanta, Georgia. The Showfloor from Citrix Synergy 2019. We're excited to welcome to theCUBE for the first time Simon Bray. Principle and Head of Leadership and Culture at Vega Factor. Simon, welcome to theCUBE. >> Thanks very much. Great to be here. >> So, I was doing some stalkin' of you online as I do for every guest. >> Simon: Thank you. >> Yup. And I read you're a culture Agent based in New York City. >> Simon: Yes. >> Then you come on set and I'm like , you're not originally from New York City. >> Simon: That is correct. >> You're a transplant and you hail from Brooklyn. >> Simon: Yes, I do. >> Which is where my mom Cathy Dally is from. >> Simon: Very nice, very nice. >> She will love you automatically because you live in Brooklyn. >> Keith: (laughter) >> I consider myself to be a New Yorker. I moved to New York in early 2006. So 14 years, and I think I can make that claim. Although, I am originally form London. >> I would say so. Although your accent is still identifiable. >> Simon: I keep-- I try to keep the accent. >> I mistaked it for a Texas accent, so that's--. >> Texas? >> Yeah. >> Yeah, yeah. >> Got confused? Oh there you go. >> I get that a lot. >> I bet. Yeah. Well, regardless of that you're a Culture Agent. >> Simon: Yes. >> What is that? >> Simon: Okay. >> Because we talk about Cultural Transformation and Corporate Cultures and how employee experience is essential. But Culture Agent, I just thought that was very interesting. >> Yes, so my job is to help organizations create great cultures. Essentially, our theory at Vega Factor is that to create a great culture-- First of all you need to make sure that you build an adaptive organization. So one that is able to change, is able to flex is able to innovate. So that's kind of part one. So my role is really to help organizations become more adaptive. The way that I do that is by trying to -- create an operating model in an organization that is highly motivating. We've developed a way of measuring motivation. We call it TOMO. Where, essentially you look at trying to create a system which drives up the Play, Purpose and Potential the individuals feel. Play is enjoying the work. Purpose is when people feel like they're makin' a difference. And Potential, is when people feel like they're developing and growing. And minimizing the emotional pressure, economic pressure and inertia people feel. So were tyin' to design an operating model that drives that up in order to help people become more adaptive. So my work is to work with leaders and organizations all over the place to help them apply the science of that approach to become more adaptive. >> Lisa: That's awesome. So I've heard of FOMO. >> Okay. >> Fear of missing out. Which I imagine -- everybody that's not here at Citrix Synergy has FOMO. >> Well, of course. It's incredible. >> I know JOMO, I don't have that right now goin' on. >> (giggles). >> TOMO. >> Yes. >> Total, motivation? >> Total motivation. Yeah, so we were asking ourselves the question how do you get people to turn up and do their best work? You know, how do you get people to be motivated not just to do what it says on their job description. To actually lean into their role. To be constantly thinking about how to improve it. About how to innovate, about to problem solve. About how to collaborate. When times are tough. And really what it boiled down to is really simple insight. Which is why we work, determines how well we work. So we started lookin' at the psychology behind motivation. That's where we developed this frame work we call TOMO or total motivation. Which is where we're lookin' at trying to get people to turn up and be excited for themselves. Versus doing things because they're being pressured to do it by external forces. >> Keith: So a lot-- a lot of great conversation on stage this mornin' talking about employee experience, employee's not getting disenfranchised or feelin' unmotivated about their jobs. What are some of the largest factors you see, did what Citrix shared this morning correlate with what you're seeing when you're talkin' to clients? >> Simon: 100%, Yeah. I think what was interesting this morning was the focus on not just the technology but the peoples side of things. And making sure that there's a close partnership between people and technology. And really seeing that through the lens of the overall employee experience. The way that we see the employee experience is everything that affects somebody's motivation in an organization is part of the employee experience. So, everything from the way that you frame up your purpose and identity as an organization. To the way that you organize yourselves and design roles and teams. To the way that you work together as a team. To the way that you set up governance, planning, the talent and performance systems. All of these things can be designed poorly. And therefore create disengagement and lack of motivation. They can also be designed really well. To drive that play, purpose and potential that I talked about earlier on. And as I said before, our work is all about helping organizations design the system within which people work to maximize TOMO. And that's our answer to some of the issues that were raised this morning about employees being disengaged. Our view is that that's just not good enough. You need to make sure that you're really focusing on how to make sure that people turn up and do their best work. And then the technology side of it is making sure that they're equipped with the tools, of course, that they need to do that. >> So, where do you start when organizations come to you in the Vega Factor and say, Hey guys, whether it's a younger organization that I would think on one hand might have an advantage being younger, maybe less kind of cultural biases built in. Versus an organization that might be a competitor with Citrix. Who's been around for decades and has a very, probably I don't want to say static culture. But probably a lot of cultural elements really locked in. What's the starting point? For that fresher organization versus a legacy organization? Are there any overlaps with where you guys recommend, all right this where we got to go. >> Yeah, I think the same overall framework applies. But just in a slightly different way. So, the way we start our conversations often is by defining performance as being, having two parts. The first part of performance is tactical performance. Which is all about strategy, planning and execution. And doing that as efficiently as possible. So tactical performance is really important. And then there's also the adaptive performance. Adaptive performance is how effectively can you diverge from the plan. Reacting to context changes, innovating, problem solving, solving issues. And those two types of performance are both important but they're opposing. So if you have too much tactical performance, you end up being very rigid. And it kills your ability to be adaptive. If you have too much adaptive performance you end up reinventing things all of the time and having no tactical performance and being a bit chaotic. I share that because when we look at two different types of company. Call it a legacy organization and a high growth start up. We often find that that high growth start ups have too much adaptive performance and that eats their ability to be tactical performance. People go crazy, because they're reinventing themselves all the time. And they haven't got the processes and systems so a lot of times with those organizations it's all about getting clear, on some of the basics. What are the guard rails within which we operate. What is our purpose, and identity? How do we want to organize? So that's all about helping a highly adaptive organization improve their tactical performance. Then the other side of it is a legacy organization. You know, think of any big mega organization. Where, actually as they've grown they've shifted from being really adaptive into being really tactical. They put in place processes and policies and structures, to help them manage their scale. The issue is, is that in doing that they can often lose their ability to be adaptive, By becoming bureaucratic. So, with those organizations a lot of our work is how can you, without losing that tactical performance create the space, and autonomy for teams to be able to be adaptive at the same time? So that's kind of where we come. Same framework, but actually a start point that's really quite different. >> So, let's talk about scale. Small organizations, start ups, I can see how that approach can be very deliberate. You can, spend a percentage of your time building culture. Let's talk about the big battle ships. When your goin' into a large organization. How does a large organization where it's very difficult to impact change and culture change. How do large organization's tackle this challenge? >> That's a great question. You're right, it is much harder to work within a big organization to affect change. I think the way that we would typically approach it is first of all, not to try to change a big organization at the same time. You know, it's hard to change the behavior of a thousands of people quickly. And so what we try to do is to start by taking a small part of the organization. To actually, show using that organization what good looks like. To, and then build from that. So, show the rest of the organization how this can work, how you can manage both tactical and adaptive performance. How you can create a high TOMO way of working. Then we find, that people gradually follow on from there. What's really important about that is, one you're not trying to boil the ocean. But secondly, you're showing people what good looks like and you're giving them the opportunity to opt in. And I found that when people opt into change and they start pulling for it that's a much better way to affect change versus operate in a situation where change is something that's done to people. Where people are told what to do. >> Lisa: It's being pushed on them. >> Yeah exactly. >> Lisa: Right, naturally, you're going to get resistance there. >> Yeah. For sure. >> Some of the stats that we heard this morning and Keith and I are both living this. I think I heard, maybe it was within the last week that by 2020, which is literally around the corner that 50% of the work force is going to be remote. >> Simon: Yeah. >> And I think they were saying this morning that in the next few years there's going to be 65 billion connected devices. With each person having about eight different connected devices. Keith and I are here with out different devices. Where do you see, the necessity of delivering mobile experiences. But also, for cultural impact for businesses, small or large to enable workers to be remote and give them access? Rather than forcing that they sit on a train for an hour, or in the car, and be in the office. Where is that conversation in the Vega platform? >> Yeah, it's an interesting one. So, one of the things that we spend quite a lot of time doing, is working with individual teams to help them operate more as a team. One of the things I found quite surprising in my work with different types of organizations is that often teams are connected by a common manager, but essentially are a collection of individual contributors who aren't actually working on shared issues. So, one of the first things that we like to do is to help teams re-orient themselves around the shared purpose. And, set themselves challenges for things that they want to solve together to improve their collective performance. So that's a foundational piece. Once we've done that, then the next question becomes, to answer your question, how do you get teams to problem solve together effectively. And there's two different times when teams problem solve. One is what we would call synchronously. Synchronicity is where teams need to get together physically, and actually brain storm and