(upbeat music) >> Welcome back, everyone, to theCUBE's coverage here live on the floor at AWS re:MARS 2022. I'm John Furrier, host for theCUBE. Great event, machine learning, automation, robotics, space, that's MARS. It's part of the re-series of events, re:Invent's the big event at the end of the year, re:Inforce, security, re:MARS, really intersection of the future of space, industrial, automation, which is very heavily DevOps machine learning, of course, machine learning, which is AI. We have Luis Ceze here, who's the CEO co-founder of OctoML. Welcome to theCUBE. >> Thank you very much for having me in the show, John. >> So we've been following you guys. You guys are a growing startup funded by Madrona Venture Capital, one of your backers. You guys are here at the show. This is a, I would say small show relative what it's going to be, but a lot of robotics, a lot of space, a lot of industrial kind of edge, but machine learning is the centerpiece of this trend. You guys are in the middle of it. Tell us your story. >> Absolutely, yeah. So our mission is to make machine learning sustainable and accessible to everyone. So I say sustainable because it means we're going to make it faster and more efficient. You know, use less human effort, and accessible to everyone, accessible to as many developers as possible, and also accessible in any device. So, we started from an open source project that began at University of Washington, where I'm a professor there. And several of the co-founders were PhD students there. We started with this open source project called Apache TVM that had actually contributions and collaborations from Amazon and a bunch of other big tech companies. And that allows you to get a machine learning model and run on any hardware, like run on CPUs, GPUs, various GPUs, accelerators, and so on. It was the kernel of our company and the project's been around for about six years or so. Company is about three years old. And we grew from Apache TVM into a whole platform that essentially supports any model on any hardware cloud and edge. >> So is the thesis that, when it first started, that you want to be agnostic on platform? >> Agnostic on hardware, that's right. >> Hardware, hardware. >> Yeah. >> What was it like back then? What kind of hardware were you talking about back then? Cause a lot's changed, certainly on the silicon side. >> Luis: Absolutely, yeah. >> So take me through the journey, 'cause I could see the progression. I'm connecting the dots here. >> So once upon a time, yeah, no... (both chuckling) >> I walked in the snow with my bare feet. >> You have to be careful because if you wake up the professor in me, then you're going to be here for two hours, you know. >> Fast forward. >> The average version here is that, clearly machine learning has shown to actually solve real interesting, high value problems. And where machine learning runs in the end, it becomes code that runs on different hardware, right? And when we started Apache TVM, which stands for tensor virtual machine, at that time it was just beginning to start using GPUs for machine learning, we already saw that, with a bunch of machine learning models popping up and CPUs and GPU's starting to be used for machine learning, it was clear that it come opportunity to run on everywhere. >> And GPU's were coming fast. >> GPUs were coming and huge diversity of CPUs, of GPU's and accelerators now, and the ecosystem and the system software that maps models to hardware is still very fragmented today. So hardware vendors have their own specific stacks. So Nvidia has its own software stack, and so does Intel, AMD. And honestly, I mean, I hope I'm not being, you know, too controversial here to say that it kind of of looks like the mainframe era. We had tight coupling between hardware and software. You know, if you bought IBM hardware, you had to buy IBM OS and IBM database, IBM applications, it all tightly coupled. And if you want to use IBM software, you had to buy IBM hardware. So that's kind of like what machine learning systems look like today. If you buy a certain big name GPU, you've got to use their software. Even if you use their software, which is pretty good, you have to buy their GPUs, right? So, but you know, we wanted to help peel away the model and the software infrastructure from the hardware to give people choice, ability to run the models where it best suit them. Right? So that includes picking the best instance in the cloud, that's going to give you the right, you know, cost properties, performance properties, or might want to run it on the edge. You might run it on an accelerator. >> What year was that roughly, when you were going this? >> We started that project in 2015, 2016 >> Yeah. So that was pre-conventional wisdom. I think TensorFlow wasn't even around yet. >> Luis: No, it wasn't. >> It was, I'm thinking like 2017 or so. >> Luis: Right. So that was the beginning of, okay, this is opportunity. AWS, I don't think they had released some of the nitro stuff that the Hamilton was working on. So, they were already kind of going that way. It's kind of like converging. >> Luis: Yeah. >> The space was happening, exploding. >> Right. And the way that was dealt with, and to this day, you know, to a large extent as well is by backing machine learning models with a bunch of hardware specific libraries. And we were some of the first ones to say, like, know what, let's take a compilation approach, take a model and compile it to very efficient code for that specific hardware. And what underpins all of that is using machine learning for machine learning code optimization. Right? But it was way back when. We can talk about where we are today. >> No, let's fast forward. >> That's the beginning of the open source project. >> But that was a fundamental belief, worldview there. I mean, you have a world real view that was logical when you compare to the mainframe, but not obvious to the machine learning community. Okay, good call, check. Now let's fast forward, okay. Evolution, we'll go through the speed of the years. More chips are coming, you got GPUs, and seeing what's going on in AWS. Wow! Now it's booming. Now I got unlimited processors, I got silicon on chips, I got, everywhere >> Yeah. And what's interesting is that the ecosystem got even more complex, in fact. Because now you have, there's a cross product between machine learning models, frameworks like TensorFlow, PyTorch, Keras, and like that and so on, and then hardware targets. So how do you navigate that? What we want here, our vision is to say, folks should focus, people should focus on making the machine learning models do what they want to do that solves a value, like solves a problem of high value to them. Right? So another deployment should be completely automatic. Today, it's very, very manual to a large extent. So once you're serious about deploying machine learning model, you got a good understanding where you're going to deploy it, how you're going to deploy it, and then, you know, pick out the right libraries and compilers, and we automated the whole thing in our platform. This is why you see the tagline, the booth is right there, like bringing DevOps agility for machine learning, because our mission is to make that fully transparent. >> Well, I think that, first of all, I use that line here, cause I'm looking at it here on live on camera. People can't see, but it's like, I use it on a couple couple of my interviews because the word agility is very interesting because that's kind of the test on any kind of approach these days. Agility could be, and I talked to the robotics guys, just having their product be more agile. I talked to Pepsi here just before you came on, they had this large scale data environment because they built an architecture, but that fostered agility. So again, this is an architectural concept, it's a systems' view of agility being the output, and removing dependencies, which I think what you guys were trying to do. >> Only part of what we do. Right? So agility means a bunch of things. First, you know-- >> Yeah explain. >> Today it takes a couple months to get a model from, when the model's ready, to production, why not turn that in two hours. Agile, literally, physically agile, in terms of walk off time. Right? And then the other thing is give you flexibility to choose where your model should run. So, in our deployment, between the demo and the platform expansion that we announced yesterday, you know, we give the ability of getting your model and, you know, get it compiled, get it optimized for any instance in the cloud and automatically move it around. Today, that's not the case. You have to pick one instance and that's what you do. And then you might auto scale with that one instance. So we give the agility of actually running and scaling the model the way you want, and the way it gives you the right SLAs. >> Yeah, I think Swami was mentioning that, not specifically that use case for you, but that use case generally, that scale being moving things around, making them faster, not having to do that integration work. >> Scale, and run the models where they need to run. Like some day you want to have a large scale deployment in the cloud. You're going to have models in the edge for various reasons because speed of light is limited. We cannot make lights faster. So, you know, got to have some, that's a physics there you cannot change. There's privacy reasons. You want to keep data locally, not send it around to run the model locally. So anyways, and giving the flexibility. >> Let me jump in real quick. I want to ask this specific question because you made me think of something. So we're just having a data mesh conversation. And one of the comments that's come out of a few of these data as code conversations is data's the product now. So if you can move data to the edge, which everyone's talking about, you know, why move data if you don't have to, but I can move a machine learning algorithm to the edge. Cause it's costly to move data. I can move computer, everyone knows that. But now I can move machine learning to anywhere else and not worry about integrating on the fly. So the model is the code. >> It is the product. >> Yeah. And since you said, the model is the code, okay, now we're talking even more here. So machine learning models today are not treated as code, by the way. So do not have any of the typical properties of code that you can, whenever you write a piece of code, you run a code, you don't know, you don't even think what is a CPU, we don't think where it runs, what kind of CPU it runs, what kind of instance it runs. But with machine learning model, you do. So what we are doing and created this fully transparent automated way of allowing you to treat your machine learning models if you were a regular function that you call and then a function could run anywhere. >> Yeah. >> Right. >> That's why-- >> That's better. >> Bringing DevOps agility-- >> That's better. >> Yeah. And you can use existing-- >> That's better, because I can run it on the Artemis too, in space. >> You could, yeah. >> If they have the hardware. (both laugh) >> And that allows you to run your existing, continue to use your existing DevOps infrastructure and your existing people. >> So I have to ask you, cause since you're a professor, this is like a masterclass on theCube. Thank you for coming on. Professor. (Luis laughing) I'm a hardware guy. I'm building hardware for Boston Dynamics, Spot, the dog, that's the diversity in hardware, it's tends to be purpose driven. I got a spaceship, I'm going to have hardware on there. >> Luis: Right. >> It's generally viewed in the community here, that everyone I talk to and other communities, open source is going to drive all software. That's a check. But the scale and integration is super important. And they're also recognizing that hardware is really about the software. And they even said on stage, here. Hardware is not about the hardware, it's about the software. So if you believe that to be true, then your model checks all the boxes. Are people getting this? >> I think they're starting to. Here is why, right. A lot of companies that were hardware first, that thought about software too late, aren't making it. Right? There's a large number of hardware companies, AI chip companies that aren't making it. Probably some of them that won't make it, unfortunately just because they started thinking about software too late. I'm so glad to see a lot of the early, I hope I'm not just doing our own horn here, but Apache TVM, the infrastructure that we built to map models to different hardware, it's very flexible. So we see a lot of emerging chip companies like SiMa.ai's been doing fantastic work, and they use Apache TVM to map algorithms to their hardware. And there's a bunch of others that are also using Apache TVM. That's because you have, you know, an opening infrastructure that keeps it up to date with all the machine learning frameworks and models and allows you to extend to the chips that you want. So these companies pay attention that early, gives them a much higher fighting chance, I'd say. >> Well, first of all, not only are you backable by the VCs cause you have pedigree, you're a professor, you're smart, and you get good recruiting-- >> Luis: I don't know about the smart part. >> And you get good recruiting for PhDs out of University of Washington, which is not too shabby computer science department. But they want to make money. The VCs want to make money. >> Right. >> So you have to make money. So what's the pitch? What's the business model? >> Yeah. Absolutely. >> Share us what you're thinking there. >> Yeah. The value of using our solution is shorter time to value for your model from months to hours. Second, you shrink operator, op-packs, because you don't need a specialized expensive team. Talk about expensive, expensive engineers who can understand machine learning hardware and software engineering to deploy models. You don't need those teams if you use this automated solution, right? Then you reduce that. And also, in the process of actually getting a model and getting specialized to the hardware, making hardware aware, we're talking about a very significant performance improvement that leads to lower cost of deployment in the cloud. We're talking about very significant reduction in costs in cloud deployment. And also enabling new applications on the edge that weren't possible before. It creates, you know, latent value opportunities. Right? So, that's the high level value pitch. But how do we make money? Well, we charge for access to the platform. Right? >> Usage. Consumption. >> Yeah, and value based. Yeah, so it's consumption and value based. So depends on the scale of the deployment. If you're going to deploy machine learning model at a larger scale, chances are that it produces a lot of value. So then we'll capture some of that value in our pricing scale. >> So, you have direct sales force then to work those deals. >> Exactly. >> Got it. How many customers do you have? Just curious. >> So we started, the SaaS platform just launched now. So we started onboarding customers. We've been building this for a while. We have a bunch of, you know, partners that we can talk about openly, like, you know, revenue generating partners, that's fair to say. We work closely with Qualcomm to enable Snapdragon on TVM and hence our platform. We're close with AMD as well, enabling AMD hardware on the platform. We've been working closely with two hyperscaler cloud providers that-- >> I wonder who they are. >> I don't know who they are, right. >> Both start with the letter A. >> And they're both here, right. What is that? >> They both start with the letter A. >> Oh, that's right. >> I won't give it away. (laughing) >> Don't give it away. >> One has three, one has four. (both laugh) >> I'm guessing, by the way. >> Then we have customers in the, actually, early customers have been using the platform from the beginning in the consumer electronics space, in Japan, you know, self driving car technology, as well. As well as some AI first companies that actually, whose core value, the core business come from AI models. >> So, serious, serious customers. They got deep tech chops. They're integrating, they see this as a strategic part of their architecture. >> That's what I call AI native, exactly. But now there's, we have several enterprise customers in line now, we've been talking to. Of course, because now we launched the platform, now we started onboarding and exploring how we're going to serve it to these customers. But it's pretty clear that our technology can solve a lot of other pain points right now. And we're going to work with them as early customers to go and refine them. >> So, do you sell to the little guys, like us? Will we be customers if we wanted to be? >> You could, absolutely, yeah. >> What we have to do, have machine learning folks on staff? >> So, here's what you're going to have to do. Since you can see the booth, others can't. No, but they can certainly, you can try our demo. >> OctoML. >> And you should look at the transparent AI app that's compiled and optimized with our flow, and deployed and built with our flow. That allows you to get your image and do style transfer. You know, you can get you and a pineapple and see how you look like with a pineapple texture. >> We got a lot of transcript and video data. >> Right. Yeah. Right, exactly. So, you can use that. Then there's a very clear-- >> But I could use it. You're not blocking me from using it. Everyone's, it's pretty much democratized. >> You can try the demo, and then you can request access to the platform. >> But you get a lot of more serious deeper customers. But you can serve anybody, what you're saying. >> Luis: We can serve anybody, yeah. >> All right, so what's the vision going forward? Let me ask this. When did people start getting the epiphany of removing the machine learning from the hardware? Was it recently, a couple years ago? >> Well, on the research side, we helped start that trend a while ago. I don't need to repeat that. But I think the vision that's important here, I want the audience here to take away is that, there's a lot of progress being made in creating machine learning models. So, there's fantastic tools to deal with training data, and creating the models, and so on. And now there's a bunch of models that can solve real problems there. The question is, how do you very easily integrate that into your intelligent applications? Madrona Venture Group has been very vocal and investing heavily in intelligent applications both and user applications as well as enablers. So we say an enable of that because it's so easy to use our flow to get a model integrated into your application. Now, any regular software developer can integrate that. And that's just the beginning, right? Because, you know, now we have CI/CD integration to keep your models up to date, to continue to integrate, and then there's more downstream support for other features that you normally have in regular software development. >> I've been thinking about this for a long, long, time. And I think this whole code, no one thinks about code. Like, I write code, I'm deploying it. I think this idea of machine learning as code independent of other dependencies is really amazing. It's so obvious now that you say it. What's the choices now? Let's just say that, I buy it, I love it, I'm using it. Now what do I got to do if I want to deploy it? Do I have to pick processors? Are there verified platforms that you support? Is there a short list? Is there every piece of hardware? >> We actually can help you. I hope we're not saying we can do everything in the world here, but we can help you with that. So, here's how. When you have them all in the platform you can actually see how this model runs on any instance of any cloud, by the way. So we support all the three major cloud providers. And then you can make decisions. For example, if you care about latency, your model has to run on, at most 50 milliseconds, because you're going to have interactivity. And then, after that, you don't care if it's faster. All you care is that, is it going to run cheap enough. So we can help you navigate. And also going to make it automatic. >> It's like tire kicking in the dealer showroom. >> Right. >> You can test everything out, you can see the simulation. Are they simulations, or are they real tests? >> Oh, no, we run all in real hardware. So, we have, as I said, we support any instances of any of the major clouds. We actually run on the cloud. But we also support a select number of edge devices today, like ARMs and Nvidia Jetsons. And we have the OctoML cloud, which is a bunch of racks with a bunch Raspberry Pis and Nvidia Jetsons, and very soon, a bunch of mobile phones there too that can actually run the real hardware, and validate it, and test it out, so you can see that your model runs performant and economically enough in the cloud. And it can run on the edge devices-- >> You're a machine learning as a service. Would that be an accurate? >> That's part of it, because we're not doing the machine learning model itself. You come with a model and we make it deployable and make it ready to deploy. So, here's why it's important. Let me try. There's a large number of really interesting companies that do API models, as in API as a service. You have an NLP model, you have computer vision models, where you call an API and then point in the cloud. You send an image and you got a description, for example. But it is using a third party. Now, if you want to have your model on your infrastructure but having the same convenience as an API you can use our service. So, today, chances are that, if you have a model that you know that you want to do, there might not be an API for it, we actually automatically create the API for you. >> Okay, so that's why I get the DevOps agility for machine learning is a better description. Cause it's not, you're not providing the service. You're providing the service of deploying it like DevOps infrastructure as code. You're now ML as code. >> It's your model, your API, your infrastructure, but all of the convenience of having it ready to go, fully automatic, hands off. >> Cause I think what's interesting about this is that it brings the craftsmanship back to machine learning. Cause it's a craft. I mean, let's face it. >> Yeah. I want human brains, which are very precious resources, to focus on building those models, that is going to solve business problems. I don't want these very smart human brains figuring out how to scrub this into actually getting run the right way. This should be automatic. That's why we use machine learning, for machine learning to solve that. >> Here's an idea for you. We should write a book called, The Lean Machine Learning. Cause the lean startup was all about DevOps. >> Luis: We call machine leaning. No, that's not it going to work. (laughs) >> Remember when iteration was the big mantra. Oh, yeah, iterate. You know, that was from DevOps. >> Yeah, that's right. >> This code allowed for standing up stuff fast, double down, we all know the history, what it turned out. That was a good value for developers. >> I could really agree. If you don't mind me building on that point. You know, something we see as OctoML, but we also see at Madrona as well. Seeing that there's a trend towards best in breed for each one of the stages of getting a model deployed. From the data aspect of creating the data, and then to the model creation aspect, to the model deployment, and even model monitoring. Right? We develop integrations with all the major pieces of the ecosystem, such that you can integrate, say with model monitoring to go and monitor how a model is doing. Just like you monitor how code is doing in deployment in the cloud. >> It's evolution. I think it's a great step. And again, I love the analogy to the mainstream. I lived during those days. I remember the monolithic propriety, and then, you know, OSI model kind of blew it. But that OSI stack never went full stack, and it only stopped at TCP/IP. So, I think the same thing's going on here. You see some scalability around it to try to uncouple it, free it. >> Absolutely. And sustainability and accessibility to make it run faster and make it run on any deice that you want by any developer. So, that's the tagline. >> Luis Ceze, thanks for coming on. Professor. >> Thank you. >> I didn't know you were a professor. That's great to have you on. It was a masterclass in DevOps agility for machine learning. Thanks for coming on. Appreciate it. >> Thank you very much. Thank you. >> Congratulations, again. All right. OctoML here on theCube. Really important. Uncoupling the machine learning from the hardware specifically. That's only going to make space faster and safer, and more reliable. And that's where the whole theme of re:MARS is. Let's see how they fit in. I'm John for theCube. Thanks for watching. More coverage after this short break. >> Luis: Thank you. (gentle music)

