(upbeat music) >> Narrator: From the CUBE studios in Palo Alto, in Boston connecting with thought leaders all around the world, this is theCUBE Conversation. >> Well, there's no question these days that in the world of business, it's all about data. Data is the king. How you harvest data, how you organize your data, how you distribute your data, how you secure your data, all very important questions. And certainly a leader in the data replication business is HVR. We're joined now by their CEO, Anthony Brooks-Williams, and by Diwakar Goel, who is the Global Chief Data Officer at GE. We're going to talk about, you guessed it, data. Gentlemen, thanks for being with us. Good to have you here on theCUBE Conversation. >> Thank you. Thanks, John. >> Yeah, well, listen, >> Thanks, John. >> first off, let's just characterize the relationship between the two companies, between GE and HVR. Maybe Diwakar, let's take us back to how you got to HVR, if you will and maybe a little bit about the evolution of that relationship, where it's gone from day one. >> No, absolutely. It's now actually a long time back. It's almost five and a half years back, that we started working with Anthony. And honestly it was our early days of big data. We all had big, different kind of data warehousing platforms, but we were transitioning into the big data ecosystem and we needed a partner that could help us to get more of the real-time data. And that's when we started working with Anthony. And I would say, John, over the years, you know we have learned a lot and our partnership has grown a lot. And it's grown based on the needs. When we started, honestly just being able to replicate a lot sources and to give you context like GBG, we have the fifth largest Oracle ERP. We have the seventh largest SAP ERP. They just, just by the nature of just getting those systems in was a challenge. And we had to work through different, different solutions because some of the normal ones wouldn't work. As we got matured, and we started using data over the last two, three years, specifically, we had different challenges. The challenges was like, you know is the data completely accurate? Are we losing and dropping some data? When you're bringing three billion, five billion rows of data, every five to six hours, even if you've dropped 1% you've lost like a huge set of insights, right? So that's when you started working with Anthony more around like the nuances as to, you know what could be causing us to lose some data, or duplicate some datasets, right? And I think our partnership's been very good, because some of our use cases have been unique and we've continuously pushed Anthony and the team to deliver that. With the light of, you know these use cases are not unique, in some cases we were just ahead, just by the nature of what we were handling. >> Okay. Anthony, about then the HVR approach, Diwakar, just took us through somewhat higher level of how this relationship has evolved. It's started with big data, now, it's gone (mumbles) in terms of even fine tuning the accuracy, that's so important. Latency is obviously a huge topic too from your side of the fence. But how do you address it then? Let's take GE for example, in terms of understanding their business, learning their business, their capabilities, maybe where their holes are, you know where their weaknesses were, and showing that up. How did you approach that from the HVR side? >> Yeah. Do you mean wanting back a few years? I mean, obviously it starts, you get in there, you find an initial use case and that was moving data into a certain data warehouse platform, whether it be around analytics or reporting such as Diwakar mentioned. And that's, I mean, most commonly what we see from a lot of customers. It's, the typical use case is real-time analytics, and moving the data to an area for consolidated reporting. It's either most (indistinct) in these times, it's in the cloud. But GE you know, where that's evolved and GE are a top customer for us. We work across many of their business units of their different BUS. GE had another arm Predix, which is the industrial IOT platform that actually OEM must as well for a solution they sell to other companies in the space. But where we've worked with GE is, you know the ability one, just to support the scale, the complexity, the volume of data, many different sources systems, many different BUS, whether it be, you know, their aviation division or our divisions, or those types, to sending that data across. And the difference being as well where we've really pushed us and Diwakar and team pushed us is around the accuracy to the exact point that Diwakar mentions. This study is typically financial data. This is data that they run their business off. This is data that the executing CEOs get dashboards on a daily basis. It can't be wrong. You may not only do businesses these days, you want to make decisions on the freshest data that they can, and specifically over the last year, because that's a matter about survival. Not only is it about winning, it's about survival and doing business in the most cost-effective way. But then that type of data, that we're moving, the financial data, the financial data lags we built for GE that is capturing this out of SAP systems, where we have some other features benefits, you know that's where that really pushed us around the accuracy. And that's whereby you mean, you can't really, these, you can't ever, but especially these days, have a typical just customer tab vendor approach. It has to be a partnership. And that was one other thing Diwakar and I spoke a while ago. It was about, how do we really push and develop a partnership between the two companies, between the two organizations? And that's key. And that's where we've been pushed. And there's much new things we're working on for them based on where they are going as a business, whether it be different sources, different targets. And so that's where it's worked out well for both companies. >> So Diwakar, about the margin of error then, in terms of accuracy, 'cause I'm hearing from Anthony that this is something you really pushed them on, right? You know, and 96, 97%, doesn't cut it, right? I mean, you can't be that close. It's got to be spot on. At what point in your data journey, if you will, did it come to roost that the accuracy, you know had to improve or, you know you needed a solution that would get you where you needed to operate your various businesses? >> I think John, it basically stems down to a broader question. You know, what are you using the data for? You know, a lot of us, when we're starting this journey we want to use the data for a lot of analytical use cases. And that basically means you want to look at a broad pattern and say, okay, you know what, do I have a significant amount of inventory sitting on one plant? Or, you know, is there a bigger problem with how I'm negotiating with a vendor, and I want to change that? And for those use cases, you know getting good enough data gives you an indicator as to how do you want to work with them, right? But when you want to take your data to a far more fidelity and more critical processes, whether, you know you're trying to capture from an airplane, the latest signal, and if you had five more signal, perhaps you solve the mystery of the Malaysian Med Sync plan, or when you're trying to solve and report on your financials, right? Then the fidelity and the accuracy of data has to be spot on. And what you realize is, you know you unlock a certain set of value with analytical use cases. But if you truly want to unlock what can be done with big data, you have to go at the operational level, you have to run your business using the data real-time. It's not about like, you know, in hindsight, how can I do things better? If I want to make real-time decisions on, you know, how, what I need to make right now, what's my healthcare indicator suggesting, how do I change the dosage for a customer or a patient, right? It has to be very operational. It has to be very accurate. And that margin of error then almost becomes zero, because you are dealing with things. If you go wrong you can cost lives, right? So that's where we are. And I think honestly being able to solve that problem has now opened up a massive door of what all we can do with data. >> Yeah. Yeah, man. I think I would just build on that as well. I mean, one, it's about us as a company. We are in the data business, obviously. Sources and targets. I mean that's the table stakes stuff. What do we support? It's our ability to bridge these modern environments and the legacy environments, that we do. And you see that across all organizations. A lot of their data source sits in these legacy top environments, but that will transition to other either target systems or the new world ones that we see, more modern bleeding edge environments. So we have to support those but they're not the same time. It's building on the performance, the accuracy of the total product, versus just being able to connect the data. And that's where we get driven down the path with companies like GE, with Diwakar. And they've pushed us. But it's really bridging those environments. >> You know, it also seems like with regard to data that you look at this almost like a verb tense, what happened, what is happening, what will happen, right? So in looking at it to that person, Diwakar, if you will, in terms of the kind of information that you can glean from this vast repository of data as opposed to, you know, what did happen, what's going on right now, and then what can we make happen down the road? Where does HVR factor into that for you in terms of not only, you know, making those, having those kinds of insights, but also making sure that the right people within your organization have access to the information that they need. And maybe just, they only need. >> No, you're right, John. It's funny, you're using a different analogy but I keep referring to as taillights versus headlights, right? Gone are the days you can refer back as to what's happening. You need to just be able to look forward, right? And I think real-time data too is no longer a question or believe, it's a necessity. And I think one of the things we often miss out is real-time data is actually a very collaborative piece of how it brings the various operators together. Because in the past, if you think, if you just go a little bit old school, people will go and do their job. And then they will come back and submit what they did, right? And then you will accumulate what everybody did and make sense out of it. Now, as people are doing things live, you are hearing about it. So for example, if I am issuing payments across different, different places I need to know how much balance I need to keep in the bank, it's the simplest example, right? Now I can keep the math, I can always stack my bank with a ton of money, then I'm losing money because now I'm blocking my money. And especially now, if you think about GE which has 6,000 bank account. If I keep stacking it, I will practically go bankrupt, right? So if I have an inference of what's happening every time a payment card issued by anybody, I am knowing it real-time. It allows me to adjust for optimal liquidity. As simple as it sounds, it saves you a hundred billion dollars if you do it right, in a year, right? So I think it is just fundamentally changes. We need to think about real-time data is no longer, it's just how you need to operate. It's no longer an option. >> Yeah. You may, we see, what we've seen as posture, we were fortunate. We had a great 2020. Just under a hundred percent year-over-year growth. Why? It's about the immediacy of data, so that they can act accordingly. You mean these days, it's table stakes. You mean, it's about winning and, or just surviving compared to, you know, years ago when day old data, week old data, that was okay. You mean, then largely these legacy type (mumbles) technologies, well it was fine. It's not anymore. You mean exactly what Diwakar was saying. It's table stakes. It's just what, that's what it is. >> And I think John, in fact, I see actually it's getting further pushed out, right? Because what happens is I get real-time data from HVR but then I'm actually doing some stuff to get real-time insights after that. And there is a lag from that time to when I'm actually generating insights on which I'm acting on. Now, there is more and more of a need that how do I even shorten that cycle time, right? I actually, from it, we are getting, not only data when it's getting refresh, I actually get signals when I need to add something. So I think in fact, the need of the future is going to be also far more event-driven, where every time something happens that I need to act on, how can technologies like HVR even help you with understanding those? >> Anthony: Yes. >> Anthony, what does scale do to all this? Diwakar touched on it briefly about accuracy and all of a sudden, if you know, if you have a, if you've got a, you know a small discrepancy on a small dataset, no big deal, right? But all of a sudden, if there are issues down the road and you're talking about, you know, millions and millions and millions of inputs, now we've got a problem. So just in terms of scale and with an operation the size of GE, what kind of impacts does that have? >> Yeah. Massive. You mean, it's part of the reason why we went, why we've been successful. We have the ability to scale very well from this highly distributed architecture that we have. And so that's what's been, you know, fortunate for us over the last year, as we know. What does the stat mean? 90% of the world's data was generated over the last two years or something like that. And that just feeds into more, human scale is key. Not only complexity at scale is a key thing, and that's where we've been fortunate to set ourselves apart on that space. I mean we, GE push us and challenge us on a daily basis. The same we do with another company, the biggest online e-commerce platform, massive scale, massive scale. Then that's, we get pushed the whole time and get pushed to improve all the time. But fortunately we have a very good solution that fits into that, but it's just, and I think it just doesn't get, worse is the wrong word. It's just, it's going to continue to grow. The problem is not going away. You know, the volumes are going to increase massively. >> So Diwakar, if I could, before we wrap up here, I'm just curious from your, if you put on your forward-thinking glasses right now, in terms of the data capabilities that HVR has provided you, are they driving you to different kinds of horizons in terms of your business strategy or are your business strategies driving the data solutions that you need? I mean, which way is it right now in terms of how you are going to expand your services down the road? >> It's an interesting question. I think, and Anthony keep correcting me on this one, but today, you know because if you think about big data solutions, right? They were largely designed for a different world historically. They were designed for our IOT parametric set of data sets in different kind of world. So there was a big catch up that a lot of these companies had to do to make it relevant even for the other relational data sets, transactional data sets and everything else, right? So a big part of what I feel like Anthony and other companies have been focusing on is really making this relevant for that world. And I feel like companies like HVR are now absolutely there. And as they are there they are now starting to think about solving or I would say focusing on people who are early in their stage, and how can they get them up and quick, you know, efficient early, because that's a lot of the challenges, right? So I would say, I don't know if Anthony's focuses me in, right? So it should not be me, but it's, I think like where they're going, for example like how do they connect with all the different cloud vendors? So when a company wants to come live and if they're using data from, you know the HR Workday solution or Concord Travel solution, they can just come pitch. We are plug and play. And say, okay, enable me data from all of these and it's there. Today what took us six months to get there, right? So I think rightly so, I think Anthony and the team are focusing on that. And I think we have been partnering on with Anthony more, I would say, perhaps pushing a little more on you know, getting not only accurate data but also now on the paradigm of compliant data. Because I think what you're going to also start seeing is as companies, especially in like different kind of industries, like financial, healthcare and others, they would need data certification also of various kinds. And that would require each of these tool to meet compliance standards that were very, they were not designed for again, right? So I think that's a different paradigm, that again Anthony and the team are really doing great in helping us get there. >> Yeah. I think there's, that was good Diwakar. There's quite a bit to unpack there, you know. With companies such as GE, we've been on a journey for many years. And so that's why we deployed across the enterprise. And let's start off with, I have this source system, I'll move my data into their target system. These targets systems you know, become more frequently either data lakes or environments that were on-premise to running in the cloud, to newer platforms that are built for the cloud, like we've seen the uptake in companies like Snowflake and those types. And you mean, we see this from you know big query from Google and those type of environments. So we see those. And that's things we've got to support along the way as well. But then at the same time, more and more data starts getting generated in your non-traditional trial platforms. I mean, cloud-based applications and those things which we then support and build into this whole framework. But at the same time to what Diwakar was saying, the eyes, you know, the legal requirements, the regulator requirements on the type of data that is now being used. Before you would never typically have years ago companies moving their most valuable or their financial data into these cloud-based type environments. Well, they are today. It happens. And so with that comes a whole bunch of regulation in security. And we've certainly seen particularly this last year the uptake in when these transactions have another level of scrutiny when you're bringing in new products into these environments. So they go through, you know, basically the security and the legal requirements are a lot longer and more depth than they used to be. And that's just the typical of the areas that they're deploying these technologies in as well, and where you're taking some technologies that weren't necessarily built for the modern world that they are now adopt in the modern world. So it's quite complex and a lot to unpack there, but it's, you've got to be on top of all of that. But that's where you then work with your top customers, like at GE, that future roadmap, that feeds where one, you obviously make a decision and you go, this is where we believe the market's going, and these are the things we need to go, we know we need to go support, no matter that no customer has asked us for it yet. But the majority of it is still where customers that are pushing, bleeding edge, that are pushing you as well, and that feeds the roadmap. And, you know, there's a number of new profile platforms GE even pushed us to go support and features that Diwakar and the team have pushed us around accuracy and security and those types of things. So it's an all encompassing approach to it. >> John, we could like-- >> Actually, I think we've set up an entirely new CUBE Conversation we're going to have down the road, I think. >> Yeah. (laughing) >> Hey, gentlemen, thank you for the time. I certainly appreciate it. Really enjoyed it. And I wish you both a very happy and importantly, a healthy 2021. >> Great. >> Thank you both. Appreciate your time. >> Thank you. >> Thanks, John. >> Thank you. >> Thanks, Anthony. Bye bye. >> Bye bye. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering UiPath Forward Americas 2019, brought to you by UiPath. >> Hi everybody welcome back to Las Vegas, we're at the Bellagio at UiPath Forward III, day two of theCUBE covers. theCUBE is a leader in live tech coverage. We go out to the events. We extract the signal from the noise. Erik Alexis here is the Vice President of Global Intelligent Process Automation at GE. Eric thanks for coming on. >> Yeah absolutely excited to be here. >> So, you guys have a COE, you're obviously heavily involved in essentially running the COE, is that right? >> Yeah that's my role at GE. I lead our Global Center of Excellence for intelligent process automation. Our journey started with UiPath a while back in 2016. So, it's been an incredible journey so far. >> And I want to get into that. So, before I do, I was struck by the Forrester analyst, Craig LeClair this morning made a statement. I don't know if you're in there, but he said, "Yeah COE, setting up a COE, "maybe that's asking too much." But I talk to a lot of people that have a center of excellence. Maybe it's definitional but what does your COE look like in terms of just it's role, size? >> Yeah it's a great question, so I think in terms of the role that we play more broadly, I mean we provide a lot of the technical expertise, the hands-on development and the operational support for our business units. And so we've really kind of developed that expertise over time, and we use our business units to really drive and identify the opportunities that come in through the COE. So, in terms of the size of the COE, we've got in total number of heads, we've got about 50 primarily technical resources there, that are supporting development as well as ongoing operation. >> Awesome, okay so let's talk about your journey. When did it start? What was the motivation behind it? How did you make the business case, and we'll get into it. >> Yeah so our journey started back in 2016, GE, we used to have a shared services organization that we had a very forward-thinking CEO at the time who wanted to really disrupt the way that we worked. And so RPA was something that was just coming out and kind of getting noticed by a lot of these shared services organizations. And so throughout the year we assessed a couple of technologies obviously landing on UiPath for a number of reasons. I would say in terms of our journey 2017 was kind of our year to prove the technology. We wanted to see if this stuff could really work long term and operate at scale. Given that I'm still here obviously, we proved that was correct and then 2018 was kind of the year of scaling and operationalizing kind of a sustainable model to support our business units across the board from an RPA standpoint. So, really building out a proper structure, building out the governance that goes along with building robots and building a kind of a resource team to continue to support the bots that we were at scale at that point, so maintaining those bots is critically important. And then 2019 has really been the year and I think the theme of this conference in general, a bot for every person I think that's the direction we're moving in 2019. We've kind of perfected the concept of the back office robot and the development of those, and running those at scale. And now we're moving towards a whole new market share when it comes to attended automation and citizen development. >> So, in '16 it was kind of kicking the tires it was almost like R&D. And then '17 was really essentially a proof-of-concept right so still a small team, a two piece kind of team kind of thing right? And then when you talked about scale, helped us understand what's involved in scale, I know it's also another big theme of this conference. What are the challenges of scaling and how did you resolve those? >> Yeah that's a very good question. I think it's a question that has been very common throughout this entire conference. I would say when I think about scaling what I've noticed over the past few years is that, the actual bot development is about 25% of the work that you need to do, right? When it comes to scale there is everything outside of the actual development is the important part. So, how are you funneling opportunities into a pipeline, how are you streamlining the entire process reengineering of fitting an RPA into an existing process, what's governance you have in place to make sure that the code of that development is clean and can be maintained long term? And then more importantly I think that people overlook, people think of scale as being able to develop a lot of bots. I think more importantly what scale is is being able to efficiently maintain a large portfolio of bots, and that's what I've realized this year. We've got now about 300 automations in production and your reputation as an organization is really on how well you maintain those bots, because if your bots are consistently failing, and you're not fixing them quick enough for your functional users to leverage them, then you lose a lot of credibility. So, I think that's been a big learning for us as we reach scale. >> That's interesting I mean I think about scripts, how fragile scripts are and you got a lot of 'em, and they almost always break. And so what is the discipline that allows you to have that quality of bot that is maintainable? Is it a coding discipline? Is it a governance? Is there other automation involved in maintaining those bots? >> No there is and I think the team that's under me, my technical team has done a phenomenal job of setting this up, but we've got some very rigorous standards that we've put in place around. We do have reusable components for example that need to be used on every single robot that goes into production, so that when I look at for example a bots login, that bots login is going to be the same across all my bots. So, every developer who's going to be maintaining that bot knows what it is and how to fix it. I think the standardized logging as well to make sure that we've got robust logging for every single robot is incredibly important because again that's going to be critical when somebody goes to try and fix the bot. >> So you are like an app store, you're enforcing rules like Apple for developers. >> Exactly. >> Okay so let me ask you a question. See now several years in if you had a mulligan, what would you do differently? >> Yeah I think that's another very good question. I think when you first start with this technology, it's unbelievably exciting, because it's something that you can immediately see the difference and the impact it can make, and so you want to try and apply it everywhere to everything, to solve every problem. And I think that's kind of where we got a little ahead of ourselves. We weren't as thoughtful as we should have been when we started taking in the use cases that we were bringing in and while I sit here and tell you that we've got 300 automations in production, I've also decommissioned about 90 automations as well. Because you kind of live and you learn as you go through that process on. This doesn't make sense for RPA. It's not driving the value anymore. It's not driving the right value for the company. >> And is that because the process needs to be reworked before it's automated or there are other factors? >> Yeah I think there's a couple of factors there. I think number one, some bots are intentionally just for short-term use. We look across the portfolio, some bots you design for to operate for two weeks for a massive for example document transition or something like that. So, that's a common reason for decommissioning. I would say secondly you just picked the wrong process. It's not big enough. You think this is perfect for RPA, but it's saving somebody maybe five or 10 minutes a week, which in reality do you really want to put all the effort and to continue to maintain something like that on a back office level? So, I think the size of the processes and the complexity you've got to be thoughtful about as well. >> Thinking about a bot for every worker, what does that actually look like? Is that like you get a laptop and you get a bot? How does that actually manifest itself? >> Yeah I think as I've talked to some of the teams and Daniel as well about this, it's really around I mean imagine opening it up just like any other application on your computer and Excel, you've got that sitting on your desktop and you use that for a number of different things. I think that's kind of how I envision it and everyone when they come into GE, they'll get their laptop and it's part of their kind of package of software that they get. One of them will be UiPath and I think again if GE where I see that as the future. We've got to be thoughtful about how that's rolled out because you want to make sure it's done the right way and you want to make sure that that succeeds and what comes along with that is a lot of education. There's a lot of people that need to be educated on the technology in order to roll that out effectively. >> It's part of the onboarding part, just part of the HR onboarding, and so you open up your laptop and based on your role you'll have a library of bots that are applicable for your job. Is that kind of what you envision? >> Again I think that's kind of the future state and so HR will have a common library that they can pull from and Finance will have a common library that they can pull from. And I think the announcement this weekend of or this week of our StudioX is going to make life significantly easier. So, if you need to kind of edit any of those components or make any custom steps, you can do that with StudioX, but I think having a pre-built set of bots by function would be extremely important. >> And StudioX is the citizen developer right? So, okay now how do you then enforce the edicts of the COE if Dave Vallente's writing automations. >> It's honestly a question that we haven't answered yet and I think that's the piece that we're trying to solve for now, to roll it out more broadly. And I think part of it's going to be training right? Educating the broader group, part of it is giving them access to front office robots and so you do have the code back at the orchestrator so that you can see kind of what's going on and make sure if there are massive changes that need to be made, you can make some of that centrally, so I think figuring out how to centrally maintain and store some of that code is going to be important. >> And the idea of moving beyond this what they call this morning the snowflake into the snowball. So, reusable components is something that I've heard a lot about. That's not trivial yeah right because mapping the right component for the right job is always going to be some kind of unique, not always, but there could be some unique element to put in words. So, what are your thoughts on kind of future? I mean we touched on some of them. It sounds like even though you started early, 2016, it sounds like you still got a long way to go. What's the roadmap look like for you guys? >> Well it's really never-ending because you know you see how quickly the industry is changing and how quickly these automation platforms. I think we're at the point now where these are no longer RPA platforms. They're automation platforms with all of the different features and you look at the broader ecosystem of the technologies being pulled into play. I think it's moving from robotics process automation into intelligent process automation. And that's really our goal and leveraging the ecosystem that the UiPath is built is I think what we want to do more of going forward. >> And the primary measurement of value to you, I'm inferring is time saved from doing non-differentiated tasks, is that really a key metric or are there others that you're looking at, bottom line dollars that you're saving or what? >> I think the way that we measure productivity is really in three major buckets. One is the hours saved so that employees can do other things and I would say that is far and away, the largest bucket that we have. But I think additionally you've got to think about direct cost out. I mean if my finance team comes to me and says, we're thinking about hiring a person to do this why not an RPA? Why can't we use an RPA to do that instead? So, it's not like anyone's losing their job over. It's just figuring out a better way to supplement your existing workforce. Then I would say the third way really is thinking about the compliance element of things. So, and that's often overlooked. You may not save anyone time. You may not save anyone hours or dollars, but what you can do is expand for example in your audit function, expand your testing or sampling of a certain criteria, instead of sampling maybe the top 20 risky units, you can now sample a 100% of a population, which fundamentally changes how you can get comfortable with your financial statements and other elements of the compliance. >> Talking earlier just I asked is sampling dead because of RPA right? >> It really feels like that you know. >> Dave: Eric it's super knowledgeable. I really appreciate you coming on. >> Absolutely. >> Dave: Congratulations on all your success really. >> Thank you very much Dave. I appreciate it. >> You're welcome. All right keep it right there everybody, we will be back with our next guest right after this short break. We're live from UiPath Forward III from Las Vegas. You're watching theCUBE. (upbeat music)