kick around a problem. And there is a time and a place to do that. That's why its still important to have get-togethers and to create that human connection. But actually more and more we find that teams need to also be able to solve problems in parallel asynchronously. And I think that's where technology comes in. Technology allows teams to work together on problems but not all be in the same place at the same time. To be able to do that in parallel and whenever they want to. It's when you get that asynchronous problem solving and synchronous problem solving that you can get teams to generally work together and that way we find people perform at a much higher level than if they're essentially just focusing on the job that they have. >> So obviously, you work across industries, groups and type of functions. Can you share with us some correlation between TOMO, the rise in kind of this-- employee experience measure and performance? Like, what are some of the key indicators that culture is improving performance? >> That's a great question as well. So, one of the things that we spend a lot of time doing in our early research is trying to quantify culture. Because you know, most of us would agree that culture is important but it becomes something that can easily get shunted down the list. Or seen as a nice to have (mumbles) especially if times are tough. So we spend a lot of time trying to measure culture and then to be able to to show a correlation between that measure and the performance of a business. So, the first thing that we did is say well how do you measure culture? And our way of measuring culture is the degree to which people are motivated. So this comes back to TOMO. The way that we calculate TOMO is by adding up the play, purpose and potential that somebody feels. And subtracting the emotional pressure, economic pressure and inertia they feel. And these are weighted according to their proximity to the work. And they end up giving us a nice neat score between minus 100 and positive 100. Like a net promoters score. We get that number by asking them six multiple choice questions. So it's two or three minutes. That gives us an individual score but also of course, we can measure that organizationally. We then looked at the correlation between that score and the performances of business across a range of different industries. And we show a straight line correlation between TOMO and business performance. So as an example, we looked at the airline industry. And we looked at the TOMO of most of the U.S airlines. And we found that the highest TOMO airline -- Can you guess what the highest TOMO airline is? >> Lisa: JetBlue? Southwest? >> Southwest. >> Keith: I was going to say SouthWest. >> JetBlue is second. So we found that when you walk on a Southwest or JetBlue airplane you feel great. It feels different. Because the employees, the flight crew, turn up in a different way. That's because their TOMO is higher. And as a result the performance of Southwest particularly around elements like Customer Experience, Customer Satisfaction is significantly higher than the rest. The lowest TOMO airline in our data set is United. Now-- >> Lisa: I was going to guess that. >> Keith: (laughter) >> Now, if you think of TOMO low TOMO tends to be when people either have low play, purpose and potential. They're not enjoying their job they don't feel like their makin' a difference or they're not learning. Or the system they're in is very high pressured. High emotional pressure, economic pressure. That creates a lower business performance. It can also have a negative effects from a behavioral point of view. As an example, if you saw the story a couple of years ago where United had a big scandal where someone was pulled, man-handled off one of their planes. That's a predictable affect of low TOMO. Our data, our research was done two years before that happened. And we would've been able to predict that United would have issues based upon their low TOMO score. To try to explain, and I wasn't there of course. But to try to explain what happened through the lens of TOMO. If you create a very high pressure system where the ground staff, are being essentially measured on their ability to get the plane to take off on time. When a passenger sits, and refuses to move, because of the pressure the ground crew are under they forget what the right thing to do is. Because of their low TOMO and pressure they ended up man-handling the passenger off. United lost a billion dollars in their share price. And that's a predictable, what we call a cobra affects. Which, is where people kind of feel like they have to cheat or short cut the system, that we are predicting is a result of low TOMO. >> So, we're almost out of time here but I'm so curious, how do you -- what the incentives are, for United airlines to really look at that kind of experience that goes viral on social media and these things happen, I don't want to say all the time. But that was not an isolated incident. >> Simon: Absolutely not. >> So for a company like that that's making money hand over fist flights are always sold out. They're not hurting for business. What incentivizes a business like that to flip that TOMO scale? >> Yeah, it's a great question. I think it's really difficult to make any kind of change happen when you're doing okay. First of all. And that's difficult. But the reality is is that, if you had measured the TOMO of United, and there are many other examples I am not just trying to pick on them. You would've been able to guess that this would happen. And so, our advise to organizations is regardless of how successful you are regardless of how well your business results are in the short term. You need to be thinking long term about culture. You need to be thinking about what is the operating system that you're putting your employees into. And getting ahead of what could be consequences that happen down the stream as a result of well intended moves that you make now to improve your tactical performance. >> Awesome, Simon. This has been so interesting. I learned a new acronym >> Together: TOMO. >> It's some great stuff. >> Lisa: I want to have TOMO everyday, and I'm going to really work on that. Being on theCUBE it's not hard to achieve that. >> Simon: This is great. >> Well Simon, we, Keith and I so appreciate you comin' by and sharing what you guys are doin' at Vega. And really, really interesting. TOMO. >> Thank you very much. Thanks guys. >> Lisa: Our pleasure. For Keith Townsend, I am Lisa Martin. You're watching theCUBE Live on the show floor of Citrix Synergy 2019, from Atlanta Georgia. Thanks for watching.

>> Live from Washington, D.C., it's theCUBE! Covering Inforum D.C. 2018. Brought to you by Infor. >> Good afternoon, and welcome back to the Walter Washington Convention Center, we're at Inforum 2018, here live on theCUBE, John Walls with Dave Vellante, and it's a pleasure now to welcome the CEO of Infor, Charles Phillips with us. Charles, good to see ya! >> Good to see you guys again, another year. It's great, it's great. >> Yeah, I tell ya, you are a man of demand aren't you? I mean, tell me about the week so far for you, how it's gone, and just your overall thoughts about the show? >> Yeah, it's been a fun Inforum for 2018 here. Great attendance, and a lot of energy level, and the common feedback we get is you guys just keep innovating and bringing new things, this is great, and that's why they come, they want to see what we're working on and kind of dream the art of the possible. We know what you, what we think you get a couple years ago, but if we don't have someone pushing us and painting a picture of what we could be doing, and we just think we might be missing it, so we want to hear it first hand. So that's what the conference is about, and hopefully they got that. >> Well, certainly thematically, human potential, you talk about that, you see that on the keynote stage, that's been a very consistent theme with our guests here, we've heard that a lot, you hear it down on the show floor. Talk about the theme if you would, a little bit, in terms of it's development, where that came from, and in how you think that's being expressed here this week. >> Well, we're one of the few companies that build mission critical operational systems, be it manufacturing or hospital operations, but we're also in HCM in a big way. And so we were talking to kind of both sides of the house, for some applications you're talking to the line of business manager, but for HCM you're talking to the CHRO, and rarely were those two people talking, and we saw obvious synergies. Don't you want to know how your people are doing, how to allocate people, and how they're performing, how they're changing the outcomes on a manufacturing floor or in a hospital, and a lot of HR directors weren't thinking like that because they think of HR, and they have their own world, they go to HR conferences and that's it. And the manufacturing guys are the same thing, and so we're trying to bring these two worlds together and say "Actually, you're in the same business, it's the same goals, and you actually could help each other a lot." And so by focusing on putting the employee at the center of all these applications and mapping all these operational processes to HR data, it's a different way of thinking about the role of HR. They can actually help drive the business, not just be an administrative function, and so it's resonating with a lot of the CHROs we met with, 'cause they want a seat at the table, they want to be more strategic, and this is a way for them to do that and at the same time the operational people want to know how their people are doing, want to develop talent, and want to know what are the tools out there I could be doing differently, and how am I doing, and which employees are working the best So, I think we can bring both sides together. >> So I first met Infor through AWS, at re:Invent, Pam Murphy came on, and we were like Infor? Back then it was like 2012, 2013 was kind of Infor who? And then we were invited to New Orleans, and then started to learn more about your micro-vertical strategy and a little bit about the platform, it was somewhat opaque to me. And now, fast forward last year and this year it's really starting to come in to view. The OS, the platform vision, the Birst acquisition, and of course Coleman, and I'm a sucker for platform plays especially when there's real R&D behind it that's actually having a business impact. So I wonder if you could talk about that piece of the strategy, I love the stack, was that sort of always your vision and now you're getting aggressive in it, did it sort of come together serendipitously, how'd we get here? >> Having our own stack and a platform was always the vision, but it's a lot harder to do than it sounds like, and it takes time. And so, when we arrived almost eight years ago, there were different applications, all had their own separate stacks and would say "This is not going to work." So, we need, just to be able to scale, to be able to serve multiple industries with different products, we can't have every development organization building their stack as well. So we set about taking that away from the development groups we're going to do this as a shared service, but it takes time, and as we build it you will adopt components of it. So what's changed is we've built out the entire stack, so, starting with ION, with integration, then we added document management, workflow, analytics, now AI and a lot of other services, Mongoose, platform as a service, on and on and on, in collaboration, those things took time, they're all on a single platform, federated security, single siloed across it all, and now it makes the developers job who's developing apps so much simpler. So they have Infor OS for the immediate platform, for cloud services they have AWS, I don't have to worry about any of those things