>> From around the globe, it's theCUBE with digital coverage of AWS re:Invent 2020. Special coverage sponsored by AWS Worldwide Public Sector. >> Hello, welcome back to theCUBES coverage, of AWS re:Invent 2020 virtual. This is theCUBE virtual, I'm John Furrier, your host. We're not there in person this year because of the pandemic, but we're doing the remote. This is special coverage of the public sector, we got two great guests, Manpreet Mattu, who was the Worldwide Public Sector of Startups and Venture Capital team with AWS, and Michael Jackson who's the leader, general manager of Public Health and Venture Capital and Startups. Gentlemen, thanks for joining me. Thanks for coming up. >> Okay, it's my pleasure, thanks for having. >> I loved love welcome to theCUBE. I just want to say that Amazon never forgets the startups, that's where are they were born and bred it's been a startup. It's always day one as the expression goes, but truly even with the success, not just in the enterprise and starts within public sector, it's still a startup agility mindset, just want to call that out and say congratulations. Okay, let's get into it. Tell us about your roles and your backgrounds and why you're here. >> So, I believe so, I'm the head of AWS Public Sector, VC and Startups team, and our mission really is to help our public sector customers, adopt innovation that is built by the startups. I've been with AWS for about two and a half years. And prior to that, I was in a similar role with Booz Allen, helping our public sector customers, adopt innovation data as well. >> Michael. >> Yeah, so I am the general manager of Public Health, for on the Venture Capital and Startups team. My career here at AWS began just over four years ago. I was brought on to the state and local government team, initially building the public health practice from inception, and I also built and led our U S elections business. And I'm really excited now to transition into this global role, to lead our public health VC and startups practice, and really democratize access to innovation for our startups in the healthcare space. >> Well, great journey. You guys are converging, the VC and startup teams are coming together. A lot of macro trends certainly are tailwinds for you guys. Obviously, the pandemic is forcing, more accelerated modern applications in public sector, and we've been covering more and more success stories, of the change happening quickly. As access to capital continues to be great, and agility with the cloud, how has that impacted your teams and your approach? Can you guys share how that's changed this year? Because there's more pressure now to be digital, there's more opportunities, there's more still capital flowing, how has it impacted your roles? >> Now, so at the very high level, Amazon invests in companies because, we want those companies to be successful. And AWS itself makes a substantial investment, in agility, the startup customers success. We have things like service credits and things like, business nurturing programs that we have built over the course of the last seven, eight years. For example, over the past, you had a loan, Amazon has provided more than a billion dollars in credits, through AWS Activate program, to help startups grow and scale their businesses. And not only that a total of more than three and a half billion dollars in credit to more than 140,000 startups, over the last seven years, all through the course of the Activate program. From more so, on the healthcare side, I would want, certainly MJ to also, speak through or speak to, the challenges that the health system has faced in the COVID times, and how AWS is helping the provider, healthcare providers and the startups, really achieve success, and help the patient populations on that note. >> Michael, weighing on this new programs, you guys are launching in the impact healthcare, I see where we're seeing the frontline workers, I mean, it's everyone seeing it on TV and the newspaper, and it's impacting friends and family, give us the update. >> Absolutely, so we're here today to launch a new program. We call it the Healthcare Acceleration program. And basically, there are two halves to the program, with an undercurrent or a recurring undercurrent, I should say. Just really quickly before I touch on that though, I'd be remissed if I didn't make note of the fact that, you're right capital is still flowing, and it's a really big deal particularly, as healthcare and public health becomes such a priority, but one of the strategic imperatives of our team's role, similar to the way we democratize access to innovation for startups, we also find it really important to democratize access, to resources for founders, underrepresented founders, so, that everyone can have a level playing field, and equal access to those resources and funding, and things of that nature. Getting back to some of the healthcare priorities, in particular, I don't have to tell you about, this pandemic where on the third, and possibly the deadliest wave losing over 1000 Americans per day. And so, not only are we interested in helping our customers, our enterprise customers inject innovation from startups so that they can address clinical aspects, of the pandemic and beyond, but there are underlying rippling societal implications as well. Things that have been exacerbated by the pandemic. Things like mental health, behavioral health, including substance use abuse, clinical clinician burnout, things like social determinants of health, which lead to disproportionately impacted demographics. So, there's a whole lot to unpack and I'm sure we will, but at the highest level, that's what we're looking to help, our enterprise customers address, with the help of our innovative high potential startups. >> I mean, strategic focus, just go a little bit further on how important this is, because, programs are needed, there is burnout, okay. >> Yeah. >> You have mental health, physical health, everything in between. What are you guys launching? What's new? What can people take away right now from AWS, and what startups and when, 'cause a lot of people are changing their focus. I was seeing people leave their jobs, to have to get on this new mission. They're seeing the pain, there's a lot of entrepreneurial energy, happening right now here. Go further, please. >> So, you touched right on it. So, there are two sides. I mentioned there are two halves, and an underlying current, right? So, the two halves are the supply and the demand. The supply side is what we refer to as the startups, vetted high potential, high growth startups, in the health tech space, that we can help to accelerate their go to market, right? We can pair them with mentorship, credits, we call it the 4Cs. There's capital, mapping them potentially to investors, who are interested into accelerating their growth. There's code, technical support, whether it's cloud formation templates, or technical expertise, connections such as other startups, incubators, accelerators, etcetera, and finally mapping them to customers. So, that's, what's in it for the startups. And then on the other side, the enterprise side, again, there are so many enterprises from payers to providers and others who are looking to accelerate their efforts, to digitally transform their enterprise. And so, by partnering with AWS, and the Healthcare Acceleration program, they can trust that there are AWS powered startups, that are vetted and prepared, to inject that sense of urgency, that sense of innovation. And the underlying current, the dots that are being connected is, workforce modernization or economic development, because in many cases, you're right, people are losing their jobs, people are looking at ways that they can, modernize the workforce is locally leverage local talent. And so, entrepreneurship is a great way, to stimulate the local economy, and help older workers or workers who are looking to transition into a more relevant occupations, to do just that. So, this is an all encompassing program. >> Let's get into this health accelerator from AWS. This is something that is on the table, AWS Health Accelerator, who are the stakeholders, and what are the benefits of this program? >> Well, I mean, before we actually, go to the accelerator for me, I think there's this focus on the healthcare, as an industry, as a vertical, is very important to talk about. The industry is experiencing transformation. It is experiencing disruption and the COVID-19 pandemic, has only accelerated that. If you made, it has sort of magnified some of the stressors, which were already there in the system. If you combine that with the sort of the undercurrent that MJ mentioned from a technological perspective, the delivery of healthcare globally is going digital. So, you see technology is like artificial intelligence, machine learning, big data, augmented reality, IoT based variables. All of these technologies are coming together, to enable applications, such as remote diagnostics, patient monitoring, predictive prescriptive healthcare. And we truly feel that this presents a tremendous opportunity to improve the patient experience, and more importantly, the patient outcomes, using these technologies, and these newly enabled applications through those technologies. And as an example, in the U S alone, there are 22 key healthcare AI use cases, that are projected to grow by, or to approximately around $22 billion by 2025. So, in AWS, we are collaborating with the wide spectrum of healthcare providers, with public health organizations, with government agencies, all around the globe to support their effort, to cope with the rippling effects of the COVID-19. And arguably, many of them are visible to us today, but I would argue that many many are not even yet, have been begun to understand by us and by our customers. So, that is the reason why we want to put some emphasis, on healthcare from a public sector standpoint. >> Yeah, that's a great call-out Manpreet, I want to just highlight that, maybe get an additional commentary because, the old days it was just the institution, the hospital and then you're done. And then it was okay, hospital plus the caregiver, the doctors, and the workers, and now the patient. So, holistically, you're calling out the big picture, the patient care, right. Their families, their environment, the caregivers, and the institution, and now the supply chain, all of it integrated together. That's where the action is. And that's where the data comes in, that's where cloud scale can come in. Is that right? Am I getting that right there? >> Yeah, that's absolutely. I'm sorry Manpreet. >> Welcome MJ, go on. >> I was going to say you're absolutely right. In fact, we like to look at it almost like a bullseye, right? So, at the center of the bullseye, like you said, usually, the first stakeholder that comes to mind, is the provider or the coordinator of care. Outside of there, you have the payer, outside of there, you have researchers. And in any even further outside still are your regulators, your healthcare agencies at the local state, and federal levels, including military health. So, it's a rippling effect of customers on that side, as well as you asked about stakeholders on the startup side, there's also a bullseye of influence. Starting with the founder herself, the founder, and her executive team, moving out from there to the startup, as an organization outside from there, we've got incubators and accelerators that are in place, to help accelerate that growth as well. And then farther out you've got investors, VCs, and investors, and so on both sides, supply and demand we're looking to tap into, and accelerate the growth, and make connections between the two. >> Yeah, (indistinct) but when I, in back in real life, when we used to go to games, you walk into the stadium, you buy your ticket with your phone, you go to your seat, concessions guys, deliver things there for you, the fan experience, the players are there. I mean, why can't we have that in healthcare? I was just everything is happening, right. Go for good, yeah. And I think that's the Nirvana, hopefully soon. >> We're working on it. >> Good stuff. I know, I just love the vision, I think is so relevant and super important. Now, let's get into this health accelerator. What's this all about? Let's get into that. >> So, the health accelerator will be, a multi-week on-demand program. Where we're going to map high potential vetted startups, to a number of resources, right. I mentioned before that there will be mentorship, there will be technical experts who will be able to, take these startups who have established some presence, but we want to accelerate their ability to go deeper specifically into public health, throughout that ecosystem that I just described, right? Starting with providers and coordinators, payers, researchers, regulators. We want to give them a way to go deep into this, heavily regulated industry, so that they can not only have access to the innovation that many startups would not otherwise, like Manpreet mentioned machine learning AI, but they also have access to the resources, to ensure their success. >> What kind of problems are you guys trying to solve with this? I mean, is there a specific vetting process, is there a criteria? Is there a bar to all over share some specifics? >> Yeah, absolutely. So, for the past few years, a lot of the major change challenges, for our public health customers have been the same, but they require a new approach. And I like to call our approach the HIGH FIVE. So, some of those challenges that have been traditionally, lingering for the past few years, equal social determinants of health. Social determinants, when we talk about that, we not only refer to the nonclinical contributors to a person's overall wellness. So, you think about issues like food deserts or recidivism homelessness, all of that transportation to access to care, right, all of that contributes. But then there's also disparities and health outcomes. When you think about socioeconomic differences, rural health, ethnic and racial minorities, so, that all factors into social determinants of health. Then there's also aging. Now, these are the strategic pillars that we like to focus on, or that we are focusing on. When I mentioned aging every day in the U S, 10,000 people celebrate their 65th birthday. Many of those individuals are suffering from comorbidities, from hypertension, diabetes, cancer, and now the lingering impact of COVID-19. And so, as these aging individuals continue to live longer, the goal is to improve the quality of their life as well. And so, many of them look to technology to age independently at home, etcetera. So, that's our second strategic pillar. The third, is mental and behavioral health. So, when I talk about mental health, I mean, everything from mild depression, all the way through suicide prevention, and especially these days with COVID-19, we see a lot of clinicians suffering from burnout. And so, it's important, that we take care of the frontline workers, those healthcare providers, and even outside of COVID-19, you think about the ways that the patient population, has continued to expand, and the growth within the provider market has not, or the pool of providers has not nearly expanded at the same rate. We've got people living longer, we've got more people than ever insured. And so, we need to leverage technology to help a stagnant, number of providers to treat a growing pool of patients, without sacrificing the quality of care. And then finally, we've got environmental health. From air quality to water purity. It's important to understand the correlation between, the environment and the health care of our population. So, those are the pillars. I know I mentioned the HIGH FIVE, the fifth is not specific to healthcare. I touched on it a little bit earlier, but the fifth is, it is democratizing access to innovation, to resources, specifically for founders from underrepresented communities. >> And that's great insight, Michael great, great Schaeffer pointed that out. Manpreet take us on the final word here. Venture Capital, Startups, AWS, what's the current state share with us, the current worldview from your perspective. >> Oh, so, bringing home this point that MJ mentioned, the strategic plan of focus areas. And if you, look at all those strategic areas there's, you can really sort of put those into two buckets. One is the patient side of the bucket, and then there's the provider side of the bucket, or the caretaker side of the bucket. And if the patient side, what we want to do is work with startups that are, really working across a broad spectrum of use cases, but to solve those two key challenges of the, one on the patient's side and other on the provider side. Then the end goal of providing patient experience, and patient outcomes. For the patient side, it's the patient experience, patient engagement, patient outcomes. So, the startups looking on those sides, on those use cases of criteria. And then we have the provider side where, we want to ensure that the providers have the right set of technologies, the right set of solutions, right set of innovation, to help them where healthcare operations. You have all seen in COVID times, how the provider systems are getting overwhelmed. And that's where the healthcare operations comes into play. Clinical decision support. Now, many patients cannot get to the hospitals. So, how do we provide through our startup partners for startup customers, those solutions where remote diagnostics, remote imaging or remote health delivery could be provided. Things like predictive and prescriptive health solutions. How can we work with our startups to provide, those sort of solutions to the providers, to again, at the end, the better the outcome of the patients, right? So, that's what we were looking at. And that's what this program is all about. Working with public sector provider side of the house and the customers understanding, and helping them understand the need as well, and then bringing the right set of startup solutions, and help solve those challenges that they are facing, and the patients are facing as well. MJ, I'm sure you want to close it out, with some thoughts too. >> Okay. >> Absolutely, I would just close it with this, our goal, like Manpreet said, is to match the high potential startups, with the, the enterprises who are desiring those solutions, and success for us, we'll have three traits. It will be valuable, meaning that there will be a true alignment between what our startups offer and what the market needs. It will be measurable, so that we can quantify the improvement and outcomes. And finally, it will be sustainable. So, beyond COVID-19 beyond the opioid crisis, beyond any situation or condition, we look to bring solutions to market through our startups, that are going to truly sustain a transformative approach to modernizing public health enterprises. >> Great job again, and important work and DevOps, impacting healthcare in all kinds of ways. And it's super important work. I'm glad you guys are doing it, and it's going to develop out beautifully, and if I can give you a high five, Michael, I'll give you a high five off in-person, but remotely, >> Virtual. >> Get virtual high five great program. We're going to spread the word, good work. >> Thank you. >> Thanks for doing it, I appreciate it. >> Thank you very much for your time. >> Okay, it's theCUBE coverage virtual, we are theCUBE virtual bringing all the coverage, super important work being done in public sector, cloud enabling it, great people important, and of course, happening at re:Invent. Thanks for watching. (upbeat music)

>> Narrator: From around the globe it's theCUBE! With digital coverage of UiPath Live, the release show. Brought to you by UiPath. >> Hi everybody this is Dave Valenti, welcome back to our RPA Drill Down. Ted Kummert is here he is Executive Vice President for Products and Engineering at UiPath. Ted, thanks for coming on, great to see you. >> Dave, it's great to be here, thanks so much. >> Dave your background is pretty interesting, you started as a Silicon Valley Engineer, they pulled you out, you did a huge stint at Microsoft. You got experience in SAS, you've got VC chops with Madrona. And at Microsoft you saw it all, the NT, the CE Space, Workflow, even MSN you did stuff with MSN, and then the all important data. So I'm interested in what attracted you to UiPath? >> Yeah Dave, I feel super fortunate to have worked in the industry in this span of time, it's been an amazing journey, and I had a great run at Microsoft it was fantastic. You mentioned one experience in the middle there, when I first went to the server business, the enterprise business, I owned our Integration and Workflow products, and I would say that's the first I encountered this idea. Often in the software industry there are ideas that have been around for a long time, and what we're doing is refining how we're delivering them. And we had ideas we talked about in terms of Business Process Management, Business Activity Monitoring, Workflow. The ways to efficiently able somebody to express the business process in a piece of software. Bring systems together, make everybody productive, bring humans into it. These were the ideas we talked about. Now in reality there were some real gaps. Because what happened in the technology was pretty different from what the actual business process was. And so lets fast forward then, I met Madrona Venture Group, Seattle based Venture Capital Firm. We actually made a decision to participate in one of UiPath's fundraising rounds. And that's the first I really came encountered with the company and had to have more than an intellectual understanding of RPA. 'Cause when I first saw it, I said "oh, I think that's desktop automation" I didn't look very close, maybe that's going to run out of runway, whatever. And then I got more acquainted with it and figured out "Oh, there's a much bigger idea here". And the power is that by really considering the process and the implementation from the humans work in, then you have an opportunity really to automate the real work. Not that what we were doing before wasn't significant, this is just that much more powerful. And that's when I got really excited. And then the companies statistics and growth and everything else just speaks for itself, in terms of an opportunity to work, I believe, in one of the most significant platforms going in the enterprise today, and work at one of the fastest growing companies around. It was like almost an automatic decision to decide to come to the company. >> Well you know, you bring up a good point you think about software historically through our industry, a lot of it was 'okay here's this software, now figure out how to map your processes to make it all work' and today the processes, especially you think about this pandemic, the processes are unknown. And so the software really has to be adaptable. So I'm wondering, and essentially we're talking about a fundamental shift in the way we work. And is there really a fundamental shift going on in how we write software and how would you describe that? >> Well there certainly are, and in a way that's the job of what we do when we build platforms for the enterprises, is try and give our customers a new way to get work done, that's more efficient and helps them build more powerful applications. And that's exactly what RPA does, the efficiency, it's not that this is the only way in software to express a lot of this, it just happens to be the quickest. You know in most ways. Especially as you start thinking about initiatives like our StudioX product to what we talk about as enabling citizen developers. It's an expression that allows customers to just do what they could have done otherwise much more quickly and efficient. And the value on that is always high, certainly in an unknown era like this, it's even more valuable, there are specific processes we've been helping automate in the healthcare, in financial services, with things like SBA Loan Processing, that we weren't thinking about six months ago, or they weren't thinking about six months ago. We're all thinking about how we're reinventing the way we work as individuals and corporations because of what's going on with the coronavirus crisis, having a platform like this that gives you agility and mapping the real work to what your computer state and applications all know how to do, is even more valuable in a climate like that. >> What attracted us originally to UiPath, we knew Bobby Patrick CMO, he said "Dave, go download a copy, go build some automations and go try it with some other companies". So that really struck us as wow, this is actually quite simple. Yet at the same time, and so you've of course been automating all these simple tasks, but now you've got real aspiration, you're glomming on to this term of Hyperautomation, you've made some acquisitions, you've got a vision, that really has taken you beyond 'paving the cow path' I sometimes say, of all these existing processes. It's really trying to discover new processes and opportunities for automation, which you would think after 50 or whatever years we've been in this industry, we'd have attacked a lot of it, but wow, seems like we have a long way to go. Again, especially what we're learning through this pandemic. Your thoughts on that? >> Yeah, I'd say Hyperautomation. It's actually a Gartner term, it's not our term. But there is a bigger idea here, built around the core automation platform. So let's talk for a second just what's not about the core