(mellow music) >> Voiceover: Live from Seattle, Washington, it's theCUBE. Covering Smartsheet ENGAGE 2019. Brought to you by Smartsheet. >> Welcome back everyone, to theCUBE's live coverage of Smartsheet ENGAGE, here in Seattle. I'm your host, Rebecca Knight, along with my co-host, Jeff Frick. We are joined by Dr. WandaJean Jones. She is the Digital Learning Evangelist at GE Healthcare. Thank you so much for coming on the show! >> Thank you for having me. I'm so excited. >> Well we're excited to have you. So tell our viewers a little bit about what you do as the Digital Learning Evangelist, which is a very cool title. >> As Digital Learning Evangelist, the main part of my job is to manage our digital learning ecosystem. So, we have a learning management system, we use Adobe Captivate Prime. And then the other part of my job is to teach people how to use digital tools that will help make their lives a little bit easier. Save time, automate processes, and, you know, all the way around, create efficiencies. >> And how (chuckles). Are the employees willing to go there? Or are they naturally skeptical? I mean, what would you say? I mean, introducing a new technology to employees is famously a hard thing to do. How do you find it? >> Well, I'm a teacher at heart, so what I like to do is take what they already know and build off of that. So typically, if an employee comes to me and says, "WandaJean, we really want to learn "how to manage all of these Excel spreadsheets, "there's lots of data." I tell them, you know, "Come to the meeting with your Excel spreadsheets," and then I want them to tell me the story about their process, and then I go through and match them, kind of play matchmaker, and match them to that technology that already fits within their current behavior. There's some things that they'll have to change just a little bit, but we don't want to do it so much that they find it overwhelming, and say, "Oh my gosh, I'm never going to get this." So, I want to make sure they're comfortable and, you know, listening to them talk and seeing the sophistication in their current process, I'll know how far I can go. >> Now are these kind of next-gen productivity tools that you're getting them onto? Or are these kind of new collaboration tools that the company's taken on? What are some of the things you're transitioning them off of and putting them onto? >> I think one of the things is, the best part is, most of the work that's coming to me to transform, if you will, it's very manual. So, it's knowing where the tools are, and I make sure that I am very tool promiscuous. I like to go and look at all of these tools, and I like to understand which tools do what. And then I want to understand the role of the person and what they do for the business. And how those two can come together. So it's a matchmaker. The tools are, most of the time, digital collaborative tools. So we have a full suite of all sorts of tools at GE Healthcare. So we're definitely no short of tools. But sometimes people just haven't taken that digital leap to figure out, "How do I get my process "a little more digitized and save myself some time?" >> So what kinds of things are the people on your team working through, in terms of the kinds of processes you're helping them automate, the kinds of things you're helping them do manually, and how is Smartsheet coming into play here? >> Okay. So, I like to look at things from the triple constraints: Cost, quality, and speed. So, when you think about cost, quality, and speed, you want to take cost out of the process. You want to improve the quality by, you know, creating some sort of a standardization that everybody's going to do. And then you want to speed up the process that people can bring that, whatever it is, to market. And when I look at those three levers, this is exactly what my end users want to do anyway. So Smartsheet is able to answer all of those in such a remarkable way. That's usually the top of the list, when it comes to, you know, how are we going to implement this new digital process, Smartsheet is up there. It's the all-in-wonder. I call it the all-in-wonder tool at work, and people say, "Okay, here she comes. "She's going to talk about Smartsheet." That's because, I always say, "Smartsheet does a thousand things." That's why I really want to listen to what is necessary. I don't want to tell you about a thousand things. I only want to tell you about the things that, you know, you're looking at in this process. When the person starts using the new Smartsheet process, almost always they come back to me and say, "Look what else I found." So as they go on that journey, they start finding other things as well. And then we get excited together, and I say, "But did you see this?" And so, this whole, you know, Santa Claus is comin' to town (all laugh) That's kind of what it feels like. >> So, how has the collaboration culture changed over time? A lot of the conversations here around Smartsheet is that, A, you know, you can bring in people from an external organization, not to mention you can bring in external people from your organization within the big company. Have you seen a big change in you know, kind of how the teams form, and what's kind of the collaborative workgroup as these collaboration tools have suddenly become available? >> I think the biggest part with collaboration is now people know the upstream process and the downstream process. So, what information is going into this process, what do I need to do with it, and then what is the way that it needs to be ready for that next handoff, from a process perspective? So I like that. The @mentions are beyond wonderful. When I think about those @mentions, we have the place, especially in Smartsheet, to create comments. And you create the comment, but I'm too busy. I'm not going to go back to row 87 and see what you said. But, if you do this @mention, I've noticed that people, when they're using the app, you know, the @mention comes through. Even if they're not directly at their email, they'll go and see, "Oh, somebody's talking to me here." And so their app is helping them respond in real time. So, another part of the collaboration piece is cutting out collaboration. So, a lot of meetings, "'Kay, give me the status, what's the status." Well we can certainly just automate those reports, and make it exactly what, you know, the executive or the leader wanted to know, from a high-level perspective. And so, we don't have to have as many meetings. >> I love it though. That collaboration means cutting out collaboration. >> Mm-hmm. >> That is so important. One of the things that you said that was really striking is, understanding the upstream and the downstream. Because we heard on the main stage, and we are hearing a lot today, about how it's providing much more visibility. And leaders are able to see the big picture, and understand where things are working and where things are not working. But it actually, it's also helpful for the everyday employees, for the people who are several notches below, to understand and have that full picture. Can you talk about how having the full information has changed the way your company gets work done? >> Absolutely. So, inside of the process that I own, I'm in a learning and development team, and there are several trainers. There are several people who own curriculum and, you know, we are serving about 4,000 employees. We want to make sure these employees are getting the right learning that they need, and preparing them to do their job. So I certainly want to empower those trainers and curriculum owners to do their thing. I'm not going to go to class with you. I probably don't even know your content. But when I looked at Smartsheet dashboards, I started, you know, reporting is great. But when you flip it around, it's now a portal. And this is a information portal that everybody can be connected to. So, if we have a release in our system, if there's new materials that they can share, these can be happening right there at that portal. So I like it that I can empower people to not need me. And sometimes that can be scary. You think, "Oh, automation, it's coming, "and a robot's going to take over my job!" It's not that it's going to do, I have lots to do. But having this portal view allows people to go in and really be empowered. The other thing I have is sort of a ticketing system. So there's one of me, and 4,000 of them, and everybody might want something from WandaJean. So, I have a intake form that could easily take that work in and talk to me, and I get to know, you know, they put timeframes around when they need this. So I get to bubble up which ones are the most important ones, and which ones I can put off for a little bit. But at the end of the year, my leader might want to come back to me and say, "You know, what have you done for me lately?" And so, all of this input that has come through in this really standardized way could create a dashboard about what I've been doing, and I get to celebrate and understand, wow, I've had 50% more learning requests, and this many people wanted to learn about a tool, and, so I would have those metrics to even celebrate my own work and what I do as an individual. >> That's really interesting, right? 'Cause then you go from, the classic paradigm is there's data, right, which then becomes information, which then hopefully becomes some insight that you can actually take action. So it sounds like you're pulling that just on your straight-up inbound form, to actually get a whole lot of information on what's going on in that community, and where you can prioritize your time, your activities. >> Yes, well we create job requisitions and we hire people for roles. You know, you get this job description, you will do this and you will do that. It will be interesting at the end of the year to look back at this intake and see everything that you've actually done, versus what you signed up to do when you took the job. So, sometimes it looks really different, like, "Wait a minute, I think I need some more money." (Rebecca laughs) "'Cause I didn't get hired for this." >> Right, right, right, I've done so much more. >> Yes. >> Talk a little bit about the silos within the organization, and the ways in which the Smartsheet is helping break down those silos. >> Okay. So I talked to you guys a little earlier and told you that I believe that silo is an acronym for Secrets in the Learning Organization. And when you have those secrets, and you have no idea what this team or this team is doing, it could really cost the company cost, quality, speed. It's going to slow us down. We're going to both duplicate processes. And the quality of our product, instead of having process excellence, we'll have pockets of excellence. And we want to make everybody into these rockstars for the company. So, putting it together and making it more of, you know, a transparent ecosystem is awesome. The one thing that I really like is, when you map out a process and you pull in the right people and get those people involved, you'll get to understand, you know, resource management, any constraints, and you know, "Why is it, Bob, that you haven't done anything with this?" Where, I don't do that. And, you know, it starts a conversation. We can see, number one, what's wrong. And then we could have a conversation with the person about what's wrong. And it gives another action item for us to make it right. So without these sorts of, you know, without Smartsheet really helping us technologically bring those things together, it would be hard for me to even know where Bob is. It's a very big company. GE Healthcare is about 60,000 people. So, I don't know. I don't even know where Bob is right now. Bob, where are you? (laughter) But if Bob gets pulled into that Smartsheet, it shrinks the world, and it makes our big giant company just that much smaller, and people start knowing who you are and what you're supposed to be doing. And you get the right traffic of work. And then anything else that doesn't belong to you, it can get rerouted. >> Love to get your take on re-skilling, which isn't directly part of what you're doing, but you're currently doing re-skilling in terms of tools to execute different, you're training people to probably be more collaborative by using these tools and that different types of process. So important that re-skilling happens in the future, as all the jobs change. Just, you know, are people up for this? Are they excited to learn a new tool? Do they see that there're different ways to get work done than maybe our tradition? Or you still got the old codgers in the back, saying, you know, "That's not the way we did it 20 years ago!" >> Exactly, you do have that, you do have that. But, you know, this whole fake it until you make it, it's not going to work anymore. There's so many opportunities, especially within our company. We are sharing with our people leaders how to have collaboration across teams. Really don't think that your whole world is just right here inside of your job. Think broadly about what you do. And I like to say that, you know, I act locally but I think globally. So that just means, if I see that there is a process that I'm a part of, this is a mindset that we're sharing with our employees. If you see there's a process that you're a part of, and you see that it's broken and you fix it, fix it in such a way that it scales, and that it's applicable. You know, if we're all process managers, you probably have this problem too. So, create the fix, and then celebrate that socially, and show someone else, you can do it too. >> Rebecca: You can replicate this. >> You can replicate this. It's the classic before and after. You know, if we want to lose weight, we don't want to see the skinny person and telling, you know, how we got skinny. We want to see when you were larger, you know? You want to see the before and the after, and make sure that, you know, and when people see that, like, "It's possible? "I don't have to be, like, this superstar coder?" When they see how easy it is and they grab that process, I've seen them just do wonderful things. It's amazing, what our employees do. >> So, as a Digital Learning Evangelist, I mean, I don't know, how many are there of you in the world? And is it lonely? Do you come to these conferences to sort of have some community and some commiseration and understanding? I mean, what is it like, and how do you share your best practices with other people who do what you do in other companies? >> Well, in other companies, of course, our social networks, LinkedIn and those professional communities that I'm a part of, Smartsheet has a user group community, we can share there. Internally, there are people who are very interested in process. We use Yammer, so Microsoft Yammer. And we have a Smartsheet Yammer channel. This is one of the most healthiest channels in our business. We can see the stats on how many people are asking questions. And you have people coming there and saying, "Has anybody ever done this?" When I see that sort of curiosity, when I see someone in Europe jumping to help somebody in Mexico, it really is energizing, and it lets us know that everybody's trying to help everybody win. But how do I collaborate and get with other people? I do. I collaborate with other companies that, you know, I found out that Starbucks actually used Smartsheet during a disaster where there was a hurricane and they sent a Smartsheet forum out to their baristas, "Are you okay? "Can you make some coffee?" And, you know-- (laughter) >> Can you make the coffee. >> "And, oh by the way, take good pictures of the damage, "so we can submit it to our insurance." So, that's something that our company can use. And I'll take that back to our team, and say, "Guess what Starbucks did with this?" And, "Guess what PayPal did with this?" I sent PayPal's Smartsheet movie around to our executive team. They were very impressed. Now, it's not just that they were impressed. It's that, over the next two months, I heard that very same executive say, "We're going to create an integrated marketing calendar, "and we're going to use Smartsheet." That just made me feel so rewarded, that, you know, somebody is listening. You're not just talking! (Rebecca laughs) There are some converts! >> Great. Well, WandaJean, a pleasure having you on the show. >> Thank you, thank you so much. >> Please come back again. >> Yes, I will! >> I'm Rebecca Knight, for Jeff Fricks, stay tuned of more of theCUBE's live coverage of ENGAGE 2019. (minimal techno tone) (mellow music)

>> Man: Live from San Francisco celebrating 10 years of high tech coverage, it's the Cube. (music) Covering VMworld 2019. (music) Brought to you by VMware and it's ecosystem partners. >> And welcome, indeed, here to the cube and our coverage of VMworld 2019. We are in the Moscone Center in San Francisco. They're open, they're back in business and so is VMware. And we're watching the folks stream out from this morning's keynote session, Pat Gelsinger hosting that session. And it was an impressive setup to say the least. Thousands packing that ballroom downstairs for a plethora of announcements, all from Pat Gelsinger. I'm John Walls, Justin Warren joins us. We haven't been together for a while, it's good to see you.- It's been a little while, yeah. >> How've you been? >> I've been well, I've been well. >> Yeah. >> Yeah. >> I'm surprised they brought us back together after the last time. >> I don't believe... let's not talk about that incident. >> I thought it went so well, we just end on a high note. But it is a pleasure to be with Justin, we'll be with him throughout the week, Monday, Tuesday, Wednesday, our coverage here. We're joined right now by two guests, Paul Savill, whose the SVP of Network and Technology Solutions at CenturyLink and Omar Sunna who is the Director of Digital Products at GE Health care. And gentlemen thanks for being with us, it's good to have you here on the Cube. >> Thank you John. >> First off, let's just, gimme, your both, your take just on VMWorld 2019. What you're looking for, what you're expecting, and kind of the early vibe that you have going on. Paul, why don't you take that first? >> Sure, one of the things I've really been impressed with is how VMware is expanding, the kind of open nature of it's relationships, it's developing it's ecosystem, really broadening it out, it's making a number of acquisitions to enable new capabilities. And we're really excited about that. CenturyLink and VMware have been partners for, I think, around 12, 15 years. As we've been building out our own cloud services and so it's a very exciting time to see all this technology coming together in the way that it is. >> I love with the way you put it too, acquisitions. Pat made a little comment about that, it's like, "I can't wait to find out who I'm "going to buy next." >> Yes. >> And they've been, certainly been in a full speed ahead modefor the past year, year and a half. Omar, you're take, early. >> Yeah, man, I think I look at it from a health care solutioning perspective and it's exciting to see this level of technology and kind of the building out of the ecosystem and what could it enable for health care consumers. Especially with the big focus around privacy and and data management. I think some of their, and security, some of their latest acquisitions could actually help grow that ecosystem and offer more options especially to the health care industry. >> All right, well now let's talk about your portfolio at work then, a little bit, at GE Healthcare. Obviously health systems, health care's a huge user you know, these days, well it's kind of simplifying it a bit, but just talk about what you're concerns are, what your attention is, and kind of the things that are keeping you up at night, these days, in terms of health care and what you're doing in the IT space. >> You know, I mean, I think the, you know when we look at our customer environment globally, you know, we tend to kind of summarize some of the key challenges for our customers around three pillars. Access, so being able to provide access to all the patients that need it, regardless of location. With aging population in a lot of developed countries, with also a lot of people having the means to receive more proactive health care, it is challenging the health systems to be able to provide adequate access to patients. Capacity, providing capacity when the resources, including the human capital resources, that health systems have. So how do you free up your specialists to make sure that they're able to provide the right level of patients who need it, patient care for the patients that need it. As well as clinical efficacy. How do we help with software applications, with technology, to help reduce the variation of care, and improve patient outcomes, regardless where the patient is receiving care, within the rural community or with advanced academic medical centers. So we try to kind of think of our solution technologies as helping our customers solve for access, capacity, and clinical efficacy. >> Yeah, so a lot of health care, it's kind of a retail setup in that there's lots of hospitals and other allied health professionals who have lots of different locations that they need to provide heath care for them and that technology needs to live where the patients are and where the doctors are. So it was interesting to see, in the key note, earlier this morning, talking about edge and different kinds of edge as well. We've got thin, medium, and thick edge, according to VMware. So how do you see that rise of edge computing effecting the way that you deal with health care. >> Yeah, I mean tremendous, actually, opportunity for us. And GE is working on capitalizing on the technology, on edge technology, to allow us to bring in AI application right to, where kind of within the customer network. And that is, that's helping us solve for a lot of concerns around private security as well as moving large data sets to the cloud to process, to be able to get benefit out of algorithm and additional applications. So that's actually an exciting area. And agree with you, I mean we're seeing more and more large distributed health care networks emorph, in the U.S. we've definitely seen huge merger and acquisition movement that we continue to see, and consolidation. And then we also see that globally. With regional delivery networks coming up and being able to have software applications live within this distributed network and provide information for the right clinician at the right time is a big initiative for us. And for us this makes a huge difference in the way our providers are able to deliver care for their patients. >> This seems like an ideal opportunity for the folks at CenturyLink to help you with that. >> Abso-- (nervous laughter) >> Yeah, that's right, I mean CenturyLink really, to that point, sees this landscape evolving rapidly. And we even have a phrase internally we use that, "The network is the data center." We believe that in the future, compute is going to be distributed so widely, in such a broad geography and dropped in places where it's most efficient to run it and where it's most efficient to connect it with network, that really, the data centers we think about it today, becomes this very widely distributed platform that is connected together with high performance networking solutions. And that's part of what we're working with GE Healthcare on. >> I'm old enough to remember when "The network is the computer" was the slogan that we're all following now, and it seems that's actually coming true now. Where we have this idea of it, it's not just cloud, and it's not just data centers, and it's not just edge, it's actually a combination of all of them. And you need to be able to deal with that technology wherever it needs to live. Which is, I think, is a positive change from what we were talking about a few years ago, where it seemed to be, we had to make one choice. Now the choice is you actually need a bit of everything. >> Right. >> Tell me about your decision, or at least in terms of on-prem, off-prem, and health care, I would assume, extremely sensitive, obviously, to security concerns and management and certain policies about who can access what, where, when and how, whatever. How are you going about making that decision in this new multi-cloud environment, this hybrid-cloud environment, when people are making migrations, you know, with their businesses, and they're going off-prem. But you, I would assume, have to be a lot more sensitive, or more sensitive to other factors than, perhaps, other businesses have to be. >> Yeah, we definitely do. There is, you know, with regulations, you know, and, for example in Europe, GDPR, there's in country regulations around where data resides. All of that kind of plays a factor in customer adoption of technologies and where they're comfortable. We've talked a lot of CIOs in the health care sector and a lot of them say, "Hey, listen we're on a journey, "we're used to hugging our servers, "we're used to controlling it, and technology has evolved. "But, in terms of our policies, ability to accept liability "of data breaches and what technology providers are willing "to sign up for. "All of that plays a roll in that journey." Like Justin had mentioned, it is actually a, in developing an ecosystem, where you have combination of on-prem and off-prem, is a lot of where health care health systems are investing their money. So we're seeing certain data that resides on-prem that is mission critical versus more historic data can go into cloud technology, cloud storage technology and others. But, there's no doubt that we're at an inflection point, we're seeing a lot more health systems sign up to cloud based SAS applications. Invest in private cloud hosting service, invest in also public cloud hosting services. And all of that actually will create, as a software provider, all that could actually help us create more opportunities and more solutioning for our customers. I love listening to some of the cloud computing power that would allow us to develop newer applications. So it's actually exciting, it's a journey with our customers, you know, we're choosing to kind of be alongside of our customers and help them. Doing a lot of education. And being able to have a relationship with CenturyLink, be able to see the advances and availability of resources that CenturyLink makes available for us as well as other partners that we have help us really make sure that we're able to build the right level of technology meeting the health care customer needs. >> So Paul, fill in the gaps a little bit about where CenturyLink is in trying to solve this, I wouldn't say dilemma, but it certainly is a puzzle of some sort, right, as decisions are made about what's going to be off loaded, what's not, how are we going to access, what do we allow. How do you see CenturyLink's role when you have a customer like Omar, like GE Healthcare, coming to you with their unique needs, and addressing those? >> Sure, well, as unique as GE Healthcare is in the health care industry, there are some common characteristics about how we are seeing enterprise customers look at these situations. And one of them is that placing compute on the premise itself, that, that is generally the most expensive real estate that an enterprise has when it has to go in the hospital, when it has to go at the retail store location. And a lot of enterprises today are doubling the amount of compute and storage that they're having at their premise locations every year because the volume is just growing so much. That's becoming a problem, because you don't want your, you don't want your hospital becoming a bigger and bigger data center, so to speak, right? And so the way that we're approaching the problem and working with this, is in VMware was actually, you know, expressing a very similar viewpoint about the edge and about how the thick edge and the thin edge, and the thin edge of the customer premise is where you want to have the lightest load, but you want to have the most critical applications that are sitting there, you want to have the information that you have to protect the most in a most guarded way that's most important for your operations there. But from there you can more efficiently run things from a distance backing out going all the way back to the public cloud core, if you connect it with high performance networking from end to end. And so what CenturyLink has been doing is putting together these solutions that make that balance of trade, so to speak, between the cost of compute, the cost of where you have to put it, to where it best can be housed, what kind of latency performance that it needs to have to meet it to the performance specification, all the way back to the public cloud design and how to tie it in to the public cloud. And that's where we've been building our competency and the solutions we've been putting together for customers. >> You mentioned the need for high performance networks in there so I've got to ask you about 5G. From what I know about 5G it looks like the kind of situation you have with health care, where you've got lots of mobile tablet devices, you've got lots of other actual equipment IoT devices in a health care situation. That seems like an ideal use case for 5G. Is that what hot 5G is actually for, is the hype real? >> Well, 5G is certainly going to transform the world in terms of it's ability to provide wireless high bandwidth connectivity and low latency connectivity to devices. But, edge compute is not about 5G. You can have edge compute without 5G. In fact, it's a bit of a myth that edge compute can't arrive until 5G comes, because edge compute is something that is available to do today. And, in fact, CenturyLink is deploying edge compute solutions with, by basically building fiber into enterprise locations and then housing compute at different areas of the network at the point that's most optimal for the solution. And there are a variety of wireless solutions that can be used in that campus environment other than 5G to connect wireless devices back securely and safely to that edge compute that sits there. >> But it seems like it still should be, or at least looks like it could be a game changer in what it's going to allow in terms of, I guess, advancing edge computing. >> Right? I mean, you're still going to provide new capabilities and new reach and new functionalities that don't currently exist. >> I take Paul's point, though, because there are other technologies like Wi-Fi 6, for example, which is, it's basically the same thing as 5G, it just uses a different radio communications mechanism. But, and I also take your point that you can do edge computing today, absolutely. You can put computing into retail situations and you can have, I mean we have tablet devices now. We have laptops. So we kind of have edge computing. We always have, it just now, now it has a name. >> Yes, that's correct. >> So, tell me before we let you go, Catalyst Award winner from CenturyLink and VMware, Paul, first off let's talk about how you assess that, what's the determination, the criteria, for that and then I'm going to let crow a little bit Omar, about receiving that award. But tell us about the Catalyst Award first. >> Yes, well we call it the Catalyst Award because, when you think about it, a catalyst is something that excites a chemical process. Technically that is the definition of catalyst. But catalyst, in the way we view it, is something that we wanted to recognize a person or a company, that we felt like was really driving innovation, that was really solving a problem and working, also collaboratively together with VMware and CenturyLink in solving some of these problems. So we looked at GE Healthcare and really felt like, in a place where certainly we have seen such great advances in health care administration and building to save people's lives. Oddly, medical errors is becoming an increasing amount of now the problems in terms of death rates. Because, while we have so many ways to solve problems, so many ways to address it, that portion of what's causing deaths is actually on the rise. And so GE Healthcare is taking the technology that they're deploying and helping to solve that problem, that's why we wanted to recognize Omar and the company today. >> An honor for you I would assume you're all pretty proud of that. >> Yeah, absolutely, and thank you, and, yeah, I mean it's was really fantastic to be recognized by our partners. And a great testimony to the team at GE Healthcare. And our team wakes up in the morning and our mission is to improve lives in the moment that matters. A lot of our technology is used in mission critical and the way we're able to deliver that to our customers relies heavily on our ability to leverage advances in technology and be able to improve our ability to deliver our different applications for our customers. So this, actually been fantastic, the relationship has been tremendous for us. Where we have hosted our solutions in CenturyLink, the level of support that we have received have really enabled us to deliver important application for our customers and meet their SLAs and meet their clinical use cases and the needs of software uptime. So that has been tremendous for us. >> Well congratulations. >> Thank you. >> Well then thanks for your time, both of you. And enjoy the show, enjoy San Francisco, we've got good weather this week. >> That's right, yeah. >> So get out and enjoy that, thank you Paul and Omar. Back with more on the Cube, you're watching our coverage here live in San Francisco in VMWorld 2019. (music)