anymore, just go and develop industry functionality. So, it's come together nicely, but the fact that we had the time to do it and the money to do it, and we weren't public, and we told our investors "This is the only way this is going to scale, this is the future, and it'll pay out later, you just got to trust us." And now that we've gotten there, they're seeing the synergy and go "Okay, now we see why you did that." >> So, Michael Dell's been on theCUBE many times, he used to talk about the 90 day shot clock, we obviously see what he's done in terms of transforming; but I want to talk about your business a little bit, because you've had that patient capital, I mean you're a quasi-public company in the sense that you do report so we can see the numbers on the income statement, but the income statement doesn't really tell the whole story It's about three billion in revenue, several hundred billion dollars on the balance sheet, but if you look at the SaaS component of it it looks rather small, maybe about 25% of the business, but from a booking standpoint I'm sure it's much, much larger than that. So how should we interpret the income statement in terms of the momentum in your business, where is all the action? >> So as a percentage of our sales, it's the highest of any of our competitors, so, about 70% of our new sales are on SaaS, we have about a $700 million SaaS business, so it's growing. There's nothing we can do about the maintenance piece of it, if it's related to perpetual, so if you take that out, it's a big percentage of our business. And over time the maintenance will turn into SaaS, so that's one of our big opportunities to look at that maintenance space and say "Move those over to cloud customers." and that's usually a financially lucrative thing for us to do, because we do even more for them, because they usually add on four or five other products when they move, they replace these third party products and so we get a bigger suite of products if they decide to move to the cloud. So that's part of the strategy, that's what UpgradeX is, let's move you from on-premise, so that maintenance revenue will turn into SaaS revenue, but bigger SaaS revenue over time. >> So let me make sure I understand, so it's not the classic case where you see a lot of software companies that are going from a perpetual model to a ratable model, you're goin' from a maintenance model which is ratable to a ratable model which is SaaS, but there's cohorts sales which increase the top line, is that correct? >> Exactly. So usually, because of what we do, we're doing something mission critical. So if you're going to take that, then you should do ACM financials, all the other things around it. So why would I move to core and leave the edge on-premise? So, almost by definition we have to do the whole suite. So when we do that it expands the deal, 'cause on-premise we may have been one vendor with 30 other ones existing, but the whole reason they want to get out of all of that is to move to the cloud and simplify. So we can't take all that with us, so we have to have the full suites, we've built that now. So now we can move them, but, it expands the size of the deal because we're replacing all these other products. >> Okay, and then some of the stats, just correct me if I don't get this right. Your SaaS business grown 50% faster than Oracle's, growing at a rate, I'd say 2X SAP's and a rate comparable to Workday, are those correct figures? >> Those are correct, and profitable. >> Oh, and profitable. >> Throw that in. (all laugh) >> Right, so okay. And then last year Koch Industries invested, so you kind of recap the company, you've made a big deal about that. One of the things that we've noted is you're seeing a tailwind there in terms of guys like Accenture and Capgemini, we've asked them "Do you guys service Koch Industries?" they said "Yep!" they helped us see the opportunity, and they said "Look, look for something substantive, we're not going to try to force you to do something, but we want you to take a look." So that's been helpful. Talk about that and maybe other things Koch has brought to the table? >> It's a, the relationship with the integrators is evolving, it probably was not a plus for us in the first four, five years. More recent years we've won enough deals where they had to say "Okay, we can't keep losin' these deals." And where they wanted to get engaged. Koch helped, because they had relationships and they wanted to run that business, that's why they're implementing our products globally, and so, they're a large customer for all of these guys, and one of the largest for Deloitte for instance, but what's really more-- that helped, but it was more the, what was happening in the market, the fact that we're in a Liberty Steel and replace SAP, or that we're in a Travis Perkins interview with SAP and Microsoft, so, if you're on the wrong side of those deals enough times your manager starts to ask you what's goin' on, and you got all these people on the bench here, okay, we train them for Infor if they're winning in that region, or in that industry. So, we just had to earn our way into it, our initial strategy was not one that, at least on the surface, looked like it was integrator-friendly because we were trying to take all those mods they like to do and put 'em in the product, and that's the whole thesis, let's the take the vertical industry features and let's put it in there once, I don't want everybody customizing my apps, we do that. And so now they've had to move up, okay we can do other things, configuration, changed management, there's AI, there's other things you can do, but you're not going to do that. So now that they've accepted that, there's a basis for us to work together, and, it just had to take time to get there. >> What can you tell us about where you want to go with this? I mean you've presided over public companies before, you know that business well, you were a rockstar analyst, is there an advantage to being a public company, is that something that you eventually want to do? >> I would say there are pluses and minuses, our board is evaluating that, that's going to be their call. The upside is, it would solve probably our biggest challenge which is brand recognition, almost instantly, because would be a top 10 tech IPO. It makes it a little easier to hire people because they can see public currency, they can value more quickly, and it gives you some acquisition currency; so those are the positives. But then you're on the 90 day cycle, and we're kind of on that anyway, 'cause we report publicly and we have publicly traded bonds. So for us it's, in some sense we have the worst of all worlds, right? We have the discipline of being a public company, and the scrutiny, without the capital, (laughs) and the branding, so. I think that's what everybody's evaluating. Every bank on Wall Street's visiting us telling us to go now, the window's great, you have the numbers. >> Oh, of course. (Dave and John laugh) >> And so, so we could do it, I just don't know what their decision's going to be. The advantages to being private as well, you have a little more flexibility obviously, and, we don't need the capital, we have plenty of capital coming from Koch and others who want to invest. >> Well, the flip side of that too, is you get to write your own narrative, right? >> Yeah. >> I mean, we're talkin' about the nuances of the income statement, the Street is obviously right now hooked on growth heroin, and if you got the transition in the base it doesn't become a tailwind, so, no rush from that standpoint. I want to pivot to the theme of this event, which is the human potential. My understanding is you sort of were instrumental in coming up with that. HCM this year got a big play on stage, where's that come from? >> Yeah, just as I talk to CEOs who are struggling to find talent, like I mentioned on stage 6.7 million jobs that are unfulfilled. It's not like we don't have people here, we have people here with their own skills, so, you're not going to fill those jobs any other way, we're not doing immigration to any degree and scaling more, that's been shut down. We have an aging population with the baby boomers, so the most logical thing that you would do is train people who are already here who want to work. And, let's take people who have jobs that they probably aren't thrilled about, and give them different skills so they can fill these 6.7 million jobs. So to do that, you have to make these applications easier to use, and I felt like we're probably in the best position to do it because we actually know what they do for a living, 'cause we wrote all those last features in those industries, we understand what they do. And if you're just doin' HR replication or financials, you actually have no idea what they do. So, we had to learn those jobs to automate those jobs, so we can find ways to use our HCM applications to better train people, professional development, coaching, take all these HR skills, and put them as part of the applications in the context of while you're working. >> We had Anne Benedict on just a little bit ago talking about really a test case that you can be for yourself. So how are you putting these things to practice yourself, and how are you working out maybe some kinks before you take them out to somebody else? And so, you can leverage your own success for your own success, and also learn from mistakes too I would think. >> We do. So we have this program called Infor at Infor, where everything we do, we want it to be on an Infor product, which was not the case when we arrived. Like a lot of companies, a mish mash of different things, and so we've implemented not only HR Financials of course, Birst, but the big innovation has really been talent science, that every employee we hire has to take that test, and all the executives have taken it as well. And what we've discovered is, is that, when people hire and go against the talent science recommendation, 68% of the time they end up being wrong. So it's better at judging people than people are sometimes, and you can't use it exclusively, but it'll tell you these are the things you should look into, some questions you might want to ask, here's how they rate on certain skillsets, they're very well meshed for this job, they look like they'd see their best performance in this area, but ask these questions. And so people don't know how to interview and how to think about this, and so, having a guide to go into an interview is actually pretty helpful. We hire much better people now by using that. >> So it's like StrengthsFinder in a way? >> No, it's different from that, this is AI, it's kind of Moneyball for business people. >> Well you're talking about that today, almost there. >> Yeah so it's 39 personality attributes, behavioral attributes we call them, so, empathy, resistance to authority, do you have the ambition or not, and depending on the job, you think all those things are good, depends on the job, so. For some jobs, it's actually better to have low ambition because, a lot of our customers who have low wage, fast food service jobs, people who have ambition are going to leave in four months, right? They're not going to stay, so, okay we're not going to be here long, at least know that going in, and know who wants to get promoted, and other people are fine with it. And so it depends on the mix of skills, just like I said, 39 attributes, and for that job role, you tune it to the people who like that job, they look like this. And, we've also found that it's 60% more diverse when you hire using science, because you don't know that when you're looking at the data, what they look like. >> It must've been super interesting getting those reports. You took it, obviously right? >> Yeah I took it. >> How'd you do? (laughs) >> Uhhh, nobody really likes their profile. (all laugh) >> I was going to say, I imagine I would be really