(upbeat music) >> Welcome back to Supercloud 22. I'm John Furrier, your host of "The Cube." We're here for a live performance in studio bringing all the thought leaders around this concept of Supercloud, which is a consortium of the smartest people in the industry, the the Cloudaratti some say, or just people in the field building out next generation Cloud technologies for businesses, for the industry, you know, software meets infrastructure at scale and platforms. All great stuff. We have an expert here, Cube alumni and friend of ours, Howie Xu, VP of machine learning and AI at Zscaler, hugely successful company, platform, whatever you want to call it. They're definitely super clouding in their own. Howie, great to see you. Thanks for spending time with us to unpack and grock the direction of the industry that we see. We call it Supercloud. >> Hey, John, great to be back. I'm expecting a nice very educational and interesting conversation here again. >> Yeah, well, you know, one of the things I love talking with you about is you're deep on the technology side, as well as you got the historian view like we do. We've seen the movies before, we've seen the patterns, and now we're seeing structural change that has happened, that's cloud. Thank you very much, AWS. And as your GCP and others. Now we're seeing structural change happening in real time and we want to talk about it as it's happening. This is the purpose of this event. And that is that Cloud is one. Okay, great Cloud operations, on premises and Edge are emerging. Software is open source. It's the perfect storm for innovation and new things are emerging. You're seeing companies like Snowflake, and Databricks, and Zscaler all building great products. But now it's not one thing anymore. It's a lot of things going on. So what is your take on Supercloud? How do you see this evolving? What is some of the structural change that's happening in your mind? >> Yeah, so when you first reached out a few weeks ago about this event, I was like, "Hey, what is Supercloud." I know you tweeted a little bit here and there, but I never really, you know, double clicked, right. So I actually listened to some of your episodes you know, the previous conversations. You know, I would say the way you define Supercloud is it's not just the multi-cloud. The multi-Cloud is probably one aspect of it, right. You know, it's actually more beyond that, right. You know, a little bit, you know, towards past, a little bit more towards the flexibility, and then, you know, including, and also you want to include the on-prem, the edge, not just the Big 3 cloud, right. So there is a lot of the, let's say hybrid, more inclusive, right. So, the way I look at it is it's now very different from my imagination of where the Cloud would be, should be 10, 12 years ago. Because, you know, at that time it was, you know, on-prem dominant and then we say, hey, let's go cloud. I never for a second thought, you know, we would've ditch the on-prem completely, right. You know, on-prem has its own value. It's own kind of characteristics we wanted to keep, right. But the way we went for the last 10 years is, hey, Cloud, Cloud everywhere. We embrace Cloud. You know, the way I look at architecture is always very much like a pendulum, right? We swung from decentralized in the mainframe days, you know back in the days, to more distributed, right, PC, kind of a architecture, you know, servers in your own data center. And then to the now, the Cloud, the Big 3 Cloud in particular, right. I think in the next 10, 15, 20 years, it will swing back to more decentralized, more distributed architecture again. Every time you have a swing, because there is some fundamental reason behind that, we all knew the reason behind the current swing to the Cloud. It's because hey, the on-prem data center was too complex, right. You know, too expensive, right. You know, it would've take at least the six months to get any business application going, right. So compared to Cloud, a swipe a credit card, frictionless, you know, pay as you go, it's so great. But I think we are going to see more and more reason for people to say, "Hey, I need a architecture the other way around because of the decentralized the use case," right. Web3 is one example. Even though Web3 is still, you know, emerging right, very, very early days. But that could be one reason, right? You mentioned the Zscaler is kind of a Supercloud of its own, right? We always embrace public Cloud, but a lot of the workloads is actually on our own, you know, within our own data center. We take advantage of the elasticity of the public Cloud, right. But we also get a value, get a performance of our private Cloud. So I want to say a company like Zscaler taking advantage of the Supercloud already, but there will be more and more use cases taking advantage. >> And the use cases are key. Let me just go back and share something we had on the panel earlier in the day, the Cloudaratti Panel. Back in 2008, a bunch of us were getting together and we kind of were riffing, oh yeah, the future's going to be web services and Clouds will talk to each other, workloads can work across this (indistinct) abstraction layer, APIs is going to be talking to each other. A little bit early but we tried to think about it in terms of the preferred architecture. Okay, way too early. Yeah. AWS was just getting going, really kind of pumping on all cylinders there, getting that trajectory up. But it was use case driven. The nirvana never happened. I mean, we were talking Supercloud back then with the Cloudaratti group and we were thinking, okay, hey this is cool. But it was just an evolutionary thing. So I want to get your reaction. Today, the use cases are different. It's not just developers deploying on public Cloud to get all those greatness and goodness of the Cloud, to your point about Zscaler and others, there's on premises use cases and edge use cases emerging. 5g is right there. That's going to explode. So, the use cases now are all Cloud based. Again, this is an input into what we're seeing around Supercloud. How do you see that? What's your reaction to that? And how do you see that evolving so that the methodologies and all the taxonomies are in place for the right solution? >> Right, I mean, you know, some of the use cases are already here, you know, have been here for the last few years. And again, I mentioned a Zscaler, right. The reason that a Zscaler needs the on-prem version of it is because it's impossible to route all the traffic to the Big 3 Cloud, because they're still far away. Sometimes you need the presence much closer to you in order for you to get the level of the performance latency you want, right. So that's why Zscaler has, you know, so many data center of our own instead of leveraging the public Cloud, you know, for most part. However, public Cloud is still super important for Zscaler. I can tell you a story, right. You know, two years ago, you know, at the beginning of the pandemics, everyone started working from home suddenly, right. You are talking about Fortune 500 companies with 200,000 employees, suddenly having 200,000 employees working from home. Their VPN architecture is not going to support that kind of the workload, right? Even Zscaler's own architecture or the presence is not enough. So overnight we just, having so many new workloads, to support this work from home, the zero trust network for our customers, literally overnight. So it wouldn't have happened without public Cloud. So we took advantage of the public Cloud. Yet at the same time, for many, many use cases that Zscaler is paying attention to in terms of the zero trust architecture, the latency, the latency guarantee aspect, the cost is so important. So we kind of take it advantage of both. >> Yeah, definitely. >> Today you may say, hey, you know, Zscaler is one of the, not a majority of the companies in terms of the Cloud adoption or public Cloud adoption, right. But I can say that, yeah, that's because it's more infrastructure, security infrastructure. It's a little bit different for some of the communication applications, right. Why not just support everything on the public Cloud? That's doable today. However, moving forward next to 5, 10, 15 years, we expect to see Web3 kind of the use cases to grow more and more. In those kind of decentralized use cases, I can totally see that we, you know, the on-prim presence is very important. >> Yeah. One of the things we're seeing with Supercloud that we're kind of seeing clarity on is that there's a lot of seamless execution around, less friction around areas that require a PhD or hard work. And you're seeing specialty Superclouds, apps, identity data security. You're also seeing vertical clouds, Goldman Sachs doing financial applications. I'm sure there'll be some insurance. People in these verse. Building on top of the CapEx on one Cloud really fast and moving to others. So that's clearly a trend. The interesting thing I want to get your thoughts on, Howie, on an architectural basis is in Cloud, public Cloud generally, SaaS depends on IAS. So there's an interplay between SaaS and the infrastructures of service and pass as well. But SaaS and IAS, they solve a lot of the problems. You mentioned latency. How do you see the interplay of these Superclouds that utilize the SaaS IS relationship to solve technical problems? So in architecturally, that's been a tight integration on these Clouds, but now as you get more complexity with Supercloud, how do you see SaaS applications changing? >> Yeah, I view the Supercloud is actually reduced the complexity. The reason I'm saying that is, think about it in the world where you have predominantly public Cloud kind of the architecture, right? 10 years ago, AWS has probably 20 services. Now they probably have, you know, more than 1,000 services. Same thing with Azure, same thing with GCP. I mean, who can make sense out of it, right. You know, if you just consume the eyes or the Big 3 Cloud service as is. You know, you need a PhD these days to make sense all of them. So the way I think about Supercloud or where, you know it is going, is it has to provide more simplicity, a better way for people to make sense out of it, right. Cause if I'm an architecture and I have to think, hey, this is a public Cloud, this is a multi-Cloud, and by the way, certain things need to be run on the on-prem. And how do I deal with the uniform nature of it? My mind would blow up. So I need a higher level abstraction. That higher level abstraction will hide the complexity of the where it is, which vendor. It will only tell me the service level, right. You know, we always say, you know, the Cloud is like electricity. I only wanted to know is that like 110 volt or 220, 240, whatever that is. I don't really want to know more than that, right. So I want to say a key requirement for the Supercloud is it's reduced the complexity, higher level abstraction. It has to be like that. >> And operational consistencies at the bottom. Howie, we have one minute left. I want to get your thoughts. I'd like you to share what you're working on that you're excited about. It doesn't have to be with Zscaler. As you see the Supercloud trend emerging, this is the next generation Cloud, Cloud 2.0, whatever we want to call it, it's happening. It's changing. It's getting better. What are you excited about? What do you see as really key inflection point variables in this big wave? >> Yeah. One of the things I really like, what I heard from you in the past about Supercloud is a Supercloud is not just a one Cloud or one vendor. It's almost like every company should have its own Supercloud, right. You're talking about JP Morgan, Goldman Sachs of the world, that they need to have their own Supercloud. Zscaler and their security vendors, they may have their own Cloud. So I think every Fortune 500, Fortune 2,000 companies will have its own Supercloud. So I'm excited about that. So why that's important? We also say that, you know, in the next 10, 20 years, AI machine learning is going to help us a lot, right. So without Supercloud, it's very hard to do AI machine learning. 'Cause if you don't have a place that you know where the data is, and then it's pretty hard. And in the context of Supercloud, I totally foresee that the AI model will follow the data. If the data is in the cloud, it will go there. If the data is on-prem, it will go there. And then the Supercloud will hide the complexity of it. So if you ask me, my passion is leveraging AI machine learning to change the world, but Supercloud will make that easier, right. If you think about why Google, Facebook of the world, are able to leverage AI better than 99% of the rest of the world, because they figure out the Supercloud for themselves, right. And I think now it's the time for the rest of the Fortune 500, of Fortune 2,000 company to figure out its own Supercloud strategy. What is my Supercloud? I need to have my own Supercloud. Each company needs to have its own Supercloud. That's how I see it. >> Howie, always great to have you on. Thanks so much for spending the time and weighing in on this really important topic. We're going to be opening this up. It's not over. We're going to continue to watch the change as it unfolds and get an open community perspective. Thank you so much for being a great expert in our network and community. We really appreciate your time. >> Thank you for having me. >> Okay. Okay, that's it. We'll be up with more coverage here, Supercloud event, after this short break. I'm John Furrier, host of "The Cube." Thanks for watching. (upbeat music)

>> Narrator: Live from Stanford University, it's theCUBE! Covering Stanford Women in Data Science 2020, brought to you by SiliconAngle Media. >> Hi, and welcome to the cube, I'm your host, Sonia Tagare. And we're live at Stanford University, covering the fifth annual WiDS, Women in Data Science Conference. Joining us today is Ya XU, the head of data science at LinkedIn. Ya Welcome to the cube. >> Thank you for having me. >> So tell us a little bit about your role and about LinkedIn. >> So LinkedIn is, first of all, the biggest professional social network, where we have a massive economic graph that we have been creating with millions actually close to 700 million members and millions of companies and jobs and of course, you know, with students of skills and also schools as well as part of it. And, and I lead the data science team at LinkedIn. And my team really spans across the global presence that LinkedIn offices have. And yeah really working on various different areas. That's both thinking about how we can iterate and understand and improve our products, that we deliver to our members and our customers. And also at the same time thinking about how we can make our infrast6ructure more efficient, and thinking about how we can make our sales and marketing more efficient as well, so we really span across. >> And how has the use of data science evolved to deliver a better user experience for users of LinkedIn? >> Yeah, so first of all, I think we LinkedIn in general, we truly believe that everybody can benefit from better data, better data access, in general. So we're certainly using data to continuously understand better of what our members are looking for. As a simple example, is that whenever we launch new feature, we're not just  blindly deciding ourselves what is the better feature for our members, but we actually understand how our users are reacting to it. Right? So we use data to understand that, and then certainly making decisions, and whether we should be eventually launching this feature to all members or not. So that's a very prominent way for us to use data. And obviously, we also use data to understand and just even before we build certain features. Is this sort of feature that's right feature to build. We do both survey and understand the survey data, but also at the same time understanding just user behavior data for us to be able to come up with better features for users. >> And do you use AB testing as well? >> Oh absolutely, Yeah. So we do a lot of AV experiments. That's what, I was not trying to use that word by that like that terminology, but this is what we use to have an understanding of user features that we are developing, that we are putting in front of our users. Is that what they enjoy as much as we think they will enjoy? >> Right, so you had a talk today about creating global economic opportunities with responsible data. So give us some highlights from your talk. >> So, first of all, at LinkedIn we we truly believe in the vision that we are working towards, which is really creating economic opportunity for every member of the global workforce. And if you're kind of starting from that, and thinking about that is our sort of the axiom that we're working towards, and then thinking about how you can do that, and obviously, the sort of the table stake or just the fundamental thing that we have to start with is to be able to preserve the privacy of our members as we are leveraging the data that our members entrust with us. Right, so how can we do that? We have some early effort in using and developing differential privacy as a technique for us to do a lot better. Always regarding preserving their privacy as we're leveraging the data, but also at the same time, it doesn't ends there, right? Because you're thinking about creating opportunity. It's not just about to preserve their privacy, but also, when we are leveraging the data, how can we leverage the data in a way that is able to create opportunity in a fair way? So here is also a lot of effort that we're having with regarding, how can we do that? And what does fairest mean? What are the ways we can actually turn some of the key concepts that we have into action that is really able to drive the way we develop product, the way that we think about responsible design, and the way that we build our algorithms, the way that we measure in every single dimension. >> And and speaking about that bias, at the opening address, they mentioned that diversity is really great because it provides many perspectives, and also helps reduce this bias. So how have you at LinkedIn been able to create a more diverse team? >> So first of all, I think it's certain we all believe that diversity is certainly better as we building product. Thinking about if you have a diverse team that is really a representation of the customer and some members that you're serving, then definitely you're able to come up with better features that is able to serve the needs of the population of our members. But also at the same time, that's just the right thing to do as well. Right, thinking about we all have had experiences we may not you know, feel as much belonging when we walk into a room that we are the only person that we identify with to be in that room. And, we certainly wanted to be able to create that environment for all the employees as well. And and thinking about, I think there is also studies that has done as what makes a high performing team. Some of the studies has done I google with the psychological safety aspects of it, which is really there's a lot of brain science that says when you make people feel they belong, that they will actually be so much more creative and innovative and everything right. So we have that belief. But tactically, there are many things that we're doing from all the divs aspect, right? How can you bring diversity, inclusion and belonging? Starting from and hiring, right? So we certainly are very much emphasized how can we increase the diversity of individuals that we're bringing to LinkedIn? And when they are at LinkedIn, can we make them feel more belonging, and feel more included in every aspects? We have different inclusion groups, right? We have I mean, obviously, I'm very much involved in Women tech. At LinkedIn we have both money efforts that we do to help women at LinkedIn in engineering, and in other groups as well to feel they belong to this community. At the same time, there is concrete actions that we're taking too. Right, that we are helping women to have a much better understanding, and aware of some of the ways that we operate that is slightly different from maybe our male colleagues will operate, right? There are certain things that we're doing to change the current processes, hiring processes, promotion process, that we are able to bring more equal footing to the way that we're thinking about gender gap and gender diversity. >> Right, that's great. And what advice would you give to women who are just starting college or who are just out of college who are interested in going into data science. >> So I want to say the biggest learning for me, is just have that can do attitude. I, you know, the woman biologically and all just like in every way, we're not any less than men. And that you certainly have seen many strong and very talented women that we have in the field. So don't let people's perceptions or biases around you to bring you down. And then thinking about what you wanted, and then just go for it, and then go for the the advice that you can get from people. And then there are so many as you can see in the conference today, so many talented women that you can reach out to who are winning and very willing to help you as well. >> And in this age of AI and ML, where do you see data science going in the future? >> That's a really interesting question. So in the way that, you know, data science I want to say is a field that is really broad, right? So if you're thinking about things that I would consider to be part of data science may not necessarily part of AI, but some of the course of influence that is extremely popular and important. And then I think the fields will continue to evolve, there are going to be and then the fields are continually overlapping with each other as well. You cannot do data science without understanding or have a strong skill in AI and machine learning. And you also can't do great machine learning without understanding the data science either. Right? So thinking about some of the talk that definitely colder earlier was sharing, as in you know, you can blind in the wrong algorithm and without realizing the bias. That all the algorithm is really just detecting the machines that's using the images versus you know, actually detecting the difference between broken bones or not right, like so. So I think having, I do see there is a continuously big overlap and I think the individuals who are involved in both communities should continue to be very comfortable being in that way too. >> Right, great. Thank you so much for being on theCUBE and thank you for your insight. >> Of course, thank you for having me. >> I'm your host, Sonia Takari. Thank you for watching theCUBE and stay tuned for more. (Upbeat music)