>> Live from Bellevue, Washington it's theCUBE. Covering Smartsheet Engage '18. Brought to you by Smartsheet. >> Welcome back to theCUBE. We are live at Smartsheet Engage 2018 in Bellevue, Washington. I am Lisa Martin with Jeff Frick, and we've had a great day talking with Smartsheet executives, analysts, users, and we're excited to welcome to theCube for the first time, Gurmeet Mangat, the site manager Wind Power Generation at GE Renewable Energy. Gurmeet, great to have you on the program. >> Thank you Lisa, thank you Jeff. I'm really happy to be here. >> So you're a user of Smartsheet, but you're also a renegade. So before we get into your renegade status, tell us a little bit about GE Renewable Energy and your role. You got a big role as site manager. What, 75 turbines across multiple locations? So let's talk about GE Renewable Energy and your role as site manager. >> Sure, no problem. So GE Renewable Energy. One of our missions statements is to unleash limitless energy. How we do that, we harness the power of the sun, the water, and the wind. So try to produce clean efficient energy to power countries, homes, businesses, whatever needs that powered energy. As a manager I manage, like you said three wind farms, three different customers. A very complex role to have. I'm coming right from not just operations, human resources, financials. So everything's required of someone like me to manage that business end to end. It's a challenge, at the same time I seek opportunity in a lot of what's going on and leveraging Smartsheet as one of the tools. It's something I've been using over the past year to optimize the business and run those turbines. >> So it's so funny because I would say GE turbine farms and GE engines are the most quoted, often referenced IOT devices in this next gen conversation about IOT and data and how much data they throw off of any other kind of product out there, and you're sitting right in the middle of it actually managing the real machines and managing the real data. >> Yeah, exactly. So I mean the, the machines themselves are highly automated. They're spinning out a lot of data and we've got great systems in place to manage that information. Make it transferrable, viewable to a lot of the people that need it. The opportunity is not necessarily in the equipment that GE manufactures but the back-end business that drives that manufacturing, that drives those services. That's where, again we leveraged Smartsheet over the last year to close a lot of data quality issues. We're ruling out and canceling a lot of the human error of the process steps that we're seeing in a lot of businesses today. We're really taking the initiative of managing our data, bringing us, making us actually competitive in the fourth industrial revolution. I mean I've had a strong believe that if you're not managing your data correctly today, you'll market yourself out of the business, you won't stay ahead of the game. So I think, like I was saying before the biggest opportunity right now is the back-end of the business. Smart GE does a great job at manufacturing and producing high quality products. I think there's huge opportunity in saving the back end and optimizing the process that runs that. >> When you say the back end, there's always a lot of conversation about you know going from reactive to predictive to prescriptive. Analytics, again everybody likes to talk about keeping the turbine up. Are you talking about those types of processes or is it more, you know how that energy is fed into the grid and more kind of the connection to the broader ecosystem, when you say back end? >> Let's talk about the proactive and reactive situation, 'cause that's really what we're trying to drive. >> Okay. >> There can be particular cases where a turbine could fail in the middle of winter, a high-wind season and the visibility's not great. So what we've done is we've taken Smartsheet. We've given our technicians a mobile application tool to collect data as they visit turbines. We're taking information within Smartsheet, we aggregate it, we quantify it, and now we're able to predict turbine behavior based on this information. A little bit faster than some of the tools that GE provides today. A perfect example is about a month ago we determined that a turbine needed a quarter of a million dollar repair before any GE tool told us that. That was simply because of giving our technicians a tool, which is a Smartsheet webform and telling us what happens everyday you visit that turbine. That goes into the background. We take the information, aggregate it into a dashboard viewings. That gives us a great visual control and visual aid of our business. >> That visibility-- >> I was going to say, is he collecting different data, or are you processing it in a different way with the tooling that you set up with Smartsheet that gives you that visibility? >> They are, so we are collecting different data. So GE gives us a lot of data on our turbine health efficiency, how it's operating. It might quantify the number of faults per megawatt hour and per (mumbles) it for us for example. But what we're creating with Smartsheet is we're creating our own organic KPIs I'll call them, some metrics that we are creating ourselves to try to drive different behavior. So when the techs go in, we talk about parts consumptions, for example. So if this part's been consumed 20 times over the last month, you've got to ask why. You know, why do you keep visiting this turbine to do that. So that visibility drives a different discussion now, so now we can engage with engineers with different type, different information. They might be able to say, "Okay, "you know what, you guys got some good data here. "We think you're right. "We should execute this repair." >> So, that example that you gave and give me the number again that working with Smartsheets your team was able to find a, what did you say, a $250 million? >> $250,000 repair. >> Thousand dollar repair. >> That's the cost of the repair, but it's a proactive repair versus reactive so now we're not facing a long wait time, finding a crane, bringing a crane on site, getting the paperwork in place to get the job done 'cause it's not an easy repair. >> But there's a very impressive snowball effect of the benefits back to the business. You've found it faster. You were able to get, you know the parts needed faster, repair it faster. Clearly that goes all the way back up the chain from a revenue perspective. >> Absolutely. >> But you, when I alluded to you earlier, this renegade status, you brought Smartsheet in from your previous job and you've said, "This has enabled us "to find something faster than "our brand of technology's product would have been "able to do." Talk to us about this conviction that you brought in and is it kind of becoming viral within GE Renewable Energy yet? >> Good question. It's becoming viral, a lot of people are listening now. So we've talked to GE digital VPs. I've talked to the ERP providers in Europe, what they're doing with GE. So we've essentially, I call it a success story. They're not going to adopt Smartsheet. They want to build their own enterprise solution but, the reason why I call it a success story is because I've changed the way that they are thinking today. >> That's huge. Cultural change? >> I've presented a solution to them. I've essentially told them, you need to give us something that works for us faster. If you do this, it gives managers capacity to improve your business, really develop people that are working underneath you, engage them, empower them, and move the business forward not on a typical five year plan that most businesses have in place. But it's a step change. >> Right, right. >> It takes you year over year and you're stepping every year to something new, and I think in today's day and age with how fast things are moving, you need that. >> And I'm curious to unpack a little bit on this example where you said you know, it's this failing part that was giving you a leading indicator that there was a bigger problem. So that was just kind of a different way to look at the solution, right? You're identifying kind of a stupid consumption pattern on a spare part that shouldn't happen as opposed to the core data that's coming off that machine and that's what gave you kind of the unique insights. Does that come from you? Does that come techs who are in the field and have kind of a sense of, "Maybe we should be looking at this, "maybe we should be looking at that." How do you start to empower people or where do some of these different kind of points of view that then can be backed up with data in the Smartsheet process come from? >> So, it's all techs. (clears throat) Coming into the job last year, I asked one of the techs, I said, "Why are you going to this turbine?" And the question why is such a powerful question to ask. They said, "We're going to fix this." So what happened last time? They had no idea. So I said, "There's no "information to support your visit today? "And you don't understand why you're going today." They said, "As a result of something that was not "done correctly before." So we fixed that part first. We started giving them the information upfront. We gave them a tool to collect the data. So now they are empowered to provide very direct feedback to myself as a manager and even to an engineering team, like in New York for example. Something technicians never felt empowered to do before. They are the driving factors for those data collection, the decision making. I definitely appreciate that by giving them feedback on a daily basis, that what you guys are doing is changing the way that we manage the business. It's a very driven culture change by the front line. It's not something that I'm pushing down. I'm asking them to help me push it upwards to the senior level. >> And they've got to love it. They've got to love thinking that they've actually got input as opposed to just being called to go out and fix things when it breaks. >> Exactly. They're driving their day. They can go to work in the morning. They can look at the whole personality of a turbine, what's outstanding, what was done last time and the conversations are very quick in the morning. It used to be a 7 o'clock startup. They're not driving out 'til eight, 8:30, nine o'clock by the time they get their stuff together. I mean we're averaging a seven am to about 7:30 departure now. >> So each person is saving 60 to 90 minutes everyday. >> Every day now departure. >> That's a big roll up. In fact, I was looking at some of the productivity stats that Smartsheet talks about on their website and they say an average per, individual user of Smartsheet will save about 300 hours a year. An organization can save up to 60,000 hours a year. >> I believe that. That's believable. I mean there's, just a technical aspect of managing a turbine. If we even talk about you know issuing a purchase order. Managing contractor labor, invoices. The tool that we're using today is a complete end to end P & L management tool. So it takes invoicing from subcontractors, labor. We are inventory tracking, we are tracking any health and safety issues. Everything from end to end, so it's really done a great job for us. >> That's all built within your Smartsheet? >> Correct. >> Wow. >> And it's all mobile, so. I mean I'm not at my site this week, but on a daily basis I have visibility to my business. You're talking about 70, 80 plus machines, that's over you know about a hundred million dollars in assets that have to be managed effectively, efficiently, and correctly. >> You have visibility into everyday from wherever you are? >> Exactly, yes. >> That's a huge transformation. So we talked about you being a renegade and other groups within GE on divisions that are curious about this. I'm curious, have you heard anything today that they have announced that excites you, or maybe was any of this part of a feedback that you provided, as we've heard all day Jeff that they're very responsive to customer feedback in terms of product innovation. Anything you're going to go back to the office and be excited, like the next generation or what's coming available soon? Is it going to enable me to do X-Y-Z now? >> That's a good question. So GE is a very tough company to change. There will be a lot of takeaways from this trip and when I go head back. After the last conversation I had with GE digital and the team, they are going to hire a new resource and set budget aside to help close the gaps that we've identified. So I think after this visit and some of the things I've learned throughout the conference and when I head back I'll only be able to identify a few more gaps that they need to fill, and I'll push that up to them probably in the next week when I get back there and hopefully they can appreciate that candid feedback and take that and run with it. >> But you were able to fund your existing project just out of your own discretionary funds? >> Exactly. I mean that's one of the benefits of Smartsheet. It costs really nothing to create something, and my job is to manage wind farms, so I've taken initiative to create, I call it a mini-ERP system using Smartsheet with an associate of mine, and it's an organic creation. It didn't take us, I mean to run three wind farms, I started last April, it probably took us less than six months to create a working system. That's awesome feedback for Smartsheet, their tools are very user-friendly. It's lightweight, it takes away the fear of coding that Excel gives to some people. If you're a new user of any application you can kind of walk into it and run with it. That's one of the reasons why we took it from nothing to something in such a short period of time. >> Wow. >> That's a ground swell in action that has some significant results. But you'd better be careful. I'm imagining your success is going to go so viral, you're going to have way more than 75 turbines and three wind farms >> That's possible. >> to manage. (laughs) >> There's been a recent acquisition and there's other sites around me that my boss is, or my directors said, "Hey, what are you doing next week?" >> Oh! (laughs) >> "Let's go visit this site for a few minutes." Okay, I know what you're getting at. >> Kind of a good problem to have, but thanks so much for stopping by and sharing with us what you're doing as a renegade. It seems pretty contagious. >> Appreciate it, thank you for having me. >> Thanks. >> Thanks. >> For Jeff Frick I'm Lisa Martin and you're watching theCUBE live from Smartsheet Engage 2018. Stick around, Jeff and I will be back to wrap up the show in just a minute. (digital music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering IMAGINE 2018. Brought to you by Automation Anywhere. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in Manhattan, New York City, at Automation Anywhere's IMAGINE 2018. We've never been to this show. Pretty interesting, about 1,100 people talking about Bots, but it's really more than Bots. It's really how do we use digital employees, digital programs, to help people be more efficient, and take advantage of a lot of the opportunities as well as the challenges that we're facing as we keep innovating, I'm really excited to have our next guest. Jeffrey Immelt, the former chairman and CEO of GE, great to see you Jeff. >> Good to see you. >> Absolutely, last I saw you I think, was at Minds and Machines, and we're huge fans, >> A couple years ago, yep. >> Beth Comstock, I loved Bill Ruh, so you know, what a fantastic team. >> A great team. >> But here you are talking about Bots, and it's interesting because at GE you guys have been involved in big industrial equipment, as well as a huge software business, so you really figured out that you've gotta have software and people to really work with these machines. >> So you know Jeff, I really am a big believer that productivity is the key, and that we, we're seeing a bow wave of technology that's really gonna impact the workplace in a meaningful way. The reason why I like RPA, what we call Bots-- >> Right, RPA. >> Is because it can happen so quickly. It can happen across the organization. It has great productivity associated with it. So I kinda view RPA as being really one of the uh, let's say early wave technologies in terms of how to drive more automation and productivity in the workplace. >> That's funny, because people ask me they're like, what's the deal with some of these stock evaluations, is it real, and think back to the ERP days right, ERP unlocked this huge amount of inefficiency. That was a long, long time ago, and yet we still continue to find these huge buckets of inefficiency over and over. >> I think it's, I mean I think to your point, the early days of IT, really if you look at ERP manufacturing systems, even CRM. They were really more around governance. They were kind of connecting big enterprises. But they really weren't driving the kind of decision support, automation, AI, that companies really need to drive productivity. And I think the next wave of tools will operate inside that envelope. You know, ultimately these will all merge. But I think these are gonna get productivity much quicker than an ERP system or an MES system did. Which are really, at the end of the day, driven by CFOs to drive compliance more than operating people to drive productivity. >> Right, but what's driving this as we've seen over and over, that consumerization of IT, not only in terms of the expected behavior of applications, you know you want everything to act like Amazon, you want everything to act like Google. But also, in terms of expectations of feedback, expectations of performance. Now people can directly connect with the customer, with companies like they never could before, and the customers, and the companies can direct with their customer directly. Where before you had channels, you had a lot of distribution steps in between. Those things are kind of breaking down. >> I think that's for sure. I mean I think that's sure. I would say beyond that is the ability to empower employees more with some of these tools so you know, an employee used to have to go to the CIO with a work ticket, hey here's what I need. You know these Bots grow virally inside organizations. They're easy to implement. They're easy to see an impact very quickly. So I just think the tools are becoming more facile. It's no longer kind of a hierarchical IT-driven technology base. It's more of a grounds-up technology base, and I think it's gonna drive more speed and productivity inside companies. >> Right, so really it's kind of, there's always a discussion of are the machines gonna take our jobs, or are they? But really there's-- >> Jeff, I'm not that smart really I mean-- >> Well, but it's funny because they're not right? I mean, everyone's got requisitions out like crazy, we need the machines to help us do the jobs. >> Nobody has, nobody has easy jobs. The fact of the matter is, nobody has easy jobs. You know, a company like GE would have 300 ERP systems right? Because of acquisitions and things like that. And the METs not a complexity, manual journal entries, things like that. So to a certain extent these, this automation is really helping people do their jobs better. >> Better. >> More than thinking about you know, where does it all go some day. So I think, I think we're much better off as an economy getting these tools out there, getting people experience with them and, and uh, seeing what happens next. >> Right, it's funny they just showed the Bot store in the keynote before we sat down, and when you look closely, a lot of them look like relatively simple processes. But the problem is, they're relatively simple, but they take up a lot of time, and they're not that automated, most of them. >> One of my favorites Jeff, is doing a quote for a gas power plant would take eight weeks. Because now we have Bots, that can draw data from different data sources, you can do it in two and a half days right? So that's not what you naturally think of for an automation technology like this. But the ability to automate from the different data sources is what creates the cycle of time reduction. >> Right, and you're fortunate, you've sat in a position where you can really look down the road at some interesting things coming forward. And we always hear kind of these two views, there's kind of the dark view of where this is all going with the automation, and the robots. And then there's the more positive view that you just touched on you know, these are gonna enable us to do more with less and, and free people up to actually be productive, and not do the mundane. >> I think productivity, productivity enables growth. The world needs more productivity. These tools are gonna be used to drive more productivity. I think many more jobs will be technically enabled, than will be eliminated by technology. Clearly there's gonna be some that are, that are, that are impacted more dramatically than others. But I would actually say, for most people, the ability to have technology to help them do their day-to-day job is gonna have a much higher impact. >> Right. What do you think is the biggest misperception of this of this combining of people and machines to do better? Where do you think people kind of miss the boat? >> Oh look I mean, I think it's that people wanna gravitate towards a macro view. A theoretical view, versus actually watching how people work. If you actually spent time seeing how a Service Engineer works, how a Manufacturing person works, how an Administrative person works, then I think you would applaud the technology. Really, I think we tend to make these pronouncements that are philosophical or, coming from Silicon Valley about the rest of the world versus, if everybody just every day, would actually observe how tasks actually get done, you'd say bring on more technology. Because this is just shitty you know, these are just horrible, you know, these are tough, horrible jobs right? A Field Engineer fixing a turbine out in the, in the middle of Texas right, a wind turbine. If we can arm them with some virtual reality tools, and the ability to use analytics so that they can fix it right the first time, that's liberating for that person. They don't look at that and say, "Oh my God, if I use this they're gonna replace me." >> Right, right. >> They really need me to do all this stuff so, I think not enough people know how people actually work. That's the problem. >> It's a tool right? It's as if you took the guy's truck away, and made him ride out there on a horse I mean-- >> It's just a, it's just a, you know look-- >> It's just another tool. >> I remember sitting in a sales office in the early 80s, when the IT guy came out and installed Microsoft Outlook for the first time. And I remember sitting there saying, who would ever need this? You know, who needs spreadsheets? >> Right, right. >> I could do it all here. >> Yeah, little did you know. >> So I just think it's kind of one of those crazy things really. >> Yeah, little did you know those spreadsheets are still driving 80% of the world's computational demands. >> Exactly. >> Great, well alright I wanna give you a last word again. You're here, it's a very exciting spot. We call 'em Bots, or robotic process automation for those that aren't dialed in to RPA stands for. As you look forward, what are you really excited about? >> Oh look, I mean I always think back to the, to kind of the four A's really, which is uh you know, kind of artificial intelligence, automation, additive manufacturing and analytics. And I think if everybody could just hone in on those four things, it's gonna be immensely disruptive, as it pertains to just how people work, how things get built, how people do their work so, when you think about RPA, I put that in the automation. It's kind of a merger of automation and AI. It's just really exciting what's gonna be available. But this, this bow wave of technology, it's just a great time to be alive, really. >> Yeah, it is. People will forget. They focus on the negative, and don't really look at the track, but you can drop into any city, anywhere in the world, pull up your phone and find the directions to the local museum. Alright, well Jeff, thanks for uh taking a few minutes of your time. >> Great. >> Alright, he's Jeff Immelt and I'm Jeff Frick, you're watching theCUBE from Automation Anywhere IMAGINE 2018. Thanks for watching. (jazz music)

(upbeat orchestral music) >> Welcome back everybody. Jeff Frick here with the CUBE. We're at our Palo Alto studios having a CUBE conversation about digital transformation, industrial internet, AI, ML, all things great, and we're really excited to have a representative of GE, one of our favorite companies to work with because they're at the cutting edge of old industrial stuff and new digital transformation and building a big software organization out in San Ramon. So we're so happy to have here first time Jeff Erhardt. He is the VP Intelligent Systems from GE Digital. Jeff, great to see you. >> Pleasure to be here. Thanks for having me. >> Absolutely, so how did you get into GE? You actually, a creature of the valley, you've been here a little while. How did you end up at GE? >> I have. I'm a new guy, so I've been here about a year and a half, I came in via the acquisition of a company called Wise IO where I was the CEO, so I've spent the last 10 years or so of my life building two different analytic startups. One was based around a very popular and powerful open source language called R and spent a lot of time working with much of the Fortune 500. Think the really data driven companies now that you would think of, the Facebooks, the Goldman Sachs, the Mercks, the Pfeizers helping them go through this data driven journey. Anyway, that company was acquired by Microsoft and is embedded into their products now. But the biggest thing I learned out about that was that even if you have really good data science teams, it's incredibly hard to go from white board into production. How do you take concepts and make them work reliably repeatably, scalably over time? And so, Wise IO was a machine learning company that was a spin out from Berkeley, and we spent time building what I now refer to as intelligent systems for the purposes of customer support automation within things like the sales force and Zendesk ecosystem, and it was really that capability that drew us to GE or drew GE to approach us, to think about how do we build that gap not just from algorithms, but into building true intelligent applications? >> Right, so GE is such a great company. They've been around for a hundred years, original DOW component, Jeff Immelt's not there now, but he was the CEO I think for 16 years. A long period of time. Beth Comstock, fantastic leader. Bill Ruth building this great organization. But it's all built around these industrial assets. But they've started, they did the industrial internet launch. We helped cover it in 2013. They have the Pridix Cloud, their own kind of industrial internet cloud, had a big developer conference. But I'm curious coming from kind of a small Silicon Valley startup situation. When you went into GE, what's kind of the state of their adoption, you know, kind of how had Bill's group penetrated the rest of GE and were they making process? We're people kinda getting it, or were you still doing some evangelical work out in the field? Absolutely both, meaning people understand it are implementing yet I think there was maybe misunderstandings about how to think about software data in particular analytics and AI machine learning. And so a big part of my first year at the company was to spend the time coming in really from the top down, from sort of the CEO and CDO levels across the different business understanding what was the state of data and data driven processes within their businesses. And what I learned really quickly was that the core of this business, and this is all public information been well publicized, is in things like GE Aviation. It's not necessarily the sale of the engine that is incredible profitable, but rather it's maintaining and servicing that over time. >> Right. >> And what organizations like them, like our oil and gas divisions, with things like their inspection capabilities like our power division had really done is they had created as a service businesses where they we're taking data across the customer base, running it through a data driven process, and then driving outcomes for our customers. And all of a sudden the aha moment was wow, wait a minute. This is the business model that every startup in the valley is getting funded to take down the traditional software players for. It's just not yet modern, scalable, repeatable, with AI machine learning built in, but that's the purpose and the value of building these common platforms with these applications on top that you can then make intelligent. >> Right. >> So, once we figure that out it was very easy to know where to focus and start building from that. >> So it's just, it's kinda weird I'm sure for people on the outside looking in to say data driven company. We all want to drive data driven companies. But then you say, well wait a minute, now GE builds jet engines. There's no greater example that's used at conferences as to the number of terabytes of data an engine throws off on a transcontinental flight. Or you think of a power plant or locomotion and you think of the control room with all this information so it probably seems counterintuitive to most that, didn't they have data, weren't they a data driven organization? How has the onset of machine learning and some of the modern architectures actually turned them into a data driven company, where before I think they were but really not to the level that we're specifying here. >> Yah, I-- >> What would be your objective, what are you trying to take on this? >> Absolutely, machine learning, AI, whatever buzz words you want to use is a fascinating topic. It's certainly come into vogue. like many things that are hyped, gets confused, gets misused, and gets overplayed. But, it has the potential to be both an incredibly simple technology as well as an incredibly powerful technology. So, one of the things I've most often seen cause people to go awry in this space is to try to think about what is the new things that I can do with machine learning? What is the green field opportunity? And whenever I'm talking to somebody at whatever level, but particularly at the higher levels of the company is I like to take a step back and I like to say, "What are the value producing, data driven workflows within your business?" And I say define for me the data that you have, how decisions are made upon it, and what outcome that you are driving for. And if you can do that, then what we can do is we can overlay machine learning as a technology to intelligently automate or augment those processes. And in turn what that's gonna do is it's gonna force you to standardize your infrastructure, standardize those workflows, quantify what you're trying to optimize for your customers. And if you do that in a standardized and incremental way, you can look backward having accomplished some very big things. >> Right, and those are such big foundational pieces that most people I think discount again, just the simple question of where is your data. >> That's right. >> What form is it in? So another interesting concept that we cover all the time with all the shows we go to is democratization, right? So it seems to me pretty simple, actually. How do you drive innovation, democratize the data, democratize the tool to manipulate the data, and democratize the ability to actually do something about it. That said, it's not that easy. And this kind of concept that we see evolving from citizen developer to citizen integrator to citizen data scientist is kinda where we all want to go to, but as you've experienced first hand it's not quite as easy as maybe it appears. >> Yah, I think that's a very fair statement and you know, one of the things, again I spend a lot of time talking about, is I like to think about getting the right people in the right roles, using the right tools. And the term data scientist has evolved over the past five plus years going from to give Drew Conway some credit of his Venn diagram of a program or a math kinda domain expert, into meaning anybody that's looking at data. And there's nothing wrong with that, but the concept of taking anybody that has ability to look at data within something like a BI or a Tableau tool, that is something that should absolutely be democratized and you can think about creating citizens for those people. On the flip side, though, how do you structure a true intelligent system that is running reliably, robustly, and particular in our field in mission critical, high risk, high stakes applications? There are bigger challenges than simply are the tools easy enough to use. It's very much more a software engineering problem than it is a data access or algorithmic problem. >> Right. >> And, so we need to build those bridges and think about where do we apply the citizens to for that understanding, and how do we build robust, reliable software over time? >> Right, so many places we can go, and we're gonna go a lot of them. But one of the things you touched on which also is now coming in vogue is kind of ML that you can, somebody else's ML, right? >> Mhmm. >> As you would buy an application at an app store, now there's all kinds of algorithmic equations out there that you can purchase and participate in. And that really begs an interesting question of kinda the classic buy versus build, or as you said before we turned on the cameras buy versus consume because with API economy with all these connected applications, it really opens up an opportunity that you can use a lot more than was produced inside your own four walls. >> Absolutely. >> For those applications. >> Yep. >> And are you seeing that? How's that kinda playing out? >> So we can parse that in a couple of different ways. So the first thing that I would say is there's a Google paper from a few years back that we love and it's required reading for every new employee that we bring on board. And the title of it was machine Learning is the High Interest Credit Card of Technical Debt. And one of the key points within that paper is that the algorithm piece is something like five percent of an overall production machine learning implementation. And so it gets back to the citizen piece. About it's not just making algorithms easier to use, but it's also about where do you consume things from an API economy? So that's the first thing I would think about. The second thing I would think about is there's different ways to use algorithms or APIs or pieces of information within an overall intelligent system. So you might think of speech to text or translation as capabilities. That's something where it probably absolutely makes sense to call an API from an Amazon or a Microsoft or a Google to do that, but then knowing how to integrate that reliably, robustly into the particular application or business problem that you have, is an important next step. >> Right. >> The third thing that I would think about is, it very much matters what your space is. And there's a difference between doing things like image classification on things like Imagenet which is publicly available images which are well documented. Is it a dog versus a cat? Is it a hot dog versus not? Versus some of the things that we face with an industrial context, which aren't really publicly available. So we deal with things like within our oil and gas business we have a very large pipeline inspection integrity business where the purpose of that is to send the equivalent of an MRI machine through the pipes and collect spectral images that collect across 14 different sensors. The ability to think that you're gonna take a pre trained algorithm based on deep learning and publicly available images to something that is noisy, dirty, has 14 different types of sensors on it and get a good answer-- >> Right. >> Is ridiculous. >> And there's not that many, right? >> And there's not that many. >> That's the other thing I think people underestimate the advantage that Google has we're all taking pictures of dogs and blueberries-- >> Correct. >> So that it's got so much more data to work with. >> That's right. >> As opposed to these industrial applications which are much smaller. >> That's right. >> Lets shift gears again, in terms of digital transformation one of the other often often said examples is when will the day come that GE doesn't sell just engines but actually sells propulsion miles? >> Yep. >> To really convert to a service. >> Yah. >> And that's ultimately where it