platform and then what Hyperautomation really means around that. And I think of that as the bookends of how do I discover and plan, how do I improve my ability to do more automations, and find the real opportunities that I have. And how do I measure and optimize? And that's a lot of what we delivered in 20.4 as a new capability. So let's talk about discover and plan. One aspect of that is the wisdom of the crowd. We have a product we call Automation Hub that is all about that. Enabling people who have ideas, they're the ones doing the work, they have the observation into what efficiencies can be. Enabling them to either with our Ask Capture Utility capture that and document that, or just directly document that. And then, people across the company can then collaborate eventually moving on building the best ideas out of that. So there's capturing the crowd, and then there's a more scientific way of capturing actually what the opportunities are. So we've got two products we introduced. One is process mining, and process mining is about going outside in from the, let's call it the larger processes, more end to end processes in the enterprise. Things like order-to-cash and procure-to-pay, helping you understand by watching the events, and doing the analytics around that, where your bottle necks, where are you opportunities. And then task mining said "let's watch an individual, or group of individuals, what their tasks are, let's watch the log of events there, let's apply some machine learning processing to that, and say here's the repetitive things we've found." And really helping you then scientifically discover what your opportunities are. And these ideas have been along for a long time, process mining is not new. But the connection to an automation platform, we think is a new and powerful idea, and something we plan to invest a lot in going forward. So that's the first bookend. And then the second bookend is really about attaching rich analytics, so how do I measure it, so there's operationally how are my robots doing? And then there's everything down to return on investment. How do I understand how they are performing, verses what I would have spent if I was continuing to do them the old way. >> Yeah that's big 'cause (laughing) the hero reports for the executives to say "hey, this is actually working" but at the same time you've got to take a systems view. You don't want to just optimize one part of the system at the detriment to others. So you talk about process mining, which is kind of discovering the backend systems, ERP and the like, where the task mining it sounds like it's more the collaboration and front end. So that whole system thinking, really applies, doesn't it? >> Yeah. Very much so. Another part of what we talked about then, in the system is, how do we capture the ideas and how do we enable more people to build these automations? And that really gets down to, we talk about it in our company level vision, is a robot for every person. Every person should have a digital assistant. It can help you with things you do less frequently, it can help you with things you do all the time to do your job. And how do we help you create those? We've released a new tool we call StudioX. So for our RPA Developers we have Studio, and StudioX is really trying to enable a citizen developer. It's not unlike the art that we saw in Business Intelligence there was the era where analytics and reporting were the domain of experts, and they produced formalized reports that people could consume. But the people that had the questions would have to work with them and couldn't do the work themselves. And then along comes ClickView and Tableau and Power BI enabling the self services model, and all of a sudden people could do that work themselves, and that enabled powerful things. We think the same arch happens here, and StudioX is really our way of enabling that, citizen developer with the ideas to get some automation work done on their own. >> Got a lot in this announcement, things like document understanding, bring your own AI with AI fabric, how are you able to launch so many products, and have them fit together, you've made some acquisitions. Can you talk about the architecture that enables you to do that? >> Yeah, it's clearly in terms of ambition, and I've been there for 10 weeks, but in terms of ambition you don't have to have been there when they started the release after Forward III in October to know that this is the most ambitious thing that this company has ever done from a release perspective. Just in terms of the surface area we're delivering across now as an organization, is substantive. We talk about 1,000 feature improvements, 100's of discreet features, new products, as well as now our automation cloud has become generally available as well. So we've had muscle building over this past time to become world class at offering SAS, in addition to on-premises. And then we've got this big surface area, and architecture is a key component of how you can do this. How do you deliver efficiently the same software on-premises and in the cloud? Well you do that by having the right architecture and making the right bets. And certainly you look forward, how are companies doing this today? It's really all about Cloud-Native Platform. But it's about an architecture such that we can do that efficiently. So there is a lot about just your technical strategy. And then it's just about a ton of discipline and customer focus. It keeps you focused on the right things. StudioX was a great example of we were led by customers through a lot of what we actually delivered, a couple of the major features in it, certainly the out of box templates, the studio governance features, came out of customer suggestions. I think we had about 100 that we have sitting in the backlog, a lot of which we've already done, and really being disciplined and really focused on what customers are telling. So make sure you have the right technical strategy and architecture, really follow your customers, and really stay disciplined and focused on what matters most as you execute on the release. >> What can we learn from previous examples, I think about for instance SQL Server, you obviously have some knowledge in it, it started out pretty simple workloads and then at the time we all said "wow, it's a lot more powerful to come from below that it is, if a Db2, or an Oracle sort of goes down market", Microsoft proved that, obviously built in the robustness necessary, is there a similar metaphor here with regard to things like governance and security, just in terms of where UiPath started and where you see it going? >> Well I think the similarities have more to do with we have an idea of a bigger platform that we're now delivering against. In the database market, that was, we started, SQL Server started out as more of just a transactional database product, and ultimately grew to all of the workloads in the data platform, including transaction for transactional apps, data warehousing and as well as business intelligence. I see the same analogy here of thinking more broadly of the needs, and what the ability of an integrated platform, what it can do to enable great things for customers, I think that's a very consistent thing. And I think another consistent thing is know who you are. SQL Server knew exactly who it had to be when it entered the database market. That it was going to set a new benchmark on simplicity, TCO, and that was going to be the way it differentiated. In this case, we're out ahead of the market, we have a vision that's broader than a lot of the market is today. I think we see a lot of people coming in to this space, but we see them building to where we were, and we're out ahead. So we are operating from a leadership position, and I'm not going to tell you one's easier that the other, and both you have to execute with great urgency. But we're really executing out ahead, so we've got to keep thinking about, and there's no one's tail lights to follow, we have to be the ones really blazing the trail on what all of this means. >> I want to ask you about this incorporation of existing systems. Some markets they take off, it's kind of a one shot deal, and the market just embeds. I think you guys have bigger aspirations than that, I look at it like a service now, misunderstood early on, built the platform and now really is fundamental part of a lot of enterprises. I also look at things like EDW, which again, you have some experience in. In my view it failed to live up to a lot of it's promises even though it delivered a lot of value. You look at some of the big data initiatives, you know EDW still plugs in, it's the system of record, okay that's fine. How do you see RPA evolving? Are we going to incorporate, do we have to embrace existing business process systems? Or is this largely a do-over in your opinion? >> Well I think it's certainly about a new way of building automation, and it's starting to incorporate and include the other ways, for instance in the current release we added support for long running workflow, it was about human workflow based scenarios, now the human is collaborating with the robot, and we built those capabilities. So I do see us combining some of the old and new way. I think one of the most significant things here, is also that impact that AI and ML based technologies and skills can have on the power of the automations that we deliver. We've certainly got a surface area that, I think about our AI and ML strategy in two parts, that we are building first class first party skills, that we're including in the platform, and then we're building a platform for third parties and customers to bring their what their data science teams have delivered, so those can also be a part of our ecosystem, and part of automations. And so things like document understanding, how do I easily extract data from more structured, semi-structured and completely unstructured documents, accurately? And include those in my automations. Computer vision which gives us an ability to automate at a UI level across other types of systems than say a Windows and a browser base application. And task mining is built on a very robust, multi layer ML system, and the innovation opportunity that I think just consider there, you know continue there. You think it's a macro level if there's aspects of machine learning that are about captured human knowledge, well what exactly is an automation that captured where you're capturing a lot of human knowledge. The impact of ML and AI are going to be significant going out into the future. >> Yeah, I want to ask you about them, and I think a lot of people are just afraid of AI, as a separate thing and they have to figure out how to operationalize it. And I think companies like UiPath are really in a position to embed UI into applications AI into applications everywhere, so that maybe those folks that haven't climbed on the digital bandwagon, who are now with this pandemic are realizing "wow, we better accelerate this" they can actually tap machine intelligence through your products and others as well. Your thoughts on that sort of narrative? >> Yeah, I agree with that point of view, it's AI and ML is still maturing discipline across the industry. And you have to build new muscle, and you build new muscle and data science, and it forces you to think about data and how you manage your data in a different way. And that's a journey we've been on as a company to not only build our first party skills, but also to build the platform. It's what's given us the knowledge that to help us figure out, well what do we need to include here so our customers can bring their skills, actually to our platform, and I do think this is a place where we're going to see the real impact of AI and ML in a broader way. Based on the kind of apps it is and the kind of skills we can bring to bear. >> Okay last question, you're ten weeks in, when you're 50, 100, 200 weeks in, what should we be watching, what do you want to have accomplished? >> Well we're listening, we're obviously listening closely to our customers, right now we're still having a great week, 'cause there's nothing like shipping new software. So right now we're actually thinking deeply about where we're headed next. We see there's lots of opportunities and robot for every person, and that initiative, and so we're launched a bunch of important new capabilities there, and we're going to keep working with the market to understand how we can, how we can add additional capability there. We've just got the GA of our automation cloud, I think you should expect more and more services in our automation cloud going forward. I think this area we talked about, in terms of AI and ML and those technologies, I think you should expect more investment and innovation there from us and the community, helping our customers, and I think you will also see us then, as we talked about this convergence of the ways we bring together systems through integrate and build business process, I think we'll see a convergence into the platform of more of those methods. I look ahead to the next releases, and want to see us making some very significant releases that are advancing all of those things, and continuing our leadership in what we talk about now as the Hyperautomation platform. >> Well Ted, lot of innovation opportunities and of course everybody's hopping on the automation bandwagon. Everybody's going to want a piece of your RPA hide, and you're in the lead, we're really excited for you, we're excited to have you on theCUBE, so thanks very much for all your time and your insight. Really appreciate it. >> Yeah, thanks Dave, great to spend this time with you. >> All right thank you for watching everybody, this is Dave Velanti for theCUBE, and our RPA Drill Down Series, keep it right there we'll be right back, right after this short break. (calming instrumental music)

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE Conversation. >> Hi, everyone. Welcome to this CUBE Conversation here in Palo Alto, theCUBE Studios. I'm John Furrier, host of theCUBE. We're here with two great guests, Carl Eschenbach, partner at Sequoia Capital on the board of Cohesity as well with the CMO Lynn Lucas. Lynn, great to see you. Carl, thanks for coming back on. >> Great to be here. >> Appreciate it. So Lynn, you know we've been following you guys for many many years, watching the rapid growth of Cohesity. Funding round after funding round, Unicorn. From a start up, to going through the atmosphere heading into orbit, nice growth. >> Mid-size company I would say now. >> Yeah >> Yeah >> No longer a startup. >> Growing like crazy. >> No longer a startup, yeah. >> Good round, good financing track. Thanks to Sequoia. >> Well, we're proud and happy investors and partners with them, that's for sure. >> Yeah, one of the things we're super excited about right now, Lynn I want to get your thoughts on this is that, how do you maintain the growth because cloud is an ever changing landscape, data management's really hot and changing. What's been the success formula for you guys, staying ahead? Both in terms of continuing to push the brand, push the message and success. What's been the formula? >> Well, I think it starts with our founder, Mohit Aron, and his vision and strategy which, if you go back, he's been extraordinarily consistent on and he saw this massive opportunity to take hyper-convergence, which of course he's really the father of from Nutanix and bring it to this whole other area of data, the vast majority of data that enterprises have. That is in all of these different silos and so really I think that Cohesity has this opportunity to be a once in a generation platform company much like VMware and really change the way enterprises, protect, manage, store and ultimately do more with their data. So, I'm going to say it's less about the brand. I'm proud about the brand. But, it's really about... >> You did a great job the brand, but I think the execution is. I think one thing I love about this market cloud in the next ten years ahead of us is that you can come into the market with a feature or a specific thing, like backup and turn it into a broad ranging high-growth, billions dollars of value. I think that's what you guys are on. But I, while we have Carl here, I want to put him on the spot because, you know, of his experience at VMware and now at Sequoia. What's he bringing to the table for Cohesity? What's his operational knowledge? What is some of the things Carl's brought to Cohesity? >> Oh, my gosh. >> What hasn't he brought. >> Well, Carl is obviously incredibly experienced and brings a wealth of go to market knowledge and connections and advice for us. I think instrumental in helping us see how to scale. As well as, change and shift the business model over to software and subscription. Which is what Cohesity did last year and is right in line with the move towards the cloud. >> Carl, your thoughts? >> I have to say one of the things just to echo, so thank you for those kind words. But quite frankly its all about execution and these folks at Cohesity know how to execute. If you just look at their scale over the last three years and their ability to execute. It's pretty impressive, not on the technology side only. But, if you think about their go to market motion and what they've not both here in the U.S., internationally, over into, you know, Asia and in Japan with the joint venture they have with SoftBank and some of the others. It's been amazing to watch them scale and to go market and also the ecosystem that they started to build around them and leveraging partners like HPE and Cisco as Cohesity has transitioned from being an appliance solution to being a software and data management platform and moving the hardware to other partners. It's been amazing to watch that transformation happen. So, it's technology, yes. But, it's also every other component and piece of the business that's been able to scale through good execution. >> Let's talk about the ecosystem, cause I think it's a super important, ever changing conversation. Especially as the bigger players get bigger and then the mid-size folks like you guys get bigger as well. The relationships change. You've certainly seen your share, Carl, at VMware. At VMworld every year, the ecosystem has its growth. It changes over, new value propositions are coming in. You have a constant rotation through the ecosystem dynamic. >> Yeah, no. >> What are some of the going on now that Cohesity's taken advantage of? >> What are they... >> Yeah, so because Cohesity is actually building a true platform as Lynn was articulating. If you're a platform in a data center it means two things. You have to partner with people on the south-bound side of that platform and the north-bound side of the platform because everything's going to go through a platform and because of that you form a very rich ecosystem but you also form sometimes competitors. In this world everyone I think describes it as friends and enemies. They're frenemies and they've done a very good job at that but at the same time they've really focused on key partners like an HPE or a Cisco or many others that can really differentiate themselves and allow them to focus on what they truly are and that's a data management software company. So, I think they've done a really good job navigating the ecosystem and building off of it and aligning with the right people. For example you sit here at VMWworld today. Look at the partnership they have with VMware they have V-ready, you know, certification across vsan, their infrastructure platform. Vcloud Director, AWS, you name it. So, I think they've done a great job and that's thanks to people like Lynn and the team. >> Lynn, talk about the ecosystem dynamic. Because you guys are actively market a big booth every year at VMworld as well as Amazon re:invent and other shows. You have to be out there. What are you hearing? What are some of the dynamics that your working through? >> Well speaking of VMworld and VMware they really were the original ecosystem partner and I think we believe that north of 70 percent of our customers are VMware customers and they're getting better value out of that. But, we haven't talked a lot about the cloud and that's obviously a massive ecosystem that's continuing to develop and bringing those two things together is something that Cohesity specializes in. With our native capabilities, with Amazon, Azure, Google but the other third piece of the ecosystem that we're now developing is the applications and that's unique to Cohesisty really redefining data management. Just announced Cohesity CyberScan based on Tenable running on the Cohesity platform. Prior to the, Splunk, running on the platform. So we're developing these ecosystem partnerships in new ways with application providers. >> So when are we going to see Cohesity world. (laughing) >> I am just so happy to be at Vmworld it's a great place for us to meet a lot of customers and partners. So we'll stay with that. >> Carl you were talking about, before we came on camera, about your first VMworld. You know, oh my god, it's huge, now it's even bigger. This is the opportunity for firms like Cohesity, if they continue the momentum. Building out applications which if you think about it that's an enabling technology. You can enable developers to be successful. That truly is a testament to what a true platform is. >> Yeah, again, I think, she said they don't have a big user conference yet. I don't think it will be long before we such momentum in the market that we will have a user conference at some point. Where you will see a large turnout of people using the technology. People from the ecosystem there and then developers as well and lastly you'll start to see application vendors like a Splunk or a Tenable who are actually now running their applications on top of this. This isn't just data management but it's also supporting applications and when you pull those three different you know constituents together you have a pretty big opportunity to pull off some type of platform show. >> Lynn, I got to put you on the spot here for a minute you got Carl, he's also a partner with Sequoia Venture Capital. What are the pros and cons with working with a big time tier one renowned VC like Sequoia is? Sequoia's Don Valentine is a well documented story. Moritz goes on, the young guns in there now. Get the operating experience from like the Carl's. Pretty established, they got a great business model, you know that. What's the pros and cons of working for the big time Sequoia. >> I've not seen any cons. Pros are as you said the operating experience and I think also the experience in guiding a company through this hyper growth. Cohesity is now well over 1200 employees. Last year, when you and I sat here much less than that, right? And they've seen it and done it before with other partners or with other portfolio companies that I think is one of the best pieces of advice that Carl has given us coming into our company is how to maintain that culture and that focus on the mission as we move through this tremendous growth phase. >> That's interesting, Sequoia loves you when your growing but then, but they've seen success. The cons haven't come yet. But, if you continue to grow there will be no cons. Everyone's happy and growing. But, I want to get your thoughts because Sequoia also builds world-class companies and they also, Apple the names are legendary. Your founder on theCUBE told me that he doesn't just want to get an exit. He wants to build world class company. >> That's right >> Well, exit is not as important as like EMEA. But in like public that happens. He's not in it for the cash. He wants build a durable world class company. >> That's exactly right, right Mohit has had a number of successes, Google, Nutanix. So he's not in this for the short return and we really are focused on building a culture and a set of values and a long term sustainable business and he really means what he says about. He's here to change the world and data is the foundation of what most businesses are going to compete on and he believes he can really empower organizations to do that and we can build a great culture and a great company while were helping. >> Carl when you hear that.. >> I want to piggyback off what Lynn just said and its exactly what Lynn articulated about Mohit to want to build a big enduring company that stands the test of time. If you look at our ethos at Sequoia we want to partner with founders from idea to IPO and beyond. We're not looking for a quit hit, a quick win. We want to be with them through IPO and beyond and build big legendary companies that stand the test of time and in the form of Cohesity we have that opportunity and we're well on that path to build a legendary platform company that will service both the enterprise in the cloud companies into the future. That's our mission, so I think our missions are aligned. >> Well you just answered the question I was going to ask you. That is music to your ears this is the kind of model you guys want and certainly you guys do a good job of exiting out on EMEA and doing, making your LPs a lot of money. You got to make money. >> Right, but, you know a lot of people think when our companies go public this is an exit for us. It's just an event. If we believe in the companies were going to hold long into the public market from that idea and that seed investment, like we did here at Cohesity, well beyond the IPO. >> There's a renaissance going on , I love it because two things are happening in this next 10 years. You seen a systems platform mindset come back versus the quick hits and also people want to build big companies they don't want to do the quick flips anymore. So at lot of young entrepreneurs are, they are in it for a mission. This is a new vibe. What kind of advice do you give entrepreneurs that are looking to bring that Cohesity model and get the attention of Sequoia? What are some of the things that you see as success for the young entrepreneurs out there? >> Yeah, so it is around the word mission. Like we want to partner with people that are mission driven that are going to have a huge impact on business and society as a whole and even you know the social efforts in our world. So were looking for people that want to change the trajectory of whatever it is they are addressing and we think for example with Cohesity there's a radical transformation taking place in the infrastructure and someone's got to innovate because a lot of innovators today are not coming from the incumbent it's coming from the next generation of founders like Mohit and he's very mission driven. Build a big company, service a community of people change the way people store and think about data and manage it and that mission-centric founder is one we love to partner with. >> Final question I'd love to get both your take on this question, Lynn and Carl is. When you meet someone that may not be inside the ropes of technology like the enterprise tech like we are the few and others and they ask you the question "Why is Cohesity so successful?" How do you describe the dynamics of the marketplace and Cohesity's role in it on it's success? What is the answer to that question? >> I think it's really two things. So one is I think that there is this generational shift in the architecture that underpins data and we've got a perfect storm with data doing exponential growth and as Carl's been saying there really hasn't been a lot of innovation in the infrastructure in more than a decade. Mohit saw that, but then that's combined with a mission, a passion for customers and sticking to that execution of serving the customer and that's making us successful. >> Carl your thoughts after that. >> Listen, it starts with technology and to have great technology you have to have a great technical founder and we have that in Mohit, time and time again. I can go, we've all talked about Mohit and how special he is. At the same time you need to build a company that has a special culture, that can stand the test of time, that is resilient, that has grit and has passion and perseverance for the work their doing around their mission and I think we have all of that in Cohesity and that's a lot of it's because of Mohit and people like Lynn that he's brought in around his executive team. You can just see that permeate through the entire organization. >> That's awesome. Thanks for sharing the insight. Carl, great to have you comment here with Lynn on Cohesity, I know your on the board. Lot of great things happening, looking to see what's happening at the VMware parties. Thanks for hosting some awesome events for the community. >> Can't wait to be back. Bring some of our customers on. >> Thanks for spending the time. This is theCUBE Conversation here at Palo Alto. I'm John Furrier, thanks for watching. (upbeat music)