(upbeat jazz music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California. This is a CUBEConversation. >> Hello everyone, welcome to this special CUBEConversation. I'm John Furrier in theCUBE Studios in Palo Alto, California. We're excited to have a great tech talk here with good friend Howie Xu, who's currently the Vice President of Machine Learning and AI at Zscaler. Formally an entrepreneur, which he sold his company Zscaler. Before that entrepreneur resident Greylock. Before that VMWare, a variety of other endeavors. Howie and I, we've known each other for a while. Great to have you come in and chat about-- >> Great to be here! >> The Zoom, Zscaler, these are the new breed modern era companies, SaaS business models. Really interesting and this is something that we were talking about on email and over text, is our topic. >> Yeah. >> Thanks for coming in. >> Great. >> So you've seen the waves at VMWare, you saw the rapid growth there. And now, you work for Zscaler which is experiencing rapid growth. You saw Zoom go public, and I just interviewed Michael Dell. We were commenting about that on text as well. He said these big markets that have big total addressable dollars associated with them are ripe for disruption. They used to have high barriers to entry in the old ways to look at it, but now with cloud and with SaaS, with data, there's different innovation speeds. This has become a big deal. Talk about your view on this. >> Well to me, when Zoom and then Zscaler founded, many years ago, no one believed that they would become this big, right? When Zoom founded, they were plenty of the conference, free even, software available out there. When Jay founded Zscaler people thought, "Well, there was enough security companies, security solutions." Clearly, they defied conventional wisdom and then they just fought on and they saw something that other people didn't see which is precisely what you were talking about. The SaaS is so different, right? The business model, the innovation speed, the data driven kind of the thing, it's so different. A lot of people say, "Hey what's the difference "between SaaS versus the convention? "Isn't that just moving that thing over to the cloud?" I actually used to think that way too, right? Isn't that just the virtual price, moving on to Amazon Cloud? After living and breathing in SaaS company and then also observing that in the VC industry as well. It's just totally different, day and night different. >> Well I wanted to get into this with you 'cause I think you bring some good perspective onto these insights and to the rocket success of say Zoom and Zscaler, but Zoom in particular, recent successful IPO. Among the recent class this past quarter. Zoom, Lyft, Uber. Zoom is standing out. They're getting profitable. This is video conferencing. You know in the old days if someone said, "Hey, I want to compete with video conferences." Well, the barriers are actually too high, but they took a very innovative approach. Cloud, data, simplicity, and the big 800 pound gorilla was the WebEx's of the world. Who was defined, divine for sharing slides, not so much pure video. (laughing) >> Yeah. >> They really innovated the focus, the speed of success. Unprecedented, in my opinion. I think this is a huge success of what the opportunities are for entrepreneurs. >> Yeah, I think on the surface, right? If you ask Eric he would tell you that, look the WebEx was designed for sharing slides, and then the Zoom was designed from ground up for video sharing, or the video conferencing, so it's very different and it requires different architecture. So that's very true. But I think there is a more fundamental to that. The more fundamental for that is, there are a few things. One is the product, the life cycle is very different. How do you approach the customer? The release cycle, the sort of the feedback loop, right? Much tighter feedback loop, much faster feedback loop between the customer and you. The release cost is much lower now as a SaaS product. So, innovation is just accelerated because it's SaaS, because it's a true SaaS. >> And this is a unique thing, you said before, SaaS isn't just lifting a on-premises workload and moving it to the cloud. It's a completely different mindset. Talk about this dynamic, because it affords new kinds of risk taking. You and I were talking about before we came on camera, share your insight on that. >> Well, you know, as kind of the traditional software you have a release cycle, you want it to have a release date, right? And then once the product is in customer hand, if you have a bug, if you have something, it's so costly to change it, right? But as a SaaS, the form factor, you can take a little bit more risk. You can even give that feature set to 10% of your audience. Not the entire set of the audience. You can do those kind of magic, so you can accelerate the innovation and as a shrink-wrapped software the traditional way. You have one shot, if that software is not good, then you are toast. >> So you can move quicker. You can push code, you don't have the on-premise dynamics. >> Yeah, the innovation and then risk taking are kind of correlated, right? Relatively more risk, the more you are willing to take risk, relatively you can take more innovation. So, that's the thing. >> Well, you and I were talking, and one of the key things that you have been talking about publicly, and amongst friends, is innovation speed. Everyone wants the innovation fever. "I got to win to innovate, digital transformation, rah rah." Easier said then done. Innovation speed is critical with cloud and SaaS, why? What's the formula there for innovation speed? >> Well, one thing we discussed, the release cycle. For a, not necessarily for Zoom and Zscaler, but you know for SaaS in general, its possible for you to have daily, weekly, monthly release. Traditional software, there is no way you can do that but that's just the release cycles of that. The other thing is, you can actually take a risk. You can say, "Hey I want you to try to raise 1% of the customer and then see how they are going to react to this." But in the traditional way you have product manager debating for six months, six years on whether or how to do things. Here, let's not debate, let's just see. >> Let's ship it. >> Right, ship it. >> And Reid Hoffman always says, "If he's not embarrassed by your first shipment then you're not doing it properly." Which begs the question, I want to get your thoughts on this because, again with VMware, you saw how early that worked and their transforming cloud is now here unlike when they started the company. What is the right way to do it? And what's the wrong way to do it? When you look at an entrepreneur or a friend, who's trying to get a business off the ground, SaaS business, when you look at what they're doing, and you look at their mechanisms and how they're organizing their team, their code. What jumps out at you as the wrong way, and what's the right way? >> Well, the, I think the coach is really it, right? You know, the kind of the coach of incremental success and the fast iteration is the culture for a SaaS company, right? For the traditional one, you cannot afford to do that, because once you make a small mistake, you are toast. So I think, you know, that the culture difference, you really want it to have faster iteration basically. >> And that also comes down to the team, the people, right? >> Yes. >> The people selection. >> Yes, if you are kind of used to the waterfall thing, it's pretty hard to adapt to this kind of the SaaS world. >> And what's your advice to entrepreneurs? Reset, because if you say speed is of the essence, resetting is probably something that's not hard to do, then. >> Well, I wouldn't say easy, but not easy-- >> I hate to use the word pivot, but you know, resetting means okay, stop, rebuild. >> I think one way to think about it is actually looking at it and how to build enterprise software, like the consumer sort of product way, right? If you think of Facebook or Google, the traditional Google, of course Google now has enterprise product, but the traditional sort of, the Google, Facebook, kind of the product, it's more for consumers to consume. I mean they are fast iterations. How often? What's the criteria to release a product? Enterprise product is getting towards there. You need that kind of the thing, so, if you don't know how to do it look at a Facebook, how Facebook, of course Facebook and YouTube pulled the other way around, they need to care more about the privacy, care about more stability. So I think you are seeing the the two sides of the world, the enterprise side and the consumer side. They are learning from each other. >> Well, I want to get to the enterprise talk track in a second, because I think you can give a lot of insight, so I want to stay on SaaS cloud native or cloud specifically, 'cause that's where SaaS really shines when you're really talking about cloud scale. Data, you're doing AI now, and you and I have both talked about data many times. >> Yes. >> You know I'm a data hardcore person. I love data. I think software and data, I wrote a blog post in 2007, that says data is the new developer kit. The word "developer kit" was used back then. You're now seeing where data is part of the developer's piece of their value creation. Highly addressable, available, usable, not stored in some silo unaddressable, high latency to get it. How important is the data for the SaaS piece? Because that's where to make these kind of changes you're talking about, you need the data, data's giving you insights, that's something that's near and dear to your heart. Explain your vision of the role of data. >> Yeah, I think, you touched up on it. If you want to make sense out of something, you need the data, right? And if it's not SaaS, I would go, maybe a more extreme way, but it's not clear to me the data's even useful to you 'cause you know the data may be for some large software company, they may have hundreds of thousands of customers out there, but the data is spread around. I mean how are you going to train a model with all the data spread around hundreds of thousands of locations? So the real, the correct, or the optimal way, is actually the SaaS model, you actually have the data with you and then you kind of leverage the data. So I would say this is actually another benefit of the SaaS, why SaaS is going to change the world or eat the world. It owns the data for real, right? The data may be not the private data, but it's actually could be a behavior data. How people are reacting to your features. From VMware days we wanted to know, is people even using this feature? How often people use this feature? You know people are always debating, "Hey what's the maximum policy we need to give this and that?" But in the SaaS world, no debate just look at it. We always say, "Don't listen to what customers are wanting you to do." But watch how they do things, so that you can sort of understand, what product you want to develop, right? Here you actually can really watch how customers using your product. Don't listen to them, if you listen to them you will give them a faster horse as we all knew. >> But what's important about the data discussion, because, a security person would say, "Hey if you put into one spot, I can hack it." But, it's not just people's names, it's other data. It's gesture data, it's usage data, so you're not talking about sign in data, it's data. >> It could be the behavior, it could be second order data. Do people use my product, that's my data. That's something I wanted to know, I'm not necessarily talking about peeking into people's email, no. It's actually the thing surrounding it. >> It's looking for the good things in the data. All right, let's talk about the customer alignment and customer expectations, you know customer user experience is driven by customer's expectations usually, right? As expectations change. And I think the Zoom thing jumped out at me, the Zoom IPO and their great success and were a customer as well, is that they really nailed the expectation of the user and cloud certainly helped them get that speed, but this is a key thing, if you could just deliver a great experience. >> Yeah. >> For those customers, you can actually win big part of the market. >> Yeah, if you Google, Eric. Eric doesn't speak to me as much, but if you Google Eric. >> We'll get him on theCUBE. >> What's sort of the jump? Hopefully I can help you to bring him here too. But what's going to be obvious if you Google search Eric he is sort of the notion of customer successes, my success. If customer is happy, I'm going to happy. So, my happiness hinges on the customer's happiness. So that's, kind of very important because only the SaaS model made that more natural. In traditional model, whether traditional on prime or we're not, you sort of celebrate when you have customer signing your PO and then you don't hear from the sales guy or three years, the sales guy may move on to another company, you don't know, right? But for the SaaS, it doesn't stop when sign the PO. You actually have to earn customers' happiness every single day. >> Adoption's critical. >> Yeah, customer success is important and then that's kind of the, so there is a huge alignment, very interesting alignment between customer's happiness, customer success, customer adoption of your product and you're sort of, the success, right? 'Cause you know, when I came to Zscaler, one of our first meeting is about, okay, we had a lot of customer interest us. They sign a PO. How to get them ramp up the actual first use, right? So, that kind of conversation doesn't happen in the traditional software company. You sign a PO. If the customer doesn't use your product for another 18 month which is actually quite normal, no one is going to jump up and say, "This is crazy!" Right? >> You know, we're going to do that on our Part Two, about the impact of the enterprise. But you made up a good point there, I want to just close out our last talk point is, the data driving the experience isn't like the old way of throw in, get the PO and celebrate. You got to, kind of, keep that going. The enterprise is changing and the enterprise has a tsunami of onboarding of new types of developers. In some cases they grow. We just had Cisco inside here on theCUBE this morning. They're turning network guys into programmers from CL command line prompt dudes to gals to coders. You're seeing developers now enter the enterprise to build the apps so there's now a digital transformation initiative for enterprises to be, I guess, SaaS-like. But it's hard. >> Yeah, I think that's, you know, this is part of the digital transformation. Every company, Fortune 500 or Fortune 2000 company need to do it, right? So, another interesting part is, when they do this on this journey of digitalization, you cannot possibly build all the infrastructure yourself. You will have to consume public cloud, you know sometimes private and hybrid cloud, and you are actually going to consume lots of the SaaS, right? Whether Zoom, the Zscaler, or the PagerDuty, I mean you are not going to be all those thing from scratch but you want it to have a very good, sort of the stack on top of it and how you going to take advantage of the SaaS, is a very interesting aspect. >> Well in Part Two of our chat, when we come back on our next discussion, I want to get into the enterprise. But to wrap up Part One here, innovation speed, leveraging data and the beautiful risk taking and benefits of SaaS. Large scale, fast, high value, target and developing an app or a venture. >> Yeah. >> What is your advice to entrepreneurs out there and/or someone who's doing a digital transformation? Where they want to leverage Saas, what's the playbook, what's the starting point, what's your advice? >> Well, there are a number of things. One, there are so many SaaS companies out there taking advantage of them, right? In the old days you have to hire email admins, you have to do this. Nowadays, all the SaaS, that's your kind of, you only need to worry about the business logic, you have some unique insight in the business and then just have, hire programmers to codify that and then the rest will magically happen because of the public cloud, because of the SaaS. So, be very mindful about the new environment you are in, that's number one. The second thing I want to say is, how do you look at AI technology? The older way is program something in a definitive way. I think there will be a limit for that. It has taken the software industry a long way to where we are. But, if you look at the next 20 years, I think a lot of the lift is going to be done by the AI Center. But it's not going to be easy to be done, you have to think about your data strategy, where are you going to have the massive, sustainable, unique, ideally even labeled data. If you don't have the labeled data, you have to have the strategy. How are you going to have some unique model with the data you have? So, the data strategy, right? So, essentially, how to take advantage of the cloud? How to take advantage of the data? And then on top of that you are going to do something that's solving an unmet um-- >> Customer problem. >> Customer problem. >> An acute landing spot in the market place. >> Unmet need. >> In a big market. >> In a big, well, in a big market. >> There it is. >> Even if there is already a mature solution I bet, since those mature solutions would not develop from that native cloud era, and the native AI era. You have plenty of opportunities. >> Howie, you and I are on the same page on this, I have been saying it truly believe we are living in an entrepreneurial era where, with your advice and what you just laid out, the better mousetrap can take down a big market. >> And, I'm hopeful that you will also disrupt the media business, you know we're-- >> Don't tell anyone! (laughing) We're still going to do that top secret of Silent Running. Howie, we're going to get Part Two. We're going to dig Deep into the enterprise, because the enterprise now has an opportunity in the first historic time in tech history, to use tools and technologies to completely reset and re-architect for this kind of capability. >> Absolutely. >> So, we'll hit that in Part Two. >> I'm super passionate about it too. >> Howie Xu, here inside theCUBE. Friend of theCUBE, legend in the industry. Great entrepreneur and technologist here, sharing CUBEConversation. I'm John Furrier, thanks for watching. (upbeat jazz music)

from New York it's the cube covering blockchain week now here's John furry hello everyone I'm John Frey here on the ground actually on the water in the majesty boat here in New York City part of blockchain week New York City I'm here at Maggie's ooh who's he whose abyss development a decentralized launched a huge party here we're on a four story boat it's like the Titanic but it's in New York you can see hopefully we won't hit me icebergs but no icebergs ahead in blockchain thanks for joining me here on the water thank you John it's actually really funny you mentioned Titanic first time we came and saw the bow we're like oh my gosh this boat look exactly like Titanic let's really do something about it because see Centro is really about technology both being forward and so yeah we I think we pulled a very crazy party right now so tell us about the event this is a really cool event how big is the book just give us the details you ran the event so I know it's hard to run these kinds of events a lot of moving parts you're giving away two aston martin cars on a bracelet that's gonna light up and turn off based upon if you want or not so is it how's it work okay so this boat has a thousand people on here right now plus our team member plus a boat people so we have about eleven hundred people here and this whole event was run in the last five weeks the team has been working so hard and right now this bracelet that you see it syncs with the music so beats per second it syncs the colors and everything with the music and 11:45 today we're going to be giving away to Aston Martin's the bracelet will dim down one by one and the five bracelets that remaining will go on the stage everyone's gonna cheer out the crowd we're really gonna get everyone you know cheered up and this is not just like you know us giving away Aston Martin's this is really about bring the whole blocking community together we want to be say hey this is a small community let's all get United the cars are just a way for us to thank our partners and everyone I found about you know and I get a little nervous when I see these kind of launch parties because it reminds me that comm bubble but what's different about what's going on with you central is you guys have a business that's up and running this is not an ICO there's no fundraising going on you guys are actually executing and this is important because you guys are doing this as a community take a minute to explain the role of the blockchain community for you guys how important that is right so if you think about a blocking community right now we have the different coins we have the different exchanges the community is very fragmented and that is unfortunate because you know someone like my mom doesn't really understand the term blockchain or cryptocurrency but at the same time it's kind of like Internet 2.0 where you know these technologies are so new there's a lot of people who are so passionate on one of them and just like we just want to spend every day trying to make this better so the central role is really a bell okay let's do all these partnerships so we have over a hundred partnerships almost 200 now all signed and these are the people that we work with like every single day and what kind of partnerships are they they code development together as an open source or they're using the Jax platform you guys made some significant announcements today yeah I'm the Jax Liberty cube ice cube for cold storage I like the cube name not be confused with the cube as in the media cube us but this is a unification strategy talk about the news what did you guys announce tonight all right so today we announced two things we announced at Jax Liberty renounced Jax unity and then we announced the other things but that are part of that whole essential project so the Jax Liberty is the platform it's kind of like an app store all of our partners are gonna be part of this app store and we're just gonna have over 200 partners and more going on onward and every single the apps and integration will be here and we'll make it kind of like a game for the new users what's the bet value proposition for people to join the network it's a free platform we're not charging anyone anything and you know we're probably gonna do that forever so for us the model here is really about bringing all of these different projects together whether it be exchanges whether it be cryptocurrency Wallis whether it be different new sites encrypted messaging all of these things that touch every part of our life we want to say hey we want to bring freedom and power back to you and freedom to us is really your ability to control the information you know I'm very impressed with anthea see I interviewed a couple times in the Bahamas and he's got a great vision and one of the things that he talked in the presentation was kind of not will say buried but I think is the most important notable thing is that he talked about a new Internet infrastructure okay and the wallet is central to this new Internet infrastructure you guys are doing something really pioneering where you're actually creating a unification around infrastructure in network effects with currency this is a super important thing do you guys is this part of your mission or is this part of a just part of the product in your mind our mission like I said is really about brain freedom back to everyone right now if you think about you know how Facebook has their social data how Google has our browsing data all these different entities have our data and we feel like that's really the only way so what descent who is doing is we're saying that we want to create a one platform where we can bring all these different partners together and in doing so we're able to allow people to you know just being able to take control of your life that that is our mission we want to empower people so your pitch basically is join dee central if you joined essentials platform you join the community that wants to unify that's pretty much sounds like the pitch yes we want to empower people and we want to unified whole block G and a world community now you talk about your background how did you get here I mean like you just wake up one day and say hey I'm gonna get in the blockchain I mean what's your background got a legal background how did you give so my background is in business and then business law so I practiced for two years as a business lawyer I may not look like one but you check my record and they were covering lawyers that's okay exactly recovery and then so what I really want to do is all about impact I went into law school because I wanted to do a lot of impact I realized a lot of it is one-on-one not really doing it going to technology and I saw I found my passion and then I found blockchain I was like oh my gosh like this is it does this really you know we are sitting at the forefront of a technology that might be able to just change millions or billions of people's life and a lot of it people are talking about it if we're not really explaining it properly or building things properly I fell decentral is really at a forefront to make sure that is being done that's awesome what are some of the partners you guys have that are notable can you share some of the names and what they're working with you guys on so we're from Toronto Canada proud Canadian and internal we have a all new Co you're a into probability blocking space we have poly mas they do security platform we also have Bri the blockchain Research Institute that's led by Tapscott you know he wrote a very famous book we also have a shift that's you know just doing the KYC AML we also have the big ones like hoeing base like just a lot like block that's the consulting firm we have a lot of different partners that are just like all to cure one ones because of Anthony's background because of our experience in the space for the last four years people trust us people trust our wallet people want to be part of our sea and be part of our mission while we're on the water gonna get you go back to all the partying and schmoozing that's going on great event thank you for putting it on and and I think the community is very very robust out there right now we're having a good time yes outside is like a zoo and I'm really excited that you're here and we're able to meet some of the really great people and you can interview them Maggie thank you for coming on the cube on the water okay with the new cube product with the central unified essential has a new offering on cube is here covering and I'm John Fourier your host thanks for watching [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)