needs to go cause it's kinda the next step beyond maintenance. >> Yep. >> How are you seeing that digital transformation play out? Do people kinda get it? Do the old line guys that run the jet engine see that this is really a better opportunity? >> Mhmm. >> Cause you guys have, and this is the broader theme, very uniques data and very unique expertise that you've aggregated across in the jet engines base all of your customers in all of the flying conditions and all of the types of airplanes where one individual mechanic or one individual airline just doesn't have an expertise. >> Yep. >> Huge opportunity. >> That's exactly right, and you can say the ame thing in our power space, in our power generation space. You can say the same thing in the one we we're just talking about, you know things like our inspection technology spaces. That's what makes the opportunity so powerful at GE and it's exactly the reason why I'm there because we can't get that any place else. It's both that history, it's that knowledge tied to the data, and very importantly it's what you hinted at that bares repeating is the customer relationships and the customer base upon which you can work together to aggregate all that data together. And if you look at what things are being done, they're already doing it. They are selling effectively, efficiency within a power plant. They are selling safety within certain systems, and again, coming back to why create a platform. Why create standardized applications? Why put these on top? Is if you standardize that, it gives you the ability to create derivative and adjacent products very easily, very efficiently, in ways that nobody else can match. >> Right, right. And I love the whole, for people who aren't familiar with the digital twin concept, but really leveraging this concept of a digital twin not to mimic kinda the macro level, but to mimic the micro level of a particular part unit engine in a particular ecosystem where you can now run simulations, you can run tests, you can do all kinds of stuff without actually having that second big piece of capital gear out there. >> That's right, and it's really hard to mimic those if you didn't start from the first phase of how did you design, build, and put it in to the field? >> Right, right. So, I want to shift gears a little bit just on to philosophical things that you've talked about and doing some research. One of them is that tech is the means to an end, and I know people talk about that all the time, but we're in the tech business. We're here in Silicon Valley. People get so enamored with the technology that they forget that it is a means to an end. It is now the end and to stay focused. >> That's right. >> How are you seeing that kind of play out in GE Digital? Obviously Bill built this humongous organization. I'm super impressed he was able to hire that many people within the last like four years in San Ramon. >> Yah. >> Originally I think just to build the internal software workings within the GE business units, but now really to go much further in terms of industrial internet connectivity, etc. So how do you see that really kinda playing out? >> Yah, I think one of my favorite quotes that I forget who it came from but I'll borrow it is, "Customers don't want to buy a one inch drill bit, they want to buy a one inch hole." >> Right. >> And I think there is both an art and a science and a degree of understanding that needs to go into what is the real customer problem that they are trying to solve for, and how do you peel the onion to understanding that versus just giving what they ask for? >> Right. >> And I think there's an organizational design to how do you get that right. So we had a visitor from Europe, the chairman of one of our large customers, who is going through this data driven journey, and they were at the stage of simply just collecting data off of their equipment. In this case it was elevators and escalators. And then understanding how was it being used? What does it mean for field maintenance, etcetera? But his guys wanted to move right to the end stage and they wanted to come in and say, "Hey, we want to build AI machine learning systems." And we spent some time talking through them about how this is a journey, how you step through it. And you could see the light bulb go off. That yes, I shouldn't try to jump right to that end state. There's a process of going through it, number one, and then the second thing we spent some time talking about was how he can think about structuring his company to create that bridge between the new technology people who are building and doing things in a certain way, and the people who have the legacy knowledge of how things are built, run, and operated? >> Right. >> And it's many times those organizational aspects that are as challenging or as big of barriers to getting it right as a specific technology. >> Oh, for sure, I mean people process and tech it's always the people that are the hard part. It's funny you bring up the elevator or escalator story, We did a show at Spunk many moons ago and we had a person on from an elevator company and the amazing insight they connected Spunk to it. They could actually tell the health of a building by the elevator traffic. >> Yah. >> Not the health of it's industrial systems and it's HVAC, but whether some of the tenants were in trouble. >> Yep. >> By watching the patterns that were coming off the elevator. While different kinda data driven value proposition than they had before. >> Yep. So again, if you could share some best practices really from your experiences with R and now kinda what you're doing at GE about how people should start those first couple of steps in being data driven beyond kinda the simple terms of getting your house in order, getting your data in order, where is it. >> Yah. >> Can you connect to it? Is it clean? >> Yah. >> How should they kinda think about prioritizing? Ho do they look for those easy wins cause at the end of the day it's always about the easiest wins to get the support to move to the next level. >> Yah, so I've sorta got a very simple Hilo play book and you know the first step is you have to know your business. And you have to really understand and prioritize. Again, sometimes I think about not the build, buy decision per say, but maybe the build consume decision. And again, where does it take the effort to go through hiring the people, understanding building those solutions, versus where is it just best to say, "I'm best to consume this product or service from somebody else." So that's number one, and you have to understand your business to do that, really well. The second one is, and we touched on this before, which is getting the right people in the right seats of the bus. Understanding who those citizen data scientists are versus who your developers are, who your analytics people are, who your machine learning people are, and making sure you've got the right people doing the right thing. >> Right. >> And then the last thing is to make sure, to understand that it is a journey. And we like to think about the journey that we go through in sort of three phases, right? Or sort of three swim lanes that could happen, both in parallel, but also as a journey. And we think about those as sort of basic BI and exploratory analytics. How do I learn is there any there there? And fundamentally you're saying, I want to ask and answer a question one time. Think about traditional business reporting. But once you've done that, your goal is always to put something into production. You say, "I've asked and answered once, now I want to ask and answer hundreds, millions, billions of times-- >> Right, right. >> In a row." And the goal is to codify that knowledge into a statistic, an analytic, a business role. And then, how do you start running those within a consistent system? And it's gonna do and force exactly what you just said. Do I have my data in one place? Is it scalable? Is it robust? Is it queryable? Where is it being consumed? How do I capture what's good or bad? And once I start to then define those, I can then start to standardize that within an application workflow and then move into, again, these complex, adaptive, intelligent systems powered by AI machine learning. And so, that's the way we think about it. Know your business, get the people right, understand that it's a systematic journey. >> Right, and then really bake it into the application. >> That's right. >> That's the thing, we don't want to make the same mistake that we do with big data, right? >> Yep. >> Just put it into the application. It's not this stand alone-- >> Correct. >> You know, kinda funny thing. >> Exactly. >> Alright, Jeff, I'll give you the last work before we wrap for the day. So you've been with GE now for about a year and a half, about halfway through 2018. What are your priorities for the next 12 months? If we sit down here, you know June one next year, what are you working on, what's kinda top of mind for you going forward? >> Yah, so top of the line for me, so as I mentioned sort of our first year here was really surveying the landscape, understanding how this company does business, where the opportunities are. Again, where those data driven work flows are. And we have an idea of of that with the core industrial. And so what we've been doing is getting that infrastructure right, getting those people right, getting the V ones of some very powerful systems set up. And so, what I'm gonna be doing over the next year or so is really working with them to scale those out within those core parts of the business, understand how we can create derivative and adjacent products over those, and then how we can take them to market more broadly based upon that, exactly as you said earlier, large scale data that we have available, that customer insight, and that knowledge of how we've been building the stuff, so. >> Alright, I look forward to it. >> I look forward to being back in a year. >> All right, Jeff Erhardt. Thanks for watching. I'm Jeff Frick. You're watching the CUBE from our Palo Alto studios. See you next time. (upbeat orchestra music)

>> Announcer: Live from Madrid, Spain. It's theCube covering HPE Discover Madrid 2017. Brought to you by Hewlett-Packard Enterprise. >> And we're back at HPE Discover Madrid 2018. This is theCube, the leader in live tech coverage. I'm Dave Vellante, with my co-host Peter Burris. This is day two of the event. Johannes Koch is here, he's the Vice President and Managing Director of Central Eastern Europe, Middle East and Africa for Hewlett-Packard Enterprise, and he's joined by Ali Saleh, he's the Senior Vice President and Chief Commercial Officer at GE Digital for Middle East and Africa. Gentlemen, thanks so much for coming to theCube. >> Appreciate it. Thank you. >> Thank you for having us. >> Johannes, let's start off with you. GE, HPE, what are you guys all about, what are you doing together? Talk about the partnership and the alliance. >> So, you know, it started actually one month ago, I suppose and it was meetings that we had with General Electric to understand the customer requirements in cybersecurity, and what we figured is in this world of IoT, Internet of Things there is an increased requirement for security. And there was, from our perspective, lots of solutions out there but it's quite difficult for customers to understand the landscape and who to turn to. And we also figured that in this world, nobody can serve every requirement of a customer, so this is how we figured out with GED that we have a joint interest here, to serve in the Central/Eastern European and then mainly in the Middle East and Africa part our customer base. And this is how it started and I think what I can say is it has accelerated incredibly during the last two months since we signed the joint agreement. We've been building a channel, we've been having lots of meetings with customers and built a really nice pipeline in the meantime, also I think here the show reflects an incredible interest by our customers. So I think we are in a very good state at the moment having a lot of interest, probably all the key customers in our region having this on their agenda. >> Ali, maybe you could just describe the situation, the industrial expansion if you will in Middle East and Africa, what you guys are seeing in terms of the big trends, and what the opportunity looks like. >> Well thank you. You know, GE has been in the Middle East, Africa, for over 80 years in some countries, and we have deep relationships on industrial side, whether it's power, oil and gas, aviation, healthcare and others. And our customers are thinking a lot about cost, quality, and access, and productivity is top of mind, and they've discovered that their industrial assets are smart and capable but the data are not being collected. So when we collaborate with ecosystem of partners, and we fetch the data and get connected, and get insights from the machine to make them able to make the right decision at the right time and then it drives optimization. This is top of mind. They want to see how they can do better for less. >> Okay, so the customers at GE Digital, the customers are going digital, they have all these devices, instruments, machines, and they're moving in a new direction you guys are trying to lead in. What are the challenges that they're facing, what are they asking your help on, what are the big problems that they're trying to solve? >> So, everyone wants to talk about productivity and calls out. The challenge is that not everyone is ready for digital transformation. Some do not feel there is a burning platform, and those that are ready when they feel there is a burning platform, they don't have a plan, they don't have a playbook. So it's important that we collaborate and help our partners and customers understand their current state and heat map and desired state and pinpoint to quick wins so that they get it and they see incremental improvement. And asset performance management has been an easy way for us to say, "Your asset is underutilized "compared to your industrial entitlement "you can do 10x better," and this gets their attention, and this is where we see the power of one in the industrial age is relevant, one percent. In our market, in the world free market, when we talk to them about one or two percent productivity they laugh at us. They say, "Talk to us about ten or twenty." Because there has been a lot of gap in productivity and efficiency. >> Are you able to, I mean, it's only been nine months, but are you able to start to see any kind of customer results at this point? Do you have some examples even early wins with customers? >> So to be exact, the start of the relationship in a formal way-- >> Was it, what'd you say? >> --is two months. >> I thought I heard nine months. >> No, no, we started our first conversations and until it was over, it came to the agreement-- >> So it was brand new, in terms of... >> It is really brand new and I think what we can say is, I think we have 180 partners already engaged. We have probably more than 500 customer contacts in the region already so with large accounts. And we have a pipeline that is multi-million dollar in size. So we're expecting the first close within our first quarter, which ends at January 2018. I think there's no question that there is a big market opportunity out there, right? And I think the show here, I think for me, even accelerated things, because I think in the past, digital transformation was sort of limited to a few industries, we always give travel industry, we take banking sometimes but here, I think what became transparent to many of the customers that we had here, that there is no industry that is sort of immune against what is happening out there and specifically also that the sensors and the devices out there require special attention. And I think with the, specifically on the OT side, we have a solution now with GED that we can basically roll out across our territory. >> So I wanna talk about three things very quickly, I'm gonna lay this out and ask you if in fact this is going to catalyze that much more attention. Number one is a lot of the industry in the Middle East and Africa are natural resource industries, where the historical ways of doing things have been relatively inefficient. So there's a lot of opportunity to use IoT and related things to bring more efficiency, better practices, overall resource management. Number two is, that the technology's now capable of doing that in places where you don't necessarily have the best infrastructure. Aruba technology, for wireless, some of the other things are now possible, that adds to it. And number three, we've seen some recent steps in liberalizing some of the countries that have the most opportunity to do some things differently. You know, Robert Mugabe, no longer in Zimbabwe, the new prince in Saudi Arabia talking about liberalizing things. Are you seeing these come together in a way that would encourage people to think new ways, do new things, use information perhaps differently than it did before? What do you think, is this a confluence, is this a moment? >> Well I agree with you, and absolutely. Today, our customers and partners in region are more ready than before, and they're pulling hard. And when we put our act together as an ecosystem of partners we make it easier on them to make the right decision. When we talk productivity, productivity comes from people, from process operation, from industrial entitlement. And when we talk about the digital thread that brings it all together whether we look at the culture and vision and mission and people utilization, look at the process defined or not, and how we can optimize it, look at the industrial entitlement, and tell them, "Compared to your peers, "this is where you can be." We have their attention. And with the push from the government for productivity and utilization and do more for less, this is becoming top of mind, everyone is talking about it. So, when we partner together and we say, "This is the playbook, this is how you can start, "and this is the edge to cloud solution in a secure way." And we link it to the industrial entitlement, and let's underline industrial, because when we speak the healthcare language and the power language and the oil and gas language we get their attention. >> Excellent, so there's an increasing interest, and you anticipate that there's going to be new action with their pocketbooks. >> Johannes: Yes. And I would add, I think we, this is not an easy marketplace but you can have some outstanding projects. And we have, in the region, you may have heard about, there was in the private investment fund, when the crown prince did announce the NEOM project. Or, we have in Dubai Smart City as a project, with the city of Dubai which are all projects that probably would not happen in Western Europe. So there is potential, there are bigger things happening, and I think there is also an understanding that this is a way how to leapfrog, to your point, to leapfrog technology. And I think that is what can happen. What we need to be careful of is where to invest, because there are lots of ideas out there, and to understand what are the real things, and what are the things that we need to make happen. This is, I think, the challenge. >> And they wouldn't happen in Western Europe because, what? The maturity of the infrastructure, the space limitations, the appetite? >> Johannes: I think, to give the example of Smart City. >> Dave: Yeah. >> So I think we have a lot of, in my remit we have lots of discussion on Smart City. But it's usually you have to find the city that is willing to pay a POC. >> Pete: 12 layers of bureaucracy. >> And exactly. And you need to talk to each and every city individually, whereas here, if you have a decision maker to say, "Yes, we do this." >> Pete: Yep. >> Dave: Right. >> And then we do it. >> Dave: You cut the line. >> And the answer is about readiness. When you go to a large enterprise that's very successful, you meet the CEO and you quickly conclude whether they're ready for digital transformation or not, are they gonna make this top of mind for them? Are they gonna give you time? Are they gonna talk about productivity? Or is this going to be an IT discussion, and they're gonna treat you as a supplier? Those that are ready, we roll up our sleeves, and we put in our dedicated resources to help them look at the transformation. When the government official is pushing and mandating for calls out, then obviously everyone wants to copy and talk about it. And this makes it easier for us to execute. >> You're talking, again, big numbers. Not one percent, ten percent, so that's the nirvana. How confident are you that you can actually have that type of impact? >> So we've got data points, right? If you look at healthcare in the Saudi Ministry of Health, we've been collaborating on looking at operating room optimization or emergency room optimization, without touching digitization. Looking at the process and utilization of appointments, no-show, and the way the clinical governance is taking place, we're showing 40 percent improvement. If you look at, the factory of the future with Obeikan in Saudi Arabia, we've got asset performance improvement project, and they already yielded a 12 percent improvement, and the entitlement is up to 20, that we're working on. When you transform something, it's iterative, right? When you transform something that you have not pushed for efficiency before it's easy for the first iteration to show an incremental change. >> Pete: Yup. >> That challenge will be for the change to last. And this is where digitization makes it last and makes it impactful. And when we look at the HPE relationship with the MOH on the electronic medical record, we've got right now two active projects with two hospitals, and it's all powered by Predix, and HP peripherals are being deployed to the site. And if we go to the Saudi Electricity Company, we've got a project now on asset performance management across all their assets and again HPE peripherals are also deployed and it's all about GE ecosystem of Predix-enabled solutions. >> So I've had the pleasure and honor of speaking in front of a relatively large group of CIOs a couple times in Africa in the past few years. And I always was surprised by the degree to which they suggested that the necessity of change in this region, and the fact that a little bit of technology can have an enormous impact, the degree to which we might actually see some leadership technology come out of this region. What do you think, are the types of issues, the types of problems that could be solved with this technology in Africa, the types of problems that solving them there could actually start driving the industry in different directions? Solving new classes, whole new classes of problems. Do you think that this type of technology can have a transformative effect, not only in Africa but more broadly? >> Absolutely, this is a way for systems to leapfrog. If you look at Kenya right now, they've got a transformation project for 98 hospitals. And they've got massive shortage of radiologists. So right now, we're replacing equipment in 98 hospitals but tele-radiology is the answer for the shortage of radiologists. If you look to South African Discovery, what Discovery is doing is best in class, and I haven't seen any other insurance company looking at the ecosystem the way they do it. So, absolutely, we're seeing pockets of excellence in Africa, and this can be a way to leapfrog. >> You said you started the conversations around security. >> Johannes: Cybersecurity. >> What was that conversation like? Why was that the starting point? I mean, obviously it's important, but why? >> To be honest, I would have to leave this to you, but I think it was because mainly there was we saw the customer interest. >> Yeah. >> And I would say, probably a year or two years ago, you would have not seen this as a very typical HPE alliance. We were technology people. We were software or hardware people. What you see in, and I mentioned in the beginning, in the world of IoT, things are blurring a bit. What is happening on the edge is very much in the business of General Electric. So I think this builds automatically the new ecosystem. When you look here at Discovery, the alliance has become more and more industrial companies. It's linked to industrial 4.0, car industries and all that. Everywhere where data is being created, we need to have the partnership because and that is because the data that is being created at the edge also needs to be computed at the edge. If we want to be successful, we gotta say, "We cannot limit ourselves to the "data centers the rest is the others." And this is where I think we find the very good connection point because now we have software that actually can operate at the edge. I think you have good examples on that. >> Yeah absolutely, if you look at the pain point in Middle East, Africa, majority of our partners and customers are government entities and for them top of mind securing their large industrial assets is important. And in the operations space there hasn't been much done on security, where you can go into a hospital and simulate light flickering with a voltmeter. And you can take over the temperature and play with it. Today there's a lot of smart sensors out there, but we're securing the IT firewall, but within the hospital, or within the plant, we can do a lot of crazy stuff. And we owe it to our partners to show our capability. That's what we do within our factories, and our platform is designed around security for operations. So the easier interlock with HPE is our ability to get closer to the edge and peripherals, and ensure the operation is secure and that's the first experiment but then, obviously, we're expanding beyond that to other opportunities. >> Dave: Excellent. Alright, gentlemen, we have to leave it there. Thanks so much for coming to theCube. >> Johannes: Thank you very much. >> Sharing your story, good luck with the partnership. >> Thank you. >> Dave: Hope you can come back, maybe in Las Vegas or maybe next year at this event, give us the update. >> For sure. Thank you very much. >> Thank you. Appreciate it. >> Dave: Okay. Keep it right there, everybody. We'll be back with our next guest. Dave Vellante, Peter Burris, this is theCube live from Madrid HPE Discover 2017. (upbeat music)

>> Hey, welcome back, everybody. Jefe Rick here with the Cube. We're in this war subscribed conference 2017 downtown San Francisco. 1,000 2 1,000 people talking about the subscription economy, I think is like the sixth year they've been doing this show. First time we've been here. We're excited to be here, but we're joined by a company that we spend a lot of time talking about. I ot in the industrial Internet, and that's G, but a new gas guidance bar. Ducasse. He's the head of predicts product management for Jean Digital. Welcome. >> Thanks, Jeff. Thanks for having me here. >> So you guys I mean, we were there in 2013 when Beth and Bill lost the industrial Internet initiative at the juiciest museum just across the street. So you guys have been in this space for a while. The G predicts cloud industrial cloud. You guys have been doing a lot of stuff there, so give us kind of an update. Where are you? Obviously picked a highlight. One of the key stories here. People don't think of G as necessarily a subscription economy type of play, but that >> so why are we here >> yet? So why are you here? >> We're here because we are subscription economy. I mean, what we're really focusing on with predicts is building a platform that allows third parties and first party applications to be built around the industrial space. And so a lot of what we're hearing from our customers is that they want to subscribe to those services, right. They want to subscribe to either the production of the services, but more importantly, maybe the different elements that bring the other solution. So the thing about the hospital like a digital twin, a virtual representation with physical asset A lot of times when people want to do is they want to build twins specific to specific asset. But they want to bring together the analytics and the data associated with that. Maybe some environmental factors that they subscribe to from 1/3 party, right, bring those all together doing analysis, right? And then basically give that stuff back. So they want to subscribe to things like analytics they want subscribe to data and the imports. So that's why we're here. We've been using Zamora a CZ part of our subscription service since the we kicked off G predicts last year way Wendy and February, and it's it's going to be a very flexible solution for us. >> So the parts and I don't think it's enough talk, and it really wasn't a lot of talking. The keynote is how a subscription relationship changes the way that you engage with a customer, because if you just sell him something, thank here's the transaction. You know, go off, you run your jet engine, go run your turbine. But if you have a subscription and it's an ongoing value delivery to pay for that ongoing money that they're giving you, it's a much kind of deeper relationship in kind of a single transact, well, >> it can develop. Do you have much deeper relationship? I think the thing that allows you to do is that allows you to experiment a little bit. Try a couple things, figure out what works best for you as a customer, right, and then invest in those areas. You don't have to make a big purchase order, right? Right. You don't have to go off and spend a lot of money on a bunch of software that may eventually go away, right? You can. You can. You can almost try before you buy or try as you buy, right? Probably better way of putting it right. And so what we're saying is you give people the ability to experiment. I think, you know, we talk within G about productivity, right? And the impact we could make him our own productivity to meet predicts, is much about innovation, right? Right. It's giving people the ability to try different things. Teo, Try on DH. See what happens when you bring in environmental factors. Right? Or usage data, right or operational data? Or, you know, we talked about jet engines lot looking at the different pilots. How do they operate the engines? Right, you know. So there's there's there's all these scenarios you can sort of experiment with on a subscription model. Find out what works and then go deep is necessary. >> It's interesting. 10. And the Kino talked about. What's different now is that you can buy. You can upgrade, you can cancel, you can downgrade. So again, this this interaction, as you just described, allows for a bunch of different types of engagement, not just the Big Bang and the other thing that's consistent with we hear over and over. I is a democratization, democratization of the data, democratization of the tools so that somebody does have a hypothesis that, you know, we've been looking at Obviously, a plane operating in the southwest United States is goingto have different characteristics. Is one operating in Alaska. But as you just said, maybe we should look att, pilot characteristics. Maybe we should look at, you know, back in. So when you open up that innovation platform now, you have so many more people coming up with hypothesis, testing hypothesis and you you open up the resource into your company to do so much better >> Well, and you have little innovation like so we have a partner based on Israel Plantain who's doing some stuff in the manufacturing space with G is we start thing about additive manufacturing. You want something about the composites and the materials that actually go into the engine, right, and sort of how of those and held up over time so you could build a much more longitudinal view of that. And again, it could be a subscription service where you start experimenting, you start understanding, especially with additive being sort of ah, mechanism to decentralize a lot of the manufacturing. You don't need to make a huge investment too. Doing that at those analytics. You put some software alongside the additive systems, and you've got the ability to innovate and understand better. Like what? Composites work better. I mean, you talk about the operation of the engine. But how about the manufacturing, the gym? Are there optimal environments right where you want to build those engines? And I think we've done great work. Is an industrial company to understand how to optimize systems and probably even like what the environmental factors are to build an engine effectively. But when you start distributing that, you really want to gauge that real time to understand what the impact would be, >> All right, So we were on short time leash here, actually, but I want to give you the last word. Give a plug for the critics. Transform show Coming up is part of minds of machines. We live for the first year. Last year that was 2,000 developers. Right? Ready? Great turnout for for really a development platform for an industrial Internet cloud. >> Yeah, s. So what we've done this year was a rain together transform, which is the event for our developer community with minds of machines, which is more targeted towards the business leaders were some of the leaders in the organization, and bringing them all under one roof will be here in San Francisco mid October. I don't have the exact dates, but I probably should. But it's like a roundabout on the >> Internet looking over there. >> But we're bringing those together, right? So we can have a dialogue that spans the complete spectrum. Yeah, right. It's the people that are building will have hackathons will have places where people can actually work on that will judge those those different solutions that are being hacked together on. Then we'll be presenting sort of the business value and the impact we're seeing with a lot of the industrial customers again. Many of them are, jeez, existing customers. We've got customers in different, you know, the auto industry elevator escalator industry, you know, fixtures manufacturing spaces that we haven't traditionally played. So we'll be talking about all the benefits were bringing this customer's Blessem new product introduction talk about >> All right, great event. I team meets ot. We went last year. Jeff was there. Beth was there, Bill was there all that? All the players that great show. Well, congratulations on your successful Zorro. And we look forward to seeing your minds machine. Okay, Thanks. Alright, He's Geeta Som Jeffrey, you're watching the cube crumbs or subscribe 2017. We'll be right back after this short break. Thanks for watching.

