(lively music) >> Hello, everyone. Welcome back to the Supercloud presentation here. I'm theCUBE, I'm John Furrier, your host. What a great segment here. We're going to unpack the networking aspect of the cloud, how that translates into what Supercloud architecture and platform deployment scenarios look like. And demystify multi-cloud, hybridcloud. We've got two great experts. Amir Khan, the Co-Founder and CEO of Alkira, Atif Khan, Co-Founder and CTO of Alkira. These guys been around since 2018 with the startup, but before that story, history in the tech industry. I mean, routing early days, multiple waves, multiple cycles. >> Welcome three decades. >> Welcome to Supercloud. >> Thanks. >> Thanks for coming on. >> Thank you so much for having us. >> So, let's get your take on Supercloud because it's been one of those conversations that really galvanized the industry because it kind of highlights almost this next wave, this next side of the street that everyone's going to be on that's going to be successful. The laggards on the legacy seem to be stuck on the old model. SaaS is growing up, it's ISVs, it's ecosystems, hyperscale, full hybrid. And then multi-cloud around the corners cause all this confusion, everyone's hand waving. You know, this is a solution, that solution, where are we? What do you guys see as this supercloud dynamic? >> So where we start from is always focusing on the customer problem. And in 2018 when we identified the problem, we saw that there were multiple clouds with many diverse ways of doing things from the network perspective, and customers were struggling with that. So we delved deeper into that and looked at each one of the cloud architectures completely independent. And there was no common solution and customers were struggling with that from the perspective. They wanted to be in multiple clouds, either through mergers and acquisitions or running an application which may be more cost effective to run in something or maybe optimized for certain reasons to run in a different cloud. But from the networking perspective, everything needed to come together. So that's, we are starting to define it as a supercloud now, but basically, it's a common infrastructure across all clouds. And then integration of high lift services like, you know, security or IPAM services or many other types of services like inter-partner routing and stuff like that. So, Amir, you agree then that multi-cloud is simply a default result of having whatever outcomes, either M&A, some productivity software, maybe Azure. >> Yes. >> Amazon has this and then I've got on-premise application, so it's kinds mishmash. >> So, I would qualify it with hybrid multi-cloud because everything is going to be interconnected. >> John: Got it. >> Whether it's on-premise, remote users or clouds. >> But have CTO perspective, obviously, you got developers, multiple stacks, got AWS, Azure and GCP, other. Not everyone wants to kind of like go all in, but yet they don't want to hedge too much because it's a resource issue. And I got to learn this stack, I got to learn that stack. So then now, you have this default multi-cloud, hybrid multi-cloud, then it's like, okay, what do I do? How do you spread that around? Is it dangerous? What's the the approach technically? What's some of the challenges there? >> Yeah, certainly. John, first, thanks for having us here. So, before I get to that, I'll just add a little bit to what Amir was saying, like how we started, what we were seeing and how it, you know, correlates with the supercloud. So, as you know, before this company, Alkira, we were doing, we did the SD-WAN company, which was Viptela. So there, we started seeing when people started deploying SD-WAN at like a larger scale. We started like, you know, customers coming to us and saying they needed connectivity into the cloud from the SD-WAN. They wanted to extend the SD-WAN fabric to the cloud. So we came up with an architecture, which was like later we started calling them Cloud onRamps, where we built, you know, a transit VPC and put like the virtual instances of SD-WAN appliances extended from there to the cloud. But before we knew, like it started becoming very complicated for the customers because it wasn't just connectivity, it also required, you know, other use cases. You had to instantiate or bring in security appliances in there. You had to secure all of that stuff. There were requirements for, you know, different regions. So you had to bring up the same thing in different regions. Then multiple clouds, what did you do? You had to replicate the same thing in multiple clouds. And now if there was was requirement between clouds, how were you going to do it? You had to route traffic from somewhere, and come up with all those routing controls and stuff. So, it was very complicated. >> Like spaghetti code, but on network. >> The games begin, in fact, one of our customers called it spaghetti mess. And so, that's where like we thought about where was the industry going and which direction the industry was going into? And we came up with the Alkira where what we are doing is building a common infrastructure across multiple clouds, across in, you know, on-prem locations, be it data centers or physical sites, branches sites, et cetera, with integrated security and network networking services inside. And, you know, nowadays, networking is not only about connectivity, you have to secure everything. So, security has to be built in. Redundancy, high availability, disaster recovery. So all of that needs to be built in. So that's like, you know, kind of a definition of like what we thought at that time, what is turning into supercloud now. >> Yeah. It's interesting too, you mentioned, you know, VPCs is not, configuration of loans a hassle. Nevermind the manual mistakes could be made, but as you decide to do something you got to, "Oh, we got to get these other things." A lot of the hyper scales and a lot of the alpha cloud players now, and cloud native folks, they're kind of in that mode of, "Wow, look at what we've built." Now, they're got to maintain, how do I refresh it? Like, how do I keep the talent? So they got this similar chaotic environment where it's like, okay, now they're already already through, so I think they're going to be okay. But then some people want to bypass it completely. So there's a lot of customers that we see out there that fit the makeup of, I'm cloud first, I've lifted and shifted, I move some stuff to the