(upbeat music) >> Hello and welcome back to theCUBE. We're here in Palo Alto, California. I'm your host, John Furrier with a special guest here in the studio. As part of our Cloud Native SecurityCon Coverage we had an opportunity to bring in Jon Turow who is the partner at Madrona Venture Partners formerly with AWS and to talk about machine learning, foundational models, and how the future of AI is going to be impacted by some of the innovation around what's going on in the industry. ChatGPT has taken the world by storm. A million downloads, fastest to the million downloads there. Before some were saying it's just a gimmick. Others saying it's a game changer. Jon's here to break it down, and great to have you on. Thanks for coming in. >> Thanks John. Glad to be here. >> Thanks for coming on. So first of all, I'm glad you're here. First of all, because two things. One, you were formerly with AWS, got a lot of experience running projects at AWS. Now a partner at Madrona, a great firm doing great deals, and they had this future at modern application kind of thesis. Now you are putting out some content recently around foundational models. You're deep into computer vision. You were the IoT general manager at AWS among other things, Greengrass. So you know a lot about data. You know a lot about some of this automation, some of the edge stuff. You've been in the middle of all these kind of areas that now seem to be the next wave coming. So I wanted to ask you what your thoughts are of how the machine learning and this new automation wave is coming in, this AI tools are coming out. Is it a platform? Is it going to be smarter? What feeds AI? What's your take on this whole foundational big movement into AI? What's your general reaction to all this? >> So, thanks, Jon, again for having me here. Really excited to talk about these things. AI has been coming for a long time. It's been kind of the next big thing. Always just over the horizon for quite some time. And we've seen really compelling applications in generations before and until now. Amazon and AWS have introduced a lot of them. My firm, Madrona Venture Group has invested in some of those early players as well. But what we're seeing now is something categorically different. That's really exciting and feels like a durable change. And I can try and explain what that is. We have these really large models that are useful in a general way. They can be applied to a lot of different tasks beyond the specific task that the designers envisioned. That makes them more flexible, that makes them more useful for building applications than what we've seen before. And so that, we can talk about the depths of it, but in a nutshell, that's why I think people are really excited. >> And I think one of the things that you wrote about that jumped out at me is that this seems to be this moment where there's been a multiple decades of nerds and computer scientists and programmers and data thinkers around waiting for AI to blossom. And it's like they're scratching that itch. Every year is going to be, and it's like the bottleneck's always been compute power. And we've seen other areas, genome sequencing, all kinds of high computation things where required high forms computing. But now there's no real bottleneck to compute. You got cloud. And so you're starting to see the emergence of a massive acceleration of where AI's been and where it needs to be going. Now, it's almost like it's got a reboot. It's almost a renaissance in the AI community with a whole nother macro environmental things happening. Cloud, younger generation, applications proliferate from mobile to cloud native. It's the perfect storm for this kind of moment to switch over. Am I overreading that? Is that right? >> You're right. And it's been cooking for a cycle or two. And let me try and explain why that is. We have cloud and AWS launch in whatever it was, 2006, and offered more compute to more people than really was possible before. Initially that was about taking existing applications and running them more easily in a bigger scale. But in that period of time what's also become possible is new kinds of computation that really weren't practical or even possible without that vast amount of compute. And so one result that came of that is something called the transformer AI model architecture. And Google came out with that, published a paper in 2017. And what that says is, with a transformer model you can actually train an arbitrarily large amount of data into a model, and see what happens. That's what Google demonstrated in 2017. The what happens is the really exciting part because when you do that, what you start to see, when models exceed a certain size that we had never really seen before all of a sudden they get what we call emerging capabilities of complex reasoning and reasoning outside a domain and reasoning with data. The kinds of things that people describe as spooky when they play with something like ChatGPT. That's the underlying term. We don't as an industry quite know why it happens or how it happens, but we can measure that it does. So cloud enables new kinds of math and science. New kinds of math and science allow new kinds of experimentation. And that experimentation has led to this new generation of models. >> So one of the debates we had on theCUBE at our Supercloud event last month was, what's the barriers to entry for say OpenAI, for instance? Obviously, I weighed in aggressively and said, "The barriers for getting into cloud are high because all the CapEx." And Howie Xu formerly VMware, now at ZScaler, he's an AI machine learning guy. He was like, "Well, you can spend $100 million and replicate it." I saw a quote that set up for 180,000 I can get this other package. What's the barriers to entry? Is ChatGPT or OpenAI, does it have sustainability? Is it easy to get into? What is the market like for AI? I mean, because a lot of entrepreneurs are jumping in. I mean, I just read a story today. San Francisco's got more inbound migration because of the AI action happening, Seattle's booming, Boston with MIT's been working on neural networks for generations. That's what we've found the answer. Get off the neural network, Boston jump on the AI bus. So there's total excitement for this. People are enthusiastic around this area. >> You can think of an iPhone versus Android tension that's happening today. In the iPhone world, there are proprietary models from OpenAI who you might consider as the leader. There's Cohere, there's AI21, there's Anthropic, Google's going to have their own, and a few others. These are proprietary models that developers can build on top of, get started really quickly. They're measured to have the highest accuracy and the highest performance today. That's the proprietary side. On the other side, there is an open source part of the world. These are a proliferation of model architectures that developers and practitioners can take off the shelf and train themselves. Typically found in Hugging face. What people seem to think is that the accuracy and performance of the open source models is something like 18 to 20 months behind the accuracy and performance of the proprietary models. But on the other hand, there's infinite flexibility for teams that are capable enough. So you're going to see teams choose sides based on whether they want speed or flexibility. >> That's interesting. And that brings up a point I was talking to a startup and the debate was, do you abstract away from the hardware and be software-defined or software-led on the AI side and let the hardware side just extremely accelerate on its own, 'cause it's flywheel? So again, back to proprietary, that's with hardware kind of bundled in, bolted on. Is it accelerator or is it bolted on or is it part of it? So to me, I think that the big struggle in understanding this is that which one will end up being right. I mean, is it a beta max versus VHS kind of thing going on? Or iPhone, Android, I mean iPhone makes a lot of sense, but if you're Apple, but is there an Apple moment in the machine learning? >> In proprietary models, here does seem to be a jump ball. That there's going to be a virtuous flywheel that emerges that, for example, all these excitement about ChatGPT. What's really exciting about it is it's really easy to use. The technology isn't so different from what we've seen before even from OpenAI. You mentioned a million users in a short period of time, all providing training data for OpenAI that makes their underlying models, their next generation even better. So it's not unreasonable to guess that there's going to be power laws that emerge on the proprietary side. What I think history has shown is that iPhone, Android, Windows, Linux, there seems to be gravity towards this yin and yang. And my guess, and what other people seem to think is going to be the case is that we're going to continue to see these two poles of AI. >> So let's get into the relationship with data because I've been emerging myself with ChatGPT, fascinated by the ease of use, yes, but also the fidelity of how you query it. And I felt like when I was doing writing SQL back in the eighties and nineties where SQL was emerging. You had to be really a guru at the SQL to get the answers you wanted. It seems like the querying into ChatGPT is a good thing if you know how to talk to it. Labeling whether your input is and it does a great job if you feed it right. If you ask a generic questions like Google. It's like a Google search. It gives you great format, sounds credible, but the facts are kind of wrong. >> That's right. >> That's where general consensus is coming on. So what does that mean? That means people are on one hand saying, "Ah, it's bullshit 'cause it's wrong." But I look at, I'm like, "Wow, that's that's compelling." 'Cause if you feed it the right data, so now we're in the data modeling here, so the role of data's going to be critical. Is there a data operating system emerging? Because if this thing continues to go the way it's going you can almost imagine as you would look at companies to invest in. Who's going to be right on this? What's going to scale? What's sustainable? What could build a durable company? It might not look what like what people think it is. I mean, I remember when Google started everyone thought it was the worst search engine because it wasn't a portal. But it was the best organic search on the planet became successful. So I'm trying to figure out like, okay, how do you read this? How do you read the tea leaves? >> Yeah. There are a few different ways that companies can differentiate themselves. Teams with galactic capabilities to take an open source model and then change the architecture and retrain and go down to the silicon. They can do things that might not have been possible for other teams to do. There's a company that that we're proud to be investors in called RunwayML that provides video accelerated, sorry, AI accelerated video editing capabilities. They were used in everything, everywhere all at once and some others. In order to build RunwayML, they needed a vision of what the future was going to look like and they needed to make deep contributions to the science that was going to enable all that. But not every team has those capabilities, maybe nor should they. So as far as how other teams are going to differentiate there's a couple of things that they can do. One is called prompt engineering where they shape on behalf of their own users exactly how the prompt to get fed to the underlying model. It's not clear whether that's going to be a durable problem or whether like Google, we consumers are going to start to get more intuitive about this. That's one. The second is what's called information retrieval. How can I get information about the world outside, information from a database or a data store or whatever service into these models so they can reason about them. And the third is, this is going to sound funny, but attribution. Just like you would do in a news report or an academic paper. If you can state where your facts are coming from, the downstream consumer or the human being who has to use that information actually is going to be able to make better sense of it and rely better on it. So that's prompt engineering, that's retrieval, and that's attribution. >> So that brings me to my next point I want to dig in on is the foundational model stack that you published. And I'll start by saying that with ChatGPT, if you take out the naysayers who are like throwing cold water on it about being a gimmick or whatever, and then you got the other side, I would call the alpha nerds who are like they can see, "Wow, this is amazing." This is truly NextGen. This isn't yesterday's chatbot nonsense. They're like, they're all over it. It's that everybody's using it right now in every vertical. I heard someone using it for security logs. I heard a data center, hardware vendor using it for pushing out appsec review updates. I mean, I've heard corner cases. We're using it for theCUBE to put our metadata in. So there's a horizontal use case of value. So to me that tells me it's a market there. So when you have horizontal scalability in the use case you're going to have a stack. So you publish this stack and it has an application at the top, applications like Jasper out there. You're seeing ChatGPT. But you go after the bottom, you got silicon, cloud, foundational model operations, the foundational models themselves, tooling, sources, actions. Where'd you get this from? How'd you put this together? Did you just work backwards from the startups or was there a thesis behind this? Could you share your thoughts behind this foundational model stack? >> Sure. Well, I'm a recovering product manager and my job that I think about as a product manager is who is my customer and what problem he wants to solve. And so to put myself in the mindset of an application developer and a founder who is actually my customer as a partner at Madrona, I think about what technology and resources does she need to be really powerful, to be able to take a brilliant idea, and actually bring that to life. And if you spend time with that community, which I do and I've met with hundreds of founders now who are trying to do exactly this, you can see that the stack is emerging. In fact, we first drew it in, not in January 2023, but October 2022. And if you look at the difference between the October '22 and January '23 stacks you're going to see that holes in the stack that we identified in October around tooling and around foundation model ops and the rest are organically starting to get filled because of how much demand from the developers at the top of the stack. >> If you look at the young generation coming out and even some of the analysts, I was just reading an analyst report on who's following the whole data stacks area, Databricks, Snowflake, there's variety of analytics, realtime AI, data's hot. There's a lot of engineers coming out that were either data scientists or I would call data platform engineering folks are becoming very key resources in this area. What's the skillset emerging and what's the mindset of that entrepreneur that sees the opportunity? How does these startups come together? Is there a pattern in the formation? Is there a pattern in the competency or proficiency around the talent behind these ventures? >> Yes. I would say there's two groups. The first is a very distinct pattern, John. For the past 10 years or a little more we've seen a pattern of democratization of ML where more and more people had access to this powerful science and technology. And since about 2017, with the rise of the transformer architecture in these foundation models, that pattern has reversed. All of a sudden what has become broader access is now shrinking to a pretty small group of scientists who can actually train and manipulate the architectures of these models themselves. So that's one. And what that means is the teams who can do that have huge ability to make the future happen in ways that other people don't have access to yet. That's one. The second is there is a broader population of people who by definition has even more collective imagination 'cause there's even more people who sees what should be possible and can use things like the proprietary models, like the OpenAI models that are available off the shelf and try to create something that maybe nobody has seen before. And when they do that, Jasper AI is a great example of that. Jasper AI is a company that creates marketing copy automatically with generative models such as GPT-3. They do that and it's really useful and it's almost fun for a marketer to use that. But there are going to be questions of how they can defend that against someone else who has access to the same technology. It's a different population of founders who has to find other sources of differentiation without being able to go all the way down to the the silicon and the science. >> Yeah, and it's going to be also opportunity recognition is one thing. Building a viable venture product market fit. You got competition. And so when things get crowded you got to have some differentiation. I think that's going to be the key. And that's where I was trying to figure out and I think data with scale I think are big ones. Where's the vulnerability in the stack in terms of gaps? Where's the white space? I shouldn't say vulnerability. I should say where's the opportunity, where's the white space in the stack that you see opportunities for entrepreneurs to attack? >> I would say there's two. At the application level, there is almost infinite opportunity, John, because almost every kind of application is about to be reimagined or disrupted with a new generation that takes advantage of this really powerful new technology. And so if there is a kind of application in almost any vertical, it's hard to rule something out. Almost any vertical that a founder wishes she had created the original app in, well, now it's her time. So that's one. The second is, if you look at the tooling layer that we discussed, tooling is a really powerful way that you can provide more flexibility to app developers to get more differentiation for themselves. And the tooling layer is still forming. This is the interface between the models themselves and the applications. Tools that help bring in data, as you mentioned, connect to external actions, bring context across multiple calls, chain together multiple models. These kinds of things, there's huge opportunity there. >> Well, Jon, I really appreciate you coming in. I had a couple more questions, but I will take a minute to read some of your bios for the audience and we'll get into, I won't embarrass you, but I want to set the context. You said you were recovering product manager, 10 plus years at AWS. Obviously, recovering from AWS, which is a whole nother dimension of recovering. In all seriousness, I talked to Andy Jassy around that time and Dr. Matt Wood and it was about that time when AI was just getting on the radar when they started. So you guys started seeing the wave coming in early on. So I remember at that time as Amazon was starting to grow significantly and even just stock price and overall growth. From a tech perspective, it was pretty clear what was coming, so you were there when this tsunami hit. >> Jon: That's right. >> And you had a front row seat building tech, you were led the product teams for Computer Vision AI, Textract, AI intelligence for document processing, recognition for image and video analysis. You wrote the business product plan for AWS IoT and Greengrass, which we've covered a lot in theCUBE, which extends out to the whole edge thing. So you know a lot about AI/ML, edge computing, IOT, messaging, which I call the law of small numbers that scale become big. This is a big new thing. So as a former AWS leader who's been there and at Madrona, what's your investment thesis as you start to peruse the landscape and talk to entrepreneurs as you got the stack? What's the big picture? What are you looking for? What's the thesis? How do you see this next five years emerging? >> Five years is a really long time given some of this science is only six months out. I'll start with some, no pun intended, some foundational things. And we can talk about some implications of the technology. The basics are the same as they've always been. We want, what I like to call customers with their hair on fire. So they have problems, so urgent they'll buy half a product. The joke is if your hair is on fire you might want a bucket of cold water, but you'll take a tennis racket and you'll beat yourself over the head to put the fire out. You want those customers 'cause they'll meet you more than halfway. And when you find them, you can obsess about them and you can get better every day. So we want customers with their hair on fire. We want founders who have empathy for those customers, understand what is going to be required to serve them really well, and have what I like to call founder-market fit to be able to build the products that those customers are going to need. >> And because that's a good strategy from an emerging, not yet fully baked out requirements definition. >> Jon: That's right. >> Enough where directionally they're leaning in, more than in, they're part of the product development process. >> That's right. And when you're doing early stage development, which is where I personally spend a lot of my time at the seed and A and a little bit beyond that stage often that's going to be what you have to go on because the future is going to be so complex that you can't see the curves beyond it. But if you have customers with their hair on fire and talented founders who have the capability to serve those customers, that's got me interested. >> So if I'm an entrepreneur, I walk in and say, "I have customers that have their hair on fire." What kind of checks do you write? What's the kind of the average you're seeing for seed and series? Probably seed, seed rounds and series As. >> It can depend. I have seen seed rounds of double digit million dollars. I have seen seed rounds much smaller than that. It really depends on what is going to be the right thing for these founders to prove out the hypothesis that they're testing that says, "Look, we have this customer with her hair on fire. We think we can build at least a tennis racket that she can use to start beating herself over the head and put the fire out. And then we're going to have something really interesting that we can scale up from there and we can make the future happen. >> So it sounds like your advice to founders is go out and find some customers, show them a product, don't obsess over full completion, get some sort of vibe on fit and go from there. >> Yeah, and I think by the time founders come to me they may not have a product, they may not have a deck, but if they have a customer with her hair on fire, then I'm really interested. >> Well, I always love the professional services angle on these markets. You go in and you get some business and you understand it. Walk away if you don't like it, but you see the hair on fire, then you go in product mode. >> That's right. >> All Right, Jon, thank you for coming on theCUBE. Really appreciate you stopping by the studio and good luck on your investments. Great to see you. >> You too. >> Thanks for coming on. >> Thank you, Jon. >> CUBE coverage here at Palo Alto. I'm John Furrier, your host. More coverage with CUBE Conversations after this break. (upbeat music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