defensive about this, oh I don't know. >> This can't be right! >> That is not me! I am not like that! (all laughing) >> Every person on our executive team said the same thing so. That's what it's for is to, you have certain perceptions even about yourself, and it calls it out, right? And there's no gaming the system because the questions have no right or wrong answer, it just puts you in scenarios that you answer what would you do, how do you feel about this? You're not clear what they're trying to get at, and you only have 27 minutes or 22 minutes to do the test. >> So you can't game it? >> You can't game it. >> Data doesn't lie! >> And we built the science, we know when someones trying to game it, they're taking to long on multiples, and changing their answers too much, so it's-- And we've now, I think we've tested some 200 million people over time, over years, so we have 20 years of data about people. >> That's, I mean, sounds unique, certainly unique of being infused into enterprise software, I've not seen anything like this from another enterprise software company. Can you confirm that, or? >> Yeah, so, we're the only ones that do this at scale, there's a few startups trying to do it, but they're trying to do it all facial recognition which is, we think pretty ridiculous, we're trying to get away from physical attributes not use that. So there's a company out there doing that, depending on your facial movements, but this is, we're eliciting responses about your personality in response to situations that we give you, and have a bunch of scientists that crunch the data and they basically shape it to the job role. And they test your best performance, and you get a DNA profile for your best performance for that job role, and then, that's what you're matching, and it's highly accurate. So we had a company on the Las Vegas Strip use it, because they have to hire in volume a lot, and essentially what they wanted to do was get better blackjack dealers. You need somebody that's good at math, good under pressure, not too emotive, don't give away anything; and so we did that, fine tuned the test, they call us back nine months later and said "We need you to change the test." We said "We did exactly what you wanted, what happened?" He said well, the winnings went up 30%, but everybody's leaving the hotel in 24 hours 'cause they lost all their money, so we don't need them to be that good. (all laugh) >> Dial it down a little bit. >> Which we did. And so that's part of the service is we fine tune it, you tell us what your goals are, and we'll tune to that. >> That's a great story. The other surprise for me this week has been the emphasis on robotic process automation, it's a space that we've kina looked at. And a lot of people are scared about software robots replacing humans, but if you talk to people who are using RPA, they love it. It's taking away these mundane tasks, I didn't realize that you guys had such capabilities there? >> Yeah, so we built that as part of a Coleman RPA platform, and not only can we automate and use RPA for ourselves, but we've built a whole development environment for our customers to build their own, 'cause we can't think of every process that they might want to automate, and we gave that platform to our partners as well, so. We don't want them doing database schema work anymore, and they used to get paid for that, there's other things you can do up the stack in AI, here's what we want you to focus on. So we had that meeting on Monday with the partners, and they all agreed that's what we're going to do. But there's tons of mundane things that people shouldn't be spending time on, and they can be much more productive, it makes them more loyal to the company, they're enjoying their job more, and they're thinking and innovating more. So I don't see it as replacing people, as making people better. And giving that engagement that I talked about during the keynote, they're engaged now, because they can do things that are more value adding now. >> So, back to New Orleans next year? That's the first Inforum that theCUBE was ever at was in N'Orleans, and, jazz, you like jazz, obviously, right? >> I like jazz, I met with the mayor when I was down there, Mitch Landrieu at the time, and he became a customer after that meeting, so the city of New Orleans runs on Infor software, it's another reason to go there; so thank you. >> You've get--nice. >> Yeah, thank you Mitch, so that worked well. And so as a thank you we're going back down there, they're a big customer now, and it's always fun, you know what I mean, you know. >> That's great. >> Just, before you go, you mention, I watched in the keynote this morning, Brooks Koepka. >> Yes. So you're working with him. I do a little bit of work on the golf side as well, so I was just intrigued because, he's not the, well he's not Tiger, right? >> Yeah. >> U.S. Open Champion, twice over. What was the attraction to him, and then can you play in the golf world a little bit, and with those brands, and is that an entry into that world? >> Well, we always like to bet on the scrappy guy, the next up and coming generation guy, and that's kind of our brand that's what we are, the Brooklyn Nets, someone who's not quite there yet, but they're moving up, that's kind of our scrappiness, that's why we like the whole Brooklyn image as well. And we started talkin' to him, like I said, before he won the U.S. Open, because he was ranking pretty high, moving up, but wasn't well known. A quite guy, very personable when you meet him, we thought he'd be good in front of clients, let's bet on his career, and we're going to work with him; and literally three weeks later he wins the U.S. Open, we go "Okay." (all laugh) >> Good grab! >> We'll take it! (laughs) So, we didn't even think it'd happen that quickly, and now he's a rockstar so. We were planning on hosting a CX event with him, and, we're not sure how many people are going to come, but when that happened, now, everybody RSVP'd right away of course. So now it's doing exactly what we wanted. >> Do you play golf? >> I don't play golf, I just started playing, 'cause we were doing these golf tournaments with customers over the last year, but I haven't had enough time to get out there yet. >> I'll bet Brooks would give you a lesson or two. (laughs) >> Yeah, he, a lot of people want to lesson from him. >> Charles thank you >> Alright, thank you guys, >> for the time, great show. >> Good to see ya again. See ya in New Orleans. >> Thank you, yeah. >> Congratulations. >> Alright guys, see ya. >> Wonderful week here in Washington, D.C. Back with more live on theCUBE here from D.C. right after this. (bubbly music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by, Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE. We're in Manhattan, New York City, at Automation Anywhere's Imagine Conference 2018. About 1,100 professionals really talking about the future of work bots, and really how automation is gonna help people do the mundane a little bit easier, and hopefully free us all up to do stuff that's a little bit more important, a little higher value. We're excited to have our next guest, he's Craig Le Clair, the VP and Principal Analyst from Forrester, and he's been covering this space for a long time. Craig, great to see ya. >> Yeah, nice to see you, thanks for having me on. >> So, first off, just kind of general impressions of the event? Have you been to this before? It's our first time. >> Yes, I did a talk here last year, so it was a little bit smaller then. There's obviously more people here today, but it's pretty much, I think it was in Brooklyn last year. >> It was in Brooklyn, okay. >> So, this is an upgrade. >> So, RP Robotic Process Automation, more affectionately, probably termed as bots. >> Yeah. >> They're growing, we're seeing more and more time and our own interactions with companies, kind of on the customer service side. How are they changing the face of work? How are they evolving as really a way for companies to get more leverage? >> Yeah, so I'll make one clarification of your sentence, and that's, you know, bots do things on behalf of people. What we're talking to in a call center environment is a chat bot. So, they have the ability to communicate or really, I would say, attempt to communicate with people. They're not doing a very good job of it in my view. But, bots work more in the background, and they'll do things for you, right? So, you know, they're having a tremendous effect. I mean, one of the statistics I was looking at the other day, per one billion dollars of revenue, the average company had about 150 employees in finance and accounting ten years ago. Now, instead of having 120 or 130, it's already down to 70 or 80, and that's because the bots that we're talking about here can mimic that human activity for posting to a general ledger, for switching between applications, and really, move those folks on to different occupations, shall we say. >> Right, right. >> Yeah. >> Well it's funny, Jeff Immelt just gave his little keynote address, and he said, "This is the easiest money you'll find in digital transformation is implementing these types of technology." >> Yeah, it's a good point, and it was a great talk, by the way, by Jeff. But, you know, companies have been under a lot of pressure to digitally transform. >> Right. >> You know, due to really the mobile, you know, mobile peaked around 2012, and that pushed everyone into this gap that companies couldn't really deal with the consumer technology that was out there, right? So then you had the Ubers of the world and digital transformation. So, there's been a tremendous focus on digital transformation, but very little progress. >> Right. >> When we do surveys, only 11% are showing any progress at all. So, along comes this technology, Robotic Process Automation that allows you to build bots without changing any of the back end systems. There's no data integration. You know, there's no APIs involved. There's no big transformation consultants flying in. There's not even a Requirements Document because you're gonna start with recording the actual human activity at a work station. >> Right. >> So, it's been an elixir, you know, frankly for CIOs to go into their boss and say, "You know what, we're doing great, you know, I've just made this invoice process exist in a lot better way." You know, we're on our path to digital transformation. >> And it's really a different strategy, because, like you said, it's not kind of rip and replace the old infrastructure, you're not rewriting a lot of applications, you're really overlaying it, right? >> Which is one of the potential downfalls is that, you know, sometimes you need to move to that new cloud platform. You don't want, to some extent, the technology institutionalizes what could be a very bad process, one that needs to be modernized, one that needs to be blown up. You know, we're still using the airline reservation systems from 1950s, and layers, and layers, and layers and layers built upon them. At some point, you're gonna have to design a new experience with new technology, so there's some dangers with the seduction of building bots against core systems. >> Right, so the other thing that's happening is the ongoing, I love Moore's Law, it's much more about an attitude then the physics of a microprocessor, but you know, compute, and store, and networking, 5Gs just around the corner, cloud-based systems now really make that available in a much different way, and as you said, mobile experience delivers it to us. So as those continue to march on and asymptomatically approach zero and infinite scale, we're not there yet, but we're everyday getting a little bit closer. Now we're seeing AI, we're seeing machine-learning, >> Yes. >> We're seeing a new kind of class of horsepower, if you will, that just wasn't available before at the scale it's at today. So, now you throw that into the mix, these