(funky guitar music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, This is theCUBE conversation. >> Everyone welcome to this CUBE conversation here in Palo Alto, California CUBE studios, I'm John Furrier, the host of theCUBE. Were with CUBE alumni, special guest Amit Walia, President of Products & Marketing at Informatica. Amit, it's great to see you. It's been a while. It's been a couple of months, how's things? >> Good to be back as always. >> Welcome back. Okay, Informatica worlds is coming up, we have a whole segment on that but we have been covering you guys for a long long time, data is at the center of the value proposition again and again, it's more amplified now, the fog is lifting. >> Sure. >> And the world is now seeing what we were talking about four years ago. (giggles) >> Yeah. >> With data, what's new? What's the big trends that going on that you guys are doubling down on? What's new, what's changed? Give us the update. >> Sure. I think we have been talking the last couple of years, I think your right, data has becoming more and more important. I think, three things we see a lot. One is obviously, you saw this whole world of digital transformation. I think that has de faintly has picked up so much steam now. I mean, every company is going digital and obviously that creates a whole new paradigm shift for companies to carry out almost recreate themselves, rebuild them, so data becomes the new definition. And that's what we call those things you saw at Infomatica even before data3.org, but data is the center of everything, right? And you see the volume of data growth, you know, the utilization of data to make decisions, whether it's, you know, decisions on the shop floor, decisions basically related to cyber security or whatever it is. And the key to what you see different now is the whole AI assisted data management. I mean the scale of complexity, the scale of growth, you know, multi-cloud, multi-platform, all the stuff that is in front of us, it's really difficult to run the old way of doing things, so that's why we see one thing that we see a whole lot is AI is becoming a lot more mainstream, still early days but it's assisting the whole ability for companies, what I call, exploit data to really become a lot more transformative. >> You have been on this for a while, again we can go back to theCUBE archives, we can almost pull out clips from two years ago, be relevant today, you know, the data control, understanding >> Yeah. >> Understanding where the data governance is-- >> Sure. >> That's always a foundational thing but you guys nailed the chat bots, you have been doing AI was previous announcements, this is putting a lot of pressure on you, the president of the products, you got to get this out there. >> What's new? What's happening inside Informatica? pedaling as fast as you can? What is some of the updates? >> No. >> Gives us the-- >> The best example always is like a duck, right? Your really swimming and feel things are calm at the top and then you are really paddling. No, I think it's great for us. I think, I look at AI's, AI is like, there is so much FUD [fear, uncertainty and doubt] around it and machine learning AI. We look at it as two different ways. One is how we leverage machine learning within our products to help our customers. Making it easy for them, like I said, so many different data types, think of IOT data, unstructured data, streaming data, how do you bring all that stuff together and marry it with your existing transactional data to make sense. So, we're leveraging a lot of machine learning to make the internal products a lot more easier to consume, a lot more smarter, a lot more richer. The second thing is that, we're what we call it our AI, CLAIRE, which we unveiled, if you remember, a couple of years ago at the Informatica World. How that then helps our customers make smarter decisions, you know, in data science and all of these data workbenches, you know, the old statistical models is only as good as they can ever be. So, we leveraging helping our customers see the value proposition of our AI, CLAIRE, then to what I make things that, you know, find patterns, you know, statistical models cannot. So, to me I look at both of those really, leveraging ML to shape our products, which is where we do a lot of innovation and then creating our AI, CLAIRE, to help customers to make smarter decisions, easier decisions, complex decisions, which I called the humans or statistical models, really cannot. >> Well this is the balance with machines and humans. >> Right. >> working together, you guys have nailed this before and I'm, I think this was two years ago. I started to hear the words, land, adopt, expand, form you guys, right? Which is, you got to get adoption. >> Right. >> And so, as you're iterating on this product focus, you got to getting working, making secure your products-- >> Big, big maniacal focus on that one. >> So, tell me what you have learned there because that's a hard thing. >> Right. >> You guy are doing well at it. You got to get adoption, which means you got to listen customers, you got to do the course correction. >> Yeah. >> what's the learnings coming out of that piece of that. >> That's actually such a good point. We've made such, we've always been a customer centric company but as you said, like, as whole world shifted towards a new subscription cloud model, we've really focused on helping our customers adopt our products and you know, in this new world, customers are struggling with new architectures and everything, so we doubled down on what we called customer success. Making sure we can help our customers adopt the products and by the way it's to our benefit. Our customers get value really quickly and of course we believe in what we call a customer for life. Our ability to then grow with our customers and help them deliver value becomes a lot better. So, we really focused, so, we have globally across the board customers, success managers, we really invest in our customers, the moment a customer buys a product from us, we directly engage with them to help them understand for this use case, how you implement the product. >> It's not just self service, that's one thing that I appreciate 'cause I know how hard it is to build products these days, especially with the velocity of change but it's also when you have a large scale data. >> Yeah. >> You need automation, you got to have machine learning, you got to have these disciplines. >> Sure. >> And this is both on your end and but also on the customer. >> Yes. >> Any on the updates on the CLAIRE and some customer learnings you're seeing that are turning into use cases or best practices, what are some of them? >> So many of them. So take a simple example, right? I mean, we think of, we take these things for granted, right? I mean, take note, we don't talk about IOB these days right? All these cell cells, we were streaming data, right? Or even robots on the shop floor. So much of that data has no schema, no structure, no definition, it's coming, right? Netflix data and for customers there is a lot of volume in it, a lot of it could be junk, right? So, how do you first take that volume of data? Create some structure to it for you to do analytics. You can only do analytics if you put some structure to it, right? So, first thing is I've leverage CLAIRE, we help our customers to create, what I call, schema and you can create some structure to it. Then what we do allow is basically CLAIRE through CLAIRE, it can naturally bring what we have the data quality on top of it, like how much of it is irrelevant, how much of it is noise, how much of it really makes sense, so, then, as you said it, signal from the noise We are helping our customers get signal from the noise of data. That's where it AI comes very handy because it's very manual, cumbersome, time consuming and sometimes very difficult to do. So, that's a area we have leveraged creating structure and data quality on top and finding rules that didn't naturally probably didn't exist, that you and me wouldn't be able to see. Machines are able to do it and to your point, our belief is, this is my 100% belief, we believe AI assisting the humans. We have given the value of CLAIRE to our users, so it complements you and that's where we are trying to help our users get more productive and deliver more value to you faster. >> Productivity is multifold, it's like, also, efficiency, people wasting time on project that can be automated, so you can focus that valuable resource somewhere else. >> Yeah. >> Okay, let's shift gears onto Informatica World coming up. Let's spend some time on that. What's the focus this year, the show, it's coming up, right around the corner, what's going to be the focus? What's going to be the agenda? What's on the plate? >> Give you a quick sense on how it's shape up, it's probably going to be our Informatica World. So, it's 20th year, again back in Waze, you know, we love Waze of course. We have obviously, a couple of days lined up over there, I know you guys will be there too. A great set of speakers. Obviously, we will have me on stage, speakers like, we'll have some, the CEO of Google Cloud, Thomas Kurian is going to be there, we'll have on the main stage with Anil, we'll have the CEO of Databricks, Ali, with me, we'll also have CMO of AWS, Ariel, there, then we have a couple of customers lined up, Simon from Credit Suisse, Daniel is the CDO of Nissan, we also have the Head of AI, Simon Guggenheimer from Microsoft as well as the Chief Product Officer of Tableau, Francois Ajenstat, so, we have a great line up of speakers, customers and some of our very very strategic partners with us. If you remember last year, We also had Scott Guthrie there main stage. 80 plus sessions, pretty much 90% lead by customers. We have 70 to 80 customers presenting. >> Technical sessions or going to be a Ctrack? >> Technical, business, we have all kinds of tracks, we have hands on labs, we have learnings, customers really want to learn our products, talk with the experts, some want to the product managers, some want to talk to the engineers, literally so many hands on labs, so, it's going to be a full blown couple of days for us. >> What's the pitch for someone watching that never been Informatica World? Why should they come for the show? >> I'll always tell them three things. Number one is that, it's a user conference for our customers to learn all things about data management and of course in that context they learn a lot about. So, they learn a lot about the industry. So, day one we kick it off by market perspectives. We are giving a sense on how the market is going, how everybody is stepping back from the day to and understanding, where are these digital transformation, AI, where is all the world of data going. We've got some great annalists coming, talkings, some customers talking, we are talking about futures over there. Then it is all about hands on learning, right?, learning about the product. Hearing from some of these experts, right?, from the industry experts as well as our customers, teaching what to do and what not to do and networking, it's always go to network, right, it's a great place for people to learn from each other. So, it's a great forum for all those three things but the theme this year is all about AI. I talked about CLAIRE, I'll in fact our tagline this year is, Clarity Unleashed. We really want, basically, AI has been developing over the last couple of years, it's becoming a lot more mainstream, for us in our offerings and this year we're really taking it mainstream, so, it's kind of like, unleashing it for everybody can genuinely use it, truly use it, for the day to day data management activities. >> Clarity is a great theme, I mean, it plays on CLAIRE but this is what we're starting to see some visiblility into some clear >> Yeah. >> Economic benefits, business benefits. >> Yep. >> Technical benefits, >> Yep. >> Kind of all starting to come in. How would you categorize those three areas because you know, generally that's the consensus these days that what was once a couple years ago was, like, foggy when you see, now you're starting to see that lift, you're seeing economic, business and technical benefits. >> To me it's all about economic and business. So, technology plays a role in driving value for the business, right, I'm a full believer in that, right, and if you think about some of the trends today, right, a billion users are coming into play that will be assisted by AI. Data is doubling every year, you know the volume of data, >> Yep. >> The amount of, and I always say business users today, I mean, I run a business, I want, I always say, tomorrow data, yesterday to make a decision today. It's just in time and that's where AI comes into play. So our goal is to help organizations transform themselves, truly be more productive, reduce operation cost, by the way governance and compliance, that's becoming such a mainstream topic. It's not just basically making analytical decisions. How do you make sure your data is safe and secure, you don't want to get basically get hit by all of these cyber attacks, they're all are coming after data. So, governance, compliance of data that's becoming very, so, those-- >> Again you guys are right on the data thing. >> Yeah. >> I want to get your reaction, you mentioned some stats. >> Sure. >> I've got some stats here. Data explosion, 15.3 zettabytes per year >> Yeah, in global traffic. >> Yeah. >> 500 million business data users and growing 20 billion in connected devices, one billion workers will be assisted by machine learning, so, thanks for plugging those stats but I want to get your reaction to some of these other points here. 80% of enterprises are looking at multicloud, their really evaluating where the data sits in that equation >> Sure. And the other thing is the responsibility and role of the Chief Data Officer >> Yes. >> These are new dynamics, I think you guys will be addressing that into the event. >> Absolutely, absolutely. >> Because organizational dynamics, skill gaps are issues but also you have multicloud. So your thoughts on those to. >> That's a big thing, look at, in the old world, John, Hidrantes is always still in large enterprises, right, and it's going to stay here. In fact I think it's not just cloud, think of it this way, on-premise is still here, it's not going a way. It's reducing in scope but then you have this multicloud world, SAS apps, PAS apps, infrastructure, if I'm a customer, I want to do all of it but the biggest problem is that my data is everywhere, how do I make sense of it and then how do I govern it, like my customer data is sitting somewhere in this SAS app, in that platform, on this on-prem application transaction app I'm running, how do I connect the three and how do I make sense it doesn't get, I can have a governance control around it. That's when data management becomes more important but more complex but that's why AI comes in to making it easier. What are the things we've seen a lot, as you touched upon, is the rise of CDO. In fact we have Daniel from Nissan, she is the CDO of Nissan North America, on main stage, talking about her role and how they have leveraged data to transform themselves. That is something we're seeing a lot more because you know, the role of the CDO is making sure that is not only a sense of governance and compliance, a sense of how do we even understand the value of data across an enterprise. Again, I see, one of the things we going to talk about is system thinking around data. We call it System Thinking 3.0, data is becoming a platform. See, there was OSA-D hardware layer whether it is server, or compute, we believe that data is becoming a platform in itself. Whether you think about it in terms of scale, in terms of governance, in terms of AI, in terms of privacy, you have to think of data as a platform. That's the other big thing. >> I think that is a very powerful statement and I like to get your thoughts, we had many conversations on camera, off camera, around product, Silicon Valley, Venture Capital, how can startups create value. On of the old antigens use to be, build a platform, that's your competitive strategy, you were a platform company and that was a strategic competitive advantage. >> Yes. >> That was unique to the company, they created enablement, Facebook is a great example. >> Yeah. >> They monetized all the data from the users, look where they are. >> Sure. >> If you think about platforms today. >> Sure. >> It seems to be table steaks, not as a competitive advantage but more of a foundational. >> Sure. >> Element of all businesses. >> Yeah. >> Not just startups and enterprises. This seems to be a common thread, do you agree with that, that platforms becoming table steaks, 'cause of if we have to think like systems people >> Mm-hmm. >> Whether it's an enterprise. >> Sure. >> Or a supplier, then holistically the platform becomes table steaks on premer or cloud. Your reaction to that. Do you agree? >> No, I think I agree. I'll say it slightly differently, yes. I think platform is a critical component for any enterprise when they think of their end to end technology strategy because you can't do piece meals otherwise you become a system integrator of your own, right? But it's no easy to be a platform player itself, right, because as a platform player, the responsibility of what you have to offer your customer becomes a lot bigger. So, we obviously has this intelligent data platform but the other thing is that the rule of the platform is different too. It has to be very modular and API driven. Nobody wants to buy a monolithic platform. I don't want to, as a enterprise, I don't buy all now, I'm going to implement five years of platform. You want it, it's going to be like a Lego block, okay you, it builds by itself. Not monolithic, very API driven, maybe microservices based and that's our belief that in the new world, yes, platform is very critical for to accelerate your transformational journeys or data driven transformational journeys but the platform better be API driven, microservices based, very nimble that is not a percussor to value creation but creates value as you go along. >> It's all, kind of up to, depends on the customer it could have a thin foundational data platform, from you guys for instance, then what you're saying, compose. >> Of different components. >> On whatever you need. >> For example you have data integration platform, you can do data quality on top, you can do master data management on top, you can provide governance, you can provide privacy, you can do cataloging, it all builds. >> Yeah. >> It's not like, oh my gosh, I have go do all these things over the course of five years, then I get value. You got to create value all along. >> Yeah. >> Today's customers want value like, in two months, three months, you don't want to wait for a year or two. >> This is the excatly the, I think, the operating system, systems mindset. >> Yes. >> You were referring too, this is kind of how enterprises are behaving now. There is the way you see on-premise, >> Yep. >> Thinking around data, cloud, multicloud emerging, it's a systems view distributed computing, with the right Lego blocks. >> That's what our belief is. That's what we heard from customers. See our, I spend most of my time talking to customers and are we trying to understand what customers want today and you know, some of this latent demands that they have, sometimes can't articulate, my job, I always end up on the road most of the time, just hearing customers, that's what they want. They want exactly to your point, a platform that builds, not monolithic, but they do want a platform. They do want to make it easy for them not to do everything piece meal. Every project is a data project. Whether it's a customer experience project, whether it's a governance project, whether it's nothing else but a analytical project, it's a data project. You don't repeat it every time. That's what they want. >> I know you got a hard stop but I want to get your thoughts on this because I have heard the word, workload, mentioned so many more times in the past year, if there was a tag cloud of all theCUBE conversations where the word workload was mentioned, it would be the biggest font. (laughs) >> Yes. >> Workload has been around for a while but now you are seeing more workloads coming on. >> Yeah. >> That's more important for data. >> Yes. >> Workloads being tied into data. >> Absolutely. >> And then sharing data across multiple workloads, that's a big focus, do you see that same thing? >> We absolutely see that and the unique thing we see also is that newer workloads are being created and the old workloads are not going away, which is where the hybrid becomes very important. See, we serve large enterprises and their goal is to have a hybrid. So, you know, I'm running a old transaction workload order here, I want to have a experimental workload, I want to start a new workload, I want all of them to talk to each other, I don't want them to become silos and that's when they look to us to say connect the dots for me, you can be in the cloud, as an example, our cloud platform, you know last time, we talked about a 5 trillion transactions a month, today is double that, eight to ten trillion transactions a month. Growing like crazy but our traditional workload is also still there so we connect the dots for our customers. >> Amit, thank you for coming on sharing your insights, obviously you guys are doing well. You've got 300,000 developers, billions in revenue, thanks for coming on, appreciate the insight and looking forward to your Informatica World. >> Thank you very much. >> Amit Walia here inside theCUBE, with theCUBE conversation, in Palo Alto, thanks for watching.