(gentle upbeat music) >> Welcome back everyone, to "theCUBE"'s live stage performance here in Palo Alto, California at "theCUBE" Studios. I'm John Furrier with Dave Vellante, kicking off our first inaugural Supercloud event. It's an editorial event, we wanted to bring together the best in the business, the smartest, the biggest, the up-and-coming startups, venture capitalists, everybody, to weigh in on this new Supercloud trend, this structural change in the cloud computing business. We're about to run the Ecosystem Speaks, which is a bunch of pre-recorded companies that wanted to get their voices on the record, so stay tuned for the rest of the day. We'll be replaying all that content and they're going to be having some really good commentary and hear what they have to say. I had a chance to interview and so did Dave. Dave, this is our closing segment where we kind of unpack everything or kind of digest and report. So much to kind of digest from the conversations today, a wide range of commentary from Supercloud operating system to developers who are in charge to maybe it's an ops problem or maybe Oracle's a Supercloud. I mean, that was debated. So so much discussion, lot to unpack. What was your favorite moments? >> Well, before I get to that, I think, I go back to something that happened at re:Invent last year. Nick Sturiale came up, Steve Mullaney from Aviatrix; we're going to hear from him shortly in the Ecosystem Speaks. Nick Sturiale's VC said "it's happening"! And what he was talking about is this ecosystem is exploding. They're building infrastructure or capabilities on top of the CapEx infrastructure. So, I think it is happening. I think we confirmed today that Supercloud is a thing. It's a very immature thing. And I think the other thing, John is that, it seems to me that the further you go up the stack, the weaker the business case gets for doing Supercloud. We heard from Marianna Tessel, it's like, "Eh, you know, we can- it was easier to just do it all on one cloud." This is a point that, Adrian Cockcroft just made on the panel and so I think that when you break out the pieces of the stack, I think very clearly the infrastructure layer, what we heard from Confluent and HashiCorp, and certainly VMware, there's a real problem there. There's a real need at the infrastructure layer and then even at the data layer, I think Benoit Dageville did a great job of- You know, I was peppering him with all my questions, which I basically was going through, the Supercloud definition and they ticked the box on pretty much every one of 'em as did, by the way Ali Ghodsi you know, the big difference there is the philosophy of Republicans and Democrats- got open versus closed, not to apply that to either one side, but you know what I mean! >> And the similarities are probably greater than differences. >> Berkely, I would probably put them on the- >> Yeah, we'll put them on the Democrat side we'll make Snowflake the Republicans. But so- but as we say there's a lot of similarities as well in terms of what their objectives are. So, I mean, I thought it was a great program and a really good start to, you know, an industry- You brought up the point about the industry consortium, asked Kit Colbert- >> Yep. >> If he thought that was something that was viable and what'd they say? That hyperscale should lead it? >> Yeah, they said hyperscale should lead it and there also should be an industry consortium to get the voices out there. And I think VMware is very humble in how they're putting out their white paper because I think they know that they can't do it all and that they do not have a great track record relative to cloud. And I think, but they have a great track record of loyal installed base ops people using VMware vSphere all the time. >> Yeah. >> So I think they need a catapult moment where they can catapult to the cloud native which they've been working on for years under Raghu and the team. So the question on VMware is in the light of Broadcom, okay, acquisition of VMware, this is an opportunity or it might not be an opportunity or it might be a spin-out or something, I just think VMware's got way too much engineering culture to be ignored, Dave. And I think- well, I'm going to watch this very closely because they can pull off some sort of rallying moment. I think they could. And then you hear the upstarts like Platform9, Rafay Systems and others they're all like, "Yes, we need to unify behind something. There needs to be some sort of standard". You know, we heard the argument of you know, more standards bodies type thing. So, it's interesting, maybe "theCUBE" could be that but we're going to certainly keep the conversation going. >> I thought one of the most memorable statements was Vittorio who said we- for VMware, we want our cake, we want to eat it too and we want to lose weight. So they have a lot of that aspirations there! (John laughs) >> And then I thought, Adrian Cockcroft said you know, the devs, they want to get married. They were marrying everybody, and then the ops team, they have to deal with the divorce. >> Yeah. >> And I thought that was poignant. It's like, they want consistency, they want standards, they got to be able to scale And Lori MacVittie, I'm not sure you agree with this, I'd have to think about it, but she was basically saying, all we've talked about is devs devs devs for the last 10 years, going forward we're going to be talking about ops. >> Yeah, and I think one of the things I learned from this day and looking back, and some kind of- I've been sauteing through all the interviews. If you zoom out, for me it was the epiphany of developers are still in charge. And I've said, you know, the developers are doing great, it's an ops security thing. Not sure I see that the way I was seeing before. I think what I learned was the refactoring pattern that's emerging, In Sik Rhee brought this up from Vertex Ventures with Marianna Tessel, it's a nuanced point but I think he's right on which is the pattern that's emerging is developers want ease-of-use tooling, they're driving the change and I think the developers in the devs ops ethos- it's never going to be separate. It's going to be DevOps. That means developers are driving operations and then security. So what I learned was it's not ops teams leveling up, it's devs redefining what ops is. >> Mm. And I think that to me is where Supercloud's going to be interesting- >> Forcing that. >> Yeah. >> Forcing the change because the structural change is open sources thriving, devs are still in charge and they still want more developers, Vittorio "we need more developers", right? So the developers are in charge and that's clear. Now, if that happens- if you believe that to be true the domino effect of that is going to be amazing because then everyone who gets on the wrong side of history, on the ops and security side, is going to be fighting a trend that may not be fight-able, you know, it might be inevitable. And so the winners are the ones that are refactoring their business like Snowflake. Snowflake is a data warehouse that had nothing to do with Amazon at first. It was the developers who said "I'm going to refactor data warehouse on AWS". That is a developer-driven refactorization and a business model. So I think that's the pattern I'm seeing is that this concept refactoring, patterns and the developer trajectory is critical. >> I thought there was another great comment. Maribel Lopez, her Lord of the Rings comment: "there will be no one ring to rule them all". Now at the same time, Kit Colbert, you know what we asked him straight out, "are you the- do you want to be the, the Supercloud OS?" and he basically said, "yeah, we do". Now, of course they're confined to their world, which is a pretty substantial world. I think, John, the reason why Maribel is so correct is security. I think security's a really hard problem to solve. You've got cloud as the first layer of defense and now you've got multiple clouds, multiple layers of defense, multiple shared responsibility models. You've got different tools for XDR, for identity, for governance, for privacy all within those different clouds. I mean, that really is a confusing picture. And I think the hardest- one of the hardest parts of Supercloud to solve. >> Yeah, and I thought the security founder Gee Rittenhouse, Piyush Sharrma from Accurics, which sold to Tenable, and Tony Kueh, former head of product at VMware. >> Right. >> Who's now an investor kind of looking for his next gig or what he is going to do next. He's obviously been extremely successful. They brought up the, the OS factor. Another point that they made I thought was interesting is that a lot of the things to do to solve the complexity is not doable. >> Yeah. >> It's too much work. So managed services might field the bit. So, and Chris Hoff mentioned on the Clouderati segment that the higher level services being a managed service and differentiating around the service could be the key competitive advantage for whoever does it. >> I think the other thing is Chris Hoff said "yeah, well, Web 3, metaverse, you know, DAO, Superclouds" you know, "Stupercloud" he called it and this bring up- It resonates because one of the criticisms that Charles Fitzgerald laid on us was, well, it doesn't help to throw out another term. I actually think it does help. And I think the reason it does help is because it's getting people to think. When you ask people about Supercloud, they automatically- it resonates with them. They play back what they think is the future of cloud. So Supercloud really talks to the future of cloud. There's a lot of aspects to it that need to be further defined, further thought out and we're getting to the point now where we- we can start- begin to say, okay that is Supercloud or that isn't Supercloud. >> I think that's really right on. I think Supercloud at the end of the day, for me from the simplest way to describe it is making sure that the developer experience is so good that the operations just happen. And Marianna Tessel said, she's investing in making their developer experience high velocity, very easy. So if you do that, you have to run on premise and on the cloud. So hybrid really is where Supercloud is going right now. It's not multi-cloud. Multi-cloud was- that was debunked on this session today. I thought that was clear. >> Yeah. Yeah, I mean I think- >> It's not about multi-cloud. It's about operationally seamless operations across environments, public cloud to on-premise, basically. >> I think we got consensus across the board that multi-cloud, you know, is a symptom Chuck Whitten's thing of multi-cloud by default versus multi- multi-cloud has not been a strategy, Kit Colbert said, up until the last couple of years. Yeah, because people said, "oh we got all these multiple clouds, what do we do with it?" and we got this mess that we have to solve. Whereas, I think Supercloud is something that is a strategy and then the other nuance that I keep bringing up is it's industries that are- as part of their digital transformation, are building clouds. Now, whether or not they become superclouds, I'm not convinced. I mean, what Goldman Sachs is doing, you know, with AWS, what Walmart's doing with Azure connecting their on-prem tools to those public clouds, you know, is that a supercloud? I mean, we're going to have to go back and really look at that definition. Or is it just kind of a SAS that spans on-prem and cloud. So, as I said, the further you go up the stack, the business case seems to wane a little bit but there's no question in my mind that from an infrastructure standpoint, to your point about operations, there's a real requirement for super- what we call Supercloud. >> Well, we're going to keep the conversation going, Dave. I want to put a shout out to our founding supporters of this initiative. Again, we put this together really fast kind of like a pilot series, an inaugural event. We want to have a face-to-face event as an industry event. Want to thank the founding supporters. These are the people who donated their time, their resource to contribute content, ideas and some cash, not everyone has committed some financial contribution but we want to recognize the names here. VMware, Intuit, Red Hat, Snowflake, Aisera, Alteryx, Confluent, Couchbase, Nutanix, Rafay Systems, Skyhigh Security, Aviatrix, Zscaler, Platform9, HashiCorp, F5 and all the media partners. Without their support, this wouldn't have happened. And there are more people that wanted to weigh in. There was more demand than we could pull off. We'll certainly continue the Supercloud conversation series here on "theCUBE" and we'll add more people in. And now, after this session, the Ecosystem Speaks session, we're going to run all the videos of the big name companies. We have the Nutanix CEOs weighing in, Aviatrix to name a few. >> Yeah. Let me, let me chime in, I mean you got Couchbase talking about Edge, Platform 9's going to be on, you know, everybody, you know Insig was poopoo-ing Oracle, but you know, Oracle and Azure, what they did, two technical guys, developers are coming on, we dig into what they did. Howie Xu from Zscaler, Paula Hansen is going to talk about going to market in the multi-cloud world. You mentioned Rajiv, the CEO of Nutanix, Ramesh is going to talk about multi-cloud infrastructure. So that's going to run now for, you know, quite some time here and some of the pre-record so super excited about that and I just want to thank the crew. I hope guys, I hope you have a list of credits there's too many of you to mention, but you know, awesome jobs really appreciate the work that you did in a very short amount of time. >> Well, I'm excited. I learned a lot and my takeaway was that Supercloud's a thing, there's a kind of sense that people want to talk about it and have real conversations, not BS or FUD. They want to have real substantive conversations and we're going to enable that on "theCUBE". Dave, final thoughts for you. >> Well, I mean, as I say, we put this together very quickly. It was really a phenomenal, you know, enlightening experience. I think it confirmed a lot of the concepts and the premises that we've put forth, that David Floyer helped evolve, that a lot of these analysts have helped evolve, that even Charles Fitzgerald with his antagonism helped to really sharpen our knives. So, you know, thank you Charles. And- >> I like his blog, by the I'm a reader- >> Yeah, absolutely. And it was great to be back in Palo Alto. It was my first time back since pre-COVID, so, you know, great job. >> All right. I want to thank all the crew and everyone. Thanks for watching this first, inaugural Supercloud event. We are definitely going to be doing more of these. So stay tuned, maybe face-to-face in person. I'm John Furrier with Dave Vellante now for the Ecosystem chiming in, and they're going to speak and share their thoughts here with "theCUBE" our first live stage performance event in our studio. Thanks for watching. (gentle upbeat music)

>> Announcer: From the Cube studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCube Conversation. >> Hi, I'm Stu Miniman. And welcome to this special presentation. We have a launch from Dell Technologies updates from the VxRail family. We're going to do things a little bit different here. We actually have a launch video Shannon Champion, of Dell Technologies. And the way we do things a lot of times, is, analysts get a little preview or when you're watching things. You might have questions on it. So, rather than me just wanting it, or you wanting yourself I actually brought in a couple of Dell Technologies expertS two of our Cube alumni, happy to welcome you back to the program. Jon Siegal, he is the Vice President of Product Marketing, and Chad Dunn, who's the Vice President of Product Management, both of them with Dell Technologies. Gentlemen, thanks so much for joining us. >> Good to see you Stu. >> Great to be here. >> All right, and so what we're going to do is we're going to be rolling the video here. I've got a button I'm going to press, Andrew will stop it here and then we'll kind of dig in a little bit, go into some questions when we're all done. We're actually holding a crowd chat, where you will be able to ask your questions, talk to the experts and everything. And so a little bit different way to do a product announcement. Hope you enjoy it. And with that, it's VxRail. Taking HCI to the extremes is the theme. We'll see what that means and everything. But without any further ado, let's let Shannon take the video away. >> Hello, and welcome. My name is Shannon Champion, and I'm looking forward to taking you through what's new with VxRail. Let's get started. We have a lot to talk about. Our launch covers new announcements addressing use cases across the Core, Edge and Cloud and spans both new hardware platforms and options, as well as the latest in software innovations. So let's jump right in. Before we talk about our announcements, let's talk about where customers are adopting VxRail today. First of all, on behalf of the entire Dell Technologies and VxRail teams, I want to thank each of our over 8000 customers, big and small in virtually every industry, who've chosen VxRail to address a broad range of workloads, deploying nearly 100,000 nodes today. Thank you. Our promise to you is that we will add new functionality, improve serviceability, and support new use cases, so that we deliver the most value to you, whether in the Core, at the Edge or for the Cloud. In the Core, VxRail from day one has been a catalyst to accelerate IT transformation. Many of our customers started here and many will continue to leverage VxRail to simply extend and enhance your VMware environment. Now we can support even more demanding applications such as In-Memory databases, like SAP HANA, and more AI and ML applications, with support for more and more powerful GPUs. At the Edge, video surveillance, which also uses GPUs, by the way, is an example of a popular use case leveraging VxRail alongside external storage. And right now we all know the enhanced role that IT is playing. And as it relates to VDI, VxRail has always been a great option for that. In the Cloud, it's all about Kubernetes, and how Dell Technologies Cloud platform, which is VCF on VxRail can deliver consistent infrastructure for both traditional and Cloud native applications. And we're doing that together with VMware. VxRail is the only jointly engineered HCI system built with VMware for VMware environments, designed to enhance the native VMware experience. This joint engineering with VMware and investments in software innovation together deliver an optimized operational experience at reduced risk for our customers. >> Alright, so Shannon talked a bit about, the important role of IT Of course right now, with the global pandemic going on. It's really, calling in, essential things, putting, platforms to the test. So, I really love to hear what both of you are hearing from customers. Also, VDI, of course, in the early days, it was, HCI-only-does-VDI. Now, we know there are many solutions, but remote work is putting that back front and center. So, Jon, why don't we start with you as the what is (muffled speaking) >> Absolutely. So first of all, Stu, thank you, I want to do a shout out to our VxRail customers around the world. It's really been humbling, inspiring, and just amazing to see The impact of our VxRail customers around the world and what they're having on on human progress here. Just for a few examples, there are genomics companies that we have running VxRail that have rolled out testing at scale. We also have research universities out in the Netherlands, doing the antibody detection. The US Navy has stood up a floating hospital to of course care for those in need. So we are here to help that's been our message to our customers, but it's amazing to see how much they're helping society during this. So just just a pleasure there. But as you mentioned, just to hit on the VDI comments, so to your points too, HCI, VxRail, VDI, that was an initial use case years ago. And it's been great to see how many of our existing VxRail customers have been able to pivot very quickly leveraging VxRail to add and to help bring their remote workforce online and support them with their existing VxRail. Because VxRail is flexible, it is agile, to be able to support those multiple workloads. And in addition to that, we've also rolled out some new VDI bundles to make it simpler for customers more cost effective cater to everything from knowlEdge workers to multimedia workers. You name it, you know from 250, desktops up to 1000. But again, back to your point VxRail, HCI, is well beyond VDI, it crossed the chasm a couple years ago actually. And VDI now is less than a third of the typical workloads, any of our customers out there, it supports now a range of workloads that you heard from Shannon, whether it's video surveillance, whether it's general purpose, all the way to mission critical applications now with SAP HAN. So, this has changed the game for sure. But the range of work loads and the flexibility of the actual rules which really helping our existing customers during this pandemic. >> Yeah, I agree with you, Jon, we've seen customers really embrace HCI for a number of workloads in their environments, from the ones that we sure all knew and loved back in the initial days of HCI. Now, the mission critical things now to Cloud native workloads as well, and the sort of the efficiencies that customers are able to get from HCI. And specifically, VxRail gives them that ability to pivot. When these, shall we say unexpected circumstances arise? And I think that that's informing their their decisions and their opinions on what their IP strategies look like as they move forward. They want that same level of agility, and ability to react quickly with their overall infrastructure. >> Excellent. Now I want to get into the announcements. What I want my team actually, your team gave me access to the CIO from the city of Amarillo, so maybe they can dig up that footage, talk about how fast they pivoted, using VxRail to really spin up things fast. So let's hear from the announcement first and then definitely want to share that that customer story a little bit later. So let's get to the actual news that Shannon's going to share. >> Okay, now what's new? I am pleased to announce a number of exciting updates and new platforms, to further enable IT modernization across Core, Edge and Cloud. I will cover each of these announcements in more detail, demonstrating how only VxRail can offer the breadth of platform configurations, automation, orchestration and Lifecycle Management, across a fully integrated hardware and software full stack with consistent, simplified operations to address the broadest range of traditional and modern applications. I'll start with hybrid Cloud and recap what you may have seen in the Dell Technologies Cloud announcements just a few weeks ago, related to VMware Cloud foundation on VxRail. Then I'll cover two brand new VxRail hardware platforms and additional options. And finally circle back to talk about the latest enhancements to our VxRail HCI system software capabilities for Lifecycle Management. Let's get started with our new Cloud offerings based on VxRail. VxRail is the HCI foundation for Dell Technologies, Cloud Platform, bringing automation and financial