guys have been around 14 years, how does AI start to really impact things? >> It's a fascinating subject and question. I mean, we're, at Forrester, talking about the forces of automation. And, by the way, RPA is just a subset of a whole set of technologies: AI, you mentioned, and AI is a subset of automation, and there's Deep Learning, is a subset of AI and you go on and on, there are 30, 40 different automation technologies. And these will have tremendous force, both on jobs in the future, and on shifting control really to machines. So, right now, you can look at this little bubble we had of consumer technology and mobile, shifting a lot of power to the consumer, and that's been great for our convenience, but now with algorithms being developed that are gonna make more and more decisions, you could argue that the power is going to shift back to those who own the machines, and those who own the algorithms. So, there's a power shift, a control shift that we're really concerned about. There's a convergence of the physical and digital world, which is IOT and so forth, and that's going to drive new scale in companies, which are gonna further dehumanize some of our life, right? So that affects, it squeezes humans out of the process. Blockchain gets rid of intermediaries that are there to really transfer ideas and money and so forth. So, all of these forces of automation, which we think is gonna be the next big conversation in the industry, are gonna have tremendous effect societally and in business. >> Right. Well, there's certainly, you know, there's the case where you just you can't necessarily rescale a whole class of an occupation, right? The one that we're all watching for, obviously, is truck drivers, right? Employs a ton of people, autonomous vehicles are right around the corner. >> Right. >> On the other hand, there's going to be new jobs that we don't even know what they're gonna be yet, to quote all the graduating seniors, it's graduation season, most of them are going to work in jobs that don't even exist 10 years from now. >> Correct, correct, very true. >> And the other thing is every company we talk to has got tons of open reqs, and they can't get enough people to fulfill what they need, and then Mihir, I think touched on an interesting point in the keynote, where, ya know, now we're starting to see literal population growth slow down in developed countries, >> Yes. >> Like in Japan is at the leading edge, and you mentioned Europe, and I'm not sure where the US is, so it's kind of this interesting dichotomy: On one side, machines are going to take more and more of our jobs, or more and more portions of our job. On the other hand, we don't have people to do those jobs necessarily anyway, not necessarily today, but down the road, and you know, will we get to more of this nirvana-state where people are being used to do higher-value types of activities, and we can push off some of this, the crap and mundane that still, unfortunately, takes such a huge portion of our day to day world? >> Yeah, yeah. So, one thought that some of us believe at Forrester, I being one of them, is that we're at a, kind of, neutral right point now where a lot of the AI, which is really the most disruptive element we're talking about here, our PA is no autonomous learning capability, there's no AI component to our PA. But, when AI kicks in, and we've seen evidence of it as we always do first in the consumer world where it's a light version of AI in Netflix. There's no unlimited spreadsheets sitting there figuring out which one to watch, right? They're taking in data about your behavior, putting you in clusters, mapping them to correlating them, and so forth. We think that business hasn't really gotten going with AI yet, so in other words, this period that you just described, where there seems to be 200,000 people hired every month in the ADP reports, you know, and there's actually 50,000 truck driver jobs open right now. And you see help-wanted signs everywhere. >> Right, right. >> We think that's really just because business hasn't really figured out what to do with technology yet. If you project three or four years, our projections are that there will be a significant number of, particular in the cubicles that our PA attacks, a significant number of dislocation of current employment. And that's going to create this job transformation, we think, is going to be more the issue then replacement. And if you go back in history, automations have always led to transformation. >> Right. >> And I won't go through the examples because we don't have time, but there are many. And we think that's going to be the case here in that automation dividends, we call them, are going to be, are being way underestimated, that they're going to be new opportunities, and so forth. The skills mis-match is the issue that, you know, you have what RPA attacks are the 60 million that are in cubicles today in the US. And the average education there is high school. So, they're not gonna be thrown out of the cubicles and become data scientists overnight, right? So, there's going to be a massive growth in the gig economy, and there's an informal and a formal segment of that, that's going to result in people having to patch together their lives in ways they they hadn't had before, so there's gonna be some pain there. But there are also going to be some strong dividends that will result from this level of productivity that we're gonna see, again, in a few years, cause I think we're at a neutral point right now. >> Well, Amara's Law doesn't get enough credit, right? We overestimate in the short-term, and then underestimate the long-term needs affect. >> Absolutely. >> And one of the big things on AI is really moving from this, in real time, right? And all these fast databases and fast analytics, is we move from a world where we are looking in the rear view mirror and making decisions on what happened in the past to you know, getting more predictive, and then even more prescriptive. >> Yes. >> So, you know, the value unlock there is very very real, I'm never fascinated to be amazed by how much inefficiency there still is every time we go to these conferences. (Craig laughs) You know we thought we solved it all at SAP and ERP, that was clearly-- >> Clearly not the case. Funny work to do. >> But, it's even interesting, even from last year, you mentioned that there the significant delta just from year to year is pretty amazing. >> Yes, I've been amazed at the level of innovation in the core digital worker platforms, the RPA platforms, in the last year has been pretty amazing work. What we were talking about a year ago when I spoke at this conference, and what we're talking about now, the areas are different. You know, we're not talking about basic control of the applications of the desktop. We're talking about integration with text analytics. We're talking about comp combining process mining information with desktop analytics to create new visions of the process. You know, we weren't talking about any of that a year ago. We're talking about bot stores. They're out there, and downloadable robots. Again, not talking about last year at all. So, just a lot of good progress, good solid progress, and I'm very happy to be a part of it. >> And really this kind of the front end scene of so much of the development is manifested on the front end, where we used to always talk about citizen developers back in the day. You know, Fred Luddy, who was just highlighted Service Now, most innovative company. That was his, you know, vision of Citizen Developer. And then we've talked about citizen integrators, which is really an interesting concept, and now we're talking about really citizens, or analysts, having the ability via these tools to do integrations and to deliver new kind of work flows that really weren't possible before unless you were a hardcore programmer. >> Yeah, although I think that conversation is a little bit premature in this space, right? I think that most of the bot development requires programming skills today, and they're going to get more complicated in that most of the bot activities today are doing, you know, three decisions or less. Or they're looking at four or five apps that are involved, or they're doing a series of four or five hundred clicks that they're emulating. And the progression is to get the digital workers to get smarter and incorporating various AI components, so you're going to have to build, be able to deal statistically with algorithm developments, and data, and learning, and all of that. So, it's not.... The core of this, the part of it that's going to be more disruptive to business is going to be done by pretty skilled developers, and programmers, and data scientists, and statistical, you know, folks that are going through. But, having said that, you're going to have a digital workforce that's got to be managed, and you know, has to be viewed as an employee at some level to get the proper governance. So you have to know when that digital worker was born, when they were hired, who do they report to, when were they terminated, and what their performance review is. You gotta be doing performance reviews on the digital workers with the kind of dashboard analytics that we have. And that's the only way to really govern, because the distinction in this category is that you're giving these bots human credentials, and you're letting them access the most trusted application boundaries, areas, in a company. So, you better treat them like employees if you want proper governance. >> Which becomes tricky as Mihir said when you go from one bot to ten bots to ten thousand. Then the management of this becomes not insignificant. >> Right. >> So Craig, I want to give you the last word. You said, you know, big changes since last year. If we sit down a year from now, 2019, _ Oh. >> Lord knows where we'll be. What are we gonna talk about? What do you see as kind of the next, you know, 12-month progression? >> You know, I hope we don't go to Jersey after Brooklyn, New York, and-- >> Keep moving. >> I see Jersey over there, but it's where it belongs, you know, across the river. I'm from Jersey, so I can say that. You know, I think next year we're gonna see more integration of AI modules into the digital worker. I think with a lot of these explosive markets, like RPA is, there's always a bit of cooling off period, and I think you're going to see some tapering off of the growth of some of the platform companies, AA, but also their peers and compatriots. That's natural. I think that the area has been a little bit, you know, analysis and tech-industry loves change. If there's no change, there's nothing for us to write about. So, we usually over-project. Now, in this case, the 2.8 billion-dollar market project five years out that I did is being exceeded, which is rare. But I expect some tapering off in a year where there's not a ceiling hit, but that, you know, you end up with going through these more simple applications that can be robotized easily. And now you're looking at slightly more complicated scenarios that take a little more, you know, AI and analytics embedded-ness, and require a little more care, they have a little more opaque, and a little more thought, and that'll slow things down a bit. But, I still think we're on our way to a supermarket and a lot of productivity here. >> So just a little less low-hanging fruit, and you gotta step up the game a little bit. >> I guess you could, you said it much simpler then I did. >> I'm a simple guy, Craig. >> But that's why you're the expert on this panelist. >> Alright, Craig, well thanks for sharing your insight, >> Alright. >> Really appreciate it, and do look forward to talking to you next year, and we'll see if that comes true. >> Alright, appreciate it, take care now. >> He's Craig Le Clair and I'm Jeff Frick. You're watching theCUBE from Automation Anywhere Imagine 2018.