>> live from Las Vegas. It's the queue covering del Technologies. World twenty nineteen. Brought to you by Del Technologies and its ecosystem partners. >> Welcome back to Las Vegas. Lisa Martin with John Ferrier. You're watching the Cube live at Del Technologies World twenty nineteen. This is our second full day of Double Cube set coverage. We've got a couple of we're gonna really cool conversation coming up for you. We've got Robbie Pender County, one of our alumni on the cue back as VP product management server solutions. Robbie, Welcome back. >> Thank you, Lisa. Much appreciated. >> And you brought some Hollywood? Yes. Glenn Glenn ER, president of Sony Innovation Studios. Glenn and welcome to the Cube. >> Thank you very much. It's great to be here. >> So you are love this intersection of Hollywood and technology. But you're a filmmaker. >> Yeah. I have been filming movies for many years. Uh, I started off making motion pictures for many years. Executive produced him and over so production for them at one of our movie labels called Screen Gems, which is part of Sony Pictures. >> Wait a tremendous amount of evolution of the creative process being really fueled by technology and vice versa. Sony Innovation Studios is not quite one year old. This is a really exciting venture. Tell us about that and and what the the impetus was to start this company. >> You know that the genesis for it was based out of necessity because I looked at a nice Well, you know, I love making movies were doing it for a long time. And the challenge of making good pictures is resource is and you never get enough money believing not you never get enough money and never get enough time. That's everybody's issue, particularly time management. And I thought, Well, you know, we got a pretty good technology company behind us. What if we looked inward towards technology to help us find solutions? And so innovation studios is born out of that idea on what was exciting about it was to know that we had, uh, invited partners to the game right here with Del so that we could make movies and television shows and commercials and even enterprise solutions leaning into state of the art and cutting edge technology. >> And what some of the work prize and you guys envision coming out this mission you mentioned commercials. TV is it going to be like an artist's studio actor? Ackerson Ball is Take us through what this is going to look like. How does it get billed out? >> I lean into my career as a producer. To answer that one and say is going to enable that's one of the greatest things about being a producer is enabling stories, uh, inspiring ideas to be Greenland. That may not have been able to be done so before. And there's a key reason why we can't do that, because one of our key technologies is what we call the volumetric image acquisition. That's a lot of words. You probably say. What the heck is that? But a volumetric image acquisition is our ability to capture a real world, this analog world and digitize it, bring it into our servers using the power of Del and then live in that new environment, which is now a virtual sets. And that virtual set is made out of billions and trillions in quadrillions of points, much like the matter around us. And it's a difference because many people use pixels, which is interpretation of like worry, using points which is representative of the world around us, so it's a whole revolutionary way of looking at it. But what it allows us to do is actually film in it in a thirty K moving volume. >> It's like a monster green screen for the world. Been away >> in a way, your your your your action around it because you have peril X so these cameras could be photographing us. And for all you know, we may not be here. Could be at stage seven at Innovation Studios and not physically here, but you couldn't tell it. If >> this is like cloud computing, we talking check world, you don't the provisional these resource is you just get what you want. This is Hollywood looking at the artistry, enabling faster, more agile storytelling. You don't need to go set up a town and go get the permit. All the all the heavy lifting you're shooting in this new digital realm. >> That's right. Exactly. Now I love going on location on. There's a lot to celebrate about going on location, but we can always get to that location. Think of all the locations that we want to be in that air >> base off limits. Both space, the one I >> haven't been, uh, but but on said I've been I've walked on virtual moons and I've walked on set moons. But what if we did a volumetric image acquisition of someone set off the moon? Now we have that, and then we can walk around it. Or what if there's a great club, a nightclub? This says guys want you shoot here, but we have performances Monday night, Tuesday night, Wednesday night there. You know they have a job. What if we grab that image, acquired it, and then you could be there anytime you want. >> Robbie, we could go for an hour here. This is just a great comic. I >> completely agree with you. >> The Cube. You could. You could sponsor a cube in this new world. We could run the Q twenty four seven. That's absolutely >> right. And we don't even have >> to talk about the relationship with Dale because on Del Technologies, because you're enabling new capabilities. New kind of artistry was just totally cool. Want to get back to the second? But you guys were involved. What's your role? How do you get involved? Tell the story about your >> John. I mean, first and foremost one of things that didn't Glendon mention is he's actually got about fifty movies to his credit. So the guy actually knows this stuff, so which is absolutely fantastic. So we said, How do you go take average to the next level? So what else is better than trying to work something out, wherein we together between what Glenn and Esteem does at the Sony Innovation Labs for Studio Sorry. And as in Dead Technologies could do is to try and actually stretch the boundaries of our technology to a next tent that when he talks about kazillion bytes of data right one followed the harmony of our zeros way have to be able to process the data quickly. We have to be able to go out and do their rendering. We probably have to go out and do whatever is needed to make a high quality movie, and that, I think, in a way, is actually giving us an opportunity to go back and test the boundaries of their technology. They're building, which we believe this is the first of its kind in the media industry. If we can go learn together from this experience, we can actually go ahead and do other things in other industries. To maybe, and we were just talking about how we could also take this. He's got his labs here in Los Angeles, were thinking maybe one of the next things we do based on the learnings we get, we probably could take it to other parts of the world. And if we are successful, we might even take it to other industries. What if we could go do something to help in this field of medicine? >> It's just thinking that, right? Yes. >> Think about it. Lisa, John. I mean, it's phenomenal. I mean, this is something Michael always talks about is how do we as del technologies help in progress in the human kind? And if this is something that we can learn from, I think it's going to be phenomenal. >> I think I think that's so interesting. Not only is that a good angle for Del Technologies, the thing that strikes me is the access toe artist trees, voices, new voices that may be missed in the prop the vetting process the old way. But, you know, you got to know where we're going. No, in the Venture Capital way seen this with democratization of seed labs and incubators, where, if you can create access to the story, tells on the artists we're gonna have one more exposure to people might have missed. But also as things change, like whether it's Ray Ray beaming and streaming, we saw in the gaming side to pull a metric or volumetric things. You're gonna have a better canvas, more paint brushes on the creative side and more. Artist. Is that the mission to get AC, get those artists in there? Is it? Is that part of the core mission submission? Because you're going to be essentially incubating new opportunities really fast. >> It's, uh, it's very important to me. Personally. I know it speaks of the values of both Sony and L. I like to call it the democratization of storytelling. You know, I've been very blessed again, a Hollywood producer, and we maybe curate a certain kind of movie, a certain kind of experience. But there's so many voices around the world that need to be hurt, and there are so many stories that otherwise can't be enabled. Imagine a story that perhaps is a unique >> special voice but requires distance. It requires five disparate locations Perhaps it's in London, Piccadilly Circus and in Times Square. And perhaps it's overto Abu Dhabi on DH Libya somewhere because that's part of the story. We can now collapse geography and bring those locations to a central place and allow a story to be told that may not otherwise have been able to be created. And that's vital to the fabric of storytelling worldwide's >> going change the creative process to you don't have to have that waterfall kind of mentality like we don't talk about intact. You're totally distributed content, decentralized, potentially the creative process going change with all the tools and also the visual tools. >> That's right. It's >> almost becoming unlimited. >> You wanted to be unlimited. You want the human spirit to be unlimited. You want to be able to elevate people on. That's the great thing about what we're trying to achieve and will achieve. >> It is your right. I mean, it is interesting, you know, we were just talking about this, too. Uh, we're in, you know, as an example. Shock tank. Yes, right. I mean, they obviously did it. The filming and stuff, and then they don't have the access. Let's say to the right studio. But the fact is, they had all this done. Andi, you know, they had all the rendering they had captured. Already done. You could now go out and do your chute without having all the space you needed. >> That's right. In the case of Shark Tank, which shoots a Sony Pictures studios, they knew they had a real estate issue. The fact of the matter is, there's a limited amount of sound stages around the world. They needed to sound stages and only had access to one. So we went in and we did a volumetric image acquisition of their exit interview stage. They're set. And then when it came time to shoot the second half a season ten, one hundred contestants went into a virtual set and were filmed in that set. And the funny thing is, one of the guys in the truck you know how you have the camera trucks and, you know, off offstage, he leaned into the mike. Is that you guys, could you move that plant a couple inches to the left and somebody said, Uh, I don't think we can do it right now, he said, We're on a movie lot. You could move a plant. They said No, it's physically not there. We're on innovation studios goes Oh, that's right. It's virtual mind. >> So he was fooled. >> He was pulled. In a way, we're >> being hashing it out within a team. When we heard about some of the things you know Glenn and Team are doing is think about this. If you have to teach people when we are running short of doctors, right? Yeah, if you could. With this technology and the learnings that come from here, if you could go have an expert surgeon do surgery once you're captured, it would be nice. Just imagine, to take that learning, go to the new surgeons of the future and trained them and so they can get into the act without actually doing it. So my point and all this is this is where I think we can take technology, that next level where we can not only learn from one specific industry, but we could potentially put it to human good in terms of what we could to and not only preparing the next of doctors, but also take it to the next level. >> This was a great theme to Michael Dell put out there about these new kinds of use case is that the time is now to do before. Maybe you could get there technology, but maybe aspirational. Hey, let's do it. I could see that, Glenn, I want to ask you specifically. The time is now. This is all kind of coming together. Timing's pretty good. It's only gonna get better. It's gonna be good Tech, Tech mojo Coming for the creative side. Where were we before? Because I can almost imagine this is not a new vision for you. Probably seen it now that this house here now what was it like before for, um and compare contrast where you were a few years ago, maybe decades. Now what's different? Why? Why is this so important >> for me? There's a fundamental change in how we can create content and how we can tell stories. It used to be the two most expensive words in the movie TV industry were what if today that the most important words to me or what if Because what if we could collapse geography? What if we could empower a new story? Technology is at a place where, if we can dream it. Chances are we can make it a reality. We're changing the dynamics of how we may content. He used to be lights, action camera. I think it's now lights, action, compute power action, you know, is that kind of difference. >> That is an amazing vision. I think society now has opportunities to kind of take that from distance learning to distance connections, the distance sharing experiences, whether it's immersion, virtual analog face, the face could really be powerful. Yeah, >> and this is not even a year old. >> That's right. >> So if you look at your your launch, you said, I think let june fourth twenty eighteen. What? Where do you go from here? I mean, like we said, this is like, unlimited possibilities. But besides putting Robbie in the movie, naturally, Yes, of course I have >> a star here >> who? E. >> So I got to say he's got star power. >> What's what's next year? Exactly? >> Very exciting. I will say we have shark tank Thie Advanced Imaging Society gives an award for being the first volume met you set ever put out on the airwaves. Uh, for that television show is a great honor. We have already captured uh, men in black. We captured a fifty thousand square foot stage that had the men in black headquarters has been used for commercials to market the film that comes out this June. We have captured sets where television shows >> and in hopes, that they got a second season and one television show called up and said, Guys, we got the second season so they don't have to go back to what was a very expensive set and a beautiful set >> way captured that set. It reminds me of a story of productions and a friend of mine said, which is every year. The greatest gift I have is building a beautiful set and and to me, the biggest challenges. When I say, remember that sent you built four years ago? I need that again. Now you can go >> toe. It's hard to replicate the exact set. You capture it digitally. It lives. >> That's exactly it. >> And this is amazing. I mean, I'd love to do a cube set into do ah, like a simulcast. Virtually. >> So. This is the next thing John and Lisa. You guys could be sitting anywhere going forward >> way. You don't have to be really sitting here >> you could be doing. What do you have to do? And, you know, you got everything rendered >> captured. We don't have to come to Vegas twenty times a year. >> We billed upset once. You >> know you want to see you here believing that So I'LL take that >> visual is a really beautiful thing. So if we can with hologram just seeing people doing conscious with Hollywood. Frank Zappa just did a concert hologram concert, but bringing real people and from communities around the world where the localization diversity right into a content mixture is just so powerful. >> Actually, you said something very interesting, John, which is one of the other teams to which is, if you have a globally connected society and he wanted try and personalize it to that particular nation ethnicity group. You can do that easily now because you can probably pop in actors from the local area with the same. Yeah, think about it. >> It's surely right. >> There's a cascade of transformations that that this is going Teo to generate. I mean just thinking of how different even acting schools and drama schools will be well, teaching people how to behave in these virtual environments, right? >> How to immerse themselves in these environments. And we have tricks up our sleeves that Khun put the actor in that moment through projection mapping and the other techniques that allow filmmakers and actors to actually understand the world. They're about to stepped in rather than a green screen and saying, OK, there's going to be a creature over here is gonna be blue Water falls over there will actually be able to see that environment because that environment will exist before they step on the stage. >> Well, great job the Del Partnership. On my final question, Glenn, free since you're awesome and got a great vision so smart, experienced, I've been really thinking a lot about how visualization and artistry are coming together and how disciplines silo disciplines like music. They do great music, but they're not translating to the graphics. It was just some about Ray tracing and the impact with GP use for an immersive experiences, which we're seeing on the client side of the house. It del So you got the back and stuff you metrics. And so, as artist trees, the next generation come up. This is now a link between the visual that audio the storytelling. It's not a siloed. >> It is not >> your I want to get your vision on. How do you see this playing out and your advice for young artists? That might be, you know, looked as country. What do you know? That's not how we do it. >> Well, the beautiful thing is that there are new ways to tell stories. You know, Hollywood has evolved over the last century. If you look at the studios and still exist, they have all evolved, and that's why they do exist. Great storytellers evolved. We tell stories differently, so long as we can emotionally relate to the story that's being told. I say, Do it in your own voice. The cinematic power is among us. We're blessed that when we look back, we have that shared experience, whether it's animate from Japan or traditional animation from Walt Disney everybody, she shares a similar history. Now it's opportunity to author our new stories, and we can do that and physical assets and volumetric assets and weaken blend the real and the unreal. With the compute power. The world is our oyster. >> Wow, >> What a nice >> trap right there. >> Exactly. That isn't my job. The transformation of of Hollywood. What it's really like the tip of the iceberg. Unlimited story potential. Thank you, Glenn. Thank you. This has been a fascinating cannot wait to hear, See and feel and touch What's next for Sony Animation studios With your technology power, we appreciate your time. >> Thank you. Thank you both. Which of >> our pleasure for John Carrier? I'm Lisa Martin. You're watching the Cube lie from Del Technologies World twenty nineteen We've just wrapped up Day two we'LL see you tomorrow.

>> from our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation. >> Welcome to this. Keep conversation here in Palo Alto, California. Keep studios. I'm John for the host of the Cube were with Cuba Lum nine. Special gas *** while the president of products and marking it in from Attica. I make great to see you has been a while, but a couple months. How's things good to be >> back has always >> welcome back. Okay, so in dramatic, a world's coming up. We have a whole segment on that, but we've been covering you guys for a long, long time. Data is at the center the value proposition. Again and again, it's Maur amplified. Now the fog is lifting. Show in the world is now seeing what we think we were told about four years ago with data. What's new? What's that? What's the big trends going on that you guys air doubling down on what's new? What's changed? Here's the update. Sure, >> I think we've been talking for the last couple of years. I think you're right. It is becoming more and more important. I think three things we see a lot one is. Obviously you saw this whole world of district transformation. I think that definitely has picked up so much steam. Now. I mean, every company's going digital and And that the officer, that creates a whole new paradigm shift for companies to come almost recreate themselves remained. And so that data becomes the new definition. And that's what we call the thing is you side and fanatical even before the data three dollar word. But data is the center of everything, right? And in basically see the volume of data growth, you know, the utilization of data to make decisions, whether it's, you know, a decision on the shop floor decisions basically related to a cyber security or whatever it is on the keel of your signal is different now. Is the hole e. I assisted data management. I mean the scale ofthe complexity, the scale of growth, you know, multi cloud, multi platform, all the stuff that's in front of us. It's very difficult to run the old way of doing things. So that's where we see the one thing that we see a whole lot is is becoming a lot more mainstream still early days. But it's assisting the whole ability for companies to what I call exploit data to really become a lot more transformative. >> You've been on this for a while again. We get what we had to go back to. The Cube archives were almost pullout clips from two years ago be relevant today. You know the data control understanding. You know that. You know, I understand where the date of governance is ours. So is the foundational thing. But you guys nailed the chat box. You've been doing a Iot of previous announcements. This is putting a lot of pressure on you. The president of products you got. Get this out there. What's new? What's happening inside in from Attica? He's pedaling as fast as you can. What are some of the updates? Give >> us the best example. I was just like the duck, right? You know, you're really selling your Felix comma the top and then you're really finally I think it's great for us. I think I look a tw ee eye ee eye. It's like this so much fun around machine learning. We look at it, it's two different ways. One is how we leverage machine learning Vidin our products to help our customers, making it easy for them to. As I said, so many different data types Think of I ot data instructor data streaming data. How do you bring all that stuff together and married with your existing transaction? It'LL make sense. So we're leveraging a lot of machine learning to make the internal products a lot more easier to consume. A lot more smarter, a lot more. Richard, The second thing is that we what we call his are a clear which we are. Really? If you remember a couple years ago and in America World, how guard then helps our customers make smarter decisions in the in the one of data signs and all these new data workbench is, you know, the old statistical models are only as good as they can never be. So we're leveraging, helping our customers take the value proposition of r B. I clear then what? I make things that, you know, find patterns that, you know, statistical models cannot. So, to me, I look att, both of those really leveraging ml to shape our products, which is married to a lot of innovation and then creating our eclair to that help customers make smarter decisions, easier decisions, complex decisions. Which would I kill the humans or the statistical models? >> Really Well, this is the balance between machines and humans working together. And you guys have nailed this before. And I think this was two years ago. I started to hear the words land adopt, expand from you guys. Write, which is you've got to get adoption, right? And so as you're iterating on this product, focus, you've got to get it working your >> butt looks big, maniacal focus of that. Let's talk about >> what? What you've learned there because that's a hard thing. You guys are doing well at it. We've got to get a doctor. Means you gotta listen to customers going do the course correction. What's the learning is coming out of that. That >> is actually such a good point. We made such. We were always a very customer centric company. But as you said like that, as the world shifted towards a new subscription cloud model, be really focused on helping our customers adopt our products. And you know, in this new world, customers are also struggling with new architectures and everything, so we double down on what we call customer success, making sure we can help our customers adopt the products. And whether it's it's, it's too will benefit. Our customers can value very quickly. And of course, we believe in what we call a customer for life. Our ability to then grow without customers and held them deliver value becomes a lot better, so we're really for So we have globally across the board customers, success managers, we really invest in a customer's. The moment we a customer, buys a product from us, we directly engage with them to help them understand forthis use case. How you >> implement its not just self serving. That's one thing which I appreciate because you know, how hard is it? Build products these days, especially with philosophy, have changed, but it's also we have in the large scale data. You need automation. You've gotta have machine learning. You gotta have these disciplines. Sure this both on your own, but also for the customer. Yes, any updates on the Clare and some customer learnings, and you're seeing that air turning into either use cases or best practices, >> many of them. So take a simple example, right? I mean, we think if we take these things for granted, right? I mean, taking over here to talk about I open these designs on all of these sensors. We were streaming data, right? Or even robots in the shop floor. Sort of. That data has no schema, no structure, nor definition. It's coming like Netflix data has to. And for customers, there's a lot of volume on it. None of it could be junk. Right? So how do you first think that volume of data creates some structure to it for you to do analytics? You You can only do analytics if you put some structure to it. Right. So first thing is that we leverage clear help customers create what are called scheme, and you can create some structure to it. Then what we do allow is basically clear through clear. It can naturally bring what we have. The data quality on top of it. Like how much of it is irrelevant? How much of it is noise? How much would it really make sense? So then what was you said? It signal from the noisy were helping customers get signal from the noise of data. That's where it becomes very handy because It's a very man will cumbersome, time consuming and something very difficult to do. So that's an area of every have leveraged, creating structure, adding data quality on top and finding rules that didn't probably naturally didn't exist, that you and he would be able to see machines are able to do it. And to your point, our belief is this is my one hundred percent believe we believe in the eye assisting the humans. We have given the value ofthe Claire, tow our users that it compliments you. And that's where we're trying to help