models, similar to public Cloud to On-premises environments. VMware recently introduced Cloud foundation for Delta, which is based on vSphere 7.0. As you likely know by now, vSphere 7.0 was definitely an exciting and highly anticipated release. In keeping with our synchronous release commitment, we introduced VxRail 7.0 based on vSphere 7.0 in late April, which was within 30 days of VMware's release. Two key areas that VMware focused on we're embedding containers and Kubernetes into vSphere, unifying them with virtual machines. And the second is improving the work experience for vSphere administrators with vSphere Lifecycle Manager or VLCM. I'll address the second point a bit in terms of how VxRail fits in in a moment for VCF 4 with Tom Xu, based on vSphere 7.0 customers now have access to a hybrid Cloud platform that supports native Kubernetes workloads and management, as well as your traditional VM-based workloads. So containers are now first class citizens of your private Cloud alongside traditional VMs and this is now available with VCF 4.0, on VxRail 7.0. VxRail's tight integration with VMware Cloud foundation delivers a simple and direct path not only to the hybrid Cloud, but also to deliver Kubernetes at Cloud scale with one complete automated platform. The second Cloud announcement is also exciting. Recent VCF for networking advancements have made it easier than ever to get started with hybrid Cloud, because we're now able to offer a more accessible consolidated architecture. And with that Dell Technologies Cloud platform can now be deployed with a four-node configuration, lowering the cost of an entry level hybrid Cloud. This enables customers to start smaller and grow their Cloud deployment over time. VCF and VxRail can now be deployed in two different ways. For small environments, customers can utilize a consolidated architecture which starts with just four nodes. Since the management and workload domains share resources in this architecture, it's ideal for getting started with an entry level Cloud to run general purpose virtualized workloads with a smaller entry point. Both in terms of required infrastructure footprint as well as cost, but still with a Consistent Cloud operating model. For larger environments where dedicated resources and role-based access control to separate different sets of workloads is usually preferred. You can choose to deploy a standard architecture which starts at eight nodes for independent management and workload domains. A standard implementation is ideal for customers running applications that require dedicated workload domains that includes Horizon, VDI, and vSphere with Kubernetes. >> Alright, Jon, there's definitely been a lot of interest in our community around everything that VMware is doing with vSphere 7.0. understand if you wanted to use the Kubernetes piece, it's VCF as that so we've seen the announcements, Dell, partnering in there it helps us connect that story between, really the VMware strategy and how they talk about Cloud and where does VxRail fit in that overall, Delta Cloud story? >> Absolutely. So first of all Stu, the VxRail course is integral to the Delta Cloud strategy. it's been VCF on VxRail equals the Delta Cloud platform. And this is our flagship on prem Cloud offering, that we've been able to enable operational consistency across any Cloud, whether it's On-prem, in the Edge or in the public Cloud. And we've seen the Dell tech Cloud Platform embraced by customers for a couple key reasons. One is it offers the fastest hybrid Cloud deployment in the market. And this is really, thanks to a new subscription offer that we're now offering out there where in less than 14 days, it can be still up and running. And really, the Dell tech Cloud does bring a lot of flexibility in terms of consumption models, overall when it comes to VxRail. Secondly, I would say is fast and easy upgrades. This is what VxRail brings to the table for all workloads, if you will, into especially critical in the Cloud. So the full automation of Lifecycle Management across the hardware and software stack across the VMware software stack, and in the Dell software and hardware supporting that, together, this enables essentially the third thing, which is customers can just relax. They can be rest assured that their infrastructure will be continuously validated, and always be in a continuously validated state. And this is the kind of thing that those three value propositions together really fit well, with any on-prem Cloud. Now you take what Shannon just mentioned, and the fact that now you can build and run modern applications on the same VxRail infrastructure alongside traditional applications. This is a game changer. >> Yeah, I love it. I remember in the early days talking with Dunn about CI, how does that fit in with Cloud discussion and the line I've used the last couple years is, modernize the platform, then you can modernize the application. So as companies are doing their full modernization, then this plays into what you're talking about. All right, we can let Shannon continue, we can get some more before we dig into some more analysis. >> That's good. >> Let's talk about new hardware platforms and updates. that result in literally thousands of potential new configuration options. covering a wide breadth of modern and traditional application needs across a range of the actual use cases. First up, I am incredibly excited to announce a brand new Dell EMC VxRail series, the D series. This is a ruggedized durable platform that delivers the full power of VxRail for workloads at the Edge in challenging environments or for space constrained areas. VxRail D series offers the same compelling benefits as the rest of the VxRail portfolio with simplicity, agility and lifecycle management. But in a lightweight short depth at only 20 inches, it's adorable form factor that's extremely temperature-resilient, shock resistant, and easily portable. It even meets milspec standards. That means you have the full power of lifecycle automation with VxRail HCI system software and 24 by seven single point of support, enabling you to rapidly react to business needs, no matter the location or how harsh the conditions. So whether you're deploying a data center at a mobile command base, running real-time GPS mapping on the go, or implementing video surveillance in remote areas, you can ensure availability, integrity and confidence for every workload with the new VxRail ruggedized D series. >> All right, Chad we would love for you to bring us in a little bit that what customer requirement for bringing this to market. I remember seeing, Dell servers ruggedized, of course, Edge, really important growth to build on what Jon was talking about, Cloud. So, Chad, bring us inside, what was driving this piece of the offering? >> Sure Stu. Yeah, yeah, having been at the hardware platforms that can go out into some of these remote locations is really important. And that's being driven by the fact that customers are looking for compute performance and storage out at some of these Edges or some of the more exotic locations. whether that's manufacturing plants, oil rigs, submarine ships, military applications, places that we've never heard of. But it's also about extending that operational simplicity of the the sort of way that you're managing your data center that has VxRails you're managing your Edges the same way using the same set of tools. You don't need to learn anything else. So operational simplicity is absolutely key here. But in those locations, you can take a product that's designed for a data center where definitely controlling power cooling space and take it some of these places where you get sand blowing or seven to zero temperatures, could be Baghdad or it could be Ketchikan, Alaska. So we built this D series that was able to go to those extreme locations with extreme heat, extreme cold, extreme altitude, but still offer that operational simplicity. Now military is one of those applications for the rugged platform. If you look at the resistance that it has to heat, it operates at a 45 degrees Celsius or 113 degrees Fahrenheit range, but it can do an excursion up to 55 C or 131 degrees Fahrenheit for up to eight hours. It's also resistant to heat sand, dust, vibration, it's very lightweight, short depth, in fact, it's only 20 inches deep. This is a smallest form factor, obviously that we have in the VxRail family. And it's also built to be able to withstand sudden shocks certified to withstand 40 G's of shock and operation of the 15,000 feet of elevation. Pretty high. And this is sort of like wherever skydivers go to when they want the real thrill of skydiving where you actually need oxygen to, to be for that that altitude. They're milspec-certified. So, MIL-STD-810G, which I keep right beside my bed and read every night. And it comes with a VxRail stick hardening package is packaging scripts so that you can auto lock down the rail environment. And we've got a few other certifications that are on the roadmap now for naval shock requirements. EMI and radiation immunity often. >> Yeah, it's funny, I remember when we first launched it was like, "Oh, well everything's going to white boxes. "And it's going to be massive, "no differentiation between everything out there." If you look at what you're offering, if you look at how public Clouds build their things, but I called it a few years or is there's a pure optimization. So you need to scale, you need similarities but you know you need to fit some, very specific requirements, lots of places, so, interesting stuff. Yeah, certifications, always keep your teams busy. Alright, let's get back to Shannon to view on the report. >> We are also introducing three other hardware-based additions. First, a new VxRail E Series model based on where the first time AMD EPYC processors. These single socket 1U nodes, offer dual socket performance with CPU options that scale from eight to 64 Cores, up to a terabyte of memory and multiple storage options making it an ideal platform for desktop VDI analytics and computer aided design. Next, the addition of the latest Nvidia Quadro RTX GPUs brings the most significant advancement in computer graphics in over a decade to professional work flows. Designers and artists across industries can now expand the boundary of what's possible, working with the largest and most complex graphics rendering, deep learning and visual computing workloads. And Intel Optane DC persistent memory is here, and it offers high performance and significantly increased memory capacity with data persistence at an affordable price. Data persistence is a critical feature that maintains data integrity, even when power is lost, enabling quicker recovery and less downtime. With support for Intel obtain DC persistent memory customers can expand in memory intensive workloads and use cases like SAP HANA. Alright, let's finally dig into our HCI system software, which is the Core differentiation for VxRail regardless of your workload or platform choice. Our joining engineering with VMware and investments in VxRail HCI system software innovation together deliver an optimized operational experience at reduced risk for our customers. Under the covers, VxRail offers best in class hardware, married with VMware HCI software, either vSAN or VCF. But what makes us different stems from our investments to integrate the two. Dell Technologies has a dedicated VxRail team of about 400 people to build market sell and support a fully integrated hyper converged system. That team has also developed our unique VxRail HCI system software, which is a suite of integrated software elements that extend VMware native capabilities to deliver seamless, automated operational experience that customers cannot find elsewhere. The key components of VxRail HCI system software shown around the arc here that include the extra manager, full stack lifecycle management, ecosystem connectors, and support. I don't have time to get into all the details of these elements today, but if you're interested in learning more, I encourage you to meet our experts. And I will tell you how to do that in a moment. I touched on the LCM being a key feature to the vSphere 7.0 earlier and I'd like to take the opportunity to expand on that a bit in the context of VxRail Lifecycle Management. The LCM adds valuable automation to the execution of updates for customers, but it doesn't eliminate the manual work still needed to define and package the updates and validate all of the components prior to applying them. With VxRail customers have all of these areas addressed automatically on their behalf, freeing them to put their time into other important functions for their business. Customers tell us that Lifecycle management continues to be a major source of the maintenance effort they put into their infrastructure, and then it tends to lead to overburden IT staff, that it can cause disruptions to the business if not managed effectively, and that it isn't the most efficient economically. Automation of Lifecycle Management and VxRail results in the utmost simplicity from a customer experience perspective, and offers operational freedom from maintaining infrastructure. But as shown here, our customers not only realize greater IT team efficiencies, they have also reduced downtime with fewer unplanned outages, and reduced overall cost of operations. With VxRail HCI system software, intelligent Lifecycle Management upgrades of the fully integrated hardware and software stack are automated, keeping clusters and continuously validated states while minimizing risks and operational costs. How do we ensure Continuously validated states for VxRail. VxRail labs execute an extensive, automated, repeatable process on every firmware and software upgrade and patch to ensure clusters are in continuously validated states of the customers choosing across their VxRail environment. The VxRail labs are constantly testing, analyzing, optimizing, and sequencing all of the components in the upgrade to execute in a single package for the full stack. All the while VxRail is backed by Dell EMC's world class services and support with a single point of contact for both hardware and software. IT productivity skyrockets with single click non disruptive upgrades of the fully integrated hardware and software stack without the need to do extensive research and testing. taking you to the next VxRail version of your choice, while always in a continuously validated state. You can also confidently execute automated VxRail upgrades. No matter what hardware generation or node types are in the cluster. They don't have to all be the same. And upgrades with VxRail are faster and more efficient with leapfrogging simply choose any VxRail version you desire. And be assured you will get there in a validated state while seamlessly bypassing any other release in between. Only VxRail can do that. >> All right, so Chad, the lifecycle management piece that Shannon was just talking about is, not the sexiest, it's often underappreciated. There's not only the years of experience, but the continuous work you're doing, reminds me back the early vSAN deployments versus VxRail jointly developed, jointly tested between Dell and VMware. So bring us inside why, 2020 Lifecycle Management still, a very important piece, especially in the VM family line. >> Yes, Stu, I think it's sexy, but, I'm pretty big nerd. (all laughing) Yeah, this is really always been our bread and butter. And in fact, it gets even more important, the larger the deployments come, when you start to look at data centers full of VxRails and all the different hardware software, firmware combinations that could exist out there. It's really the value that you get out of that VxRail HCI system software that Shannon was talking about and how it's optimized around the VMware use case. Very tightly integrated with each VMware component, of course, and the intelligence of being able to do all the firmware, all of the drivers, all the software all together in tremendous value to our customers. But to deliver that we really need to make a fairly large investment. So as Shannon mentioned, we run about 25,000 hours of testing across Each major release for patches, express patches, that's about 7000 hours for each of those. So, obviously, there's a lot of parallelism. And we're always developing new test scenarios for each release that we need to build in as we as we introduce new functionality. And one of the key things that we're able to do, as Shannon mentioned, is to be able to leapfrog releases and get you to that next validated state. We've got about 100 engineers just working on creating and executing those test cases on a continuous basis and obviously, a huge amount of automation. And we've talked about that investment to execute those tests. That's one worth of $60 million of investment in our lab. In fact, we've got just over 2000 VxRail units in our testbed across the US, Shanghai, China and Cork, Ireland. So a massive amount of testing of each of those components to make sure that they operate together in a validated state. >> Yeah, well, absolutely, it's super important not only for the day one, but the day two deployments. But I think this actually a great place for us to bring in that customer that Dell gave me access to. So we've got the CIO of Amarillo, Texas, he was an existing VxRail customer. And he's going to explain what happened as to how he needed to react really fast to support the work-from-home initiative, as well as we get to hear in his words the value of what Lifecycle Management means. So Andrew, if we could queue up that customer segment, please? >> It's been massive and it's been interesting to see the IT team absorb it. As we mature, I think they embrace the ability to be innovative and to work with our departments. But this instance, really justified why I was driving progress. So fervently why it was so urgent today. Three years ago, the answer would have been no. We wouldn't have been in a place where we could adapt With VxRail in place, in a week we spun up hundreds of instant balls. We spun up a 75-person call center in a day and a half, for our public health. We rolled out multiple applications for public health so they could do remote clinics. It's given us the flexibility to be able to roll out new solutions very quickly and be very adaptive. And it's not only been apparent to my team, but it's really made an impact on the business. And now what I'm seeing is those of my customers that work, a little lagging or a little conservative, or understanding the impact of modernizing the way they do business because it makes them adaptable as well. >> Alright, so great, Richard, you talked a bunch about the the efficiencies that that the IT put in place, how about that, that overall just managed, you talked about how fast you spun up these new VDI instances. need to be able to do things much simpler? So how does the overall Lifecycle Management fit into this discussion? >> It makes it so much easier. And in the old environment, one, It took a lot of man hours to make change. It was very disruptive, when we did make change, it overburdened, I guess that's the word I'm looking for. It really overburdened our staff to cause disruption to business. That wasn't cost efficient. And then simple things like, I've worked for multi billion dollar companies where we had massive QA environments that replicated production, simply can't afford that at local government. Having this sort of environment lets me do a scaled down QA environment and still get the benefit of rolling out non disruptive change. As I said earlier, it's allowed us to take all of those cycles that we were spending on Lifecycle Management because it's greatly simplified, and move those resources and rescale them in other areas where we can actually have more impact on the business. It's hard to be innovative when 100% of your cycles are just keeping the ship afloat. >> All right, well, nothing better than hearing it straight from the end user, public sector reacting very fast to the COVID-19. And, if you heard him he said, if this is his, before he had run this project, he would not have been able to respond. So I think everybody out there understands, if I didn't actually have access to the latest technology, it would be much harder. All right, I'm looking forward to doing the CrowdChat letting everybody else dig in with questions and get follow up but a little bit more, I believe one more announcement he can and got for us though. Let's roll the final video clip. >> In our latest software release VxRail 4.7.510, We continue to add new automation and self service features. New functionality enables you to schedule and run upgrade health checks in advance of upgrades, to ensure clusters are in a ready state for the next upgrade or patch. This is extremely valuable for customers that have stringent upgrade windows, as they can be assured the clusters will seamlessly upgrade within that window. Of course, running health checks on a regular basis also helps ensure that your clusters are always ready for unscheduled patches and security updates. We are also offering more flexibility and getting all nodes or clusters to a common release level with the ability to reimage nodes or clusters to a specific VxRail version, or down rev one or more nodes that may be shipped at a higher rate than the existing cluster. This enables you to easily choose your validated state when adding new nodes or repurposing nodes in a cluster. To sum up all of our announcements, whether you are accelerating data sets modernization extending HCI to harsh Edge environments, deploying an on-premises Dell Technologies Cloud platform to create a developer ready Kubernetes infrastructure. VxRail is there delivering a turn-key experience that enables you to continuously innovate, realize operational freedom and predictably evolve. VxRail provides an extensive breadth of platform configurations, automation and Lifecycle Management across the integrated hardware and software full stack and consistent hybrid Cloud operations to address the broadest range of traditional and modern applications across Core, Edge and Cloud. I now invite you to engage with us. First, the virtual passport program is an opportunity to have some fun while learning about VxRail new features and functionality and sCore some sweet digital swag while you're at it. Delivered via an augmented reality app. All you need is your device. So go to vxrail.is/passport to get started. And secondly, if you have any questions about anything I talked about or want a deeper conversation, we encourage you to join one of our exclusive VxRail Meet The Experts sessions available for a limited time. First come first served, just go to vxrail.is/expertsession to learn more. >> All right, well, obviously, with everyone being remote, there's different ways we're looking to engage. So we've got the CrowdChat right after this. But Jon, give us a little bit more as to how Dell's making sure to stay in close contact with customers and what you've got for options for them. >> Yeah, absolutely. So as Shannon said, so in lieu of not having done Tech World this year in person, where we could have those great in-person interactions and answer questions, whether it's in the booth or in meeting rooms, we are going to have these Meet The Experts sessions over the next couple weeks, and we're going to put our best and brightest from our technical community and make them accessible to everyone out there. So again, definitely encourage you. We're trying new things here in this virtual environment to ensure that we can still stay in touch, answer questions, be responsive, and really looking forward to, having these conversations over the next couple of weeks. >> All right, well, Jon and Chad, thank you so much. We definitely look forward to the conversation here and continued. If you're here live, definitely go down below and do it if you're watching this on demand. You can see the full transcript of it at crowdchat.net/vxrailrocks. For myself, Shannon on the video, Jon, Chad, Andrew, man in the booth there, thank you so much for watching, and go ahead and join the CrowdChat.