>> Hey welcome back here everybody. Jeff Frick here with theCUBE. We're at the Zuora Subscribe Conference 2017, downtown on San Francisco. 1,000, 2,000 people talking about the subscription economy. I think it's like the sixth year they've been doing the show. First time we've been here. We're excited to be here. But we're joined by a company that we spent a lot of time talking about IOT and the industrial internet, and that's GE, but a new guest, Gytis Barzdukas, he is the head of Predix Product Management for GE Digital. Welcome. >> Thanks Jeff, thanks for having me here. >> So you guys, I mean, we were there in 2013 when Beth and Bill launched the industrial internet initiative at the Jewish History Museum just across the street. So you guys have been in this space for a while, the GE Predix Cloud, industrial internet cloud, you guys have been doing a lot of stuff there. So give us a kind of update, where are you? Obviously picked to highlight one of the key stories here. People probably don't think of GE as necessarily a subscription economy type of play, but, >> So why are we here? >> Jeff: Yeah, so why are you here? >> Well we're here because we are a subscription economy. What we're really focusing on with Predix is building a platform that allows third-parties and first-party applications to be built around the industrial space, and so a lot of what we're hearing from our customers is that they want to subscribe to those services. They want to subscribe to either the production of the services, but more importantly maybe the different elements that bring together a solution. So think about the concept like a digital twin, a virtual representation of a physical asset. A lot of times what people want to do is they want to build twins specific to a specific asset. But they want to bring together the analytics, and the data associated with that, and maybe some environmental factors that they subscribe to from a third-party, bring those all together, do an analysis, And then basically give that stuff back. So they want to subscribe to things like analytics. They want to subscribe to data and the inputs, so that's why we're here. We've been using Zuora as part of our subscription service since we kicked off GE Predix last year. We went GA in February, and it's proven to be a very flexible solution for us. >> So the part that I don't think gets enough talk, and there really wasn't a lot of talk in the keynote, is how a subscription relationship changes the way that you engage with the customer. 'Cause if you just sell 'em something, here's the transaction, you know, go off, go run your jet engine, run your turbine, but if you have a subscription, and it's an ongoing value delivery to pay for that ongoing money that they're giving you, it's a much kind of deeper relationship than kind of a single transaction relationship. >> It can develop to be a much deeper relationship. I think the thing that it allows you to do is, it allows you to experiment a little bit, try a couple things, figure out what works best for you as a customer and then invest in those areas. You don't have to make a big purchase order. You don't have to go off and spend a lot of money on a bunch of software that may eventually go away. You can almost try, before you buy, or try as you buy is probably a better way of putting it. And so what we're seeing is we give people the ability to experiment. I think, we talk within GE about productivity and the impact we can make in our own productivity. To me Predix is as much about innovation. It's giving people the ability to try different things, to try and see what happens when you bring in environmental factors or usage data, or operational data, or we talk about jet engines a lot. Looking at the different pilots, how do they operate the engines? So there's all these scenarios you can sort of experiment with on a subscription model, find out what works and then go deep as necessary. >> And it's interesting, Tien in the keynote talked about how what's different now is that you can buy, you can upgrade, you can cancel, you can downgrade, so again this interaction as you just described, allows for a bunch of different types of engagement, not just the big bang. >> Yep, yeah. >> And the other thing that's consistent with who you're over and overwrite is the democratization. Democratization of the data, democratization of the tools so that if somebody does have a hypothesis, we've been looking at obviously a plane operating in the southwest United States is going to have different characteristics as one operating in Alaska. But as you just said maybe we should look at pilot characteristics. Maybe we should look at back ends, so when you open up that innovation platform, now you have so many more people coming up with hypothesis, testing hypothesis, and you open up the resources to your company to do so much better. >> Well, and you have little innovation, so we have a partner based in Israel, Plataine, who's doing some stuff in the manufacturing space with GE as we start thinking about additive manufacturing. You want to start thinking about the composites and the materials that actually go into the engine, and sort of how have those held up over time? So you can build a much more longitudinal view of that, and again, it can be a subscription service where you start experimenting, you start understanding, especially with additive being sort of a mechanism to decentralize a lot of the manufacturing. You don't need to make a huge investment to doing those analytics. You put some software alongside the additive systems, and you've got the ability to innovate and understand better what composites work better. You talk about the operation of the engine, but how about the manufacturing of the engine? Are there optimal environments where you want to build those engines? And I think we've done great work as an industrial company and understand how to optimize systems and probably even like what the environmental factors are to build an engine effectively, but when you start distributing that, you really want to gauge that real time to understand what the impact could be. >> All right, so we're on short time leash here, unfortunately, but I want to give you the last word, give a plug for the Predix Transform Show coming up as part of Minds and Machines. We went for the first year last year. It was 2,000 developers, pretty great turnout for really a development platform for an industrial internet cloud. >> Yeah, so what we've done this year is we're bringing together Transform, which is the event for our developer community with Minds and Machines which is more targeted towards the business leaders or some of the IT leaders in their organization and bringing them all under one roof. It'll be here in San Francisco mid-October. I don't have the exact dates. I probably should, but I think it's like-- >> I can look it up on the internet. That's why we have the internet. >> But we're bringing those together. So we can have a dialogue that spans the complete spectrum. It's the people that are building, and we'll have hackathons, we'll have places where people can actually work on that. We'll judge those different solutions that are being hacked together. And then we'll be presenting sort of the business value and the impact we're seeing with a lot of the industrial customers. Again, many of them are GE's existing customers. But we've got customers in the auto industry, elevator, escalator industry, fixtures, manufacturing, spaces that we haven't traditionally played, and so we'll be talking about all of the benefits. We're bringing in those customers plus some new product introductions which I can't talk about now. >> All right great event, IT meets OT. We went last year. Jeff was there, Beth was there, >> They will be there. >> Jeff: Bill was there, all the players. A great show. >> okay, Jeff. >> Jeff: Congratulations on your success with Zuora and we look forward to seeing you at Minds and Machines. >> Okay, thanks Jeff. >> All right, he's Gytis, I'm Jeff Frick. You're watching theCUBE from Zuora Subscribe 2017. We'll be right back after this short break. Thanks for watching.

>> Narrator: Live from Las Vegas, it's theCUBE covering HPE Discover 2017 brought to you by Hewlett Packard Enterprise. >> Welcome back, everyone. We are here live in Las Vegas for HPE Discover 2017 exclusives look at angle cube coverage, our seventh year. I'm John Furrier with my co-host Dave Vellante. Our next guest is Tripp Partain, HPE CTO for GE General Electric and Anthony Rokis, VP of Software Engineering at Predix with GE Digital. Guys, welcome back to theCUBE. Good to see you. >> Thanks guys. >> Thanks for coming on. Obviously, GE has really been on the front end of IOT. You guys have been doing extremely well and changing over, bringing digital to analog, kind of connecting those worlds. What's your take on this intelligent Edge? You got to love the messaging. You got to love the messaging with HP. >> God, it's great. I think this is really starting to take off. If you look at our positioning, we really are going after the Edge, right. And with Predix being our forefront in the Predix system, we really believe in the opportunity here. I think, as you heard Meg speak yesterday, the engagement between GE Digital and HPE is getting stronger, we're finding more and more synergies over time. And both our strategy and their strategy are really starting to line up very nicely, both Edge and computing in general. >> I had a chance a couple years ago to host a panel with your CEO Jeff Amels, and United Airlines, Hospital in Chicago and at that time it was really hardcore, tangible dollars on the line. I mean, we're talking highly instrumented devices and machinery that you guys are in and there were some significant dollars involved. Just getting the data is a very low-hanging fruit, but big numbers, this is now going mainstream where everyone's kind of having this awakening moment, Tripp, where it's kind of like, "Hey, we're just going mainstream." So what's next for you guys, as the world starts getting up to speed on IOT, what's next for GE? What are you guys doing now to go onto the next level? What's that next tier of digital IOT for you guys? >> Yeah, honestly in my view and GE's view if you look at what we've done in the past, it's really the foundations getting in place. It's censor-enabled devices getting assets. The censor is more progressive, and that's kind of been the first sort of step, right. Then we get into how do we collect that data? Where you think GE is headed now, are the smart analytics. It's the outcomes that are going to drive those big dollars in productivity. It's really getting into the digital industrial revolution area. To date, it's been a lot of the foundation getting in place, and I think that's where you're going to see tremendous growth over time is. When you unleash data scientists on wealth of information, the outcomes in the productivity, the world and the economy is going to see is going to be great. >> I love that quote, with Jeff Immelt. We refer to it all the time. I went to bed an industrial giant, and woke up, you know a software company. And so it clearly underscores the transformation. We were talking off-camera about the study that we did many, many years ago. I mean, the numbers are staggering. It's in the trillions. But one of the things that we found was this notion of, and we talk about it all the time and I'd love to get your take on it is the IT and OT. They're not talking to each other. Typically, they're not birds of a feather. What are you seeing, Tripp, in your experience with customers in terms of those organizational, let's start with the IT side and we can talk about the OT side. >> Yeah, and as we've had our partners show up with GE continue to develop, the one thing we've found is we have a lot of similar customers. And in these same customers are extremely large customers, but what's interesting we don't talk to any of the same people. Right, on the HPE side we tended to talk to the IT teams and data center and GE would be out in the factory floor or out in the field and more industrial. But in order to really fulfill the IOT promise, the two groups are really having to come together and I think it's taking time for messaging to really sort out there. And one of the things that we're really doing, taking advantage of our partnership to help solve the problem is when we have IT teams come to visit HPE, we bring along GE operational experts to actually talk about the business side of the outcome so it's not just an IT conversation. And really intentionally crossing those paths and leveraging our partner in GE to bring that capability to us so we can have a holistic conversation to the customer. >> So who's in charge here, who's driving the bus? Is it the OT guys, or the IT guys, or somebody above? >> It's both, there's two drivers. >> Uh oh. >> Two hands, four hands on the wheel almost. If you look at the OT side, there's a lot of challenges we're facing where HPE and the IT community is coming to help. For instance, data sovereign team, right. So one of the challenges we have is a lot of our companies, our customers, want data sovereignty and this is where IT has solved that problem for us and on the OT side, we need to figure out how do we store, maintain, analyze that data within a country. And again, that's why we're bringing the IT companies with us and partner to help us. >> So when a plane flies from Spain, crosses France, Germany, and ends up in Ireland, where is the data? (laughs) >> Very good question. >> Well it infringes the data, because there's sort of a data love triangle going on. You've obviously got devices installed, HPE brings equipment, and the customer. So, talk about the conversations that you're having with your customers. I mean, who owns the data. The factory says, "Hey, wait a minute it's a system. That's my data." GE obviously has to do predictive maintenance and same with HPE. There's all this data flowing. What about data, I don't know, ownership or IP, what are those conversations like? >> Yeah, I can say certainly from the GE side it's always been our stance that the customer owns their data, right. We are running a multi-tenency environment and a platform. And they own that data. How that data is stored, we can help facilitate, right. We offer Cloud store and a couple other technologies that allow that. But at the end of the day in a multi-tenent environment, the customer owns that data. And we will facilitate with HPE where that data needs to reside based on the customer's need. >> So you're not trying in any way to monetize that data? I mean, I'm astounded, why not? >> I think the monetization really comes in with how you empower the customer to get the value out of the data. And in a former life, I worked through the data monetization world and there is certain amounts of value in the data itself. There's also value in helping the customer determine what their data can offer to them and the business cases that we're able to jointly present to the customer and the value that that generates still allows for us to monetize the process by which we help enable the customer to really bring these data assets together. Really understand areas that they may have seen silos of the data before, but they weren't looking holistically at it and being able to, in a very timely fashion correlate between that and then actually see a different answer to a problem where yes, this meter may be reading 80 and it should be 60, but if I throttle it to 70 and I get 10% more output, it's worth running at 70 because of the benefit on the revenue. So you actually can make trade offs across certain areas where you weren't able to do that. >> But Predix is informing models, is it not, I mean. >> Yeah, I mean at the end of the day, we're taking that data and for the customer created an outcome. Right, the analytic, the information that we can derive out of it to make a more productive or a more efficient outcome of running operation, that's where we get the monetization from. >> If data's a new oil then you need to refine it, was your point about the monetization question. That's interesting because we see the same thing where if you make the data freely available or you treat it as an asset to the customer, it's how it's monetized in its effect. Or there's a tacticle, let's monetize our data. So depending on how you look at it, there's different approaches, right? I mean this is kind of the key thing. >> Right, and even though this is not the way now, if you follow the history of how other industries have dealt with the data. So I came out of credit services long ago, and it's very common now, in the credit services industry for data to be monetized and leveraged like for credit reports and for that whole banking financial process to take place, but it didn't start that way. So my guess is, as we continue to show value to the customer of their own data as they then start to think about, "Wow but if I could do comparables between my data and industry data that would help me even more." I expect that the customers that today that are worried about who owns the data, will eventually start asking players like HPE and GE Digital to help them solve that problem. And they'll evolve to that sort of data monetization like a lot of the other industries have. >> A whole new digital just creates a whole new way to look at things, it's not a linear supply chain anymore whether relative to data or what not, so super cool. Final question for you guys and I appreciate you coming on theCUBE and sharing your insights. What's next for the partnership with HPE and GE Digital? Obviously, the digital transformation's in full swing impacting business transformation, impacting the Dev Ops aspect of Cloud. All this cool stuff's happening, true private Cloud's on fire, hybrid's the doorway to Multi Cloud. A lot of cool stuff happening, what's next for you guys? >> Yeah I think from our side we're really excited about the partnership on the Edge, right. When we start looking at the computing requirements and needs at the Edge, close to the asset, low latency that's where HPE and GE are really going to start to partner very heavily and you're going to see a lot more engagement at that level. So I think the Edge is going to be our focal point. >> Oh absolutely, and I think the uniqueness we bring to the market with our Edge line converged systems, we're able to do things at the Edge, leveraging GE Predix and then also bringing in other third party partners in conjunction and now you have enough computer power in the right form factor that can all sit and reside at the Edge, process at the Edge and solve the problems there locally. Doesn't take away from the Cloud aspect, doesn't take away from being able to have a macro view across multiple scenarios. But if I'm on an oil rig in the middle of the North Sea, you know it's going to be very important for me to have everything I need in the right form factor at the lowest power utilization possible and still solve my problems. >> And can process all the data right there. Guys, we are pushing it to the Edge here theCUBE goes out to the events, that's the Edge of the action. We'll bring you all the great videos. Thanks for coming on, this is theCUBE live coverage from the Edge at HPE Discover 2017. I'm John Furrier, Dave Vellante. Be right back with more, stay with us. (digital music)

>> Welcome back everybody. Jeff Frick here with theCUBE we're in San Francisco at the Minds and Machines conference.  Three thousand people the fifth year of the show. Really everything about GE all the players from GE are here but are really being driven by the digital and the digitization of what was a bunch of stuff and still a bunch of stuff. But now we're digitizing it all. Yeah I'm really excited to get this bill saw you what nine months ago six months ago Timeflies to the Chief Digital Officer of chief power. Welcome. Great to see you again. >> Thank you. Thanks for being here. >> Absolutely. So just first impressions of this event. Pretty amazing. >> Yes it's gotten really bad. Right and I I remember stories of people telling me that hey this is the fifth one we're doing the first one we almost had like pull people to come here. Now we are like figure out how do we get to a bigger location because this is getting mainstream. Everybody is looking at how does digital help their business. Because in the industrial sector productivity had slowed down right over the last four or five years. It had become only 25 percent of what it used to be. So the biggest lever for productivity efficiency and creating new value is through digital transformation. It's not just automation. It's about creating new value new revenue from digital assets and that's why you see the excitement across all of the industries here. What's interesting you came from the I.T. world. >> Yeah there's already kind of been the digital transformation in the I.T. world that a lot of the I.T. stuff has now been Olek been turned into electronic assets right. You have no paper but that that can't happen in the OT world right. We still got generator just for gadget engines. You still got physical things but it's still a digital transformation. So how are those things kind of meshing together. Yeah so you know having worked in software all my career in Silicon Valley you write like you think about Cambridge with a belief that every business every industry will be reimagined with software. We've seen it in retail and music and entertainment and travel but there the software our aid the world. Yes software is going to aid the world but here software is transforming the world too because the physical assets matter. But all of the machines that we make for example in power we make machines that power the world more than one third of the world's electricity comes from a machine. Right. So all of these machines generate electrons but they also generate a lot of data more than you know two terabytes of data a day from a power plant can be generated. That's more data and more consumers will generate across an entire year old social media. So this data matters we can learn a lot from this data and make these machines efficient more productive and kind of like a 360 sexiest word for some of the industrialist is no unplanned downtime right. Element breakdowns which turns into massive productivity and value for our customers. The thing I think that would surprise most people Jeff talked about it in his keynote yesterday is that there has not been the kind of the long traditional productivity gains in the industrial machines themselves and you think wow they've been around for a long time. I would think they would be pretty pretty efficient. But in fact there's still these huge inefficiency opportunities to take advantage of with software which is why there's this huge kind of value creation opportunity. Absolutely. So now also think where the cycle time of innovation. Right. All of these are mechanical machines right. We know with advances in materials science and engineering and you know brilliant manufacturing we can get more out of the physical asset but that requires a big upgrade cycle. What if we agreed to the machine with software and that's really what we did in our businesses across power right where we called them edge applications where it's about improving the flexibility of a machine or they 50 of them. All of these are modeled and algorithms and the way to think about it is all these machines in fact outside we have a giant machine that powers this entire event. And you can see the digital twin version of that machine right here on the screen. All that is is a virtual representation of that machine from the physical world where we have all the thermal models the Trancy models the heat models the performance models all connected. But now we can run the simulation in real time all of the operation data and apply algorithms to get more performance out. A great example as we just launched one of the world's most efficient most flexible gas turbine a giant turbine called H.A.. >> But with the additional software we were able to improve the efficiency it's now the Guinness World Record holder as the most efficient flexible power plant in the world. That was then a brand new unit that was developed with the benefit of software or was that really applying a Software to our approach that was a brand new unit. But overlaid with software was able to eke out more efficiency as well. But we're doing this an older power plants as well. In fact a great story is we had a customer and Italy called A2A their multi utility company in Italy. They have a power plant and Cuba also in northern Italy. They had shut it down because it was no longer competitive to operate that power plant in the modern world where there was so much renewables. Because you got to compete in a market called ancillary services meaning you need to be able to quickly ramp up power when the wind doesn't blow or the sun doesn't shine bright and shouted down right away. You can't do that with giant power plants. What we did was we completely model that's how plant and software and digital trend we show them that this actually can be competitive. So with the addition of software we were able to reopen a power plant that was mothballed and jobs were reinstated and the Paul plan is actually flexible in the open competitive ancillary services market. So all of this is possible because of software we're able to breathe new life into big giant heavy machines. So just a year in the power space I'm just tired. You know we've seen kind of in the US. No the nukes are being turned turned off. >> I grew up in Portland got trojan on the Columbia River we could take field trips with the smoke come out the cooling tower. We've got the rise of renewables are really really really going crazy. He's got this crazy dynamics and the price of oil. How's that played. How are you guys helping kind of deal with this multimodal. It's interesting here that oil and gas is still its own separate group. I'm like they got it like we want to be part of the renewables and didn't just become energy and not renewables oil and gas nuclear etc.. So you know that's a great question the industry is oil and gas has lots of other things and downstream stream and so on. And but at least across all of the electricity businesses we're coming together. And we call this the electricity Value Network. Think about where we used to think about a value chain where the Greens got generated and they traveled to the consumer. It was a linear model. And we know from Silicon Valley when digital anchors industries they all become network model. Right. Right. So we're calling this the electricity Value Network. And the interesting thing is our customers have different mix of fuel. And every part of the geography in the world in North America is still a good mix. Renewables is on the rise in California. We're going to have 50 percent power from renewables by 2030. But you still have to balance and optimize the mix of power from gas and nuclear and other sources of fuel and hydro and steam and so on. Right. And in Europe it's our abundance of renewables. >> They're struggling to integrate them into the great abundance of renewables or abundant capacity right. Renewables are growing and so they have to integrate them better in China and India for example still coal and steam is the big source of power because that's the fuel they have. They don't have as much gas. So the mix of fuel will change the world. The beauty of software as we can help optimize the mix. In the past we always talked about renewables as a silver bullet or gas silver bullet. Now we're saying software is a silver bullet regardless of what the mix of fuel we can optimize the generation of electrons and we're seeing this entire industry of electricity being transformer and digital and we call that the electricity Value Network. It's crazy interesting times so big show any big announcements happening here at the show yeah we know lots of big announcements one of the biggest ones is we're just dying day big enterprise wide digital transformation and relationship with Exelon Exelon is the largest utility in North America and they so are 10 million customers but they also generate a lot of power over 35000 megawatts of cross nuclear wind solar hydro gas and you know a year and a half ago we started a journey with them on understanding what the value of vigilance. There is such a believer and we learned a lot working with them as well and now they're deploying our Predix platform the industrial platform and APM which is our asset command and software and our food speed of operations optimization business optimization and cyber across the entire enterprise. >> So it's a big strategic agreement with them and where we're allowed to tell people is that you know a year and a half ago we were talking about what would happen if a wind farm went digital or a power plant. When you don't right now we're talking about what happens an entire utility goes digital or an entire industry of electricity goes digital and leaders like Exelon have the opportunity to create that tipping point in the industry. It does feel like this is the moment I think digital transformation of the electricity industry went real and this is it I presume not everything that they own is jii equipment no software is agnostic. Right. Right so this is really a software deal with their existing infrastructure that probably has a blend of G gear and who knows what other year that are generating. This is no different than how we in Silicon Valley would think about a enterprise software deal. It is the Enterprise subscription deal for them except it's to our cloud and our edge solutions and it's every machine right every single asset whether it's a giant gas turbine or a small little pump every machine has some sense or we will sense the rise or does the environment but all that data is being put into Predix. We will build digital twins of their entire power plants and give them more new insight and help them you know eliminate unplanned downtime and reduce operational costs citing times. We've got to get on buses to get those batteries done right till we get stored where we can we can connect them and optimize them as well. Right. Absolutely. >> I look forward to catching up six months from now and see where you guys are going out fast Bill and you and the team have grown you know from from a little bit of these kind of software skunkworks out there. Yeah I know many people are in San Ramon now. Now I think we're about a hundred people I think we're diversifying I think and it's a great challenge. So when we get the Adsit camping on the horizon. Oh and Sarah will be there. You can hit me up on Twitter again as well if you're interested in working in meaningful purposeful things like energy and the coolest things and software super. All right good. Thanks for stopping by. All right. Thank you. You have been asking us belum Jeffrey. You're watching the queue. We'll be back with our next segment after this short break.