our users get more productive and deliver more value faster. >> Productivity is multifold. It's like also efficiency. You don't want people wasting time on project that can be automated. You focus that valuable resource somewhere else. Yeah, okay, so let's shift gears on. Taking from Attica World coming up. Let's spend some time on that. What's the focus this year? The show. It's coming up right around the corner. What's going to focus on what's going to be the agenda? What's on the plate >> give you a quick sense of how it's the shape of its going to be our biggest in from Attica well, so it's twentieth year again. Back in Vegas, you know we love Vegas. Of course, we have obviously a couple of days line up over there and you guys will be there too Great sort of speakers. So obviously we'LL have mean stage speakers like so we'LL have some CEO of Google Cloud Thomas Korean is going to be there We'LL have on main stage with Neil We'LL have the CEO of dealer Breaks Ali with me We'LL also have the CMO off a ws ariel there. Then we have a couple of customers lined up Simon from Credit Suisse Daniels CD over Nissan. We also have the head of the eye salmon Guggenheimer from Microsoft, as well as the chief product officer of Tableau Francois on means. So we have a great lineup of speakers, customers and some of our very, very strategic partners with us. Remember last year we also had Scott country. That means too eighty plus session's pretty much a ninety percent led by customers. We have seventy to eighty customers. Presentable sessions, technical business. We have all kinds of tracks. We have hands on labs. We have learnings. Customers really want to come. Lana products. Talked to the experts someone to talk to the product manager. Someone talk to the engineers literally, so many hands on lab. So it's going to be a full blown a couple of days. What's >> the pitch for someone watching that has never been in from Attica world? Why should they come for the show? >> I always tell them three things. Number one is that it's a user conference for our customers to known all things about data management. And then, of course, in that context, they learned a lot about so they learned a lot about the industry. So Dave one we kicked around by market perspective giving Assessor the market is going, how everybody should be stepping back from the data and understanding. Where are these district transformation? E I? Where is the world of detail going? We have some great analysts coming, talking, some customers talking. We'LL be talking about futures over there. Then it is all about hands on learning, right, learning about the product hearing from some of these experts, right from the industry experts as well as our customers teaching what to do, what not to do and networking. It's always great to network writes a great place for people to learn from each other. So it's a great forum for for two of those three things. But the team this year is all around here. I talked about clear. In fact, our tagline Dissidents, clarity unleashed. I really want to, basically has been developing for the last couple of years. It's become becoming a lot who means stream for us in our offerings. And this year we really are taking it being stream. So it's kinda like unleashing it where everybody can genuinely use a truly use it from the data data management. Active >> clarity is a great team. I mean plays on Claire, But this is what we're starting to see. Some visibility into some clear economic benefits, business benefits, technical benefits, kind of all starting to come in. How would you categorize those three years? Because, you know, that's generally the consensus these days is that what was once a couple years ago was like foggy. When you see now you're starting to see that lift. You see economic, business and technical benefits. >> To me, it's all about economic and business. Anniversary technology plays a role in driving value for the business, my gramophone believing that right? And if you think about some of the trans today, right, ah, billion users are coming into play. That he be assisted by data is doubling every year. You know, the volume of data and and amount ofthe amount off. And I obviously business users today. I mean, when I run a business I want, I always say, tomorrow's data yesterday to make a decision. Today it's just in time, and that's where it comes into play. So our goal is to help organizations transformed themselves truly, you know, be more productive, produce operational cost by the government and compliance that's becoming such a mainstream topic. It's not just basically making analytical decisions. How do you make sure that your data is safe and secure? You don't want to get basically hit by any of these cyberattacks. They're all coming after data. So governance and compliance of data that's becoming but in the end got stored on the >> data thing. Yeah, I wanna get your reactions. You mention some shots like some stats here. Date explosion fifteen point three's added bytes per year in traffic, five million business data users and growing twenty billion connected devices. One billion workers will be assisted by learning. So no thanks for putting those stats, but I want to get your reactors. Some of these other points here, eighty percent of enterprises air that we're looking at multi cloud. They're really evaluating their where the data sits in that kind of equation short. And then the other thing is that the responsibility and role of the chief data? Yes, these air new dynamic. I think you guys will be addressing that. And because organizational stuff dynamics, skill, gaps are issues. But also you have multi clouds form. >> And that's a big thing. I mean, look thin. The old World John hatred Unite is always too large in the price is right, and it's going to stay here. In fact, I think it's not just cloud. Think of it this way, one promised. Ilya is not going away. It's producing in school. But then you have this multi cloud world sassafras pass halves infrastructure. If I'm a customer, I want to do all of it. But the biggest problem comes, you said, is that my data is everywhere. How do I make sense of it? And then how do I go on it like my customer data sitting somewhat in this *** up in that platform in this on prime application transaction after running hardware Connect three. And how do I make sense? It doesn't get. I can have a governance and control around it. That's where data management becomes more important but more complex. But that's where it comes into making it easier. One of the things we've seen a lot of you touched upon is the rise of the Sirio. In fact, we have Danielle from the Sanchez, a CD off Mr North America on Main Stage, talking about her rule and how they've leveraged data to transform themselves. That is something we're seeing a lot more because you know, the rule of the city or making sure there is, You know, not only a sense of governance and compliance, a sense of how to even understand the value of dude across an enterprise again. I see one of the things we're gonna talk about this. It's old system thinking around data. We call it system, thinking three daughter data is becoming a platform C. There was always that the hard way earlier, whether it is server or computer. We believe that data is becoming a platform in itself. Whether you think about it in terms of scary, in terms ofthe governance, in terms of e i times a privacy, you have to think of data as a platform. That's the that's the other. But >> I think that is very powerful statement, and I'd like to get your thoughts. You know, we've had many countries. Is on camera off camera around product. Silicon Valley Venture Capital. How come started to create value. One of the old adage is used to be build a platform. That's your competitive strategy. There were a platform company, and >> that was a >> strategic competitive advantage that is unique to the company. And they created enablement. Facebook's a great example. Monetize all the data from users. Look where they are short. If you think about platforms today, Charlie, it seems to be table stakes. Not as a competitive is more of a foundational element of all businesses, not just startups enterprises. This seems to be a common thread. Do you agree with that that platforms were becoming table stakes? Because if we have to think like systems people, whether it's an enterprise show supplier ballistically the platform becomes stable. States that could be on primary cloud. Your reactions >> are gonna agree that I'll say it slightly differently. Yes, I think I think platform is a critical competent for any enterprise when they think of their entire technology strategy because you can't do peace feels otherwise. You become a system integrated over your own right. But it's not easy to be a platform clear itself, right? Because it's a platform player. The responsibility of what you have to offer your customer becomes a lot bigger. So we always t have this intelligent in a platform. Uh, but the other thing is that the rule of the platform is different. It has to be very modeling and FBI driven. Nobody wants to buy a monolithic platform. I don't want as an enterprise it on my own. I'm gonna implement five years a platform you want. It's gonna be like a Lego block. Okay? You It builds by itself, not monolithic, very driven my micro services based And that's our belief that in the new World, yes, black form is very critical for youto accelerate your district transformation journeys or data driven district transformation journeys but the platform better be FBI driven micro services based, very nimble that it's not a precursor to value creation but creates value as you want. It's >> all kind of depends on the customer. Get up a thin, foundational data platform from you guys, for instance. And then what you're saying is composed off >> different continents. For example, you have a data integration platform, then you can do the quality on top. You do. You could do master data management on top. You can provide governance. You can provide privacy. You could do cataloging it all builds its not like Oh my gosh, I have to go do all these things over the course of five years. Then I'LL get value. You gotta create value all along. Today's customers want value like in two months. Three months. You don't wait for a year or >> two years. This is exactly why I think the kind of Operation Storm systems mindset that you're referring to. This is kind of enterprises. They're behaving others the way that you see on premise, thinking around data and cloud multi cloud emerging. It's a systems view of distributed computing with the right block Lego blocks >> that that's what I believe is. That's what we heard from customers. He r I spend most of my time traveling, talking to customers on my way to try to understand what customers want today. And you know some of this late and demand that they have it. They can't sometimes articulate my job. I always end up on the road most of the time just to hearing customers, and that's what they want. They want exactly appoint a platform that Bill's not monolithic, but they don't want the platform. They do want to make it easy for them not to do everything piecemeal. Every project is a data project, whether it's a customer experience project, whether it's the government's project, whether it is nothing else but an analytical. It's a data project, but you don't want to repeat it every time. That's what they want, >> but I know you got a hard stuff, but I want your thoughts on this because I've heard the word workload mentioned so many more times these in the past year. It was a tad cloud of all the cute conversation with a word workload was mentioned to be the biggest fund. Yes, work has been around for a while, but nice seeing more and more workloads coming on. Yeah, that's more important for day that we're close to being tied into the data absolutely, and then sharing data cross multiple workloads. That's a big focus. Perhaps you see that same thing. >> We absolutely see that, Onda. The unique thing that we see also that new work towards getting created and the old workloads are not going away, which is where the hybrid becomes very important. See, these serve large enterprises and their goal is to have an hybrid. So, you know, I'm running a old transaction workload over here. I want to have an experimental workload. I want to start a new book. I want all of them to talk to each other. I don't want them to become silos. And that's when they look to us to say connect the dots for me. You can be in the cloud as an example. Our cloud platform, you know, last time and fanatical will remember we talked about like it wasn't five trillion transactions a month, but it's double that it to pen trillion transaction a month growing like crazy. But our traditional workload is also still there. So we connect the dots for customers. >> I mean, thank you for coming on sharing the insights house. You guys doing well? You got three thousand developers, billions in revenue. Thanks for coming. Appreciate the insight. And looking for Adrian from Attica World. Thank you very much. Meanwhile, here inside the Cuban shot furry with cute conversation in Palo Alto. Thanks for watching.

>> From Sand Hill Road in the heart of Silicon Valley, it's theCUBE. Presenting, the People First Network, insights from entrepreneurs and tech leaders. >> Hello everyone I'm John Furrier with theCUBE, we are here in Sand Hill Road up at Mayfield Venture Capital Firm for their 50th anniversary, their People First Network series, produced with theCUBE and Mayfield, I'm John Furrier, with Bill Schlough, the Chief Information Officer of the San Francisco Giants, CUBE alumni, great to see you thanks for joining me today for this People First Series we're doing with Mayfield's 50th anniversary, thanks for coming in. >> Good to be here, John. >> So, been a while since we chatted, it's been a year, A lot's happening in tech, you can't go a year, that's like seven dog years in tech, lot happening, you're managing, as the CIO for the Giants, a lot of things going on in baseball, what's the priorities for you these days, obviously, you guys, great social, great fan experience, what's new for you, what's the priority? >> Man, there's always something new. It's what I love about it, this'll be my 20th season with the Giants comin' up. And, it never gets old, there's always new challenges. On the field, in the seats, off the field, you name it. As we look toward next year, really excited about bringin' in a new video board, which we haven't publicly announced, maybe I just did publicly announce, we're breaking news on theCUBE today. So we're puttin' in a new video board, it'll be over three times the size of the one we have today. That's big news, we're doing a lot of exciting things in the ticketing world. The ticketing world is really transforming right before our eyes in terms of the way fans buy tickets. It's changed a lot. Once up on a time you could call a game a sellout, and we sold out 530 straight games at AT&T Park, but really there's no such thing as a sellout anymore I mean, at any point you can get a great ticket, so we have to adapt to that and change the product that we're delivering to fans, so making some changes on the ticketing front, the fan experience, the ballpark with the video board, and another thing that's changing a lot is the way fans consume our game when they're not at the ballpark. It's rare that you're going to see somebody sit on a couch for three plus hours and watch a game continuously anymore. Fans are consuming through mobile devices, streaming, catching clips here and there, all different methods, and it's fun to be a part of that, because, fans still love the game, but they're just consuming it in different ways. >> Yeah, I love having chats with you on theCUBE because one of the things that have always been the same from nine years doing theCUBE is, the buzzword of consumerization of IT has been out there, overused, but you're living it, you have a consumer product, the ultimate consumer product, in Major League Baseball, and the Giants, great franchise, in a great city, in a great stadium, with a rabid fanbase, and they know tech, so you have all the elements of tech, but the expectation of consumers, and the experiences are changing all the time, you got to deliver on the expectations and introduce new experiences that become expectations, and this is the flywheel of innovation, and it's really hard, but I really respect what you guys are doing over there, and that's why I'm always curious, but, always, the question comes back to, is, can I get faster wifi in the stadium? (laughs) It's always the number one question >> It's funny that you ask that because it is AT&T Park, you know, so, honestly, we got to check that box, and we've had to for years, all the way back to when we first rolled it out, way back in 2004 when we first rolled out wifi in the park, people weren't asking for it then, people were coming to the ballpark with a laptop and plugging a card into it, and there were about a hundred of them that were accessing it, but today, what's interesting is, who knows what next, but we're not talkin' about wifi as much, wifi is just kind of, expected, you got to have it, like water. You're talkin' about 5G networks, and new ways to connect. Honestly, this past season, our wifi usage in terms of the number of fans that use wifi, what we call the take rate, the percentage of fans, was actually down 30% from the previous year. Not because we had less fans in the stadium, because this is the take rate, a percentage of fans in the stadium, went down, because AT&T made some massive investments in their cellular infrastructure at the ballpark, and if you're just connecting, and you got great bandwidth, you don't feel the need to switch over to wifi, so who knows what the future will hold? That's a great point, and you see the LTE networks have so much more power, it used to be you needed wifi to upload your photos, so you'd go in, log in, and if they auto login that's cool, but people don't need to. >> Not with photos, what they need it now for is when we see it really maxing out is events, like our Eagles concert, or Journey concert, or a really big game, like opening day, or honestly, Warriors playoffs game, 49ers football games, that's when folks are streamin' to video. For streamin' to video, they're still goin' to that wifi. Yeah, that's the proven method, plus they don't want to jack up their charges on the AT&T site, but I won't go there, Let's talk about innovat-- Most say unlimited, I will go there, most say unlimited these days. >> Really, I got to find that plan, my daughter's killin' me with her watchin' Netflix on LTE, I tell her. Innovation is changing, I want to get your thoughts on this, 'cause I know you're on the front end of a lot of innovations, you do a lot of advising here at Mayfield. The VC's always trying to read the tea leaves, you're living it, what's the innovation formula look like now for you 'cause as you're sittin' in your staff meetings, as you look at the team of people around you, you guys want to foster, you do foster, innovation culture. What's the formula, what do you guys do when you have those meetings, when everyone's sitting around the table sayin', what do we do next? "How do we create a better experience? "How can we get better fans, and better product "in their hands as fast as possible?" What's your strategy? >> You know, it's funny, people talk about the secret sauce for innovation, what's the formula? I would say, for us, it's really a symbiotic relationship with a lot of things, first of all, where we are, geographically, we've got folks like Mayfield, down the street, and many others, that we can talk to, that are, when innovation is happening, when the startups are incubating, they're being funded by these guys, a lot of times they are here, and our phones are ringing off the hook with a lot of folks so my formula for innovation is answer the phone and take the meetings, but, to be honest, that creates its own problems, because there's so many great ideas out there, if you try to do all of them, you're going to fail at all of them. You got to pick a very small few to try to experiment with, give it a shot, we just don't have the bandwidth, we only have 250 full-time staff on the business side. For us, geographically, you have to really be laser-focused and say okay, there are so many great ideas out here, which are the three or four that we're going to focus on this year, and really give it a try, that's really going to drive, propel our business forward, enhance our product on the field, whatever it might be, but I'll tell you where it really truly starts. It's from the top with our CEO. And, I've had a few different bosses over the years, but with the Giants, our CEO is singularly focused on all of us doing things folks have never done before regardless of what business unit you're in. Whether you're in ticketing, finance, marketing, sales, what drives him, and drives all of us, is innovation. And his eyes glaze over when I talk to him about cost-cutting, and his eyes can glaze over really fast. But when I talk to him about doing something no one's ever done before, that's when he sits forward in his chair, he gets engaged, and I just have a great boss, Larry Baer, he's been with us for 25 years wit the Giants, and he is the driver for it, he creates the culture from the top, where all of us, we want to impress him, and to impress him, you got to do sometin' nobody's ever done before, and what's even more interesting is there are some challenges and some changes talking place across our industry, as I said before, ticketing and other areas, and I've sat in meetings with him where somebody might raise their hand and say, "But this is happening across the industry, "so it's just a macro trend," and he'll get upset, be like, "I don't care about macro trends. "We are here in the Bay Area, "we're the San Francisco Giants, "we're going to do it our way." >> And so when you do it your way, he promotes risk-taking, so that's a great culture. What are some of the things you have tried that were risky, and/or risque, or maybe an experiment, that went well, and maybe ones that didn't go well, can you share some color commentary around that? >> Sure, over 20 years we've had some of all of those. I would say, I've had some real scary moments, our culture is collaborative, but I wouldn't call it combative, but we all have strong opinions, a lot of us have been there a long time, and we have strong opinions and so we'll battle, internally, a lot, but then once the battle is over, we'll all align behind the victory. Thinking back, one of the most stressful times for me at the ballpark was related to wifi, when we decided to take our antennas and put 'em under people's seats. No one had ever done that before, and there were two major concerns with that. One is, honestly are people going to get cancer from these antennas under their seats, it's never been done before, what's going to happen, and whether it's going to happen or not, what's the perception of our fans going to be, because, these are, the bread and butter is, the golden goose here, all the fans, so, yeah it's great that they're going to be, have faster connection here at AT&T Park, but if they think they're going to get cancer, they're going to cancel their season ticket plans, we got to problem. Number two is, we're taking away a little storage space also, under the seats, so it was very controversial internally, we did all of our research, we proved that having a wifi antennae under your seat is the equivalent to having a cell phone in your pocket, most people do that, so we're pretty safe there, and from the storage space perspective, honestly, it actually elevates your stuff, if somebody spills a Coke behind ya, it'll fall all around your purse, which is sitting on top of that wifi antenna so we came up with a good solution, but that was an example of something that was really controversial >> So beer goes on the antennae not your bag. (laughs) >> Exactly, your bag stays dry, we found a way to spin that but, there have been so many, I can go way back in time, back to the days when it was the PalmPilot that ruled the day instead of the apple >> Well you guys also did a good job on social media, I got to give you guys props, because, you're one of the first early adopters on making the fan experience very interactive. That was, at that time, not viewed as standard. Yeah, built the @Cafe at our ballpark, which is still there really to try to bring social media to the fans. >> I think you're the first ballpark to have a kale garden, too, I think. >> That's a little off topic, but yes, driven by one of our players, who's a big kale fan, yeah, the garden out in center field. >> So sustainibility's certainly important, okay, I got to ask the question around your role in the industry, because one of the things that's happening more and more in Major League Baseball and certainly as it crosses over to tech her at Mayfield Venture Capital, there's a lot of collaboration going on, and it's a very people-centric culture where, it used to be people would meet at conferences, or you'd do conference calls, now people are in touch in real time, so these networks are forming. It takes a village to create innovative products, whether you're inside the Giants, or outside in the ecosystem, how have you personally navigated that, and can you share some experiences to the folks watching, how you became successful working in an environment where it's collaborative inside the walls of the San Francisco Giants, but also outside? >> %100, the topic is near and dear to my heart, and from when I started with the Giants, that's what I love about our industry We compete on the field, and only on the field. When you look at who the Giants competitors are, from a business perspective, honestly the Dodgers are not a competitor from a business perspective. The A's are barely a competitor from a business perspective. We got a lot of competitors and very few of them are in our actual industry, so we collaborate all day, and it's been amazing, I can count on one hand, across all of sports, folks who have not been collaborative. There's a very small group of teams, your favorite team, the Boston Red Sox, are not on that list, they are very collaborative, but their arch rival, well there's a few others out there that may be less collaborative, but most of them are highly collaborative, from top down, and so, what I did from when I first started the first trip I made, was to Cleveland. And this was many years ago, Cleveland Indians had a reputation of being very progressive so I called up my counterpart there, I said, "I'm new to the industry, can I come out, "can I learn from you?" And that's where it started, and ever since, every year, we travel to two cities, I take at least four of my staff, to two cities each year and we meet with all the sports teams in those cities. This year, we went to Milwaukee and we met with the Brewers, and we did the Packers as well. Every year, over the 20 years we've visited pretty much every professional sports city, and we just go through it again, and always, red carpet, open door, and you build those face-to-face relationships, that you can pick up the phone and make the call, in a few weeks we're all going to get together in Denver at our MLB IT Summit, my job at the IT Summit every year is I host the golf classic, so I bring all the golfers, the hackers, the duffers out, and we have a great time on the golf course and build those relationships and again, the only thing that we don't really talk about that much is the technology we use to enhance the product on the field. Everything else is fair game. >> So share the business side, but the competitive advantage, where the battle's really having Dodger and Giants obviously on the field, highly competitive-- >> But what's cool about that is then I can meet with the other sports teams to talk about that, so I'll leave the teams nameless, but we've had some awesome collaborative discussions with NBA teams especially to talk about what they're doing to assess talent, and there's no competition there. >> So there's kind of rules of the road, kind of like baseball, unwritten rules. >> Right. >> So talk about the coolest thing that you guys have done this year, share something that you personally feel proud of, or fans love, what were some of the cool things this year that pops out for you? >> Sure, the technology that we invested in this year that I thought was a game-changer, we saw, we experimented with last season, but this year, we've been experimenting with VR and AR a little bit. But, a technology that we thought was really cool is called 4DReplay, it's a company out of Korea. And we saw them, we did an experiment with them, and then we implemented them for the full season this year and we've seen them at some other venues as well, the Warriors tried them at the Playoffs, but we had 'em full year and what we did was they put in about 120 cameras, spaced approximately five feet apart, between the bases. 