>> Announcer: From the Cube studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCube Conversation. >> Hi, I'm Stu Miniman. And welcome to this special presentation. We have a launch from Dell Technologies updates from the VxRail family. We're going to do things a little bit different here. We actually have a launch video Shannon Champion, of Dell Technologies. And the way we do things a lot of times, is, analysts get a little preview or when you're watching things. You might have questions on it. So, rather than me just wanting it, or you wanting yourself I actually brought in a couple of Dell Technologies expertS two of our Cube alumni, happy to welcome you back to the program. Jon Siegal, he is the Vice President of Product Marketing, and Chad Dunn, who's the Vice President of Product Management, both of them with Dell Technologies. Gentlemen, thanks so much for joining us. >> Good to see you Stu. >> Great to be here. >> All right, and so what we're going to do is we're going to be rolling the video here. I've got a button I'm going to press, Andrew will stop it here and then we'll kind of dig in a little bit, go into some questions when we're all done. We're actually holding a crowd chat, where you will be able to ask your questions, talk to the experts and everything. And so a little bit different way to do a product announcement. Hope you enjoy it. And with that, it's VxRail. Taking HCI to the extremes is the theme. We'll see what that means and everything. But without any further ado, let's let Shannon take the video away. >> Hello, and welcome. My name is Shannon Champion, and I'm looking forward to taking you through what's new with VxRail. Let's get started. We have a lot to talk about. Our launch covers new announcements addressing use cases across the Core, Edge and Cloud and spans both new hardware platforms and options, as well as the latest in software innovations. So let's jump right in. Before we talk about our announcements, let's talk about where customers are adopting VxRail today. First of all, on behalf of the entire Dell Technologies and VxRail teams, I want to thank each of our over 8000 customers, big and small in virtually every industry, who've chosen VxRail to address a broad range of workloads, deploying nearly 100,000 nodes today. Thank you. Our promise to you is that we will add new functionality, improve serviceability, and support new use cases, so that we deliver the most value to you, whether in the Core, at the Edge or for the Cloud. In the Core, VxRail from day one has been a catalyst to accelerate IT transformation. Many of our customers started here and many will continue to leverage VxRail to simply extend and enhance your VMware environment. Now we can support even more demanding applications such as In-Memory databases, like SAP HANA, and more AI and ML applications, with support for more and more powerful GPUs. At the Edge, video surveillance, which also uses GPUs, by the way, is an example of a popular use case leveraging VxRail alongside external storage. And right now we all know the enhanced role that IT is playing. And as it relates to VDI, VxRail has always been a great option for that. In the Cloud, it's all about Kubernetes, and how Dell Technologies Cloud platform, which is VCF on VxRail can deliver consistent infrastructure for both traditional and Cloud native applications. And we're doing that together with VMware. VxRail is the only jointly engineered HCI system built with VMware for VMware environments, designed to enhance the native VMware experience. This joint engineering with VMware and investments in software innovation together deliver an optimized operational experience at reduced risk for our customers. >> Alright, so Shannon talked a bit about, the important role of IT Of course right now, with the global pandemic going on. It's really, calling in, essential things, putting, platforms to the test. So, I really love to hear what both of you are hearing from customers. Also, VDI, of course, in the early days, it was, HCI-only-does-VDI. Now, we know there are many solutions, but remote work is putting that back front and center. So, Jon, why don't we start with you as the what is (muffled speaking) >> Absolutely. So first of all, Stu, thank you, I want to do a shout out to our VxRail customers around the world. It's really been humbling, inspiring, and just amazing to see The impact of our VxRail customers around the world and what they're having on on human progress here. Just for a few examples, there are genomics companies that we have running VxRail that have rolled out testing at scale. We also have research universities out in the Netherlands, doing the antibody detection. The US Navy has stood up a floating hospital to of course care for those in need. So we are here to help that's been our message to our customers, but it's amazing to see how much they're helping society during this. So just just a pleasure there. But as you mentioned, just to hit on the VDI comments, so to your points too, HCI, VxRail, VDI, that was an initial use case years ago. And it's been great to see how many of our existing VxRail customers have been able to pivot very quickly leveraging VxRail to add and to help bring their remote workforce online and support them with their existing VxRail. Because VxRail is flexible, it is agile, to be able to support those multiple workloads. And in addition to that, we've also rolled out some new VDI bundles to make it simpler for customers more cost effective cater to everything from knowlEdge workers to multimedia workers. You name it, you know from 250, desktops up to 1000. But again, back to your point VxRail, HCI, is well beyond VDI, it crossed the chasm a couple years ago actually. And VDI now is less than a third of the typical workloads, any of our customers out there, it supports now a range of workloads that you heard from Shannon, whether it's video surveillance, whether it's general purpose, all the way to mission critical applications now with SAP HAN. So, this has changed the game for sure. But the range of work loads and the flexibility of the actual rules which really helping our existing customers during this pandemic. >> Yeah, I agree with you, Jon, we've seen customers really embrace HCI for a number of workloads in their environments, from the ones that we sure all knew and loved back in the initial days of HCI. Now, the mission critical things now to Cloud native workloads as well, and the sort of the efficiencies that customers are able to get from HCI. And specifically, VxRail gives them that ability to pivot. When these, shall we say unexpected circumstances arise? And I think that that's informing their their decisions and their opinions on what their IP strategies look like as they move forward. They want that same level of agility, and ability to react quickly with their overall infrastructure. >> Excellent. Now I want to get into the announcements. What I want my team actually, your team gave me access to the CIO from the city of Amarillo, so maybe they can dig up that footage, talk about how fast they pivoted, using VxRail to really spin up things fast. So let's hear from the announcement first and then definitely want to share that that customer story a little bit later. So let's get to the actual news that Shannon's going to share. >> Okay, now what's new? I am pleased to announce a number of exciting updates and new platforms, to further enable IT modernization across Core, Edge and Cloud. I will cover each of these announcements in more detail, demonstrating how only VxRail can offer the breadth of platform configurations, automation, orchestration and Lifecycle Management, across a fully integrated hardware and software full stack with consistent, simplified operations to address the broadest range of traditional and modern applications. I'll start with hybrid Cloud and recap what you may have seen in the Dell Technologies Cloud announcements just a few weeks ago, related to VMware Cloud foundation on VxRail. Then I'll cover two brand new VxRail hardware platforms and additional options. And finally circle back to talk about the latest enhancements to our VxRail HCI system software capabilities for Lifecycle Management. Let's get started with our new Cloud offerings based on VxRail. VxRail is the HCI foundation for Dell Technologies, Cloud Platform, bringing automation and financial models, similar to public Cloud to On-premises environments. VMware recently introduced Cloud foundation for Delta, which is based on vSphere 7.0. As you likely know by now, vSphere 7.0 was definitely an exciting and highly anticipated release. In keeping with our synchronous release commitment, we introduced VxRail 7.0 based on vSphere 7.0 in late April, which was within 30 days of VMware's release. Two key areas that VMware focused on we're embedding containers and Kubernetes into vSphere, unifying them with virtual machines. And the second is improving the work experience for vSphere administrators with vSphere Lifecycle Manager or VLCM. I'll address the second point a bit in terms of how VxRail fits in in a moment for VCF 4 with Tom Xu, based on vSphere 7.0 customers now have access to a hybrid Cloud platform that supports native Kubernetes workloads and management, as well as your traditional VM-based workloads. So containers are now first class citizens of your private Cloud alongside traditional VMs and this is now available with VCF 4.0, on VxRail 7.0. VxRail's tight integration with VMware Cloud foundation delivers a simple and direct path not only to the hybrid Cloud, but also to deliver Kubernetes at Cloud scale with one complete automated platform. The second Cloud announcement is also exciting. Recent VCF for networking advancements have made it easier than ever to get started with hybrid Cloud, because we're now able to offer a more accessible consolidated architecture. And with that Dell Technologies Cloud platform can now be deployed with a four-node configuration, lowering the cost of an entry level hybrid Cloud. This enables customers to start smaller and grow their Cloud deployment over time. VCF and VxRail can now be deployed in two different ways. For small environments, customers can utilize a consolidated architecture which starts with just four nodes. Since the management and workload domains share resources in this architecture, it's ideal for getting started with an entry level Cloud to run general purpose virtualized workloads with a smaller entry point. Both in terms of required infrastructure footprint as well as cost, but still with a Consistent Cloud operating model. For larger environments where dedicated resources and role-based access control to separate different sets of workloads is usually preferred. You can choose to deploy a standard architecture which starts at eight nodes for independent management and workload domains. A standard implementation is ideal for customers running applications that require dedicated workload domains that includes Horizon, VDI, and vSphere with Kubernetes. >> Alright, Jon, there's definitely been a lot of interest in our community around everything that VMware is doing with vSphere 7.0. understand if you wanted to use the Kubernetes piece, it's VCF as that so we've seen the announcements, Dell, partnering in there it helps us connect that story between, really the VMware strategy and how they talk about Cloud and where does VxRail fit in that overall, Delta Cloud story? >> Absolutely. So first of all Stu, the VxRail course is integral to the Delta Cloud strategy. it's been VCF on VxRail equals the Delta Cloud platform. And this is our flagship on prem Cloud offering, that we've been able to enable operational consistency across any Cloud, whether it's On-prem, in the Edge or in the public Cloud. And we've seen the Dell tech Cloud Platform embraced by customers for a couple key reasons. One is it offers the fastest hybrid Cloud deployment in the market. And this is really, thanks to a new subscription offer that we're now offering out there where in less than 14 days, it can be still up and running. And really, the Dell tech Cloud does bring a lot of flexibility in terms of consumption models, overall when it comes to VxRail. Secondly, I would say is fast and easy upgrades. This is what VxRail brings to the table for all workloads, if you will, into especially critical in the Cloud. So the full automation of Lifecycle Management across the hardware and software stack across the VMware software stack, and in the Dell software and hardware supporting that, together, this enables essentially the third thing, which is customers can just relax. They can be rest assured that their infrastructure will be continuously validated, and always be in a continuously validated state. And this is the kind of thing that those three value propositions together really fit well, with any on-prem Cloud. Now you take what Shannon just mentioned, and the fact that now you can build and run modern applications on the same VxRail infrastructure alongside traditional applications. This is a game changer. >> Yeah, I love it. I remember in the early days talking with Dunn about CI, how does that fit in with Cloud discussion and the line I've used the last couple years is, modernize the platform, then you can modernize the application. So as companies are doing their full modernization, then this plays into what you're talking about. All right, we can let Shannon continue, we can get some more before we dig into some more analysis. >> That's good. >> Let's talk about new hardware platforms and updates. that result in literally thousands of potential new configuration options. covering a wide breadth of modern and traditional application needs across a range of the actual use cases. First up, I am incredibly excited to announce a brand new Dell EMC VxRail series, the D series. This is a ruggedized durable platform that delivers the full power of VxRail for workloads at the Edge in challenging environments or for space constrained areas. VxRail D series offers the same compelling benefits as the rest of the VxRail portfolio with simplicity, agility and lifecycle management. But in a lightweight short depth at only 20 inches, it's adorable form factor that's extremely temperature-resilient, shock resistant, and easily portable. It even meets milspec standards. That means you have the full power of lifecycle automation with VxRail HCI system software and 24 by seven single point of support, enabling you to rapidly react to business needs, no matter the location or how harsh the conditions. So whether you're deploying a data center at a mobile command base, running real-time GPS mapping on the go, or implementing video surveillance in remote areas, you can ensure availability, integrity and confidence for every workload with the new VxRail ruggedized D series. >> All right, Chad we would love for you to bring us in a little bit that what customer requirement for bringing this to market. I remember seeing, Dell servers ruggedized, of course, Edge, really important growth to build on what Jon was talking about, Cloud. So, Chad, bring us inside, what was driving this piece of the offering? >> Sure Stu. Yeah, yeah, having been at the hardware platforms that can go out into some of these remote locations is really important. And that's being driven by the fact that customers are looking for compute performance and storage out at some of these Edges or some of the more exotic locations. whether that's manufacturing plants, oil rigs, submarine ships, military applications, places that we've never heard of. But it's also about extending that operational simplicity of the the sort of way that you're managing your data center that has VxRails you're managing your Edges the same way using the same set of tools. You don't need to learn anything else. So operational simplicity is absolutely key here. But in those locations, you can take a product that's designed for a data center where definitely controlling power cooling space and take it some of these places where you get sand blowing or seven to zero temperatures, could be Baghdad or it could be Ketchikan, Alaska. So we built this D series that was able to go to those extreme locations with extreme heat, extreme cold, extreme altitude, but still offer that operational simplicity. Now military is one of those applications for the rugged platform. If you look at the resistance that it has to heat, it operates at a 45 degrees Celsius or 113 degrees Fahrenheit range, but it can do an excursion up to 55 C or 131 degrees Fahrenheit for up to eight hours. It's also resistant to heat sand, dust, vibration, it's very lightweight, short depth, in fact, it's only 20 inches deep. This is a smallest form factor, obviously that we have in the VxRail family. And it's also built to be able to withstand sudden shocks certified to withstand 40 G's of shock and operation of the 15,000 feet of elevation. Pretty high. And this is sort of like wherever skydivers go to when they want the real thrill of skydiving where you actually need oxygen to, to be for that that altitude. They're milspec-certified. So, MIL-STD-810G, which I keep right beside my bed and read every night. And it comes with a VxRail stick hardening package is packaging scripts so that you can auto lock down the rail environment. And we've got a few other certifications that are on the roadmap now for naval shock requirements. EMI and radiation immunity often. >> Yeah, it's funny, I remember when we first launched it was like, "Oh, well everything's going to white boxes. "And it's going to be massive, "no differentiation between everything out there." If you look at what you're offering, if you look at how public Clouds build their things, but I called it a few years or is there's a pure optimization. So you need to scale, you need similarities but you know you need to fit some, very specific requirements, lots of places, so, interesting stuff. Yeah, certifications, always keep your teams busy. Alright, let's get back to Shannon to view on the report. >> We are also introducing three other hardware-based additions. First, a new VxRail E Series model based on where the first time AMD EPYC processors. These single socket 1U nodes, offer dual socket performance with CPU options that scale from eight to 64 Cores, up to a terabyte of memory and multiple storage options making it an ideal platform for desktop VDI analytics and computer aided design. Next, the addition of the latest Nvidia Quadro RTX GPUs brings the most significant advancement in computer graphics in over a decade to professional work flows. Designers and artists across industries can now expand the boundary of what's possible, working with the largest and most complex graphics rendering, deep learning and visual computing workloads. And Intel Optane DC persistent memory is here, and it offers high performance and significantly increased memory capacity with data persistence at an affordable price. Data persistence is a critical feature that maintains data integrity, even when power is lost, enabling quicker recovery and less downtime. With support for Intel obtain DC persistent memory customers can expand in memory intensive workloads and use cases like SAP HANA. Alright, let's finally dig into our HCI system software, which is the Core differentiation for VxRail regardless of your workload or platform choice. Our joining engineering with VMware and investments in VxRail HCI system software innovation together deliver an optimized operational experience at reduced risk for our customers. Under the covers, VxRail offers best in class hardware, married with VMware HCI software, either vSAN or VCF. But what makes us different stems from our investments to integrate the two. Dell Technologies has a dedicated VxRail team of about 400 people to build market sell and support a fully integrated hyper converged system. That team has also developed our unique VxRail HCI system software, which is a suite of integrated software elements that extend VMware native capabilities to deliver seamless, automated operational experience that customers cannot find elsewhere. The key components of VxRail HCI system software shown around the arc here that include the extra manager, full stack lifecycle management, ecosystem connectors, and support. I don't have time to get into all the details of these elements today, but if you're interested in learning more, I encourage you to meet our experts. And I will tell you how to do that in a moment. I touched on the LCM being a key feature to the vSphere 7.0 earlier and I'd like to take the opportunity to expand on that a bit in the context of VxRail Lifecycle Management. The LCM adds valuable automation to the execution of updates for customers, but it doesn't eliminate the manual work still needed to define and package the updates and validate all of the components prior to applying them. With VxRail customers have all of these areas addressed automatically on their behalf, freeing them to put their time into other important functions for their business. Customers tell us that Lifecycle management continues to be a major source of the maintenance effort they put into their infrastructure, and then it tends to lead to overburden IT staff, that it can cause disruptions to the business if not managed effectively, and that it isn't the most efficient economically. Automation of Lifecycle Management and VxRail results in the utmost simplicity from a customer experience perspective, and offers operational freedom from maintaining infrastructure. But as shown here, our customers not only realize greater IT team efficiencies, they have also reduced downtime with fewer unplanned outages, and reduced overall cost of operations. With VxRail HCI system software, intelligent Lifecycle Management upgrades of the fully integrated hardware and software stack are automated, keeping clusters and continuously validated states while minimizing risks and operational costs. How do we ensure Continuously validated states for VxRail. VxRail labs execute an extensive, automated, repeatable process on every firmware and software upgrade and patch to ensure clusters are in continuously validated states of the customers choosing across their VxRail environment. The VxRail labs are constantly testing, analyzing, optimizing, and sequencing all of the components in the upgrade to execute in a single package for the full stack. All the while VxRail is backed by Dell EMC's world class services and support with a single point of contact for both hardware and software. IT productivity skyrockets with single click non disruptive upgrades of the fully integrated hardware and software stack without the need to do extensive