>> Hey welcome back everybody. Jeff Frick here with the Cube. We're at the Hotel Nikko in downtown San Francisco, International Women's Day. Accenture's putting on a big event today. It's called Getting to Equal, about 400 executives. Packed house in the little conference area. So we're excited to sit down with some of the leadership team and talk about some interesting research that Accenture's come out with. And also just talk to some terrific guests and we're excited by our first guest. She's Jennifer Cabalquinto. She's the CFO of the Golden State Warriors. Jennifer, great to see you. >> Thank you. >> I'm joined by Mike Sutcliff. He's a group chief executive for Accenture Digital. Great to see you Mike. >> Great to be hear. >> Alright, so let's just jump in to it. We're a little short on time and got a packed schedule. But I want to jump in, Jennifer with you, in culture. >> Yeah. >> Talk about the culture at the Golden State Warriors. I think it's such a phenomenal example that we can all see. We can't see in lot's of other companies, but with a professional sports franchise, we can see what a top down culture change when the change of management happened. When, when >> Sure >> Joe and Peter came in and how they've been able to change the culture, but then also drive that through all the way down to the greatest operations. >> Yeah, no we've really been fortunate. Our ownership group has been so supportive. And they really want us to succeed and they gave us all the resources to do it. And they've really brought that sort of Silicon Valley leadership style and fast fail and really make us push to be innovative and to grow. I love, you know, they brought on Bob Myers as our general manager for the basketball operation side. And he always says that he recruits for character first. And then tall 'cause you can't teach tall, but character is really something that I think, we as part of the whole organization really focuses on is that, you know, it's that are we all willing to be a team and have that sort of drive together. >> Right. >> And Joe and Peter embody that from the top down and I think it really permeates. And it's really our desire to be innovative and to drive this business, both on the basketball side and on the business side. >> And what's interesting, I mean they're good guys, but they're not doing it to be good guys, they're doing it to win. I mean, it's a competitive business >> Sure. >> that we can all watch the winners and losers. It's a business decision for better business. >> That's exactly right and you know, they really do want to win. They're competitive and every single person I think in the organization is competitive. But I think they want to win in the right way. And I think you can see it in the way that we approach both the basketball side and the business side really wanting to, you know, I think do, I think the community the best that we can. I mean, we really want to reflect our community, as well as our business partners and really succeed together >> Right. So Mike, you're out on the field. You talk to a lot of customers. I mean, do people get it? Do people get that diversity of opinions, points of views, teams, isn't just to do the right thing? It's actually to drive better business outcomes? >> I think they do. I mean one of the reasons we were attracted to work with the Warriors is they were looking not just to change their game, but to change the community that they were involved in. We see lot's of clients with the same aspiration. They're trying to figure out how to improve the way the world works and lives. And so if you want improve the way the world works and lives, you got to have diversity of thought. People with different educational backgrounds, cultural backgrounds, different experiences who can look at those really tough problems and say there's a better way. >> Right. >> And that's where we think diversity brings powers. That diversity of experience allowing you to come up with new solutions. >> So Jennifer, just from a woman's perspective being in obviously a very male dominated world. Of course, a lot of the tech companies around here are as well, how are you attracted to this industry? You know, kind of, what was your experience going in knowing that you were going to be in the minority in terms of the executives around the table? >> Right. >> And how did you overcome? >> You know, I am one of five children. I have four brothers, two older, two younger. And raised in Brooklyn. I'd like to think that I've been competing with boys my entire life. And I think my environment sort of gave me a tough skin. So I don't look at it in that lens. I didn't approach the job thinking I'm the only woman, or I'm one of a handful of women. I really approached the job saying I can make a difference in this organization and to help drive and bring a new perspective to the sports industry. It was my first sports job I was out of entertainment space and not really the sports entertainment world. And I really thought that I could bring a different perspective. And I think, you know, the ownership saw the same thing. And that's why I came aboard. And I think not filtering anything that I do with the lens of I'm a woman. >> Right. >> I think really makes a difference in terms of how I approach the role and then how other people, you know, sort of receive that. >> Right. So that said, for the gals that weren't raised in Brooklyn with four brothers. Fighting for food at the table probably since you were a little kid. You know, what advice would you give them? I mean, is it just, there's some really great advice coming out of the panel in terms of just focus on data, focus on results, you know, raise your hand. What advice would you give to, you know, say young women, say a junior in college, a senior in college, first years out, who want to get started, and are attracted to a traditionally male dominated space? >> Sure, I think one, don't self edit. Like know you can succeed in that space. Just because it's male dominated doesn't mean that it needs to always be that way. I also think you have to be great at what you do. I mean it's performance first, I think in any industry. And so, when you can actually have the confidence in your abilities, I think it starts to show through and then people, you know, I think respond to that. So I think perform really, really well. Be deliberate about what you want. Ask for what you want. Set your rules. You know, I think all of that is really important. Find your voice. >> Alright, well we could go on and on, and I want to continue this later at the San Antonio game this evening, but we'll make that work out, but we got to drop. So I'll leave it there. Jennifer, Mike, thanks for >> See you there. >> taking a few minutes. >> Great to see you today. >> Alright, I'm Jeff Frick, we're at the Accenture International Women's Day celebration in downtown San Francisco. Thanks for watching. (upbeat music)

>> Narrator: From Hell's Kitchen in New York City, it's theCUBE, on the ground at Serverlessconf brought to you by SiliconAngle Media >> Hi, I'm Stu Miniman, here with theCUBE at Serverless Conference in New York City, Hell's Kitchen. Happy to have with me, first time guest on the program Sam Kroonenburg, we had your brother on the program at the AWS Summit not far from here, at the Javits Center in New York City, but you're also one of the co-founders its the two brothers for A Cloud Guru. Thanks so much for joining me, and thank you for allowing us to come get some phenomenal content here. >> Yeah, no problem. Thank you for coming for the conference today. >> Alright, so Sam, take me back, you know, we talked to your brother a little bit about, well it was an interesting story, he said actually I got turned down for a job from Amazon and ended up creating a training company. But you built this and you built it on Serverless. >> I did yeah. >> So walk us through a little bit the thought process, the timing, you know, aren't you a little bit ahead of your time on that? >> Yeah, it was mid 2015, it was a strange time. We decided we wanted to build this school, this online learning platform, but the challenge we had was that we didn't have a lot of time, we both had families, kids, you know, mortgages, financial commitments. Basically I had four weeks. I had four weeks of leave owing to me, from my employer at the time. My wife and I had been planning this big family holiday with the kids for years and we were about to take it, and I remember having this phone call with Ryan and we were talking about how there were these people taking these online courses and they were really liking them. And we thought, what if we could build this school to teach people cloud computing. It was such a buzz and we just thought, there's something in this. But the challenge was the timing. I remember my wife turned to me and she said, "Look you've got to do it, we'll cancel the holiday, "take the four weeks and give it a try." So that's what we did, we actually flew down to live with Aaron, my in-laws and help look after the kids and I locked myself in a bedroom for four weeks and tried to build an online school. And that was there was no epiphany to go Serverless there was no grand plan. It was, we had a constraint, which was time. I had no time to build this thing. And so ended up using some of the latest technologies like AWS Lambda, API Gateway, a whole bunch of Serverless technologies because I saw that they would help me build this faster. And I could get something to market in the four weeks that I had. I actually spent the first couple of days trying to skin and configure Moodle, the learning management system and I tore my hair out and yeah, ended up putting this thing together with Serverless technologies. >> Ryan just walked by-- >> Oh, there he is. >> It's a llama unicorn with a cat or something like that. >> I'm going to put in the background. >> In the back of our video. Sam, what's your brother doing here? >> He's always trying to troll me. >> So talk to us, you know one of the things the maturation, kind of the speed of change in the industry for new technologies is just so fast these days. Take us through from those early days to you know Serverless today. What's your experience been? What would you say to people that look at this technology? >> I think it's a lot easier to get into now than it was two years ago. The ecosystem has grown around it, the core technologies are pretty much the same as they were two years ago, function as a service, execute functions in the cloud very similar, but the tooling around it, the ecosystem around it has grown. There's great deployment tools, orchestration systems that have come along. It's a lot easier to just get in now and early on, when we started we had to roll a lot of things ourselves, which took a lot of time, and that's what you're trying to stop, is losing time. Yeah, so there's that and the community has really grown, there's a lot of support in the community now. >> So if you had to do it all over, you could have done it in a weekend, rather than the four weeks. >> Yeah, instead of the four weeks. >> Yeah, I mean what's-- >> That's the interesting thing about what happened to us, we would not exist, our business would not exist if it wasn't for Serverless technologies. I literally couldn't, we could not have, built that school. It's not like it was the