120 of 'em, and they focus on the pitcher and the batter, so when you have a play, you can 3D, or 4D, 4D rotate around that play and watch the ball as it's moving off the bat, and get it from that full perspective, it's awesome for the fan experience, it gives them a perspective they never have, I love watching the picture, because you can see that hand, in full 4D glory pronating as it comes through on every pitch, if you can watch that hand carefully you can predict what kind of pitch it is, it's something that a fan has never had access to before, we did that for the first time this year. >> I had a new experience, obviously you see Statcast on TV now, a lot of this overlayed stuff happening, kind of creates like an esports vibe to the table. Esports is just coming. >> And it's just the beginning >> Your thoughts on esports, competitor, natural evolution, baseball's going to be involved in it, obviously, thing in the emerging technology's looking interesting, and the younger generation wants the hot, young... Sure, we feel like our game has been around a long time, and it still is, the rules haven't changed that much, but fans still enjoy it, but they just consume it differently and our game can be incredibly exciting in moments, but, there's also some gaps in there when you can build relationships. Some of the younger generation may fill those gaps with watching somethin' else, or two other things on their devices, but that's okay, we embrace that at the ballpark, but in terms of the emergence of esports, and the changing demographic of our fanbase, what we're trying to do is just package our game differently. One thing I'm really excited about, and startin' to see, we're in the early days, I consider with virtual reality, we experiment with it, maybe two or three years ago we've been doing some stuff with it, but I'd say it feels like we're in the second or third inning with virtual reality, where we're really going, and I've seen Intel doin' some of this stuff, I was out working with Intel in Pyeongchang, at the Olympics this past year, working with their PR team, and where it's going I can already visualize what this is going to be like, this concept of volumetric video. Where, it's not about having that courtside seat, in basketball, or that seat right behind home plate, it's about being wherever you want to be, anywhere in the action. And to me it's not about doin' it live, because in baseball, you don't know where the ball's going to go, it's about doin' it, replay, right after, okay, that ball was shot to Brandon Crawford, he made the most amazing diving play, picked it up, gunned it to first, where do you want to watch that from? Everybody's different, some people might want to watch it from right behind first base, some people might want to watch it right Brandon Crawford, behind the batter, with volumetric video and the future of VR, you'll be able to do that, and this esports generation, this fan's instant gratification want, unique experiences, that's what's going to deliver it. >> This is such an immersive environment, we're looking at this kind of volumetric things from Intel, and you got VR and AR, immersion, is a new definition, and it's not, I won't say putting pressure, it's evolving the business model, who would've thought that DraftKings and these companies would be around and be successful, that's gambling, okay, you now you got that, your VR so the business model's changing, I've been hearing even token and cryptocurrency, maybe baseball cards will be tokenized. So these are kind of new, crazy ideas that might be new fan experience and a business model for you guys. Your thoughts on those kind of wacky trends. >> That's why I love working with companies like Mayfield 'cause they're seeing the future before we see it, and I love being where we are, so we can talk to them, and learn about these companies. Another example, along those lines is, how are fans going to get to the ballpark five years from now, and how do we adapt to that because we're doing a major development right adjacent to the ballpark, we've got 4,000 parking spaces. Are we going to need those five years from now? Well we're going to build out that whole parking lot, we're going to put a structure in there. But five, ten years from now, we're building that structure so it can be adaptable, because, is anyone going to need to park? Is parking going to be like typing, you know on a typewriter, 10, 15 years now because everybody is in either self-driving cars, or ride shares, and the cars just, poof, go away, and they come back when you need 'em. >> Like I said, everything that's been invented's been on Star Trek except for the transporter room, but maybe they could transport to the game. >> We could use that in San Francisco. >> Bill, got to ask you about your role with Mayfield, because one of the things I've always been impressed with you is that you always have a taste for innovation, you're not afraid to put the toe in the water or jump in the deep end where the technology is, these guys are lookin' for some trends, too. How do you advise some of these guys, how do you work with Mayfield, what's the relationship, how are they to work with, what's the intersection between Mayfield and you? >> Well the one thing that Mayfield does is they put together a conference, each Summer, that I love comin' down to, and I get to meet a lot of my counterparts and we talked about meeting with my counterparts in sports, but I love meetin' with my counterparts across all industries, and Mayfield makes that possible, they bring us all together with some really interesting speakers on a variety of topics not all directly tech related, so it's a great opportunity for me to just get outside of the daily routine, get outside the box, open my mind, and I just have to drop down the road to do it. So that's an example, another thing is, Mayfield, and other firms will come to me, and just say, "Hey, here's a technology we're evaluating, "they think it would be a great fit in sports, "what do you think?" And so, I can give them some valuable feedback, on company's they're evaluating, companies will come to us, and I might throw them their way, so it's really a two way street >> Great relationship, so you're a sounding board for some ideas, you get to peek into the future, I mean, we've interviewed entrepreneurs, successful entrepreneurs here, it's a seven, eight year build out, so it's almost like an eight year peek into the future. >> Yeah, and it's super valuable, especially given where we are geographically and our inclination toward being on the leading edge. >> I want to just end the segment by sayin', thanks for comin' in, and I want you to show the ring there, 'cause I always, can't stop starin' at the hardware, you got the ring there, the world champion. >> It's a few years old at the moment, we're going to have to get a new one sometime soon. >> We got to work on that, so is there any cutting edge technology to help you evaluate the best player, who you lookin' at next year, what's goin' on? What's the trades goin' on, share us-- >> Are we off the record now, 'cause I have a feeling you're asking this for personal reasons, for your squad, so. >> I'm a Red Sox fan of the AL, obviously, moved here 20 years ago, big fan of the Giants, I love comin' to the games, you guys do a great job, fan experience is great, you guys do great job and I'm looking forward to seeing a great season. >> Thanks, yeah, hope springs eternal this time of year, we always block off October and expect to be busy, but when we have it back, it just gives us an opportunity to get a head start on everybody. >> Well Bill, thanks for coming in, Bill Schlough, CIO for the San Francisco Giants, here on Sand Hill Road talkin' about the 50th anniversary of Mayfield, and this is the People First Network, getting ideas from entrepreneurs, industry executives, and leaders. I'm John Furrier with theCUBE, thanks for watching. (electronic music)

(triumphant orchestral music) >> Hello, everyone, and welcome to a special CUBE conversation. I'm John Furrier, here inside theCUBE Studios in Palo Alto. We have a great CUBE conversation around security, malware, phishing, and we got Atif Mushtaq who's the CEO of SlashNext. It's a startup here in the Bay Area with a Series A funding and they really solved probably one of the hardest problems that people are trying to crack the code on, which is how do you solve the human problem of not getting phished? And that is the technique how people are getting in. Actually, welcome to theCUBE, thanks for coming in. >> Thanks for having me. >> So I love bringing the startups in to get the real lay of the land because you got some funding, you got customers, you just kind of get out in the market, you're at the frontlines of security. And you're solving one of the hardest problems. >> That's right. >> Malware, phishing. >> Phishing, yes. >> So before we get into it, take a minute to explain what the company's doing. What is SlashNext? Why did you start the company? What's the early product look like? And what's the core problem you're targeting? >> Yeah, of course, I mean, I think you already told that. We are a company that is completely focused on phishing and social engineering. We are not a part-time, phishing is not a part-time problem for us. The company was built on the problem that, okay, that phishing is a growing problem, and we really need a technology and a company who's dedicatedly focused on social engineering and phishing. Before founding SlashNext, I worked for a company called FireEye. And the FireEye was not about phishing. FireEye was all about malware problem, right? So when I came out of that, I started to see that there was a time when the malware were really growing rapidly, right? And at that time, they were trying to exploit problems in the software, and exploiting that without any human intervention, right? And over the period of time, what we saw that Google, Microsoft, the world, they tried to make their software really secure. So during my last days at FireEye, I started to feel that malware growth is going down, and the reason is that Microsoft software are much better than they used to be. Google is really determined that nobody should really exploit my software to install malware. But at the same time I was seeing that, okay, the cyber crimes are rising. So if the malware are going down, what is really causing the cyber crimes? And, end of the day, I found that, okay, the game has changed. Now it's more about tricking humans and tricking in such a way that they give you their information, they click on the malware themselves, without exploiting anything in the software. And I also found that, you know what, I mean, you can't really solve this problem with just conventional computing, right? With just the algorithm. You really need to understand the human psychology because these guys are exploiting that psychology. Fear, trust, and reward. All of us have these emotions, right? They just have to exploit them in such a way that we get excited enough to hand over our information willingly to them. And this is where we start-- >> And it's working too, by the way. We know the numbers are off the charts and we cover it heavily on siliconangle.com, and we're about to do a bunch more content on cybersecurity and national security. So now it's not just the individual, the implications are broader. >> That's right. >> But let's go back. Before we get into that, I want to get it back, when you said at FireEye, the company you worked for, you said they were just doing malware. So they saw malware declining, you saw the trends going up. Before you wrote a line of code, that's what you saw. When you started the technology, what did you do next? >> I think it started with the problem. I think first of all, I really wanted to make sure that I'm solving a growing problem. If the problem is going down, eventually other people will catch up and by the time you have a solution, maybe the problem is not really there. So it's funny that at that time there were so many other companies trying to solve the malware problem, and they didn't realize that, okay, the malware problems are going down, right? And because I was working for a company who started the malware thing around 2004 or '05, right? So I had already seen-- >> A little bit older. The trend moves on. The fashion moved to phishing. But what did you start writing code on? Is it born in the cloud, did you have servers? What were you doing? How were you getting going? >> Yes, the code technology is based on cognitive computing. And the reason you really need a cognitive computing or artificial intelligence because you need computer software who could understand emotions. Because phishing is about exploiting the human emotion. And they try to exploit you by giving you a piece of text or some visuals in order to trick you. Okay, your CEO lookalike say, okay, transfer me $50,000. There's nothing really malware in it, right? It's just $50,000 transfer to me, right? They give you a fake login page of PayPal. No malware in that, they're just using the logo and sometimes they ask you, okay, there are various computer problems on your laptop, right? In order to fix that, you need to call us, right? So they're trying to exploit your emotion of trust, reward, and greed. So, end of the day, we thought that, okay, unless we have an army of researchers who are doing all this job because they understand the human emotions, or we can build programs that can understand these emotions, and whenever they see someone is trying to exploit this emotion, they can trigger on that. So result is that we have built a technology in the cloud. So while your user is checking an email, or a webpage is being rendered on the computer screen, within milliseconds we find, okay, something suspicious is going on. And we send the information to a cloud, and from our cloud we launch the browser in realtime. So while I'm seeing this webpage on my screen, the computer programs are actually seeing a copy of that from the cloud. The only difference is that, this, I might not be the tech-savvy guy, but the computer algorithm that actually looking into that webpage, seeing what logo is being used and reading the natural language, they're quite tech-savvy. So with it-- >> Talk about the technology. So, you had customers out of the gate before you had one dime of venture capital. You started getting paying customers. How are they deploying? What was the original product? What was their initial traction? Is it a SaaS model? Do they buy software? What were they paying you for? >> The form factor was hardware based. The hardware was cloud-powered. The whole purpose of the hardware was to sniff the network traffic, all the web traffic at the network switch level, and whenever they see something suspicious, they engage that cloud. So all the secret sauce and the main technology resided at the cloud. It was just a mechanical way for us to sniff the traffic. So the first product that we sold was that hardware device. And now we're moving more towards other form factor-- >> And you guys catch some phishing out of the gate? Did you guys solve some problems out of the gate? >> Yeah, within seconds, we started catching stuff. We, first of all, started seeing direct filtration attempts. We started seeing the phishing attempt right away. And this is where, I think, we got them by surprise because they already have all these big vendors already in place, and they were kind of over confident. They said, okay, you know what? You look like a young guy who's rarely had big claims. >> You had FireEye, you must know what you're talking about, we'll give it a shot. >> We'll give it a shot and they never believed that, okay? They thought, okay, maybe I can catch one or two phishing attacks, right? >> I have nothing to lose. I'll try it, I'm probably >> I'll try-- >> going to be on the plan, one more, what's one more box? >> But we got them by surprise. At the very, very beginning, the moment you attach the network traffic, we'll start tripping and this is how we got, I mean, no marketing material, no website. A founder is going without any presentation, and just selling. And I a hired a VP of sales who would actually carry the box with me. I would manufacture the box in my bedroom. My wife would put stickers, she's really good at that. And we actually pack it-- >> It looks good, yeah. >> It looks good. >> Little micro boxes, well, trying the chip on there. No, only kidding. Yeah, so you got the products, how many customers did you get on the early stages? How many did you get in that month? >> We had around 10 paying customer, and the revenue for around three, $400,000 ARR before we went in front of the VCs. And these guys had actually seen FireEye, and FireEye took a lot of money before they even had the paying customer. And they said, you know, what are you doing? >> You did a good move there. So, Atif, bootstrapping is a great, I think it's not only brave from an entrepreneurial standpoint, it really gives you the more creative freedom, because if you're putting your own cash on the table. So it's commitment and also it gives you creative license, not like that extra pressure. Most VCs might, some of these might give you a pass. Most are a bunch of board meetings and want to put pressure on you. >> That's right. >> Let's take a step back. Give us a 101 on the current state of malware. What are the different types of malware out there? You mentioned a few of them just a second ago. Break down the top malware, I mean, the phishing attacks. What are the top phishing attacks that you're seeing right now that people should know about? That may not know about. >> Okay, so there are two things. I would call it, first of all, there are two things that are happening when it comes to phishing. First of all, the mechanism that phishing attacks for using is moving beyond email. That is the first change. Now we are seeing phishing attacks spreading through advertisement, through social media, through messaging apps. Previously it was just emails. So that's one difference that we are seeing. Another difference is that the type of phishing's changing as well. Historical, it has been about fake login pages or money transfer scams. Now we are seeing a lot more things that were never been tried by the bad guys. You are seeing the scareware scams where suddenly there's a popup on your screen and they're asking you, to install a malware because there's a problem on your system and so-called anti-virus is going to solve that problem, right? We're seeing browser extensions being spread through phishing, right? We are seeing telephone fraud happening through this phishing, right? So it has moved beyond just fake login pages. So, first of all, more communication medium, and at the same time, more type of phishing attacks that are happening. So, right now, if you say around 20 to 30% of attacks that we are catching are the credential stealing, fake login pages. Around 20 to 30% are the rogue software, fake Flash player, fake PDF readers, and all that. And then the rest are the, you know what, browser extensions. >> So what is spear phishing? I hear that term a lot. >> Spear phishing is the targeted phishing. Spear phishing is that I'm not sending it to hundreds and thousands of people randomly, and who are gets victim to it, that's a bonus, right? >> The system admin for the Linux kernel for the bank. >> Yeah, I'm targeting you. >> I'm targeting him, social engineering. >> So I'm going to LinkedIn. I'm going to LinkedIn. I want to target your company. So I got your name, I got your email, and I'm sending one email to you. That is spear phishing, right? The drive by phishing is all about sending it to thousands and thousands of peoples, and then getting them phished. But there's one thing, there's one trend that is happening that is actually making spear phishing going away. What's really happening is that a lot of people who are targeting you, they don't need to send you the direct email. They actually go to the black market and all these guys who are randomly hunting you, they got your name from there. So they don't have to work hard. >> Dark web has my contact. >> Right, so I can go there and say, you know what, John, is there anyone with this email who you recently phished? And the guy who never really cared about you acted and die. I got that guy infected, how much you going to pay me for that? I pay you $50, and now I got access to your information without even sending you any spear phishing email. So this dark market and this overall cyber crime business actually has made much easier for the guys who really want to target you. Spend 50 bucks instead of I try to send you emails, and I have to set up all these website. I don't have to do anything. I can simply go to that dark web and can buy your information. >> This is a really good point. I think this is some people, it scares a lot of people, but it's well known the crime syndicates in the dark web are well advanced and well funded. So a lot of Bitcoin and cryptocurrencies help fueling that. Share your opinion on that. Share some color commentary about how sophisticated and how robust the economy is in the dark web. >> There are hundreds and millions of dollars. I mean, the guys are making millions of dollars. There was a ransomware called CryptoLocker and called in to FBI. They made tons of millions of dollars. So the money is huge. And Bitcoin is actually fueling that. Previously it was very difficult. You can always track by it. Previously, around 2006, I remember there was a ransomware, and they were asking you to transfer money through Western Union. But you can really catch those guys, the money trail always there. Bitcoin is one thing that really fueled the dark web. Because for the very first time, you can steal people's money without leaving any trail. And that is actually, I think, is the unfortunate consequences is it is really fueling the cyber crimes because now you don't have to care about you getting tracked, getting arrested. >> Yeah, I mean, we have a debate on theCUBE all the time about this. I mean, that with every dark movement there's also a light at the end of the tunnel. Gaming culture leads a lot of the user experience. The dark web, I think, is leading a lot of the transactional things. If you think about Shadow IT before cloud was popular, Shadow IT is what drove a lot of the cloud early adopter. Some are saying that the dark web, and cryptocurrency, and blockchain, token economics, actually is a leading indicator of what we might become. So the dark web might become the operational model. >> That's right. >> Because you just turn the lights on and say, hey, if this is so inefficient, why not just adopt this efficient market? Yeah, you can't track it but it's more efficient. So, again, that's a little bit provocative and a little bit radical, but, I mean, think about it. A lot of problems going on. Bitcoin certainly is a great way to clear that cash out. >> That's right. >> And cannabis sales in the US is driving a lot of Bitcoin as well. >> That's right. >> Moving money around. So, follow the money, you'll find the technology, is what I always say. So, your thoughts now on the business. How do you see the business shaping? What are you guys trying to do? What's the product currently? You got some venture capital. You got Wing VC. >> That's right. >> And Norwest too. >> Norwest Partners. >> Great firms. What's it like? How much did you raise? What are you looking to do? >> So, we raised around $9 million last year, and we are gearing up for our CDSP earlier next year. So we have actually made great progress, and I think that one of the biggest thing that we're getting from our investors is that, I mean, just like FireEye, we got into the business of all this multi-vector phishing at the early stage. So, we have an advantage of around two to three years, as compared to our competitors, right? And at the same time, they also know that we are not developing a niche enterprise product. There are four billion internet users and phishing is all of them problem. So just think about that, right? We just have a tiny customer base, right? But if you target all those internet users, it's going to be around seven billion internet users. >> So do you have a strategy laid out yet? It's going to be an enterprise business? You're targeting individuals? Have you had a clear visibility on some of the target beach yet? >> So next two to three years is going to be all enterprise, right? And we'll start with the Northern America and all that. Maybe a later stage, little bit of the international expansion. But, overall, if you see the road map, and we really want to make a great company. I never really started this company to at least sell it for $100 million. >> You probably made some good dough at FireEye, so. They take care of you? >> Yeah, yeah, of course. (John and Atif laughing) But I think the purpose was that, I mean, I have nothing else to do, right? I mean, and so I'm not a serial entrepreneur. It was never the purpose that I can sell something quickly. >> You want to build a durable company. >> I want to build a durable company, and all the VCs, they