research and testing. taking you to the next VxRail version of your choice, while always in a continuously validated state. You can also confidently execute automated VxRail upgrades. No matter what hardware generation or node types are in the cluster. They don't have to all be the same. And upgrades with VxRail are faster and more efficient with leapfrogging simply choose any VxRail version you desire. And be assured you will get there in a validated state while seamlessly bypassing any other release in between. Only VxRail can do that. >> All right, so Chad, the lifecycle management piece that Shannon was just talking about is, not the sexiest, it's often underappreciated. There's not only the years of experience, but the continuous work you're doing, reminds me back the early vSAN deployments versus VxRail jointly developed, jointly tested between Dell and VMware. So bring us inside why, 2020 Lifecycle Management still, a very important piece, especially in the VM family line. >> Yes, Stu, I think it's sexy, but, I'm pretty big nerd. (all laughing) Yeah, this is really always been our bread and butter. And in fact, it gets even more important, the larger the deployments come, when you start to look at data centers full of VxRails and all the different hardware software, firmware combinations that could exist out there. It's really the value that you get out of that VxRail HCI system software that Shannon was talking about and how it's optimized around the VMware use case. Very tightly integrated with each VMware component, of course, and the intelligence of being able to do all the firmware, all of the drivers, all the software all together in tremendous value to our customers. But to deliver that we really need to make a fairly large investment. So as Shannon mentioned, we run about 25,000 hours of testing across Each major release for patches, express patches, that's about 7000 hours for each of those. So, obviously, there's a lot of parallelism. And we're always developing new test scenarios for each release that we need to build in as we as we introduce new functionality. And one of the key things that we're able to do, as Shannon mentioned, is to be able to leapfrog releases and get you to that next validated state. We've got about 100 engineers just working on creating and executing those test cases on a continuous basis and obviously, a huge amount of automation. And we've talked about that investment to execute those tests. That's one worth of $60 million of investment in our lab. In fact, we've got just over 2000 VxRail units in our testbed across the US, Shanghai, China and Cork, Ireland. So a massive amount of testing of each of those components to make sure that they operate together in a validated state. >> Yeah, well, absolutely, it's super important not only for the day one, but the day two deployments. But I think this actually a great place for us to bring in that customer that Dell gave me access to. So we've got the CIO of Amarillo, Texas, he was an existing VxRail customer. And he's going to explain what happened as to how he needed to react really fast to support the work-from-home initiative, as well as we get to hear in his words the value of what Lifecycle Management means. So Andrew, if we could queue up that customer segment, please? >> It's been massive and it's been interesting to see the IT team absorb it. As we mature, I think they embrace the ability to be innovative and to work with our departments. But this instance, really justified why I was driving progress. So fervently why it was so urgent today. Three years ago, the answer would have been no. We wouldn't have been in a place where we could adapt With VxRail in place, in a week we spun up hundreds of instant balls. We spun up a 75-person call center in a day and a half, for our public health. We rolled out multiple applications for public health so they could do remote clinics. It's given us the flexibility to be able to roll out new solutions very quickly and be very adaptive. And it's not only been apparent to my team, but it's really made an impact on the business. And now what I'm seeing is those of my customers that work, a little lagging or a little conservative, or understanding the impact of modernizing the way they do business because it makes them adaptable as well. >> Alright, so great, Richard, you talked a bunch about the the efficiencies that that the IT put in place, how about that, that overall just managed, you talked about how fast you spun up these new VDI instances. need to be able to do things much simpler? So how does the overall Lifecycle Management fit into this discussion? >> It makes it so much easier. And in the old environment, one, It took a lot of man hours to make change. It was very disruptive, when we did make change, it overburdened, I guess that's the word I'm looking for. It really overburdened our staff to cause disruption to business. That wasn't cost efficient. And then simple things like, I've worked for multi billion dollar companies where we had massive QA environments that replicated production, simply can't afford that at local government. Having this sort of environment lets me do a scaled down QA environment and still get the benefit of rolling out non disruptive change. As I said earlier, it's allowed us to take all of those cycles that we were spending on Lifecycle Management because it's greatly simplified, and move those resources and rescale them in other areas where we can actually have more impact on the business. It's hard to be innovative when 100% of your cycles are just keeping the ship afloat. >> All right, well, nothing better than hearing it straight from the end user, public sector reacting very fast to the COVID-19. And, if you heard him he said, if this is his, before he had run this project, he would not have been able to respond. So I think everybody out there understands, if I didn't actually have access to the latest technology, it would be much harder. All right, I'm looking forward to doing the CrowdChat letting everybody else dig in with questions and get follow up but a little bit more, I believe one more announcement he can and got for us though. Let's roll the final video clip. >> In our latest software release VxRail 4.7.510, We continue to add new automation and self service features. New functionality enables you to schedule and run upgrade health checks in advance of upgrades, to ensure clusters are in a ready state for the next upgrade or patch. This is extremely valuable for customers that have stringent upgrade windows, as they can be assured the clusters will seamlessly upgrade within that window. Of course, running health checks on a regular basis also helps ensure that your clusters are always ready for unscheduled patches and security updates. We are also offering more flexibility and getting all nodes or clusters to a common release level with the ability to reimage nodes or clusters to a specific VxRail version, or down rev one or more nodes that may be shipped at a higher rate than the existing cluster. This enables you to easily choose your validated state when adding new nodes or repurposing nodes in a cluster. To sum up all of our announcements, whether you are accelerating data sets modernization extending HCI to harsh Edge environments, deploying an on-premises Dell Technologies Cloud platform to create a developer ready Kubernetes infrastructure. VxRail is there delivering a turn-key experience that enables you to continuously innovate, realize operational freedom and predictably evolve. VxRail provides an extensive breadth of platform configurations, automation and Lifecycle Management across the integrated hardware and software full stack and consistent hybrid Cloud operations to address the broadest range of traditional and modern applications across Core, Edge and Cloud. I now invite you to engage with us. First, the virtual passport program is an opportunity to have some fun while learning about VxRail new features and functionality and sCore some sweet digital swag while you're at it. Delivered via an augmented reality app. All you need is your device. So go to vxrail.is/passport to get started. And secondly, if you have any questions about anything I talked about or want a deeper conversation, we encourage you to join one of our exclusive VxRail Meet The Experts sessions available for a limited time. First come first served, just go to vxrail.is/expertsession to learn more. >> All right, well, obviously, with everyone being remote, there's different ways we're looking to engage. So we've got the CrowdChat right after this. But Jon, give us a little bit more as to how Dell's making sure to stay in close contact with customers and what you've got for options for them. >> Yeah, absolutely. So as Shannon said, so in lieu of not having done Tech World this year in person, where we could have those great in-person interactions and answer questions, whether it's in the booth or in meeting rooms, we are going to have these Meet The Experts sessions over the next couple weeks, and we're going to put our best and brightest from our technical community and make them accessible to everyone out there. So again, definitely encourage you. We're trying new things here in this virtual environment to ensure that we can still stay in touch, answer questions, be responsive, and really looking forward to, having these conversations over the next couple of weeks. >> All right, well, Jon and Chad, thank you so much. We definitely look forward to the conversation here and continued. If you're here live, definitely go down below and do it if you're watching this on demand. You can see the full transcript of it at crowdchat.net/vxrailrocks. For myself, Shannon on the video, Jon, Chad, Andrew, man in the booth there, thank you so much for watching, and go ahead and join the CrowdChat.

>>Fly from San Francisco. It's the cube covering RSA conference, 2020 San Francisco brought to you by Silicon angle media. >>Hi everyone. Welcome back to the cubes coverage here at in San Francisco, the Moscone center for RSA conference 2020 I'm job for your host. We are the very special guests, the COO of VMware, Sanjay Poonen, cube alumni. When you talk about security, talk about the modern enterprise as it transforms new use cases, new problems emerge. New opportunities exist here to break it down. Sanjay, welcome back. Thank you John. Always a pleasure to be on your show and I think it's my first time at RSA. We've talked a number of times, but nice to see you here. Well, it's a security guard. Well, this is really why I wanted you to talk, talk to you because operations is become now the big conversation around security. So you know, security was once part of it. It comes out and part of the board conversation, but when you look at security, all the conversations that we're seeing that are the most important conversations are almost a business model conversation. >>Almost like if you're the CEO of the company, you've got HR people, HR, organizational behavior, collaboration, technology, stack compliance and risk management. So the threat of cyber has to cut across now multiple operational functions of the business. It's no longer one thing, it's everything. So this is really kind of makes it the pressure of the business owners to be mindful of a bigger picture. And the attack velocity is happening so much faster, more volume of attacks, milliseconds and nanosecond attacks. So this is a huge, huge problem. I need you to break it down for me. >> Good. But then wonderful intro. No, I would say you're absolutely right. First off, security is a boardroom topic. Uh, audit committees are asking, you know, the CIO so often, you know, reports a report directly, sometimes, often not even to the CIO, to the head of legal or finance and often to the audit. >>So it's a boardroom topic then. You're right, every department right now cares about security because they've got both threat and security of nation state, all malicious, organized crime trying to come at them. But they've also got physical security mind. I mean, listen, growing a virus is a serious threat to our physical security. And we're really concerned about employees and the idea of a cyber security and physical security. We've put at VMware, cybersecurity and, and um, um, physical security. One guy, the CIO. So he actually runs vote. So I think you're absolutely right and if you're a head of HR, you care about your employees. If you're care ahead of communications, you care about your reputation and marketing the same way. If you're a finance, you care about your accounting systems and having all of the it systems that are. So we certainly think that holistic approach does, deserves a different approach to security, which is it can't be silo, silo, silo. >>It has to be intrinsic. And I've talked on your show about why intrinsic and how differentiated that intrinsic security, what I talked about this morning in my keynote. >> Well, and then again, the connect the dots there. It's not just security, it's the applications that are being built on mobile. For instance, I've got a mobile app. I have milliseconds, serious bond to whether something's yes or no. That's the app on mobile. But still the security threat is still over here and I've got the app over here. This is now the reality. And again, AirWatch was a big acquisition that you did. I also had some security. Carbon black was a $2 billion acquisition that VMware made. That's a security practice. How's it all coming together? Can you think of any questions? Blame the VMware because it's not just security, it's what's around it. >> Yeah. I think we began to see over the course of the last several years that there were certain control points and security that could help, you know, bring order to this chaos of 5,000 security vendors. >>They're all legitimate. They're all here at the show. They're good vendors. But you cannot, if you are trying to say healthy, go to a doctor and expect the doctor to tell you, eat 5,000 tablets and sailed. He just is not sustainable. It has to be baked into your diet. You eat your proteins, your vegetables, your fruit, your drink, your water. The same way we believe security needs to become intrinsically deeper parts, the platform. So what were the key platforms and control points? We decided to focus on the network, the endpoint, and you could think of endpoint as to both client and workload identity, cloud analytics. You take a few of those and network. We've been laboring the last seven years to build a definitive networking company and now a networking security company where we can do everything from data center networking, Dell firewalls to load balancing to SDN in this NSX platform. >>You remember where you bought an nice syrup. The industry woke up like what's VM ever doing in networking? We've now built on that 13,000 customers really good growing revenue business in networking and and now doing that working security. That space is fragmented across Cisco, Palo Alto, FIU, NetScaler, checkpoint Riverbed, VMware cleans that up. You get to the end point side. We saw the same thing. You know you had an endpoint management now workspace one the sequel of what AirWatch was, but endpoint security again, fragmented. You had Symantec McAfee, now CrowdStrike, tenable Qualis, you know, I mean just so many fragmented IOM. We felt like we could come in now and clean that up too, so I have to worry about to do >> well basically explaining that, but I want to get now to the next conversation point that I'm interested in operational impact because when you have all these things to operationalize, you saw that with dev ops and cloud now hybrid, you got to operationalize this stuff. >>You guys have been in the operations side of the business for our VMware. That's what you're known for and the developers and now on the horizon I gotta operationalize all the security. What do I do? I'm the CSO. I think it's really important that in understanding operations of the infrastructure, we have that control point called vSphere and we're now going to take carbon black and make it agentless on the silverside workloads, which has never been done before. That's operationalizing it at the infrastructure level. At the end point we're going to unify carbon black and workspace one into a unified agent, never been done before. That's operationalizing it on the client side. And then on the container and the dev ops site, you're going to start bringing security into the container world. We actually happened in our grade point of view in containers. You've seen us do stuff with Tansu and Kubernetes and pivotal. >>Bringing that together and data security is a very logical thing that we will add there. So we have a very good view of where the infrastructure and operations parts that we know well, a vSphere, NSX workspace one containers with 10 Xu, we're going to bring security to all of them and then bake it more and more in so it's not feeling like it's a point tool. The same platform, carbon black will be able to handle the security of all of those use cases. One platform, several use cases. Are you happy with the carbon black acquisition? Listen, you know, you stay humble and hungry. Uh, John for a fundamental reason, I've been involved with number of acquisitions from my SAP VMware days, billion dollar plus. We've done talking to us. The Harvard business review had an article several years ago, which Carney called acquisitions and majority of them fail and they feel not because of process of product they feel because good people leave. >>One of the things that we have as a recipe does acquisition. We applied that to AirWatch, we apply the deny Sera. There is usually some brain trust. You remember in the days of nice area, it was my team Cosato and the case of AirWatch. It was John Marshall and that team. We want to preserve that team to help incubate this and then what breve EV brings a scale, so I'm delighted about Patrick earlier. I want to have him on your show next time because he's now the head of our security business unit. He's culturally a fit for the mr. humble, hungry. He wants to see just, we were billion dollar business now with security across networking endpoint and then he wants to take just he's piece of it, right? The common black piece of it, make it a billion dollar business while the overall security business goes from three to five. >>And I think we're going to count them for many years to come to really be a key part of VMware's fabric, a great leader. So we're successful. If he's successful, what's my job then? He reports to me is to get all the obstacles out of the way. Get every one of my core reps to sell carbon black. Every one of the partners like Dell to sell carbon black. So one of the deals we did within a month is Dell has now announced that their preferred solution on at Dell laptops, this carbon bike, they will work in the past with silence and crowd CrowdStrike. Now it's common black every day laptop now as a default option. That's called blank. So as we do these, John, the way we roll is one on here to basically come in and occupy that acquisition, get the obstacles out of the way, and that let Patrick scaled us the same way. >>Martine Casado or jumbo. So we have a playbook. We're gonna apply that playbook. Stay humble and hungry. And you ask me that question every year. How are we doing a carbon black? I will be saying, I love you putting a check on you. It will be checking in when we've done an AirWatch. What do you think? Pretty good. Very good. I think good. Stayed line to the radar. Kept growing. It's top right. Known every magic quadrant. That business is significant. Bigger than the 100 million while nice here. How do we do a nice hero? NSX? It's evolved quite a bit. It's evolved. So this is back to the point. VMware makes bets. So unlike other acquisitions where they're big numbers, still big numbers, billions or billions, but they're bets. AirWatch was a good bet. Turned out okay. That the betting, you're being conservative today anyway. That's it. You're making now. >>How would you classify those bets? What are the big bets that you're making right now? Listen, >> I think there's, um, a handful of them. I like to think of things as no more than three to five. We're making a big bet. A multi-cloud. Okay. The world is going to be private, public edge. You and us have talked a lot about VMware. AWS expanded now to Azure and others. We've a big future that private cloud, public cloud edge number two, we're making a big bet on AB motorization with the container level 10 zoos. I think number three, we're making a big bet in virtual cloud networking cause we think longterm there's going to be only two networking companies in matter, VMware and Cisco. Number four, we're making a big bet in the digital workspace and build on what we've done with AirWatch and other technologies. Number five, and make it a big bet security. >>So these five we think of what can take the company from 10 to 20 billion. So we, you know, uh, we, we've talked about the $10 billion Mark. Um, and the next big milestone for the company is a 20 billion ball Mark. And you have to ask yourself, can you see this company with these five bets going from where they are about a 10 billion revenue company to 20. Boom. We hope again, >> Dave, a lot that's doing a braking and now he might've already shipped the piece this morning on multi-cloud. Um, he and I were commenting that, well, I said it's the third wave of cloud computing, public cloud, hybrid multi-cloud and hybrids, the first step towards multi-cloud. Everyone kind of knows that. Um, but I want to ask you, because I told Dave and we kind of talked about this is a multi-decade growth opportunity, wealth creation, innovation, growth, new opportunity multicloud for the generation. >>Take the, this industry the next level. How do you see that multicloud wave? Do you agree on the multigenerational and if so, what specifically do you see that unfolding into this? And I'm deeply inspired by what Andy Jassy, Satya Nadella, you know, the past leading up to Thomas Korea and these folks are creating big cloud businesses. Amazon's the biggest, uh, in the iOS pass world. Azure is second, Google is third, and just market shares. These folks collectively are growing, growing really well. In some senses, VM-ware gets to feed off that ecosystem in the public cloud. So we are firm believers in what you're described. Hybrid cloud is the pot to the multicloud. We coined that term hybrid thought. In fact, the first incantation of eco there was called via cloud hybrid service. So we coined the term hybrid cloud, but the world is not multi-cloud. The the, the key though is that I don't think you're gonna walk away from those three clouds I mentioned have deep pockets. >>Then none of them are going away and they're going to compete hard with each other. The market shares may stay the same. Our odd goal is to be a Switzerland player that can help our customers take VM or workloads, optimize them in the private cloud first. Okay? When a bank of America says on their earnings caller, Brian Warren and said, I can run a private cloud better than a public cloud and I can save 2 billion doing that, okay? It turns off any of the banks are actually running on VMware. That's their goal. But there are other companies like Freddie Mac, we're going all in with Amazon. We want to ride the best of both worlds. If you're a private cloud, we're going to make you the most efficient private cloud, VMware software, well public cloud, and going to Amazon like a Freddie Mac will help you ride your apps into that through VMware. >>So sometimes history can be a predictor of future behavior. And just to kind of rewind the computer industry clock, if you looked at mainframe mini-computers, inter networking, internet proprietary network operating systems dominated it, but you saw the shift and it was driven by choice for customers, multiple vendors, interoperability. So to me, I think cloud multicloud is going to come down to the best choice for the workload and then the environment of the business. And that's going to be a spectrum. But the key in that is multi-vendor, multi, a friend choice, multi-vendor, interoperability. This is going to be the next equation in the modern error. It's not gonna look the same as mainframe mini's networking, but it'll create the next Cisco, the create the next new brand that may or may not be out there yet that might be competing with you or you might be that next brand. >>So interoperability, multi-vendor choice has been a theme in open systems for a long time. Your reactions, I think it's absolutely right, John, you're onto something there. Listen, the multicloud world is almost a replay of the multi hardware system world. 