(gentle upbeat music) >> Hello, everyone, welcome to theCUBE's coverage of International Women's Day. I'm John Furrier host here in Palo Alto, California. theCUBE's second year covering International Women's Day. It's been a great celebration of all the smart leaders in the world who are making a difference from all kinds of backgrounds, from technology to business and everything in between. Today we've got a great guest, Dominique Bastos, who's the senior Vice President of Cloud at Persistent Systems, formerly with AWS. That's where we first met at re:Invent. Dominique, great to have you on the program here for International Women's Day. Thanks for coming on. >> Thank you John, for having me back on theCUBE. This is an honor, especially given the theme. >> Well, I'm excited to have you on, I consider you one of those typecast personas where you've kind of done a lot of things. You're powerful, you've got great business acumen you're technical, and we're in a world where, you know the world's coming completely digital and 50% of the world is women, 51%, some say. So you got mostly male dominated industry and you have a dual engineering background and that's super impressive as well. Again, technical world, male dominated you're in there in the mix. What inspires you to get these engineering degrees? >> I think even it was more so shifted towards males. When I had the inspiration to go to engineering school I was accused as a young girl of being a tomboy and fiddling around with all my brother's toys versus focusing on my dolls and other kind of stereotypical toys that you would give a girl. I really had a curiosity for building, a curiosity for just breaking things apart and putting them back together. I was very lucky in that my I guess you call it primary school, maybe middle school, had a program for, it was like electronics, that was the class electronics. So building circuit boards and things like that. And I really enjoyed that aspect of building. I think it was more actually going into engineering school. Picking that as a discipline was a little bit, my mom's reaction to when I announced that I wanted to do engineering which was, "No, that's for boys." >> Really. >> And that really, you know, I think she, it came from a good place in trying to protect me from what she has experienced herself in terms of how women are received in those spaces. So I kind of shrugged it off and thought "Okay, well I'm definitely now going to do this." >> (laughs) If I was told not to, you're going to do it. >> I was told not to, that's all I needed to hear. And also, I think my passion was to design cars and I figured if I enroll in an industrial engineering program I could focus on ergonomic design and ultimately, you know have a career doing something that I'm passionate about. So yeah, so my inspiration was kind of a little bit of don't do this, a lot of curiosity. I'm also a very analytical person. I've been, and I don't know what the science is around left right brain to be honest, but been told that I'm a very much a logical person versus a feeler. So I don't know if that's good or bad. >> Straight shooter. What were your engineering degrees if you don't mind sharing? >> So I did industrial engineering and so I did a dual degree, industrial engineering and robotics. At the time it was like a manufacturing robotics program. It was very, very cool because we got to, I mean now looking back, the evolution of robotics is just insane. But you, you know, programmed a robotic arm to pick things up. I actually crashed the Civil Engineering School's Concrete Canoe Building Competition where you literally have to design a concrete canoe and do all the load testing and the strength testing of the materials and basically then, you know you go against other universities to race the canoe in a body of water. We did that at, in Alabama and in Georgia. So I was lucky to experience that two times. It was a lot of fun. >> But you knew, so you knew, deep down, you were technical you had a nerd vibe you were geeking out on math, tech, robotics. What happened next? I mean, what were some of the challenges you faced? How did you progress forward? Did you have any blockers and roadblocks in front of you and how did you handle those? >> Yeah, I mean I had, I had a very eye-opening experience with, in my freshman year of engineering school. I kind of went in gung-ho with zero hesitation, all the confidence in the world, 'cause I was always a very big nerd academically, I hate admitting this but myself and somebody else got most intellectual, voted by the students in high school. It's like, you don't want to be voted most intellectual when you're in high school. >> Now it's a big deal. (laughs) >> Yeah, you want to be voted like popular or anything like that? No, I was a nerd, but in engineering school, it's a, it was very humbling. That whole confidence that I had. I experienced prof, ooh, I don't want to name the school. Everybody can google it though, but, so anyway so I had experience with some professors that actually looked at me and said, "You're in the wrong program. This is difficult." I, and I think I've shared this before in other forums where, you know, my thermodynamic teacher basically told me "Cheerleading's down the hall," and it it was a very shocking thing to hear because it really made me wonder like, what am I up against here? Is this what it's going to be like going forward? And I decided not to pay attention to that. I think at the moment when you hear something like that you just, you absorb it and you also don't know how to react. And I decided immediately to just walk right past him and sit down front center in the class. In my head I was cursing him, of course, 'cause I mean, let's be real. And I was like, I'm going to show this bleep bleep. And proceeded to basically set the curve class crushed it and was back to be the teacher's assistant. So I think that was one. >> But you became his teacher assistant after, or another one? >> Yeah, I gave him a mini speech. I said, do not do this. You, you could, you could have broken me and if you would've done this to somebody who wasn't as steadfast in her goals or whatever, I was really focused like I'm doing this, I would've backed out potentially and said, you know this isn't something I want to experience on the daily. So I think that was actually a good experience because it gave me an opportunity to understand what I was up against but also double down in how I was going to deal with it. >> Nice to slay the misogynistic teachers who typecast people. Now you had a very technical career but also you had a great career at AWS on the business side you've handled 'em all of the big accounts, I won't say the names, but like we're talking about monster accounts, sales and now basically it's not really selling, you're managing a big account, it's like a big business. It's a business development thing. Technical to business transition, how do you handle that? Was that something you were natural for? Obviously you, you stared down the naysayers out of the gate in college and then in business, did that continue and how did you drive through that? >> So I think even when I was coming out of university I knew that I wanted to have a balance between the engineering program and business. A lot of my colleagues went on to do their PEs so continue to get their masters basically in engineering or their PhDs in engineering. I didn't really have an interest for that. I did international business and finance as my MBA because I wanted to explore the ability of taking what I had learned in engineering school and applying it to building businesses. I mean, at the time I didn't have it in my head that I would want to do startups but I definitely knew that I wanted to get a feel for what are they learning in business school that I missed out in engineering school. So I think that helped me when I transitioned, well when I applied, I was asked to come apply at AWS and I kind of went, no I'm going to, the DNA is going to be rejected. >> You thought, you thought you'd be rejected from AWS. >> I thought I'd be, yeah, because I have very much a startup founder kind of disruptive personality. And to me, when I first saw AWS at the stage early 2016 I saw it as a corporation. Even though from a techie standpoint, I was like, these people are insane. This is amazing what they're building. But I didn't know what the cultural vibe would feel like. I had been with GE at the beginning of my career for almost three years. So I kind of equated AWS Amazon to GE given the size because in between, I had done startups. So when I went to AWS I think initially, and I do have to kind of shout out, you know Todd Weatherby basically was the worldwide leader for ProServe and it was being built, he built it and I went into ProServe to help from that standpoint. >> John: ProServe, Professional services >> Professional services, right. To help these big enterprise customers. And specifically my first customer was an amazing experience in taking, basically the company revolves around strategic selling, right? It's not like you take a salesperson with a conventional schooling that salespeople would have and plug them into AWS in 2016. It was very much a consultative strategic approach. And for me, having a technical background and loving to solve problems for customers, working with the team, I would say, it was a dream team that I joined. And also the ability to come to the table with a technical background, knowing how to interact with senior executives to help them envision where they want to go, and then to bring a team along with you to make that happen. I mean, that was like magical for me. I loved that experience. >> So you like the culture, I mean, Andy Jassy, I've interviewed many times, always talked about builders and been a builder mentality. You mentioned that earlier at the top of this interview you've always building things, curious and you mentioned potentially your confidence might have been shaken. So you, you had the confidence. So being a builder, you know, being curious and having confidence seems to be what your superpower is. A lot of people talk about the confidence angle. How important is that and how important is that for encouraging more women to get into tech? Because I still hear that all the time. Not that they don't have confidence, but there's so many signals that potentially could shake confidence in industry >> Yeah, that's actually a really good point that you're making. A lot of signals that women get could shake their confidence and that needs to be, I mean, it's easy to say that it should be innate. I mean that's kind of like textbook, "Oh it has to come from within." Of course it does. But also, you know, we need to understand that in a population where 50% of the population is women but only 7% of the positions in tech, and I don't know the most current number in tech leadership, is women, and probably a smaller percentage in the C-suite. When you're looking at a woman who's wanting to go up the trajectory in a tech company and then there's a subconscious understanding that there's a limit to how far you'll go, your confidence, you know, in even subconsciously gets shaken a little bit because despite your best efforts, you're already seeing the cap. I would say that we need to coach girls to speak confidently to navigate conflict versus running away from it, to own your own success and be secure in what you bring to the table. And then I think a very important thing is to celebrate each other and the wins that we see for women in tech, in the industry. >> That's awesome. What's, the, in your opinion, the, you look at that, the challenges for this next generation women, and women in general, what are some of the challenges for them and that they need to overcome today? I mean, obviously the world's changed for the better. Still not there. I mean the numbers one in four women, Rachel Thornton came on, former CMO of AWS, she's at MessageBird now. They had a study where only one in four women go to the executive board level. And so there's still, still numbers are bad and then the numbers still got to get up, up big time. That's, and the industry's working on that, but it's changed. But today, what are some of the challenges for this current generation and the next generation of women and how can we and the industry meet, we being us, women in the industry, be strong role models for them? >> Well, I think the challenge is one of how many women are there in the pipeline and what are we doing to retain them and how are we offering up the opportunities to fill. As you know, as Rachel said and I haven't had an opportunity to see her, in how are we giving them this opportunity to take up those seats in the C-suite right, in these leadership roles. And I think this is a little bit exacerbated with the pandemic in that, you know when everything shut down when people were going back to deal with family and work at the same time, for better or for worse the brunt of it fell on probably, you know the maternal type caregiver within the family unit. You know, I've been, I raised my daughter alone and for me, even without the pandemic it was a struggle constantly to balance the risk that I was willing to take to show up for those positions versus investing even more of that time raising a child, right? Nevermind the unconscious bias or cultural kind of expectations that you get from the male counterparts where there's zero understanding of what a mom might go through at home to then show up to a meeting, you know fully fresh and ready to kind of spit out some wisdom. It's like, you know, your kid just freaking lost their whatever and you know, they, so you have to sort a bunch of things out. I think the challenge that women are still facing and will we have to keep working at it is making sure that there's a good pipeline. A good amount of young ladies of people taking interest in tech. And then as they're, you know, going through the funnel at stages in their career, we're providing the mentoring we're, there's representation, right? To what they're aspiring to. We're celebrating their interest in the field, right? And, and I think also we're doing things to retain them, because again, the pandemic affected everybody. I think women specifically and I don't know the statistics but I was reading something about this were the ones to tend to kind of pull it back and say well now I need to be home with, you know you name how many kids and pets and the aging parents, people that got sick to take on that position. In addition to the career aspirations that they might have. We need to make it easier basically. >> I think that's a great call out and I appreciate you bringing that up about family and being a single mom. And by the way, you're savage warrior to doing that. It's amazing. You got to, I know you have a daughter in computer science at Stanford, I want to get to that in a second. But that empathy and I mentioned Rachel Thornton, who's the CMO MessageBird and former CMO of AWS. Her thing right now to your point is mentoring and sponsorship is very key. And her company and the video that's on the site here people should look at that and reference that. They talk a lot about that empathy of people's situation whether it's a single mom, family life, men and women but mainly women because they're the ones who people aren't having a lot of empathy for in that situation, as you called it out. This is huge. And I think remote work has opened up this whole aperture of everyone has to have a view into how people are coming to the table at work. So, you know, props are bringing that up, and I recommend everyone look at check out Rachel Thornton. So how do you balance that, that home life and talk about your daughter's journey because sounds like she's nerding out at Stanford 'cause you know Stanford's called Nerd Nation, that's their motto, so you must be proud. >> I am so proud, I'm so proud. And I will say, I have to admit, because I did encounter so many obstacles and so many hurdles in my journey, it's almost like I forgot that I should set that aside and not worry about my daughter. My hope for her was for her to kind of be artistic and a painter or go into something more lighthearted and fun because I just wanted to think, I guess my mom had the same idea, right? She, always been very driven. She, I want to say that I got very lucky that she picked me to be her mom. Biologically I'm her mom, but I told her she was like a little star that fell from the sky and I, and ended up with me. I think for me, balancing being a single mom and a career where I'm leading and mentoring and making big decisions that affect people's lives as well. You have to take the best of everything you get from each of those roles. And I think that the best way is play to your strengths, right? So having been kind of a nerd and very organized person and all about, you know, systems for effectiveness, I mean, industrial engineering, parenting for me was, I'm going to make it sound super annoying and horrible, but (laughs) >> It's funny, you know, Dave Vellante and I when we started SiliconANGLE and theCUBE years ago, one of the things we were all like sports lovers. So we liked sports and we are like we looked at the people in tech as tech athletes and except there's no men and women teams, it's one team. It's all one thing. So, you know, I consider you a tech athlete you're hard charging strong and professional and smart and beautiful and brilliant, all those good things. >> Thank you. >> Now this game is changing and okay, and you've done startups, and you've done corporate jobs, now you're in a new role. What's the current tech landscape from a, you know I won't say athletic per standpoint but as people who are smart. You have all kinds of different skill sets. You have the startup warriors, you have the folks who like to be in the middle of the corporate world grow up through corporate, climb the corporate ladder. You have investors, you have, you know, creatives. What have you enjoyed most and where do you see all the action? >> I mean, I think what I've enjoyed the most has been being able to bring all of the things that I feel I'm strong at and bring it together to apply that to whatever the problem is at hand, right? So kind of like, you know if you look at a renaissance man who can kind of pop in anywhere and, oh, he's good at, you know sports and he's good at reading and, or she's good at this or, take all of those strengths and somehow bring them together to deal with the issue at hand, versus breaking up your mindset into this is textbook what I learned and this is how business should be done and I'm going to draw these hard lines between personal life and work life, or between how you do selling and how you do engineering. So I think my, the thing that I loved, really loved about AWS was a lot of leaders saw something in me that I potentially didn't see, which was, yeah you might be great at running that big account but we need help over here doing go to market for a new product launch and boom, there you go. Now I'm in a different org helping solve that problem and getting something launched. And I think if you don't box yourself in to I'm only good at this, or, you know put a label on yourself as being the rockstar in that. It leaves room for opportunities to present themselves but also it leaves room within your own mind to see yourself as somebody capable of doing anything. Right, I don't know if I answered the question accurately. >> No, that's good, no, that's awesome. I love the sharing, Yeah, great, great share there. Question is, what do you see, what do you currently during now you're building a business of Persistent for the cloud, obviously AWS and Persistent's a leader global system integrator around the world, thousands and thousands of customers from what we know and been reporting on theCUBE, what's next for you? Where do you see yourself going? Obviously you're going to knock this out of the park. Where do you see yourself as you kind of look at the continuing journey of your mission, personal, professional what's on your mind? Where do you see yourself going next? >> Well, I think, you know, again, going back to not boxing yourself in. This role is an amazing one where I have an opportunity to take all the pieces of my career in tech and apply them to building a business within a business. And that involves all the goodness of coaching and mentoring and strategizing. And I'm loving it. I'm loving the opportunity to work with such great leaders. Persistent itself is very, very good at providing opportunities, very diverse opportunities. We just had a huge Semicolon; Hackathon. Some of the winners were females. The turnout was amazing in the CTO's office. We have very strong women leading the charge for innovation. I think to answer your question about the future and where I may see myself going next, I think now that my job, well they say the job is never done. But now that Chloe's kind of settled into Stanford and kind of doing her own thing, I have always had a passion to continue leading in a way that brings me to, into the fold a lot more. So maybe, you know, maybe in a VC firm partner mode or another, you know CEO role in a startup, or my own startup. I mean, I never, I don't know right now I'm super happy but you never know, you know where your drive might go. And I also want to be able to very deliberately be in a role where I can continue to mentor and support up and coming women in tech. >> Well, you got the smarts but you got really the building mentality, the curiosity and the confidence really sets you up nicely. Dominique great story, great inspiration. You're a role model for many women, young girls out there and women in tech and in celebration. It's a great day and thank you for sharing that story and all the good nuggets there. Appreciate you coming on theCUBE, and it's been my pleasure. Thanks for coming on. >> Thank you, John. Thank you so much for having me. >> Okay, theCUBE's coverage of International Women's Day. I'm John Furrier, host of theCUBE here in Palo Alto getting all the content, check out the other interviews some amazing stories, lessons learned, and some, you know some funny stories and some serious stories. So have some fun and enjoy the rest of the videos here for International Women's Days, thanks for watching. (gentle inspirational music)

(upbeat music) >> Okay, welcome back everyone at Supercloud 2 event, live here in Palo Alto, theCUBE Studios live stage performance, virtually syndicating it all over the world. I'm John Furrier with Dave Vellante here as Cube alumni, and special influencer guest, Howie Xu, VP of Machine Learning and Zscaler, also part-time as a CUBE analyst 'cause he is that good. Comes on all the time. You're basically a CUBE analyst as well. Thanks for coming on. >> Thanks for inviting me. >> John: Technically, you're not really a CUBE analyst, but you're kind of like a CUBE analyst. >> Happy New Year to everyone. >> Dave: Great to see you. >> Great to see you, Dave and John. >> John: We've been talking about ChatGPT online. You wrote a great post about it being more like Amazon, not like Google. >> Howie: More than just Google Search. >> More than Google Search. Oh, it's going to compete with Google Search, which it kind of does a little bit, but more its infrastructure. So a clever point, good segue into this conversation, because this is kind of the beginning of these kinds of next gen things we're going to see. Things where it's like an obvious next gen, it's getting real. Kind of like seeing the browser for the first time, Mosaic browser. Whoa, this internet thing's real. I think this is that moment and Supercloud like enablement is coming. So this has been a big part of the Supercloud kind of theme. >> Yeah, you talk about Supercloud, you talk about, you know, AI, ChatGPT. I really think the ChatGPT is really another Netscape moment, the browser moment. Because if you think about internet technology, right? It was brewing for 20 years before early 90s. Not until you had a, you know, browser, people realize, "Wow, this is how wonderful this technology could do." Right? You know, all the wonderful things. Then you have Yahoo and Amazon. I think we have brewing, you know, the AI technology for, you know, quite some time. Even then, you know, neural networks, deep learning. But not until ChatGPT came along, people realize, "Wow, you know, the user interface, user experience could be that great," right? So I really think, you know, if you look at the last 30 years, there is a browser moment, there is iPhone moment. I think ChatGPT moment is as big as those. >> Dave: What do you see as the intersection of things like ChatGPT and the Supercloud? Of course, the media's going to focus, journalists are going to focus on all the negatives and the privacy. Okay. You know we're going to get by that, right? Always do. Where do you see the Supercloud and sort of the distributed data fitting in with ChatGPT? Does it use that as a data source? What's the link? >> Howie: I think there are number of use cases. One of the use cases, we talked about why we even have Supercloud because of the complexity, because of the, you know, heterogeneous nature of different clouds. In order for me as a developer, in order for me to create applications, I have so many things to worry about, right? It's a complexity. But with ChatGPT, with the AI, I don't have to worry about it, right? Those kind of details will be taken care of by, you know, the underlying layer. So we have been talking about on this show, you know, over the last, what, year or so about the Supercloud, hey, defining that, you know, API layer spanning across, you know, multiple clouds. I think that will be happening. However, for a lot of the things, that will be more hidden, right? A lot of that will be automated by the bots. You know, we were just talking about it right before the show. One of the profound statement I heard from Adrian Cockcroft about 10 years ago was, "Hey Howie, you know, at Netflix, right? You know, IT is just one API call away." That's a profound statement I heard about a decade ago. I think next decade, right? You know, the IT is just one English language away, right? So when it's one English language away, it's no longer as important, API this, API that. You still need API just like hardware, right? You still need all of those things. That's going to be more hidden. The high level thing will be more, you know, English language or the language, right? Any language for that matter. >> Dave: And so through language, you'll tap services that live across the Supercloud, is what you're saying? >> Howie: You just tell what you want, what you desire, right? You know, the bots will help you to figure out where the complexity is, right? You know, like you said, a lot of criticism about, "Hey, ChatGPT doesn't do this, doesn't do that." But if you think about how to break things down, right? For instance, right, you know, ChatGPT doesn't have Microsoft stock price today, obviously, right? However, you can ask ChatGPT to write a program for you, retrieve the Microsoft stock price, (laughs) and then just run it, right? >> Dave: Yeah. >> So the thing to think about- >> John: It's only going to get better. It's only going to get better. >> The thing people kind of unfairly criticize ChatGPT is it doesn't do this. But can you not break down humans' task into smaller things and get complex things to be done by the ChatGPT? I think we are there already, you know- >> John: That to me is the real game changer. That's the assembly of atomic elements at the top of the stack, whether the interface is voice or some programmatic gesture based thing, you know, wave your hand or- >> Howie: One of the analogy I used in my blog was, you know, each person, each professional now is a quarterback. And we suddenly have, you know, a lot more linebacks or you know, any backs to work for you, right? For free even, right? You know, and then that's sort of, you should think about it. You are the quarterback of your day-to-day job, right? Your job is not to do everything manually yourself. >> Dave: You call the play- >> Yes. >> Dave: And they execute. Do your job. >> Yes, exactly. >> Yeah, all the players are there. All the elves are in the North Pole making the toys, Dave, as we say. But this is the thing, I want to get your point. This change is going to require a new kind of infrastructure software relationship, a new kind of operating runtime, a new kind of assembler, a new kind of loader link things. This very operating systems kind of concepts. >> Data intensive, right? How to process the data, how to, you know, process so gigantic data in parallel, right? That's actually a tough job, right? So if you think about ChatGPT, why OpenAI is ahead of the game, right? You know, Google may not want to acknowledge it, right? It's not necessarily they do, you know, not have enough data scientist, but the software engineering pieces, you know, behind it, right? To train the model, to actually do all those things in parallel, to do all those things in a cost effective way. So I think, you know, a lot of those still- >> Let me ask you a question. Let me ask you a question because we've had this conversation privately, but I want to do it while we're on stage here. Where are all the alpha geeks and developers and creators and entrepreneurs going to gravitate to? You know, in every wave, you see it in crypto, all the alphas went into crypto. Now I think with ChatGPT, you're going to start to see, like, "Wow, it's that moment." A lot of people are going to, you know, scrum and do startups. CTOs will invent stuff. There's a lot of invention, a lot of computer science and customer requirements to figure out. That's new. Where are the alpha entrepreneurs going to go to? What do you think they're going to gravitate to? If you could point to the next layer to enable this super environment, super app environment, Supercloud. 