most amazing school when we launched it, but it was enough. It was just enough to get people using it, to get to market, to start to build a business around it. >> Alright, talk to me about this event. So, its the 5th Serverlessconf, not unheard of a company that does training to get involved with physical events, 'cause you bring them together, you know, what's the thought process, talk to us a little bit about that journey and this event itself. >> Yeah, I mean, a lot of this is organic for us. We built, it was early last year, you know we're part of the Serverless communities, a lot of pioneering going on here, a lot of people facing the same challenges. And we thought, well there's no event to bring all of these people together. And there's a lot of very fast pace of change here, a lot of rapid ideation and new technologies. Let's bring everyone together and see what we can do. That's what we did with Serverlessconf. We've never run a conference before, we just hired a warehouse in Brooklyn, a bunch of Australians and British guys coming over and we just invited a bunch of people on Twitter and 250 people turned out to the first one. It just got bigger and bigger from there. So this is actually the 5th Serverlessconf now. >> Well, its a hot week again, so we appreciate that the air conditioning works at this one. >> Yes, we have air conditioning at this one. >> 460 people here, you brought in some great speakers, we had a number of them on our program this week, speak to us, I mean you've got sponsors here, you've got good speakers, give us some of the highlights. >> We've got all of the main Cloud vendors are here, Google, IBM, Microsoft, Amazon and it's actually the product teams who build this stuff. That's what I love about this event, it's actually the people who build it. It's vendor neutral, it's really cool. You get great thought leaders from the community, Simon Wardley was a highlight this morning, his talk on Value Chain Mapping and Strategy was really interesting. Randall Hunt from AWS X Space X, talking about the continuous integration process when building rockets. Space X was absolutely fascinating and what bugs in production mean when you're building a rocket. It means the rocket blows up. Really interesting variety of talks from those tooling providers, companies like us who are just building on Serverless and then Serverless tooling companies and vendors. Really fascinating. >> Alright, Sam what should we be looking for in the future from Serverless and from A Cloud Guru? >> We're going to be doing a whole lot more Serverless content. You're going to see a lot of really interesting new content through our site, a lot of teaching on Serverless, we're going to be doing more Serverless Conferences. You'll see a lot from us, not just us, but from the wider community who come to the conference, who we know well, a lot of the experts, we're going to be doing a lot of work with those people. >> Well Sam Kroonenburg, really appreciate you joining us, appreciate the media sponsorship to allow theCube to come get some great content and share it with our communities, hope to see you at many more events in the future. >> Thank you for coming. >> Thank you so much. Sam Kroonenburg, I'm Stu Miniman. Thank you for watching theCUBE. (upbeat music)

>> Announcer: Live from Las Vegas, its theCUBE, covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back the the Aria in Las Vegas, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, I'm here with Stu Miniman. Angelo Sciascia is here, big Tom Brady fan, Senior Vice President of NetX Information Systems, from Brooklyn, New York, I don't think so. >> Not a Tom Brady fan. >> Thanks for coming on theCUBE do you think it matters, how much it airs at a football. >> No, not at all, Tom Brady doesn't care about that. >> No, well, listen, thanks for coming on. We have a great conversation, we love talking sports on the Cube. So welcome, how's the show going for you? >> Ah, it's fantastic, you know, lots of great material Veritas has been talking about. 360 Data Management, obviously we all know the benefits of that by now. So we have a lot of customers here so I'm glad they they got to see it from a senior leadership perspective, rather than our sales guys and sales engineers going in there and talking to them, and seeing Veritas executives really getting behind what we're talking about. So it backs up our story and, you know, our customers are pretty excited about it, actually. >> What's the nature of your relationship with Veritas. I know you have a relationship, and maybe still do, with Symantec. How's that all, how did it all evolve? >> Yeah, so we are a Veritas Platinum Partner, we would be, what we consider, a solution-provider type partner. A lot of our business today is either directly or indirectly tied to Veritas, which was kind of funny because we started as a security company, so our roots are systems management, you know. That's where we were in 2005 when I joined NetX, that's where we were for many, many years after Symantec acquired a company called Altiris. We just stayed in that vein, you know, managing endpoints, securing endpoints, encrypting data. And then, somewhere in 2013, we said hey, you know, let's try to diversify the portfolio a little bit. And we used to manufacture an endpoint management appliance for Altiris so we said hey, Symantec's got these things called NetBackup Appliances, let's check it out. It's a formed fact that we know how to sell and, shoot, four years later it's been a great partnership for us, great partnership, I'm sure, for Veritas, and for our customers and that's a lot of our business today. >> So, I mean, it's hot market, you know. Data protection is exploding, and security. I mean, you're in two of the sweet spots in the market right now. So how do you approach the business with customers? Do you, are you a specialist around data protection? You deliver services around them. Maybe you can explain it on the model? >> Yeah, you know, that's actually a good question, because it's evolved quite a bit, right? So, you know, when you had a limited portfolio of just one or two products that you can sell to a customer, you're really doing a product sale, right, which, I would say that was probably the most difficult transition from the split from Symantec to Veritas, because at Symantec we had thousands of products in the portfolio, or hundreds of products in the portfolio that we could actually talk to. And for a little while, really we had a handful, you know, we had NetBackup Appliances, Enterprise Vault and ancillary things to bulk on to that, like Clearwell. I think one of the most exciting things for us, as a reseller, is to now be able to go have a discussion with our customers that we were never able to have before. And rather than sit there and try to sell them a backup product or a storage solution, we could sell them a platform that solves many problems for them, right? Rather than sitting there and trying to sell one-off. So, our conversations are significantly more strategic now then they've ever been, and frankly I speak for myself and my whole team, I know everyone enjoys the conversation more now that we have a portfolio to talk about, than just a handful of products. >> Angelo, you've got an interesting viewpoint on this split off of Aritas from Symantec. What have your customers said about it? What's been your interaction with the organization? What can you tell us about kind of the inside going on? >> Yeah, look, I've lived firsthand on a Symantec acquisition of a company, okay. I was, we were not a Symantec partner when they acquired Veritas. Funny enough, I was actually doing Veritas consulting, you know, on my own on the side prior to Symantec purchasing Veritas. So I really, I'd made my career on two products; Veritas for backup and Altiris for systems management. Symantec bought Veritas and I was like okay, you know, I'm just going to stay with Altiris. Symantec bought Altiris and here we are now, so we can talk about all of them. The thing I noticed was Symantec was always going to be a security company, right, and they weren't going to change that no matter how much they try to integrate it. It's two radically different stories. You know, and for many, many years, things that we look at as new products today were kind of already there in the Symantec portfolio, but buried underneath other products that really never saw the light of day because when you have hundreds or thousands of products, like I said earlier, you know, the ones that are going to move the most are the ones that are going to get the attention. So I think the benefit of the split is that it really allowed Veritas to focus on what they do well, which is managing data, and Symantec to do what they do well, which is securing your infrastructure and securing your data. From my perspective, our customers really appreciated that. Sure, a couple of them were a little annoyed that they had to now split contracts and deal with that kind of stuff, but I think that was a momentary blip and for the most part, it's been well-received from everyone we've spoken to. >> Angelo, you said you're having, your conversations are evolving. Who are you talking to? And maybe take us inside some of those conversations. What are the big challenges they're having? >> Yeah, a year ago, a year and a half ago I was talking to either somebody who was on the messaging side and needed to archive emails or IMs, or on the backup side and they just wanted to be able to meet their backup windows and maybe to get some better d dub rates, right. Fun conversation to have, bit mundane. It's not really solving problems as much as backing up data or archiving data. Today, we're having overarching conversations at a C-level, or a senior VP level, or a director level, and talking about dramatic changes to the way they do business, and how we can do business with them. Six months ago, NetX, we weren't doing anything in the Cloud, you know. We were selling to some customers' Vdub space to the Cloud, and that's about it. We weren't talking Cloud strategy with them. Today we're talking to our customers about moving workloads to the Cloud, doing it in a way that's predictable for them, and doing it with Veritas. >> That's a really interesting point. I have to imagine that changed who you're talking with inside the company. Can you walk us through kind of a typical customer's, you know, and how you kind of move up into a more strategic discussion for Cloud strategy? >> You know, so for full transparency, that whole thing's still evolving, right. 