20 years ago, if you asked who was a multi hardware player before, it was Dell, HP at the time, IBM, now, Lenovo, EMC, NetApp, so and so forth and Silva storage, networking. The multicloud world today is Amazon, Azure, Google. If you go to China, Alibaba, so on and so forth. A Motiva somebody has to be a Switzerland player that can serve the old hardware economy and the new hardware economy, which is the, which is the cloud and then of course, don't forget the device economy of Apple, Google, Microsoft, there too. I think that if you have some fundamental first principles, you expressed one of them. >>Listen where open source exists, embrace it. That's why we're going big on Kubernetes. If there are multiple clouds, embrace it. Do what's right for the customer, abstract away. That's what virtualization is. Managed common infrastructure across Ahmed, which is what our management principles are, secure things. At the point of every device and every workload. So those are the principles. Now the engineering of it changes. The way in which we're doing virtualization today in 2020 is slightly different from when Diane started the company and around the year 2020 years ago. But the principals are saying, we're just not working just with the hardware vendors working toward the cloud vendors. So using choices where it's at, the choice is what they want. Absolutely, absolutely. And you're right. It's choice because it was the big workloads. We see, for example, Amazon having a headstart in the public cloud markets, but there's some use cases where Azure is applicable. >>Some use his word, Google's applicable, and to us, if the entire world was only one hardware player or only one cloud player, only one device player, you don't need VMware. We thrive in heterogeneity. It's awesome. I love that word. No heterogeneity provides not 3000 vendors. There's almost three, three of every kind, three silver vendors, three storage vendors, three networking vendors, three cloud vendors, three device vendors. We was the middle of all of it. And yeah, there may be other companies who tried to do that too. If they are, we should learn from them, do it better than them. And competition even to us is a good thing. All right. My final question for you is in the, yeah, the Dell technologies family of which VMware is a part of, although big part of it, the crown jewel as we've been calling them the cube, they announced RSA is being sold to a private equity company. >>What's the general reaction amongst VMware folks and the, and the Dell technology family? Good move, no impact. What we support Dell and you know, all the moves that they've made. Um, and from our perspective, you know, if we're not owning it, we're going to partner it. So I see no overlap with RSA. We partner with them. They've got three core pillars, secure ID, net witness and Archer. We partnered with them very well. We have no aspirations to get into those aspects of governance. Risk and compliance or security has been, so it's a partner. So whoever's running it, Rohit runs on very well. He also owns the events conference. We have a great relationship and then we'll keep doing that. Well, we are focused in the areas I described, network, endpoint security. And I think what Michael has done brilliantly through the course of the last few years is set up a hardware and systems company in Dell and allow the software company called Vima to continue to operate. >>And I think, you know, the movement of some of these assets between the companies like pivotal to us and so on and so forth, cleans it up so that now you've got both these companies doing well. Dell has gone public, we Hammer's gone public and he has said on the record, what's good for Dell is good, what's good for VMware and vice versa and good for the customer. And I think the key is there's no visibility on what cloud native looks like. Hybrid, public, multi, multi, not so much. But you get almost, it's an easy bridge to get across and get there. AI, cyber are all big clear trends. They're waves. Sasha. Great. Thank you. Thanks for coming on. Um, your thoughts on the security show here. Uh, what's your, what's your take to, uh, definitive security shows? I hope it stays that way. Even with the change of where RSA is. >>Ownership goes is this conference in black hat and we play in both, uh, Amazon's conference. I was totally starting to, uh, reinforce, reinforce cloud security will show up there too. Uh, but we, we think, listen, there's what, 30,000 people here. So it's a force. It's a little bit like VMworld. We will play here. We'll play a big, we've got, you know, it just so happens because the acquisition happened before we told them, but we have two big presences here. We were at carbon black, um, and it's an important business for us. And I said, like I said, we have $1 billion business and security today by 30,000 customers using us in a security network, endpoints cloud. I want to take that to be a multi, multiple times that size. And I think there's a pot to do that because it's an adjacent us and security. So we have our own kind of selfish motives here in terms of getting more Mindshare and security. >>We did a keynote this morning, which was well received with Southwest airlines. She did a great job. Carrie Miller, she was a fantastic speaker and it was our way of showing in 20 minutes, not just to our point of view, because you don't want to be self serving a practitioner's point of view. And that's what's really important. Well finally on a personal note, um, you know, I always use the term tech athlete, which I think you are one, you really work hard and smart, but I got to get your thoughts. But then I saw you're not on Twitter. I'm on. When IBM announced a new CEO, Arvin, um, fishnet Indian American, another CEO, this is a pattern. We're starting to see Indian American CEOs running cup American companies because this is the leadership and it's really a great thing in my mind, I think is one of the most successful stories of meritocracy of all time. >>You're quick. I'm a big fan of oven, big fan of Shantanu, Sundar Pichai, something that Ellen, many of them are close friends of mine. Uh, many of them have grown up in Southern India. We're a different ages. Some of them are older than me and in many cases, you know, we were falling behind other great players like Vino Cosla who came even 10 to 15 years prior. And you know, it's hard for an immigrant in this country. You know, um, when I first got here and I came as an immigrant to Dartmouth college, there may have been five or 10 Brown skin people in the town of Hanover, New Hampshire. I don't know if you've been to New Hampshire. I've been there, there's not many at that time. And then the late 1980s, now of course, there's much more, uh, so, you know, uh, we stay humble and hungry. >>There's a part of our culture in India that's really valued education and hard work and people like Arvin and some of these other people are products. I look up to them, the things I learned from them. And um, you know, it's true of India. It's a really good thing to see these people be successful at name brand American companies, whether it's IBM or Microsoft or Google or Adobe or MasterCard. So we're, we're, I'm in that fan club and there's a lot I learned from that. I just love being around people who love entrepreneurship, love innovation, love technology, and work hard. So congratulations. Thank you so much for your success. Great to see you again soon as you put in the COO of VM-ware here on the ground floor here at RSA conference at Moscone, sharing his insight into the security practice that is now carbon black and VMware. All the good things that are going on there. Thanks for watching.

>> Live from Las Vegas, it's theCUBE covering Informatica World 2019. Brought to you by Informatica. >> Welcome everyone, you are watching theCUBE. We are kicking off a two-day event here at Informatica World 2019 in Las Vegas. I'm your host, and I'm co-hosting along with John Furrier. It's great to have you. Great to be here. >> Great to see you again. >> So, Informatica is really sitting in the sweet spot of a fast-growing area of technology, cloud and big data. I want to ask you a big question. Where is the market? What do you see happening in this sweet spot area? >> Well we're here in Informatica World. I think it's our fourth Cube coverage. We've been following these guys since they've gone private two years ago in depth. Interesting changeover. They went private just like Michael Dell did with Dell Technologies. And then they went public in great performance. We said at that time, if they can go private with the product skills that they have in their senior leadership, they could do well. And they've been on the same trend line, which has been really positive data. Now data is the hottest thing on the planet. This is the theme of the industry. Data is everything. Machine learning needs data. Data feeds machine learning. Machine learning feeds AI. This is a core innovator. Now the challenge is on the enterprise side is that data is structured. It's in all these different databases. So in an enterprise, data's kind of has all these legacy structures and legacy systems. And the cloud for instance. Cloud is where SaaS wins. And SaaS winners like Zoom Communications, Air BNB, you name all those successful cloud data companies. Data's at the heart of their value proposition. And data is unencumbered. There's no restrictions. They use data, data as analysis. They look at customer behavior, AB testing. So data is the heart of innovation. This is Informatica's plan here. CLAIRE is their AI product. Their theme is kind of clever. CLAIRE starts here. And this is really the focus for Informatica. Their opportunity is to be that independent vendor supplier, the Switzerland as it has been called, the neutral third party to bring data together On Premise and Cloud. That's what they're saying. That's their opportunity. The challenges are high. The data business is being regulated. We talk about it last time. You know, privacy, GDPR one-year anniversary, Microsoft's calling for more privacy. As more regulation comes in, that puts more restrictions on data. That requires more software. That creates overhead. Overhead is not good for SaaS business models. And that is where the conflict is. This is the opportunity, and if they can overcome that as a supplier, then they can do well. And data growth is just massive. Cloud, IoT Edge, you name it. Data is the center of the value proposition. >> Well, and we're going to have a lot of great guests on the program this week, in particular we're going to have Sally Jenkins talking about these four customer journeys that the customers are going on. And in fact data governance and privacy is one of the big tenants. So, they are making, they are saying this is our wheelhouse. We can do this. We can help you do this. >> Well, the thing is we're going to ask every guest the question of the week is What's the skill gaps? Because digital transformation although very relevant is only as good as the people and the culture that's behind it. And that's a theme that we hear all throughout our different CUBE events. If people have the culture for it, they could do it. DevOps is another word that has been kicked around. But ultimately if you don't have the people and just machines, it's really going to be a tough balance to strike. You need the machines, you need the data, you need the people. And this is where the challenge is in the industry. I think the skill gaps is a huge problem for digital transformation. It's to me the big blocker in seeing innovation accelerate. So customers are now having that journey. They're starting, they really think about how to architect their enterprise with an On Premise, with a Legacy and Cloud Native with full SaaS. And the companies that can get to a SaaS business model, managing the On-Premise's legacy will have a winning shot at taking new market share or top one down incumbents in leadership positions. >> I'm really excited about this idea. Asking people about the skill gap and where the next generation of jobs are going to be in big data. I saw a statistic, a survey from Google, 94% of IT managers can't find qualified candidates for open Cloud roles. That is-that's astonishing. I also saw an interesting quote from Tim Cook, who recently said that half of Apple's new hires are not going to have a college degree this year. He said when our own founder didn't have one. It kind of really shows you what you can do. >> It's really early. >> You might not need this degree. >> First of all, it's really, first of all I agree that degrees don't really matter. In some cases, old degrees might not apply to the new jobs. I'll give you an example. My daughter just graduated from Cal Berkeley this week. And they had the inaugural class of data, data science, data analytics. For the first time, first graduating class. That's a tell-sign that we're at the early, early stages. But data science can come from anyone. You could be, you know, anthropologist, you could be any any skill. You can solve a problem, you're good at math. You can see the big picture. You're seeing data science really becoming a career. And again, there's just not enough job openings. And data science isn't just for the data jockeys out there who just want to do data. There's cyber security, huge data-driven. Everything is data-driven. The big growth area in the enterprise is the IoT, the Edge. As devices come online for manufacturing to oil rigs to wind farms. The edge computing is a huge thing. And that's a data problem. Everything is a data problem. So this is where the industry is focused I think Informatica was really on it early. And now everyone's jumping in. You got Amazon, Google, Microsoft, the big cloud players, and you got all the existing incumbent enterprise suppliers all putting data at the center-value proposition. You know you got a lot of competition now for Informatica, and they have to make some good moves here. And what I'm going to be looking for here, Rebecca, is how they transform as a company. Because I think that they have to be an integration company. They want to be that Switzerland. They got to integrate to all the clouds. They got to integrate to all the different platforms and environments on the enterprise and create that one operating model. And this is something they say they want to do, and we're going to ask them. >> And you not only called them Switzerland, they've called themselves Switzerland. And so I think that they are. They do want that. They want that for themselves. They want they are having these partnerships with all of the major cloud providers. So, you said this is what you're going to be asking. This is what you're going to be looking for. What is it that you think will set them apart? >> I think ultimately I think Informatica's got a great management team when it comes to product and engineering. One of the things I've been impressed with is they get the product around data. The only thing I think that could be a headwind for them as a challenge is this regulatory environment. I brought that up earlier. I think this could be a challenge and an opportunity, and it could be the difference maker because there's no question that their value proposition or how they're dealing with data management, their deals we're going to hear about with the cloud and all of the new innovation they have with CLAIRE and AI. Certainly that's good. But if you don't have data-feeding machine learning, and the data's hard to get at, and it's regulated, you got clouds with geographies and countries have new regulations. This is a complicated problem. If they could create software to make that easier and create an abstraction layer and use the power of the cloud, I think they could have a winning formula. So to me, that's a killer opportunity. And then making data work for SaaS-oriented business models, On-Premise and in the cloud. >> I think you're absolutely right and we heard Anil Chakravarthy say this today. Data needs the machine learning an AI, AI machine learning need data. And any application of AI and machine learning is only as good as the data that's been collected. So, the other big challenge is what I think is going to be really exciting about for this show is seeing all of these use cases. In industry after industry we are seeing applications of AI and machine learning transforming business models and approaches and leadership and big ideas around these important game-changers in our industry. >> Yeah, one of the things that's interesting I had an interview with in the city of Howie Xu, who's formally VMWare engineer, entrepreneur, sold his company to Zscaler. He's an AI guy, and we talked about the SaaS business model. And one of the things that's key is if you don't have the data feeding the SaaS, it's not going to work, so to me if they could get that data back in to the system quicker with all that regulation, that's going to be a game changer. And I think they got to start thinking how they can show the customer proof points. That's going to be interesting when the customers start adapting in that scale. >> And as we've also said many times on theCUBE the governance is kind of a mess itself. I mean Washington doesn't quite know what to do with this and how to regulate it. How do you think that these technology companies should be working with Washington on this? >> Well that's a loaded question. First of all, I think the government is not the bellwether for technology innovation. In fact, I think innovation is stifled by too much regulation. There's got to have a balance there. One of the things that's positive is in the cyber-security area you see private, public partnerships go on where there's some joint sharing. I think cloud is going to be a catalyst. We're going to have the VP of marketing from Amazon web services on, I'm going to ask him that direct question. This is where the action is. So I think this notion of collaboration the enterprise and cloud players is going to be key because if you look at like just how search engines used to work back in the old days, if it was not encumbered by all this legacy infrastructure in the enterprise, it works great. The more you add complexity to things, the more you need software. The more you need software, you need horsepower to compute. You need more storage. So all these things are creating a different environment than it was just three years ago. So, you know can they adjust, can the industry shape itself out? I think the industry needs to lead here, not the government. >> What about the idea of Informatica working together with customers and making sure that they are in fact deriving value? Because I mean I think that's the other thing is that all of these companies know they need to have an AI strategy, they need to be using more machine learning. It's very complicated as you said. But then there's this question of am I really going to see a return of investment on this? >> Well, I think Informatica can do a good job working with cloud architecture and looking at because you got again IoT edge is coming around the corner. But if they can nail the architecture On-Premises and Cloud, that is a great start. The second thing that Informatica can help customers at, and this is a customer challenge, is where do you store the data? Because moving data around is very expensive. So this scenario is where you want it all on the cloud. This scenario is where you want it all On Premise. And this scenario is where you want it on both locations. And then with the edge, you want to move data I mean compute to where the data is. So, data becomes a very critical piece of the overall architecture and whoever can build this operating system's mindset will have a winning formula, and again being neutral is a critical strategy. And the more Informatica can help enterprise be more like consumer companies, the better. If you look at Slack for instance, it's an IPO candidate coming out very popular. It's just a chat kind of message board app. What made Slack successful is that they built connectors and APIs into all different tools. If Informatica could do that, that would be a winning formula because they want to be data brokering, they want to be data connecting, and they want to feed the applications and machine learning data. If they can't get data to the machine learning and AI, the AI will not be sufficient. And that will be a problem. >> Well, this is all the things we are going to be talking about over these next two days. John, I look forward to it. I'm Rebecca Knight, you are watching theCUBE. (lighthearted techno music)