want us to build a durable company because they want really, want a big exit, right? But I think the roadmap that they're seeing is that, okay, you know what, you can start with enterprise, and then you can go into the consumer space. And then, I think the problem is huge. It's not something that you can only sell to enterprise, or you can only sell to consumer, right? Every internet user is a victim. >> Yeah, and I think there's an opportunity for a vendor to come, I mean, a supplier, to come out of the market. And I've always said to the Illumio guys, Alan Cohen, and a bunch of other venture-backed companies, that it's going to be a new company, a new brand, that will be the big player. Because if you look at the market share, no one company actually has dominant market share in cybersecurity. >> That's right. >> So you have thousands of flowers blooming, but no clear winner yet. And I think that's a function of throwing everything at cybersecurity, and the buyers are like, I'll take anything. I'm so desperate. So there's a huge factor of desperation. How do you see that being solved? Because it is a desperate market, because people, they can't play offense, they got to play defense, they got to protect. And so the perimeter's gone. Used to be the moat and the firewall switch. Now it's gone, the perimeter. >> Is gone. >> Is gone, and so now you have service areas off the charts. So how do you protect it? (chuckles) What do you see? >> I think we started with the device model, right? But I think now we moving towards the software and the endpoint business. And we really believe that you need to cover the remote user. I mean, you just barely spend eight hours in the office, right? So we are actually developing technologies that are going to target the remote users, and we going to target multiple type of devices and all that. So that's our next big thing. Off of the same cloud technology. Cloud you have already developed, right? Now you have to develop multiple form factors or multiple ways to actually access that cloud. >> Multi-factor authentication, not just two-factor authentication really is the key, biometrics, things of that nature. Google's got some stuff going on there. But I want to get your thoughts on the cloud. I mean, cloud obviously is something you, cloud's your secret sauce. >> A big part of it. >> Is it on Amazon, Google? Which cloud do you use? >> It's distributed between AWS, but the core of our logic is actually reside in our own data centers. The reason is that the kind of GPU power that we wanted, because we are rendering all these pages in realtime, right? So we never got that kind of GPU support from the off-the-shelf AWS, right? So we really built our own-- >> So custom GPU powerhouse? >> Yes. >> For all the floating point calculations. >> Yeah, because you have to run millions of browser instances. Can you imagine? We are running all these virtual browser, continue-- >> Why didn't you start a GPU cloud? It's another venture. >> Yeah, another venture. (John laughing) But I think that's the lead for that because AI and the metrics calculation is going to be the key, right? And they're adding support. But around 2014 to be really frag-a-mit, it look like a joke. That you can have hundreds of millions of browser getting up and down, getting up and down, in realtime, right? So we got a very customized cloud for that purpose, and that's actually barrier to entry for a lot of other vendors. >> Yeah, and I think the cloud provides you some good agility as well. And they have, Amazon's kicking butt, we love Amazon. Okay, so now on the future. Hiring, you got some people. What are the key priorities for you guys? Engineering, obviously. More and more engineering. >> Engineering. >> Technology's cognitive. What kind of skill sets are you looking build? Machine learning, AI? >> It's already based on the machine learning and AI because we're doing the natural language processing, computer vision analysis. Because you want computer to see things, what's being rendered on the screen, right? So we already have the technology. What we really want to do now is to make it accessible for a variety of customers. Not every customer wants a hardware device, not every customer wants endpoint solution, right? You need to order multiple form factors. So you want to use this cloudware endpoint? Okay, you take that one. Okay, you love hardware device, right? But, end of the day, you're offering your cloud service to other people. So, first of all, building more form factors and definitely more customer traction. >> I better ask you the question, 'cause I just love the entrepreneurial hustle. And congratulations on the startup and it's looking really, great space to be in, by the way. So it's super, super great. 10 years out from now, in your mind's eye, what's the preferred future look like in your mind? For your company and the outcome that 10 years from now. What's it going to look like? What's the state of phishing and security? If you're successful, if you achieve your mission, what happens? >> Okay, so, I think, I mean, it's kind of funny. Over success lies with the bad news, right? I think every tech landscape is changing. It's usually one train lost was seven to eight years, before it goes down and the bad guys move to the next train. I think this is the very first time they have started targeting humans viciously, right? The problem is that by the time you have a trained professional, the new people who are emerging in, right? I don't think, right, this problem is going to get solved any time sooner. We can't rely on the humans to train, to get trained. You can't really make a user a computer security researches, right? In my opinion, eventually technology has to catch up. In my opinion. So I think we have to keep innovating because hackers are going to find new methods, and we have to keep on catching up. And I think we'll be a phishing protection company in the next 10 years. Maybe adjacent product, but I think we really want to be focus on this. >> And social engineering, to your point, and tell me if you agree with this, it's been very successful for hackers. Social engineering has been the tactic. And there's a variety of forms of social engineering. >> That's right. >> Great, awesome. Well, good luck with everything. Thanks for coming on theCUBE. We have Atif Mushtaq, the CEO of SlashNext. Hot startup funded by Norwest Venture Capital and Wing VC, two good firms that we know very well. They know their tech. And, again, security. Great problem to solve. And if there's a big thing you want to go after and solve a big problem, it's security. It's theCUBE bringing you the theCUBE coverage here in Palo Alto. I'm John Furrier, thanks for watching. (triumphant orchestral music)

(Exciting Techno Music) >> Live from the Computer History Museum in the heart of Silicon Valley, it's theCUBE covering food IT: Fork to Farm. Brought to you by Western Digital. >> Hi, welcome to theCUBE. We are live at the fourth annual food IT Fork to Farm Event. I am Lisa Martin with my Co-Host Jeff Frick. Jeff, this is a really interesting event. The first time we've been here with The Cube, and one of the first things I said to you this morning was "Fork to Farm - we always kind of think of it as "farm to fork, right, farm to table." But it's really interesting mix of investors here, people that are very educated in food and agriculture and one of the things they're focused on is connecting people who are feeding the world, billions and billions of people, with the people who are changing the world through technologies. And nowadays we're all this tech enabled food consumer which has really flipped farm to fork from fork to farm which I found really interesting. >> It's pretty interesting, our first kickoff call with Michael Rose from The Mixing Bowl and we were talking about the Conference. I'm like, "Michael didn't you get that mixed up? "Isn't it supposed to be Farm to Fork?" But as you said it's really now the tech enabled consumer and what they want to eat, like everything else, is being so consumer driven that we see in our other shows is driving now what the food producers have to create. And what's interesting is they don't necessarily think of all the ramifications of those decisions upstream and downstream. And so that's a big topic of the theme here. The other thing that struck me is some of the sponsors: Yamaha is here >> Yes. >> And one of the main sponsors. Google is here as one of the main sponsors. And we just had one of the opening keynotes from one of the guys from Google talking about how they've taken really just the task of feeding the employees to a much greater responsibility in both what people eat, how it gets produced, and really more sustainable longterm food kind of as a circle he called it. So it's pretty interesting, I'm excited. We've got Deans from a lot of big schools, we've got, of course, like I said, Yamaha. I'm really curious to find out what they're doing in this space. And it's fun to get, you know, out of the tech infrastructure space to see what's really happening on the front lines. I really want to get into edge computing, I really want to get into cloud, data, you know, all of the themes that we follow over and over and over again, but now a real specific application. And doing some of the research, you know, we have to feed 10 billion people in just a couple years and we're not growing any more land. So how are those challenges being addressed with technology? How are cloud, mobile, data helping solve those problems? And then how are the consumer driven prioritization impacting all of this? So it should be a great day. >> Absolutely, like you said, a great spectrum of guests on the show today. And we think of food and agriculture as one of the largest industries globally and as you said, there's a daunting responsibility feeding billions of people in a very short period of time. Having to deal with environmental sustainability, we're going to be talking about that on the program today, climate change, and also the consumer. But there's tremendous potential for big data and IOT and analytics to improve farming efficiencies from planting to weeding to fertilizing to the post-harvest supply chain logistics, traceability. There's, you know, opportunities for GPS sensors on tractors and columbines, as well as robotics and automation. We're going to be talking to a guy, the CEO Chell Botics, who invented Sally, a robot that makes salads. So there's a tremendous amount of opportunity and I'm really curious to see how these, from the University Folks, the Deans, to the investors, how Venture Capital is really seeing big data as revolutionary, the potential to be revolutionary, for the entire food supply, the food chain. >> Right, right. And another topic that's come up is really transparency and enabling consumers to see kind of where their food comes from, how it was raised, but as come up again in one of the earlier Keynotes, there's no perfect solution, right? There's always trade offs. So how are people creating values, making trade offs based on those values, and how are the food producers now being able to deliver to those values? So it should be, like I said, a fantastic day. We're going to go wall to wall. We'll be here till 5 o'clock today, full slate of guests, a lot of two guests, so we're going to pack them in. And it should be fantastic. >> Absolutely, I'm excited. >> Alright. >> A lot of great topics. >> So she's Lisa Martin, I'm Jeff Frick, you're watching theCUBE from Food IT: from Fork to Farm. We'll be right back with our first guest after this short break. Thanks for watching.

okay we're back this is Dave vellante Wikibon organ this is the cube where we go out to the events we extract the signal from the noise we bring you the best guests that we can find we like to call them Tech athletes I'm here with my co-host Jeff Frick Doug Leone is here he's a partner at Sequoia Capital very well-known VC on the board of service now Doug welcome to the cube >> thank you so today here >> here you know a lot of times venture >> it's great to have you capitalists they'll get in they'll help see the company's help grow the company's go to go to an IPO successful IPO and kind of go on to the next one so you're here and you're seeing the growth of this company the meteoric rise and your see this user conference you must be delighted to see the the degree the enthusiasm of the user base it's very exciting >> it's very exciting to be here and see close to 4,000 people being here and hearing some other feedback from the customers terrific >> so how is it that that they've been able to keep you interested in in this journey and you know you're still here you're helping you know grow the company >> the short answer is that the job is not well I think done yet we we are in the early innings if one thinks about IT service management we're well on our way but one thing we learned from the conference is that customers are finding many use cases for the software and the software is spreading in IT, in HR in many other areas so I actually think we're in the early innings and so I think there's a great deal of opportunities for the company and I would like to very much try to help in garner as much market share in that opportunity as we can >> been around the technology industry for >> yeah you've a while why is it if you feel that I t is now ready to change >> well i think it's-- ready to change for the simple reason that the world has changed if you think of IT maybe four or five years ago essentially what the role of IT was a defensive role to protect the enterprise and the employees and the technology were enclosed in  four walls and a little bit on the tax side where no was the first answer and yes was the other answer and they work mainly in infrastructure I think our that is the plumbing well suddenly the the role of the CIO is completely changed the defensive part of the house has become much more challenging that technology is out of the building and the employees are out of the building so that requires a lot more skill set and it's way more exciting and the plumbing side of the house is completely change where the CIO is no longer the plumber is a business partner so his role has been elevated within the corporation and I think it's the most exciting time to be a CIO in a history of CEOs so I think that the future is very bright for this market segment lastly for the very first time the IT function touches every employee in a company and so that there's a lot to be done for every employee >> we talk a lot on the cube about the whole hyperscale trend and people I colleague John first is if you want to know what's going to happen in the enterprise five years from now go look at what's happening at you know Google and Facebook and Amazon and you remember after the calm crash and Nick Carr wrote his famous book does IT matter everybody just pulled back like you said got defensive but the hyperscale crowd showed us that technology actually can be used to create competitive advantage nonetheless a lot of traditional IT has continued to be defensive do you think that platforms like ServiceNow can actually change that mindset and bring IT back to being a competitive advantage and also importantly catalyze increased spending within IT >> would take it one step further I think  well I actually that companies like service now offer a product that are extremely necessary for IT to change I don't think it can be done with our ServiceNow for the very first time we have employees that can create applications on the fly that can create application many applications that talk to one another in a single type of a data model therefore the ERP for IT and instead of the end uses having to wait weeks months for any changes that can be done very quickly very overnight by a user so I think having learned a little bit from amazon and from Google in the expectations of the end user within a corporation's a company like ServiceNow now offers a solution where companies can make those kinds of changes and build those kinds of systems very very quickly >> so Doug I wonder if you could talk from step back from kind of a VC perspective where we saw a few years back you know tremendous investment and valuation creation in Facebook's and and Google of course and a lot of consumer facing buzz Zynga and this and that and now you know it seems to kind of shift it back to the enterprise side but I think what's what's interesting is how the consumerization and those applications both in infrastructure as well as user experience seem to really now be influencing where the enterprise side of the house is going you speak this >> sure please keep in mind that the business of investing in these small companies is a business of latency if you invest in one year products on the market for two years later and consumer adoption is three or four years later and unfortunately the venture industry tends to run with momentum investing so 50,000 venture guys do consumer 50,000 venture guys do infrastructure and IT I think the good investors have seen some of these trends just begin to evolve four or five years ago and we you have to be quite consistent and be true to your vision if you start coming in to companies in infrastructure right now one could argue that you're investing at a local maximum maybe four or five years ago but unfortunately in the investment industry is momentum driven industry for most investors and you know the thing that happens with momentum you're always a little late i'm paying the highest price and then the moment that you get there that you see a peak so i think the trick is to have careful market maps have a clear vision and then have dumbo like ears available to listen to guys like Fred Luddy so when you run across them and they have a crystal-clear vision of the future you're ready to jump on him for the simple reason you've thought I had and maybe it was one of your veins of your market maps >> What was it  when you first talked to Fred that really struck to you what was the vision that resonated >> I think two or three things one he was crystal clear in what he wanted to do and the great founders are crystal clear because they are great thinkers they spend all the time thinking and therefore when you spend a lot of time thinking then what you can do is articulate in very few words second Fred knew exactly as the founder in very few words of the company what is strengths were and what his strengths were not or his weaknesses were and he asked some of his trusted friends investors and colleague to help them find people to shore up the other side and third he just told it like it is no surprises as a matter of fact for every board meeting we went to  for the first year and a half the only surprises we got was surprised on the upside and I will tell you that never happens >> Doug  you have said that the the the next big thing in enterprise IT really doesn't exist you're telling us now your philosophy is somewhat non contrarian most VCS like you said are out chasing a trend they're trying to focus on momentum so so talk about that a little bit if there is no next big thing in IT well how do you decide what to invest in you said you have these market maps talk a little bit about that philosophy so I I think what I really said is that there's no way we know what the next big thing is as a matter of fact if I could articulate what the next big thing is i'll tell you it is not the next big thing as i said earlier in a presentation the day before we met Fred ludie if you had asked me that question I would not have told you IT Service Management is the next big thing it took Fred to come in and explain to us why that was going to be a market opportunity and we jumped on it so if we make ten investments four or five fits some kind of market map it's an extension of the world we know mobile is going to penetrate I can tell you the real exciting investments are the ones where no one's paying attention and someone like Fred lady can see the future so there is no so yes there's going to be next big thing is going to be wearable computing is going to be Google glass who the heck knows but there's going to be a founder an entrepreneur that's going to explain to us here's an application for google so you haven't thought of that's going to make it very clear why we want to chase that and not just wearing a pair of glasses marc andreessen was on CNBC yesterday talking about the perils of public companies and and and basically well it was somewhat self-serving I tended to agree with a lot of what are you saying i mean the barriers for a public company are now so high but now here you are with with service now what's that experience been like taking the company public i guess if you're always beating on the upside that helps but you know there's eventually going to be some bumps in the road so what's your you know opinion on the whole public market you know so what's your stance on that well the position i have is that it's better to stay private because that you can do a lot more so there's only two or three reasons to go public one is a branding event your competitors will say oh it's a small private company they're running out of cash and so on sensing your financials are not public some customers may tend to believe it second is to finance a company although one thing I'd argue is that if you've got a great investment with lots of money whether your private or public and third is to provide some liquidity for employees unfortunately the liquidity for them is not something that happens overnight you know one day you go public the next day is not the david you sell all your shares and so it really comes down to a branding event and our position is keep companies private until they get very strong practice for a year or so done to what it's like to be public have your financial house in order then go public and always start with an o first and move the way towards a yes because the IPO is simply a day in the life of the company as you're trying to build a great business it's not the other way where you go public let's all go public for the heck of it so start with an old justified chuoi yes your life was change and you better have control over your forecast your financial systems and so on prior to being published yeah so service now obviously New York Stock Exchange selling to the global 2000 the biggest companies that had to help from a branding standpoint it helped a lot because old the fight in the business or in the market that was spread by our competitors we're not financially viable well I think the whole world sees that we are way more than financially viable all that junk that a local salesman is going to say against another local salesman in the heat of sale situations is completely out of the market because now what you're dealing was with facts and we knew that our fax way better than our competitors facts well there's so many insularity benefits to it wasn't the motivation for going public but you've you know prior to going public cash flow was king and you had to you know invoice a certain way and now you've got you know hundreds of millions of dollars in the balance sheet and and so you're able to it gives you greater financial flexibility as well yeah we have cash flows as a private company and you know and as a public company it's not that if you have a lot of cash that you can spend it for the heck of it you have to justify model why doing so is the the right thing cash cash is always available if you have a terrific company there's people that are willing to throw cash in bucketfuls of you so it's not cash um we talked it was interesting to hear Frank today talking about Facebook he was my second topic just definitely the first major IPO and technology right after Facebook he called it the face plant IPO tongue-in-cheek but then of course you had work day as well and you guys seem to be more work day like you know kind of similar transformation even though you're going to IT is that a fair comparison yes I I think it's a fair comparison is that it's too fabulous SAS companies you know about six months ago if I act if I'd ask someone what's the grade the second greatest company in the SAS marketplace nobody could name it Salesforce nobody new number two now people know its sales force its work day and it's service now it's a fair comparison I think that both companies have a very long term market opportunities and I think both companies have standalone possibility have the possibilities of being large and standalone companies for many years to come so Sequoia obviously great firm you know one of the leading venture capital firms in the in the west coast in the win the world what's that what sets Sequoia apart we've been in business for 40 years and we've been on top of our game for 40 years or on top of the business I hate calling it a game we tend to hot sports analogies here that's okay no there's dangerous with sports analogies because the moment I mentioned team and a sports team there's only room for five people and a basketball team was starts and that's the koya if you've got ten people were skillful we have room for all 10 of them so I'm always a bit leery of the sports analogy but but it's the culture it the culture of people that came from humble beginnings who have a deep-rooted need to win we have good business instincts who are willing to learn and we're willing to be business partners and that's a key set of words business partners to founders to help them build a great business over the very long term you've spent some time in business development and sales over the years how has sales or has sales changed over that time frame some things have some things haven't I remember 15 years ago 20 years ago wait you could not get to what we call the SMB the small businesses because the cost of sales was too expensive now due to telesales and the internet that you can get there but there are some things that have not changed if you've got a sales force you they should be very well paid they should not have a high base they should be able to make a ton of money sales leadership you come from a former salesperson so some things have change and some things are deeply rooted in the DNA of a salesperson and may never change I took the only we're out of time but I want one last question is we're observers of service now outside observers what should we be watching for what are the things that you would ask us to pay attention to what watch how deeply ingrained throughout the many departments of a company the ServiceNow software becomes not just for IT Service Management but for a variety of applications written by employees of that company for the benefit of that company all right Chuck thank you very much really exciting to have you on the cube great job congratulations let you said you're not done yet so good luck when you're your future journey is really a thank-you a measure thank you thank you very much all righty buddy I'll be right there we will be back with our next guest this is service nows knowledge conference i'm dave vellante with Jeff Rick this is the cube we'll be right back after this short break