360 Data Management is still fairly new. So what we're seeing, the conversations turned, it would start, again we're talking to somebody that we've been talking to historically in the backup side or architecture side, and we talk to them about wanting to do better things than what their backup is, and start to talk about, hey this is what 360 Data Management is. What's relevant to that person he's going to want to talk about but then there's going to be things in there that are not relevant to him. So he'll make that introduction and he'll get other stakeholders in the boat with him. And that's something we've really appreciated because the people you used to talk to are now bringing in stakeholders to offset their own desires and their own budgets, so want to bring in other technology. And typically, when we get to that point when we're starting to talk about strategic pricing, is when you're getting that C-level person to really have that aha moment, and say wow, we're offsetting costs here, we're doing things like truly getting rid of tape, or moving to the Cloud and things like that, and it's a conversation that really evolves and it's still starts at the bottom. But we're figuring out ways to start it at a higher point. >> Well, those strategies are still evolving for most customers; the roles of those people that might have had one role definitely are changing. I'm curious, one of the big transition points, especially for a company like Veritas, is going from licenses to some kind of more of a subscription model. Any commentary you have on your customers; their embrace, or like, dislike of some of those transitions? >> I think the one thing the Cloud has done is it's opened up a different avenue of how people consume IT, right. Cloud is very much consumption-based billing, and while that can complicate our lives from a reseller perspective in terms of how to collect and track monthly billing and things like that, they like it because they feel like, and it's the truth, they're only paying for what they're truly using, rather than paying for products or infrastructure that they're only using part of the day, or software that they're only using for a particular project. A lot of our healthcare systems might have a research project that their going on, and they might like to scale up for some backup licensing and scale back down once that project is done. Consumption licensing allows that, versus having to go to them and saying, hey, well now you got to buy 200 terabytes of perpetual licensing, and justify that capital expense, rather than having an operational expense on just that one particular workload that you have to back up for that one period of time. >> Angelo, Stu and I are always interested in the human capital management aspects of things, and you talked about, you went from sort of talking about having a conversation around email archiving or backup, to one about the Cloud, Cloud strategies. From your internal organization perspective, how did you manage that? Are you rescaling, are you retraining? Is it just you got really supersmart people that can adapt? >> We definitely have supersmart people, because they're all over there, that's right. But I definitely have supersmart people. But, you know, it's a little bit of both. It's a little bit of, you know, you take one of our data protection projects; see Christian Muma, you know, he's been in the data center for god knows how many years, he has seen technology evolve. It was a natural fit to look at Cloud infrastructure. Started taking some classes, consumed it, all the information he could, and now we're out there actively selling it. In some other respects, we had to hire from outside and bring in some services ourselves to actually use, maybe some third party partnerships to help us better understand how we price out Cloud for our customers. So it's a little bit of everything, and I think that that's what's exciting about it, because I think for the first time in a long time, everyone's learning something new at the same time, because, I don't care what anyone said about the Cloud years ago; it's different today, it's going to be different in six months, it's going to be different in nine months. And I think that that's exciting, and I've been in this industry since 1996. I've seen a lot of really cool things come and go. I just think that there's still infancy in the Cloud and I think it's exciting because everyone's still learning. And any time you can still learn, I think that's, I think an important part of your job. >> So when you think about your, sort of, near-term and midterm and long-term plan for the company, how do you sort of describe that? Where do you want to take this thing? >> Near-term, I want to have a solid end of the quarter. >> Business is good, right, I mean market's booming right now. >> Business is very good. Veritas will tell me it's not good enough but they're just never happy. No, business is, business is very good. I think, near-term for us, you said hey, how do we get our head around it? Near-term for us is, as we're absorbing all this information, is start to really figure out what our path is going to be. So near-term, I think we still have to identify other ancillary partners that we need to bring to the table. We've got our partnerships with Azure, Microsoft Azure, and our partnerships with AWS. We'll probably have to look at Google and IBM and see what they're doing, and then we have to look at other partnerships that are not related to Veritas but still drive that home. We maybe look at a different colo partnership or partnerships around outsourcing billing, things like that, that we can make where it's easier for our customers to consume the technology. So I think six to nine months from now if we were to have the same conversation, everything that we're doing today is probably going to be somewhat different. But I just think that there's still a lot of planning to do. >> Angelo, any feedback from your customers on what there's still on the to-do list from the vendors? We talked, you know, the strategy, Cloud's changing a lot, you know. What are some of the pinpoints that they said hey, if we could get this into the offering from Veritas or some of the others it would make our lives a lot easier. >> I mean, that's a tough question, because we're going to them now and changing the conversation already. You know, obviously they're always asking for different features, but I don't like to get into a feature conversation with the customers. I try to solve the problem. >> Dave: You're leading that conversation, is what you're saying. >> Yeah, I don't want to get into the weeds of talking about well, this widget does it at 50% and you do it at 48%. You know, I try to sit a little bit more macro. I think that one of the things our customers have asked us to do a better job at is figure out better ways to make it easier to consume the technology from budget perspective. So we're trying to figure that out now; 360 Data Management is a subscription, Veritas would like them sold in three years, we're trying to figure out ways to get creative with our customers on that. What's the right bundle, what's not the right bundle. One thing that I've noticed, and Veritas have been great at it, is we have to have some flexibility in terms of adding things in and make it seem like it's all part of that bundle. There's been some flexibility and I think that, because of that, we haven't hit that roadblock yet where, well, we really want this product in the bundle. Reality is that we'll work through that and try to add it in there, some way, shape or form, even if behind the scenes. >> The customers see you as the experts, and what we often see is that technology is the technology; it's pretty much understood. What's not understood by the customers is how to apply it to their business, and their business is changing so fast that it seems like they're looking to organizations like yours saying okay, here's our business challenge. How can you help me? You tell me, and then the best answer is somebody he'll be able to work with. Is that a valid, sort of, premise? >> Yeah, it is, it certainly is and I think we're really uniquely positioned in the fact that, here we've got, we've got our partnership with Veritas and we're 100% focused to everything in the Veritas portfolio so we don't compete from within. That's the same thing that we could say, basically, on Symantec and some of our traditional storage partners as well. That'll change most likely, on our storage partners, especially because of what Veritas have been releasing with Access and some of the other software providing storage technology. When we're brought in, we're brought in as the experts in that finite area, so we're not brought in as a generalist-type of reseller. We're brought in as, hey, I've got a data management problem, I've got a data security problem, or I'm trying to do some high-performance workloads on storage. So yeah, we are the experts, but at the same time we're being brought in for those handfuls of things, so we're not having these, hey, can you maximize my span on anti-virus software because I want to sell you commoditized software. It's just not us, it's not our thing. We're not adding any value to the customers, or the poor owners for that matter. >> Angelo, curious that there's a lot of startups in the data protection space. What do you here, your customers asking you about them? You know, what's your thoughts there? >> I guess I got to be nice, right? Because I'm being streamed everywhere. >> Stu: They're not listening, go ahead, be a New Yorker. >> Listen, I challenge Rubrik at any point of time, you know, those guys, Rubrik, Cohesity, those guys, they're new, they're the shiny new toy. The problem, the problem is they have their messaging out there, and the problem we have is that they're the shiny new toy. But when the rubber hits the road and when it's time to actually go and prove out what the technology can do, we'll win all the time. We will win ten out of ten times if we get the seat at the table, right. The problem is is because we were a limited portfolio, a limited product, limited integration type of company before, we weren't getting that seat at the table. I think they see it now, I think they're starting to get a little concerned about, hey, you know what, if this 360 Data Management is what it's going to be, and we all know it is, I think they're going to be concerned. They're new, and they're going to get attention. My honest opinion: I'm glad they came out, I'm glad that Rubrik and Cohesity and all these guys came out and did all this different ways to go to market, because I think it really forced all of us to say hey, we got some real tough decisions to make here, the competition has caught up, in certain ways. Let's change the game, and 360 Data Management does that. I think they should take as much business as they can right now, because it's going to be short-lived. >> You said it makes you rethink your strengths, and like you said, change the game. >> Yeah, it changes the game. >> Yeah. Uh, okay, predictions on the MLB? Yankees won their getaway game today to put the pressure on the Red Sox, two and a half to two and a half games back. You know, the Indians are looking good, my man, Terry Francona. What's your prediction for it? >> The Sox fan's outnumbered two to one here, so go ahead. >> You know, so I shouldn't say that the Yankees are going to win the World Series? >> No, he's a Yankees fan. >> I'm a Yankee fan, too. >> Honestly, as a Yankee fan, I think we all know that they weren't supposed to be this team, so I think this is, that's the team to look out for. >> Dave: Maybe this is their year. >> I think this is the year that they're going to challenge people, I mean, are they going to win? It's Cleveland, do you really think Cleveland's going to win anything? They won one thing in the last, what, 30 years. >> That's what they used to say about us in Boston. Angelo, thanks so much coming on, really appreciate it. Keep right there, buddy, we'll be back with our next guest right after this short break. We're live from-- (electronic music)