'Cause there's a lot to do to enable what you just said. >> Howie: Right. You know, if you think about using internet as the analogy, right? You know, in the early 90s, internet came along, browser came along. You had two kind of companies, right? One is Amazon, the other one is walmart.com. And then there were company, like maybe GE or whatnot, right? Really didn't take advantage of internet that much. I think, you know, for entrepreneurs, suddenly created the Yahoo, Amazon of the ChatGPT native era. That's what we should be all excited about. But for most of the Fortune 500 companies, your job is to surviving sort of the big revolution. So you at least need to do your walmart.com sooner than later, right? (laughs) So not be like GE, right? You know, hand waving, hey, I do a lot of the internet, but you know, when you look back last 20, 30 years, what did they do much with leveraging the- >> So you think they're going to jump in, they're going to build service companies or SaaS tech companies or Supercloud companies? >> Howie: Okay, so there are two type of opportunities from that perspective. One is, you know, the OpenAI ish kind of the companies, I think the OpenAI, the game is still open, right? You know, it's really Close AI today. (laughs) >> John: There's room for competition, you mean? >> There's room for competition, right. You know, you can still spend you know, 50, $100 million to build something interesting. You know, there are company like Cohere and so on and so on. There are a bunch of companies, I think there is that. And then there are companies who's going to leverage those sort of the new AI primitives. I think, you know, we have been talking about AI forever, but finally, finally, it's no longer just good, but also super useful. I think, you know, the time is now. >> John: And if you have the cloud behind you, what do you make the Amazon do differently? 'Cause Amazon Web Services is only going to grow with this. It's not going to get smaller. There's more horsepower to handle, there's more needs. >> Howie: Well, Microsoft already showed what's the future, right? You know, you know, yes, there is a kind of the container, you know, the serverless that will continue to grow. But the future is really not about- >> John: Microsoft's shown the future? >> Well, showing that, you know, working with OpenAI, right? >> Oh okay. >> They already said that, you know, we are going to have ChatGPT service. >> $10 billion, I think they're putting it. >> $10 billion putting, and also open up the Open API services, right? You know, I actually made a prediction that Microsoft future hinges on OpenAI. I think, you know- >> John: They believe that $10 billion bet. >> Dave: Yeah. $10 billion bet. So I want to ask you a question. It's somewhat academic, but it's relevant. For a number of years, it looked like having first mover advantage wasn't an advantage. PCs, spreadsheets, the browser, right? Social media, Friendster, right? Mobile. Apple wasn't first to mobile. But that's somewhat changed. The cloud, AWS was first. You could debate whether or not, but AWS okay, they have first mover advantage. Crypto, Bitcoin, first mover advantage. Do you think OpenAI will have first mover advantage? >> It certainly has its advantage today. I think it's year two. I mean, I think the game is still out there, right? You know, we're still in the first inning, early inning of the game. So I don't think that the game is over for the rest of the players, whether the big players or the OpenAI kind of the, sort of competitors. So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest, to get, you know, another shot to the OpenAI sort of the level?" You know, I did a- (laughs) >> Line up. >> That's classic VC. "How much does it cost me to replicate?" >> I'm pretty sure he asked the question to a bunch of guys, right? >> Good luck with that. (laughs) >> So we kind of did some napkin- >> What'd you come up with? (laughs) >> $100 million is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So 100 million. >> John: Hundreds of millions. >> Yeah, yeah, yeah. 100 million order of magnitude is what I came up with. You know, we can get into details, you know, in other sort of the time, but- >> Dave: That's actually not that much if you think about it. >> Howie: Exactly. So when he heard me articulating why is that, you know, he's thinking, right? You know, he actually, you know, asked me, "Hey, you know, there's this company. Do you happen to know this company? Can I reach out?" You know, those things. So I truly believe it's not a billion or 10 billion issue, it's more like 100. >> John: And also, your other point about referencing the internet revolution as a good comparable. The other thing there is online user population was a big driver of the growth of that. So what's the equivalent here for online user population for AI? Is it more apps, more users? I mean, we're still early on, it's first inning. >> Yeah. We're kind of the, you know- >> What's the key metric for success of this sector? Do you have a read on that? >> I think the, you know, the number of users is a good metrics, but I think it's going to be a lot of people are going to use AI services without even knowing they're using it, right? You know, I think a lot of the applications are being already built on top of OpenAI, and then they are kind of, you know, help people to do marketing, legal documents, you know, so they're already inherently OpenAI kind of the users already. So I think yeah. >> Well, Howie, we've got to wrap, but I really appreciate you coming on. I want to give you a last minute to wrap up here. In your experience, and you've seen many waves of innovation. You've even had your hands in a lot of the big waves past three inflection points. And obviously, machine learning you're doing now, you're deep end. Why is this Supercloud movement, this wave of Supercloud and the discussion of this next inflection point, why is it so important? For the folks watching, why should they be paying attention to this particular moment in time? Could you share your super clip on Supercloud? >> Howie: Right. So this is simple from my point of view. So why do you even have cloud to begin with, right? IT is too complex, too complex to operate or too expensive. So there's a newer model. There is a better model, right? Let someone else operate it, there is elasticity out of it, right? That's great. Until you have multiple vendors, right? Many vendors even, you know, we're talking about kind of how to make multiple vendors look like the same, but frankly speaking, even one vendor has, you know, thousand services. Now it's kind of getting, what Kid was talking about what, cloud chaos, right? It's the evolution. You know, the history repeats itself, right? You know, you have, you know, next great things and then too many great things, and then people need to sort of abstract this out. So it's almost that you must do this. But I think how to abstract this out is something that at this time, AI is going to help a lot, right? You know, like I mentioned, right? A lot of the abstraction, you don't have to think about API anymore. I bet 10 years from now, you know, IT is one language away, not API away. So think about that world, right? So Supercloud in, in my opinion, sure, you kind of abstract things out. You have, you know, consistent layers. But who's going to do that? Is that like we all agreed upon the model, agreed upon those APIs? Not necessary. There are certain, you know, truth in that, but there are other truths, let bots take care of, right? Whether you know, I want some X happens, whether it's going to be done by Azure, by AWS, by GCP, bots will figure out at a given time with certain contacts with your security requirement, posture requirement. I'll think that out. >> John: That's awesome. And you know, Dave, you and I have been talking about this. We think scale is the new ratification. If you have first mover advantage, I'll see the benefit, but scale is a huge thing. OpenAI, AWS. >> Howie: Yeah. Every day, we are using OpenAI. Today, we are labeling data for them. So you know, that's a little bit of the- (laughs) >> John: Yeah. >> First mover advantage that other people don't have, right? So it's kind of scary. So I'm very sure that Google is a little bit- (laughs) >> When we do our super AI event, you're definitely going to be keynoting. (laughs) >> Howie: I think, you know, we're talking about Supercloud, you know, before long, we are going to talk about super intelligent cloud. (laughs) >> I'm super excited, Howie, about this. Thanks for coming on. Great to see you, Howie Xu. Always a great analyst for us contributing to the community. VP of Machine Learning and Zscaler, industry legend and friend of theCUBE. Thanks for coming on and sharing really, really great advice and insight into what this next wave means. This Supercloud is the next wave. "If you're not on it, you're driftwood," says Pat Gelsinger. So you're going to see a lot more discussion. We'll be back more here live in Palo Alto after this short break. >> Thank you. (upbeat music)

>>Set restaurants. And who says TEUs had got a little ass more skin in the game for us, in charge of his destiny? You guys are excited. Robert Worship is Chief Alumni. >>My name is Dave Ante, and I'm a long time industry analyst. So when you're as old as I am, you've seen a lot of transitions. Everybody talks about industry cycles and waves. I've seen many, many waves. Met a lot of industry executives and of a little bit of a, an industry historian. When you interview many thousands of people, probably five or 6,000 people as I have over the last half of a decade, you get to interact with a lot of people's knowledge and you begin to develop patterns. And so that's sort of what I bring is, is an ability to catalyze the conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody's expert at something. Everybody's passionate about something and has real deep knowledge about that's something well, we wanna focus in on that area and extract that knowledge and share it with our communities. This is Dave Ante. Thanks for watching the Cube. >>Hello everyone and welcome back to the Cube where we are streaming live this week from CubeCon. I am Savannah Peterson and I am joined by an absolutely stellar lineup of cube brilliance this afternoon. To my left, a familiar face, Lisa Martin. Lisa, how you feeling? End of day two. >>Excellent. It was so much fun today. The buzz started yesterday, the momentum, the swell, and we only heard even more greatness today. >>Yeah, yeah, abs, absolutely. You know, I, I sometimes think we've hit an energy cliff, but it feels like the energy is just >>Continuous. Well, I think we're gonna, we're gonna slide right into tomorrow. >>Yeah, me too. I love it. And we've got two fantastic analysts with us today, Sarge and Keith. Thank you both for joining us. We feel so lucky today. >>Great being back on. >>Thanks for having us. Yeah, Yeah. It's nice to have you back on the show. We were, had you yesterday, but I miss hosting with you. It's been a while. >>It has been a while. We haven't done anything in since, Since pre >>Pandemic, right? Yeah, I think you're >>Right. Four times there >>Be four times back in the day. >>We, I always enjoy whole thing, Lisa, cuz she's so well prepared. I don't have to do any research when I come >>Home. >>Lisa will bring up some, Oh, sorry. Jeep, I see that in 2008 you won this award for Yeah. Being just excellent and I, I'm like, Oh >>Yeah. All right Keith. So, >>So did you do his analysis? >>Yeah, it's all done. Yeah. Great. He only part, he's not sitting next to me too. We can't see it, so it's gonna be like a magic crystal bell. Right. So a lot of people here. You got some stats in terms of the attendees compared >>To last year? Yeah, Priyanka told us we were double last year up to 8,000. We also got the scoop earlier that 2023 is gonna be in Chicago, which is very exciting. >>Oh, that is, is nice. Yeah, >>We got to break that here. >>Excellent. Keith, talk to us about what some of the things are that you've seen the last couple of days. The momentum. What's the vibe? I saw your tweet about the top three things you were being asked. Kubernetes was not one of them. >>Kubernetes were, was not one of 'em. This conference is starting to, it, it still feels very different than a vendor conference. The keynote is kind of, you know, kind of all over the place talking about projects, but the hallway track has been, you know, I've, this is maybe my fifth or sixth CU con in person. And the hallway track is different. It's less about projects and more about how, how do we adjust to the enterprise? How do we Yes. Actually do enterprise things. And it has been amazing watching this community grow. I'm gonna say grow up and mature. Yes. You know, you know, they're not wearing ties yet, but they are definitely understanding kind of the, the friction of implementing new technology in, in an enterprise. >>Yeah. So ge what's your, what's been your take, We were with you yesterday. What's been the take today to take aways? >>NOMA has changed since yesterday, but a few things I think I, I missed talking about that yesterday were that, first of all, let's just talk about Amazon. Amazon earnings came out, it spooked the market and I think it's relevant in this context as well, because they're number one cloud provider. Yeah. And all, I mean, almost all of these technologies on the back of us here, they are related to cloud, right? So it will have some impact on these. Like we have to analyze that. Like will it make the open source go faster or slower in, in lieu of the fact that the, the cloud growth is slowing. Right? So that's, that's one thing that's put that's put that aside. I've been thinking about the, the future of Kubernetes. What is the future of Kubernetes? And in that context, I was thinking like, you know, I think in, when I put a pointer there, I think in tangents, like, what else is around this thing? So I think CN CNCF has been writing the success of Kubernetes. They are, that was their number one flagship project, if you will. And it was mature enough to stand on its own. It it was Google, it's Google's Borg dub da Kubernetes. It's a genericized version of that. Right? So folks who do tech deep down, they know that, Right. So I think it's easier to stand with a solid, you know, project. But when the newer projects come in, then your medal will get tested at cncf. Right. >>And cncf, I mean they've got over 140 projects Yeah. Right now. So there's definitely much beyond >>Kubernetes. Yeah. So they, I have numbers there. 18 graduated, right, 37 in incubation and then 81 in Sandbox stage. They have three stages, right. So it's, they have a lot to chew on and the more they take on, the less, you know, quality you get goes into it. Who is, who's putting the money behind it? Which vendors are sponsoring like cncf, like how they're getting funded up. I think it >>Something I pay attention to as well. Yeah. Yeah. Lisa, I know you've got >>Some insight. Those are the things I was thinking about today. >>I gotta ask you, what's your take on what Keith said? Are you also seeing the maturation of the enterprise here at at coupon? >>Yes, I am actually, when you say enterprise versus what's the other side? Startups, right? Yeah. So startups start using open source a lot more earlier or lot more than enterprises. The enterprise is what they need. Number one thing is the, for their production workloads, they want a vendor sporting them. I said that yesterday as well, right? So it depend depending on the size of the enterprise. If you're a big shop, definitely if you have one of the 500 or Fortune five hundreds and your tech savvy shop, then you can absorb the open source directly coming from the open source sort of universe right. Coming to you. But if you are the second tier of enterprise, you want to go to a provider which is managed service provider, or it can be cloud service provider in this case. Yep. Most of the cloud service providers have multiple versions of Kubernetes, for example. >>I'm not talking about Kubernetes only, but like, but that is one example, right? So at Amazon you can get five different flavors of Kubernetes, right? Fully manage, have, manage all kind of stuff. So people don't have bandwidth to manage that stuff locally. You have to patch it, you have to roll in the new, you know, updates and all that stuff. Like, it's a lot of work for many. So CNCF actually is formed for that reason. Like the, the charter is to bring the quality to open source. Like in other companies they have the release process and they, the stringent guidelines and QA and all that stuff. So is is something ready for production? That's the question when it comes to any software, right? So they do that kind of work and, and, and they have these buckets defined at high level, but it needs more >>Work. Yeah. So one of the things that, you know, kind of stood out to me, I have good friend in the community, Alex Ellis, who does open Fast. It's a serverless platform, great platform. Two years ago or in 2019, there was a serverless day date. And in serverless day you had K Native, you had Open Pass, you had Ws, which is supported by IBM completely, not CNCF platforms. K native came into the CNCF full when Google donated the project a few months ago or a couple of years ago, now all of a sudden there's a K native day. Yes. Not a serverless day, it's a K native day. And I asked the, the CNCF event folks like, what happened to Serverless Day? I missed having open at serverless day. And you know, they, they came out and said, you know what, K native got big enough. >>They came in and I think Red Hat and Google wanted to sponsor a K native day. So serverless day went away. So I think what what I'm interested in and over the next couple of years is, is they're gonna be pushback from the C against the cncf. Is the CNCF now too big? Is it now the gatekeeper for do I have to be one of those 147 projects, right? In order enough to get my project noticed the open, fast, great project. I don't think Al Alex has any desire to have his project hosted by cncf, but it probably deserves, you know, shoulder left recognition with that. So I'm pushing to happen to say, okay, if this is open community, this is open source. If CNC is the place to have the cloud native conversation, what about the projects that's not cncf? Like how do we have that conversation when we don't have the power of a Google right. Or a, or a Lenox, et cetera, or a Lenox Foundation. So GE what, >>What are your thoughts on that? Is, is CNC too big? >>I don't think it's too big. I think it's too small to handle the, what we are doing in open source, right? So it's a bottle. It can become a bottleneck. Okay. I think too big in a way that yeah, it has, it has, it has power from that point of view. It has that cloud, if you will. The people listen to it. If it's CNCF project or this must be good, it's like in, in incubators. Like if you are y white Combinator, you know, company, it must be good. You know, I mean, may not be >>True, but, >>Oh, I think there's a bold assumption there though. I mean, I think everyone's just trying to do the best they can. And when we're evaluating projects, a very different origin and background, it's incredibly hard. Very c and staff is a staff of 30 people. They've got 180,000 people that are contributing to these projects and a thousand maintainers that they're trying to uphold. I think the challenge is actually really great. And to me, I actually look at events as an illustration of, you know, what's the culture and the health of an organization. If I were to evaluate CNCF based on that, I'd say we're very healthy right now. I would say that we're in a good spot. There's a lot of momentum. >>Yeah. I, I think CNCF is very healthy. I'm, I'm appreciative for it being here. I love coupon. It's becoming the, the facto conference to have this conversation has >>A totally >>Different vibe to other, It's a totally different vibe. Yeah. There needs to be a conduit and truth be told, enterprise buyers, to subject's point, this is something that we do absolutely agree on, on enterprise buyers. We want someone to pick winners and losers. We do, we, we don't want a box of Lego dumped on our, the middle of our table. We want somebody to have sorted that out. So while there may be five or six different service mesh solutions, at least the cncf, I can go there and say, Oh, I'll pick between the three or four that are most popular. And it, it's a place to curate. But I think with that curation comes the other side of it. Of how do we, how, you know, without the big corporate sponsor, how do I get my project pushed up? Right? Elevated. Elevated, Yep. And, and put onto the show floor. You know, another way that projects get noticed is that startups will adopt them, Push them. They may not even be, I don't, my CNCF project may not, my product may not even be based on the CNCF product. But the new stack has a booth, Ford has a booth. Nothing to do with a individual prod up, but promoting open source. What happens when you're not sponsored? >>I gotta ask you guys, what do you disagree on? >>Oh, so what, what do we disagree on? So I'm of the mindset, I can, I can say this, I I believe hybrid infrastructure is the future of it. Bar none. If I built my infrastructure, if I built my application in the cloud 10 years ago and I'm still building net new applications, I have stuff that I built 10 years ago that looks a lot like on-prem, what do I do with it? I can't modernize it cuz I don't have the developers to do it. I need to stick that somewhere. And where I'm going to stick that at is probably a hybrid infrastructure. So colo, I'm not gonna go back to the data center, but I'm, I'm gonna look, pick up something that looks very much like the data center and I'm saying embrace that it's the future. And if you're Boeing and you have, and Boeing is a member, cncf, that's a whole nother topic. If you have as 400 s, hpu X, et cetera, stick that stuff. Colo, build new stuff, but, and, and continue to support OpenStack, et cetera, et cetera. Because that's the future. Hybrid is the future. >>And sub g agree, disagree. >>I okay. Hybrid. Nobody can deny that the hybrid is the reality, not the future. It's a reality right now. It's, it's a necessity right now you can't do without it. Right. And okay, hybrid is very relative term. You can be like 10% here, 90% still hybrid, right? So the data center is shrinking and it will keep shrinking. Right? And >>So if by whole is the data center shrinking? >>This is where >>Quick one quick getting guys for it. How is growing by a clip? Yeah, but there's no data supporting. David Lym just came out for a report I think last year that showed that the data center is holding steady, holding steady, not growing, but not shrinking. >>Who sponsored that study? Wait, hold on. So the, that's a question, right? So more than 1 million data centers have been closed. I have, I can dig that through number through somebody like some organizations we published that maybe they're cloud, you know, people only. So the, when you get these kind of statements like it, it can be very skewed statements, right. But if you have seen the, the scene out there, which you have, I know, but I have also seen a lot of data centers walk the floor of, you know, a hundred thousand servers in a data center. I cannot imagine us consuming the infrastructure the way we were going into the future of co Okay. With, with one caveat actually. I am not big fan of like broad strokes. Like make a blanket statement. Oh no, data center's dead. Or if you are, >>That's how you get those esty headlines now. Yeah, I know. >>I'm all about to >>Put a stake in the ground. >>Actually. The, I think that you get more intelligence from the new end, right? A small little details if you will. If you're golden gold manak or Bank of America, you have so many data centers and you will still have data centers because performance matters to you, right? Your late latency matters for applications. But if you are even a Fortune 500 company on the lower end and or a healthcare vertical, right? That your situation is different. If you are a high, you know, growth startup, your situation is different, right? You will be a hundred percent cloud. So cloud gives you velocity, the, the, the pace of change, the pace of experimentation that actually you are buying innovation through cloud. It's proxy for innovation. And that's how I see it. But if you have, if you're stuck with older applications, I totally understand. >>Yeah. So the >>We need that OnPrem. Yeah, >>Well I think the, the bring your fuel sober, what we agree is that cloud is the place where innovation happens. Okay? At some point innovation becomes legacy debt and you have thus hybrid, you are not going to keep your old applications up to date forever. The, the, the math just doesn't add up. And where I differ in opinion is that not everyone needs innovation to keep moving. They need innovation for a period of time and then they need steady state. So Sergeant, we >>Argue about this. I have a, I >>Love this debate though. I say it's efficiency and stability also plays an important role. I see exactly what you're talking about. No, it's >>Great. I have a counter to that. Let me tell you >>Why. Let's >>Hear it. Because if you look at the storage only, right? Just storage. Just take storage computer network for, for a minute. There three cost reps in, in infrastructure, right? So storage earlier, early on there was one tier of storage. You say pay the same price, then now there are like five storage tiers, right? What I'm trying to say is the market sets the price, the market will tell you where this whole thing will go, but I know their margins are high in cloud, 20 plus percent and margin will shrink as, as we go forward. That means the, the cloud will become cheaper relative to on-prem. It, it, in some cases it's already cheaper. But even if it's a stable workload, even in that case, we will have a lower tier of service. I mean, you, you can't argue with me that the cloud versus your data center, they are on the same tier of services. Like cloud is a better, you know, product than your data center. Hands off. >>I love it. We, we are gonna relish in the debates between the two of you. Mic drops. The energy is great. I love it. Perspective. It's not like any of us can quite see through the crystal ball that we have very informed opinions, which is super exciting. Yeah. Lisa, any last thoughts today? >>Just love, I love the debate as well. That, and that's, that's part of what being in this community is all about. So sharing about, sharing opinions, expressing opinions. That's how it grows. That's how, that's how we innovate. Yeah. Obviously we need the cloud, but that's how we innovate. That's how we grow. Yeah. And we've seen that demonstrated the last couple days and I and your, your takes here on the Cuban on Twitter. Brilliant. >>Thank you. I absolutely love it. I'm gonna close this out with a really important analysis on the swag of the show. Yes. And if you know, yesterday we were looking at what is the weirdest swag or most unique swag We had that bucket hat that took the grand prize. Today we're gonna focus on something that's actually quite cool. A lot of the vendors here have really dedicated their swag to being local to Detroit. Very specific in their sourcing. Sonotype here has COOs. They're beautiful. You can't quite feel this flannel, but it's very legit hand sound here in Michigan. I can't say that I've been to too many conferences, if any, where there was this kind of commitment to localizing and sourcing swag from around the corner. We also see this with the Intel booth. They've got screen printers out here doing custom hoodies on spot. >>Oh fun. They're even like appropriately sized. They had local artists do these designs and if you're like me and you care about what's on your wrist, you're familiar with Shinola. This is one of my favorite swags that's available. There is a contest. Oh going on. Hello here. Yeah, so if you are Atan, make sure that you go and check this out. The we, I talked about this on the show. We've had the founder on the show or the CEO and yeah, I mean Shine is just full of class as since we are in Detroit as well. One of the fun themes is cars. >>Yes. >>And Storm Forge, who are also on the show, is actually giving away an Aston Martin, which is very exciting. Not exactly manufactured in Detroit. However, still very cool on the car front and >>The double oh seven version named the best I >>Know in the sixties. It's love it. It's very cool. Two quick last things. We talk about it a lot on the show. Every company now wants to be a software company. Yep. On that vein, and keeping up with my hat theme, the Home Depot is here because they want everybody to know that they in fact are a technology company, which is very cool. They have over 500,000 employees. You can imagine there's a lot of technology that has to go into keeping Napa. Absolutely. Yep. Wild to think about. And then last, but not at least very quick, rapid fire, best t-shirt contest. If you've ever ran to one of these events, there are a ton of T-shirts out there. I rate them on two things. Wittiest line and softness. If you combine the two, you'll really be our grand champion for the year. I'm just gonna hold these up and set them down for your laughs. Not afraid to commit, which is pretty great. This is another one designed by locals here. Detroit Code City. Oh, love it. This one made me chuckle the most. Kiss my cash. >>Oh, that's >>Good. These are also really nice and soft, which is fantastic. Also high on the softness category is this Op Sarah one. I also like their bird logo. These guys, there's just, you know, just real nice touch. So unfortunately, if you have the fumble, you're not here with us, live in Detroit. At least you're gonna get taste of the swag. I taste of the stories and some smiles hear from those of us on the cube. Thank you both so much for being here with us. Lisa, thanks for another fabulous day. Got it, girl. My name's Savannah Peterson. Thank you for joining us from Detroit. We're the cube and we can't wait to see you tomorrow.

>>Hello and welcome back to the live coverage of the Cube here. Live in Detroit, Michigan for Cub Con, our seventh year covering all seven years. The cube has been here. M John Fur, host of the Cube, co-founder of the Cube. I'm here with Lisa Mart, my co-host, and our new host, Savannah Peterson. Great to see you guys. We're wrapping up day one of three days of coverage, and our guest analyst is Sario Wall, who's the cube analyst who's gonna give us his report. He's been out all day, ear to the ground in the sessions, peeking in, sneaking in, crashing him, getting all the data. Great to see you, Sarvi. Lisa Savannah, let's wrap this puppy up. >>I am so excited to be here. My first coupon with the cube and being here with you and Lisa has just been a treat. I can't wait to hear what you have to say in on the report side. And I mean, I have just been reflecting, it was last year's coupon that brought me to you, so I feel so lucky. So much can change in a year, folks. You never know where you're be. Wherever you're sitting today, you could be living your dreams in just a few >>Months. Lisa, so much has changed. I mean, just look at the past this year. Events we're back in person. Yeah. Yep. This is a big team here. They're still wearing masks, although we can take 'em off with a cube. But mask requirement. Tech has changed. Conversations are upleveling, skill gaps still there. So much has changed. >>So much has changed. There's so much evolution and so much innovation that we've also seen. You know, we started out the keynote this morning, standing room. Only thousands of people are here. Even though there's a mass requirement, the community that is CNCF Co Con is stronger than I, stronger than I saw it last year. This is only my second co con. But the collaboration, what they've done, their devotion to the maintainers, their devotion to really finding mentors for mentees was really a strong message this morning. And we heard a >>Lot of that today. And it's going beyond Kubernetes, even though it's called co con. I also call it cloud native con, which I think we'll probably end up being the name because at the end of day, the cloud native scaling, you're starting to see the pressure points. You're start to see where things are breaking, where automation's coming in, breaking in a good way. And we're gonna break it all down Again. So much going on again, I've overs gonna be in charge. Digital is transformation. If you take it to its conclusion, then you will see that the developers are running the business. It isn't a department, it's not serving the business, it is the business. If that's the case, everything has to change. And we're, we're happy to have Sarib here with us Cube analysts on the badge. I saw that with the press pass. Well, >>Thank you. Thanks for getting me that badge. So I'm here with you guys and >>Well, you got a rapport. Let's get into it. You, I >>Know. Let's hear what you gotta say. I'm excited. >>Yeah. Went around, actually attend some sessions and, and with the analysts were sitting in, in the media slash press, and I spoke to some people at their booth and the, there are a few, few patterns, you know, which are, some are the exaggeration of existing patterns or some are kind of new patterns emerging. So things are getting complex in open source. The lawn more projects, right. They have, the CNCF has graduated some projects even after graduation, they're, they're exploring, right? Kubernetes is one of those projects which has graduated. And on that front, just a side note, the new projects where, which are entering the cncf, they're the, we, we gotta see that process and the three stages and all that stuff. I tweeted all day long, if you wanna know what it is, you can look at my tweets. But when I will look, actually write right on that actually after, after the show ends, what, what I saw there, these new projects need to be curated properly. >>I think they need to be weed. There's a lot of noise in these projects. There's a lot of overlap. So the, the work is cut out for CNCF folks, by the way. They're sort of managerial committee or whatever you call that. The, the people who are leading it, they're try, I think they're doing their best and they're doing a good job of that. And another thing actually, I really liked in the morning's keynote was that lot of women on the stage and minorities represented. I loved it, to be honest with you. So believe me, I'm a minority even though I'm Indian, but from India, I'm a minority. So people who have Punjab either know that I'm a minority, so I, I understand their pain and how hard it is to, to break through the ceiling and all that. So I love that part as well. Yeah, the >>Activity is clear. Yeah. From day one. It's in the, it's in the dna. I mean, they'll reject anything that the opposite >>Representation too. I mean, it's not just that everyone's invited, it's they're celebrated and that's a very big difference. Yeah. It's, you see conferences offer discounts for women for tickets or minorities, but you don't necessarily see them put them running where their mouth is actually recruit the right women to be on stage. Right. Something you know a little bit about John >>Diversity brings better outcomes, better product perspectives. The product is better with all the perspectives involved. Percent, it might go a little slower, maybe a little debates, but it's all good. I mean, it's, to me, the better product comes when everyone's in. >>I hope you didn't just imply that women would make society. So >>I think John men, like slower means a slower, >>More diversity, more debate, >>The worst. Bringing the diversity into picture >>Wine. That's, that's how good groups, which is, which is >>Great. I mean, yeah, yeah, >>Yeah, yeah. I, I take that mulligan back and say, hey, you knows >>That's >>Just, it's gonna go so much faster and better and cheaper, but that not diversity. Absolutely. >>Yes. Well, you make better products faster because you have a variety >>Of perspectives. The bigger the group, there's more debate. More debate is key. But the key to success is aligning and committing. Absolutely. Once you have that, and that's what open sources has been about for. Oh God, yeah. Generations >>Has been a huge theme in the >>Show generations. All right, so, so, >>So you have to add another, like another important, so observation if you will, is that the security is, is paramount right. Requirement, especially for open source. There was a stat which was presented in the morning that 60% of the projects in under CNCF have more vulnerabilities today than they had last year. So that was, That's shocking actually. It's a big jump. It's a big jump. Like big jump means jump, jump means like it can be from from 40 to 60 or or 50 or 60. But still that percentage is high. What, what that means is that lot more people are contributing. It's very sort of di carmic or ironic that we say like, Oh this project has 10,000 contributors. Is that a good thing? Right. We do. Do we know the quality of that, where they're coming from? Are there any back doors being, you know, open there? How stringent is the process of rolling those things, which are being checked in, into production? You know, who is doing that? I've >>Wondered about that. Yeah. The quantity, quality, efficacy game. Yes. And what a balance that must be for someone like CNCF putting in the structure to try and >>That's >>Hard. Curate and regulate and, and you know, provide some bumpers on the bowling lane, so to speak, of, of all of these projects. Yeah. >>Yeah. We thought if anybody thought that the innovation coming from, or the number of services coming from AWS or Google Cloud or likes of them is overwhelming, look at open source, it's even more >>Overwhelming. What's your take on the supply chain discussion? More code more happening. What are you hearing there? >>The supply chain from the software? Yeah. >>Supply chain software, supply chain security pays. Are people talking about that? What are you >>Seeing? Yeah, actually people are talking about that. The creation, the curation, not creation. Curation of suppliers of software I think is best done in the cloud. Marketplaces Ive call biased or what, you know, but curation of open source is hard. It's hard to know which project to pick. It's hard to know which project will pan out. Many of the good projects don't see the day light of the day, but some decent ones like it becomes >>A marketing problem. Exactly. The more you have out there. Exactly. The more you gotta get above the noise. Exactly. And the noise echo that. And you got, you got GitHub stars, you got contributors, you have vanity metrics now coming in to this that are influencing what's real. But sometimes the best project could have smaller groups. >>Yeah, exactly. And another controversial thing a little bit I will say that is that there's a economics of the practitioner, right? I usually talk about that and economics of the, the enterprise, right? So practitioners in our world, in software world especially right in systems world, practitioners are changing jobs every two to three years. And number of developers doubles every three years. That's the stat I've seen from Uncle Bob. He's authority on that software side of things. Wow. So that means there's a lot more new entrance that means a lot of churn. So who is watching out for the enterprise enterprises economics, You know, like are we creating stable enterprises? How stable are our operations? On a side note to that, most of us see the software as like one band, which is not true. When we talk about all these roles and personas, somebody's writing software for, for core layer, which is the infrastructure part. Somebody's writing business applications, somebody's writing, you know, systems of bracket, some somebody's writing systems of differentiation. We talk about those things. We need to distinguish between those and have principle based technology consumption, which I usually write about in our Oh, >>So bottom line in Europe about it, in your opinion. Yeah. What's the top story here at coupon? >>Top story is >>Headline. Yeah, >>The, the headline. Okay. The open source cannot be ignored. That's a headline. >>And what should people be paying attention to if there's a trend coming out? See any kind of trends coming out or any kind of signal, What, what do you see that people should pay attention to here? The put top >>Two, three things. The signal is that, that if you are a big shop, like you'd need to assess your like capacity to absorb open source. You need to be certain size to absorb the open source. If you are below that threshold, I mean we can talk about that at some other time. Like what is that threshold? I will suggest you to go with the managed services from somebody, whoever is providing those managed services around open source. So manage es, right? So from, take it from aws, Google Cloud or Azure or IBM or anybody, right? So use open source as managed offering rather than doing it yourself. Because doing it yourself is a lot more heavy lifting. >>I I, >>There's so many thoughts coming, right? >>Mind it's, >>So I gotta ask you, what's your rapport? You have some swag, What's the swag look >>Like to you? I do. Just as serious of a report as you do on the to floor, but I do, so you know, I come from a marketing background and as I, I know that Lisa does as well. And one of the things that I think about that we touched on in this is, is you know, canceling the noise or standing out from the noise and, and on a show floor, that's actually a huge challenge for these startups, especially when you're up against a rancher or companies or a Cisco with a very large budget. And let's say you've only got a couple grand for an activation here. Like most of my clients, that's how I ended up in the CU County ecosystem, was here with the A client before. So there actually was a booth over there and I, they didn't quite catch me enough, but they had noise canceling headphones. >>So if you just wanted to take a minute on the show floor and just not hear anything, which I thought was a little bit clever, but gonna take you through some of my favorite swag from today and to all the vendors, you know, this is why you should really put some thought into your swag. You never know when you're gonna end up on the cube. So since most swag is injection molded plastic that's gonna end up in the landfill, I really appreciate that garden has given all of us a potable plant. And even the packaging is plantable, which is very exciting. So most sustainable swag goes to garden. Well done >>Rep replicated, I believe is their name. They do a really good job every year. They had some very funny pins that say a word that, I'm not gonna say live on television, but they have created, they brought two things for us, yet it's replicated little etch sketch for your inner child, which is very nice. And given that we are in Detroit, we are in Motor City, we are in the home of Ford. We had Ford on the show. I love that they have done the custom K eight s key chains in the blue oval logo. Like >>Fords right behind us by the way, and are on you >>Interviewed, we had 'em on earlier GitLab taking it one level more personal and actually giving out digital portraits today. Nice. Cool. Which is quite fun. Get lap house multiple booths here. They actually IPOed while they were on the show floor at CubeCon 2021, which is fun to see that whole gang again. And then last but not least, really embracing the ship wheel logo of a Kubernetes is the robusta accrue that is giving out bucket hats. And if you check out my Twitter at sabba Savvy, you can see me holding the ship wheel that they're letting everyone pose with. So we are all in on Kubernetes. That cove gone 2022, that's for sure. Yeah. >>And this is something, day one guys, we've got three. >>I wanna get one of those >>Hats. We we need to, we need a group photo >>By the end of Friday we will have a beverage and hats on to sign off. That's, that's my word. If I can convince John, >>Don, what's your takeaway? You guys did a great kind of kickoff about last week or so about what you were excited about, what your thoughts were going to be. We're only on day one, There's been thousands of people here, we've had great conversations with contributors, the community. What's your take on day one? What's your, what's your tagline? >>Well, Savannah and I had at we up, we, we were talking about what we might see and I think we, we were right. I think we had it right. There's gonna be a lot more people than there were last year. Okay, check. That's definitely true. We're in >>Person, which >>Is refreshing. I was very surprised about the mask mandate that kind of caught me up guard. I was major. Yeah. Cause I've been comfortable without the mask. I'm not a mask person, but I had to wear it and I was like, ah, mask. But I understand I support that. But whatever. It's >>Corporate travel policy. So you know, that's what it is. >>And then, you know, they, I thought that they did an okay job with the gates, but they wasn't slow like last time. But on the content side, definitely Kubernetes security, top line headline, Kubernetes at scale security, that's, that's to me the bumper sticker top things to pay attention to the supply chain and the role of docker and the web assembly was a surprise. You're starting to see containers ecosystem coming back to, I won't say tension growth in the functionality of containers cuz they have to solve the security problem in the container images. Okay, you got scanning technology so it's a little bit in the weeds, but there's a huge movement going on to fix that problem to scale it so it's not a problem area contain. And then Dr sent a great job with productivity interviews. Scott Johnston over a hundred million in revenue so far. That's my number. They have not publicly said that. That's what I'm reporting from sources extremely well financially. And they, and they love their business model. They make productivity for developers. That's a scoop. That's new >>Information. That's a nice scoop we just dropped there on the co casually. >>You're watching that. Pay attention to that. But that, that's proof. But guess what, Red Hat's got developers too. Yes. Other people have to, So developers gonna go where it's the best. Yeah. Developers are voting with their code, they're voting with their feet. You will see the winners with the developers and that's what we've talked about. >>Well and the companies are catering to the developers. Savannah and I had a great conversation with Ford. Yeah. You saw, you showed their fantastic swag was an E for Ev right behind us. They were talking about the, all the cultural changes that they've really focused on to cater towards the developers. The developers becoming the influencers as you say. But to see a company that is as, as historied as Ford Motor Company and what they're doing to attract and retain developer talent was impressive. And honestly that surprised me. Yeah. >>And their head of deb relations has been working for, for, for 29 years. Which I mean first of all, most companies on the show floor haven't been around for 29 years. Right. But what I love is when you put community first, you get employees to stick around. And I think community is one of the biggest themes here at Cuco. >>Great. My, my favorite story that surprised me and was cool was the Red Hat Lockheed Martin interview where they had edge deployments with micro edge, >>Micro shift, >>Micro >>Shift, new projects under, there's, there are three new projects under, >>Under that was so, so cool because it was an edge story in deployment for the military where lives are on the line, they actually had it working. That is a real world example of Kubernetes and tech orchestrating to deploy the industrial edge. And I think that's proof in my mind that Kubernetes and this ecosystem is gonna move faster through this next wave of growth. Because once things start clicking, you get hybrid on premise to super cloud and edge. That was, that was my favorite cause it was real. That was real >>Story that it can make is literally life and death on the battlefield. Yeah, that was amazing. With what they're doing and what >>They're talking check out the Lockheed Martin Red Hat edge story on Silicon Angle and then a press release all pillar. >>Yeah. Another actually it's impressive, which we knew this which is happening, but I didn't know that it was happening at this scale is the finops. The finops is, I saw your is a discipline which most companies are adopting bigger companies, which are spending like hundreds of millions dollars in cloud average. Si a team size of finops for finops is seven people. And average number of tools is I think 3.5 or around 3.7 or something like that. Average number of tools they use to control the cost. So finops is a very generic term for years. It's not financial operations, it's the financial operations for the cloud cost, you know, containing the cloud costs. So that's a finops that is a very emerging sort of discipline >>To keep an eye on. And well, not only is that important, I talked to, well one of the principles over there, it's growing and they have real big players in that foundation. Their, their events are highly attended. It's super important. It's just, it's the cost side of cloud. And, and of course, you know, everyone wants to know what's going on. No one wants to leave there. Their Amazon on Yeah, you wanna leave the lights on the cloud, as we always say, you never know what the bill's gonna look like. >>The cloud is gonna reach $3 billion in next few years. So we might as well control the cost there. Yeah, >>It was, it was funny to get the reaction I found, I don't know if I was, how I react, I dunno how I felt. But we, we did introduce Super Cloud to a couple of guests and a, there were a couple reactions, a couple drawn. There was a couple, right. There was a couple, couple reactions. And what I love about the super cloud is that some people are like, oh, cringing. And some people are like, yeah, go. So it's a, it's a solid debate. It is solid. I saw more in the segments that I did with you together. People leaning in. Yeah. Super fun. We had a couple sum up, we had a couple, we had a couple cringes, I'll say their names, but I'll go back and make sure I, >>I think people >>Get 'em later. I think people, >>I think people cringe on the, on the term not on the idea. Yeah. You know, so the whole idea is that we are building top of the cloud >>And then so I mean you're gonna like this, I did successfully introduce here on the cube, a new term called architectural list. He did? That's right. Okay. And I wanna thank Charles Fitzgerald for that cuz he called super cloud architectural list. And that's exactly the point of super cloud. If you have a great coding environment, you shouldn't have to do an architecture to do. You should code and let the architecture of the Super cloud make it happen. And of course Brian Gracely, who will be on tomorrow at his cloud cast said Super Cloud enables super services. Super Cloud enables what Super services, super service. The microservices underneath the covers have to be different. High performing, automated. So again, the debate and Susan, the goal is to keep it open. And that's our, that's our goal. But we had a lot of fun with that. It was fun to poke the bear a little bit. So >>What is interesting to see just how people respond to it too, with you throwing it out there so consistently, >>You wanna poke the bear, get a conversation going, you know, let let it go. We'll see, it's been positive so far. >>There, there I had a discussion outside somebody who is from Ford but not attending this conference and they have been there for a while. I, I just some moment hit like me, like I said, people, okay, technologists are horizontal, the codes are horizontal. They will go from four to GM to Chrysler to Bank of America to, you know, GE whatever, you know, like cross vertical within vertical different vendors. So, but the culture of a company is local, right? Right. Ford has been building cars for forever. They sort of democratize it. They commercialize it, right? But they have some intense culture. It's hard to change those cultures. And how do we bring in the new thinking? What is, what approach that should be? Is it a sandbox approach for like putting new sensors on the car? They have to compete with te likes our Tesla, right? Yeah. But they cannot, if they are afraid of deluding their existing market or they're afraid of failure there, right? So it's very >>Tricky. Great stuff. Sorry. Great to have you on as our cube analyst breaking down the stories. We'll document that, that we'll roll out a post on it. Lisa Savannah, let's wrap up the show for day one. We got day two and three. We'll start with you. What's your summary? Quick bumper sticker. What's today's show all about? >>I'm a community first gal and this entire experience is about community and it's really nice to see the community come together, celebrate that, share ideas, and to have our community together on stage. >>Yeah. To me, to me it was all real. It's happening. Kubernetes cloud native at scale, it's happening, it's real. And we see proof points and we're gonna have faster time to value. It's gonna accelerate faster from here. >>The proof points, the impact is real. And we saw that in some amazing stories. And this is just a one of the cubes >>Coverage. Ib final word on this segment was well >>Said Lisa. Yeah, I, I think I, I would repeat what I said. I got eight, nine years back at a rack space conference. Open source is amazing for one biggest reason. It gives the ability to the developing nations to be at somewhat at par where the dev develop nations and, and those people to lift up their masses through the automation. Cuz when automation happens, the corruption goes down and the economy blossoms. And I think it's great and, and we need to do more in it, but we have to be careful about the supply chains around the software so that, so our systems are secure and they are robust. Yeah, >>That's it. Okay. To me for SAR B and my two great co-host, Lisa Martin, Savannah Peterson. I'm John Furry. You're watching the Cube Day one in, in the Books. We'll see you tomorrow, day two Cuban Cloud Native live in Detroit. Thanks for watching.