cloud. But I want to bypass all that learnings from all the people that are gone through the past three years. Can I just skip that and go to a multi-cloud or coherent infrastructure? What do you think about that? What's your view? >> So yeah, so if you look at these enterprises, you know, many of them just to find like the talent, which for one cloud as far as the IT staff is concerned, it's hard enough. And now, when you have multiple clouds, it's hard to find people the talent which is, you know, which has expertise across different clouds. So that's where we come into the picture. So our vision was always to simplify all of this stuff. And simplification, it cannot be just simplification because you cannot just automate the workflows of the cloud providers underneath. So you have to, you know, provide your full data plane on top of it, fed full control plane, management plane, policy and management on top of it. And coming back to like your question, so these nowadays, those people who are working on networking, you know, before it used to be like CLI. You used to learn about Cisco CLI or Juniper CLI, and you used to work on it. Nowadays, it's very different. So automation, programmability, all of that stuff is the key. So now, you know, Ops guys, the DevOps guys, so these are the people who are in high demand. >> So what do you think about the folks out there that are saying, okay, you got a lot of fragmentation. I got the stacks, I got a lot of stove pipes, if you will, out there on the stack. I got to learn this from Azure. Can you guys have with your product abstract the way that's so developers don't need to know the ins and outs of stack's, almost like a gateway, if you will, the old days. But like I'm a developer or team develop, why should I have to learn the management layer of Azure? >> That's exactly what we started, you know, out with to solve. So it's, what we have built is a platform and the platform sits inside the cloud. And customers are able to build their own network or a virtual network on top using that platform. So the platform has its own data plane, own control plane and management plane with a policy layer on top of it. So now, it's the platform which is sitting in different clouds, but from a customer's point of view, it's one way of doing networking. One way of instantiating or bringing in services or security services in the middle. Whether those are our security services or whether those are like services from our partners, like Palo Alto or Checkpoint or Cisco. >> So you guys brought the SD-WAN mojo and refactored it for the cloud it sounds like. >> No. >> No? (chuckles) >> We cannot said. >> All right, explain. >> It's way more than that. >> I mean, SD-WAN was wan. I mean, you're talking about wide area networks, talking about connected, so explain the difference. >> SD-WAN was primarily done for one major reason. MPLS was expensive, very strong SLAs, but very low speed. Internet, on the other hand, you sat at home and you could access your applications much faster. No SLA, very low cost, right? So we wanted to marry the two together so you could have a purely private infrastructure and a public infrastructure and secure both of them by creating a common secure fabric across all those environments. And then seamlessly tying it into your internal branch and data center and cloud network. So, it merely brought you to the edge of the cloud. It didn't do anything inside the cloud. Now, the major problem resides inside the clouds where you have to optimize the clouds themselves. Take a step back. How were the clouds built? Basically, the cloud providers went to the Ciscos and Junipers and the rest of the world, built the network in the data centers or across wide area infrastructure, and brought it all together and tried to create a virtualized layer on top of that. But there were many limitations of this underlying infrastructure that they had built. So number of routes per region, how inter region connectivity worked, or how many routes you could carry to the VPCs of V nets? That all those were becoming no common policy across, you know, these environments, no segmentation across these environments, right? So the networking constructs that the enterprise customers were used to as enterprise class carry class capabilities, they did not exist in the cloud. So what did the customer do? They ended up stitching it together all manually. And that's why Atif was alluding to earlier that it became a spaghetti mess for the customers. And then what happens is, as a result, day two operations, you know, troubleshooting, everything becomes a nightmare. So what do you do? You have to build an infrastructure inside the cloud. Cloud has enough raw capabilities to build the solutions inside there. Netflix's of the world. And many different companies have been born in the cloud and evolved from there. So why could we not take the raw capabilities of the clouds and build a network cloud or a supercloud on top of these clouds to optimize the whole infrastructure and seamlessly connecting it into the on-premise and remote user locations, right? So that's your, you know, hybrid multi-cloud solution. >> Well, great call out on the SD-WAN in common versus cloud. 'Cause I think this is important because you're building a network layer in the cloud that spans out so the customers don't have to get into the, there's a gap in the system that I'm used to, my operating environment, of having lockdown security and network. >> So yeah. So what you do is you use the raw capabilities like bandwidth or virtual machines, or you know, containers, or, you know, different types of serverless capabilities. And you bring it all together in a way to solve the networking problems, thereby creating a supercloud, which is an abstraction layer which hides all the complexity of the underlying clouds from the customer, right? And it provides a common infrastructure across all environments to that customer, right? That's the beauty of it. And it does it in a way that it looks like, if they have the networking knowledge, they can apply it to this new environment and carry it forward. One way of doing security across all clouds and hybrid environments. One way of doing routing. One way of doing large-scale network address translation. One way of doing IPAM services. So people are tired of doing individual things and individual clouds and on-premise locations, right? So now they're getting something common. >> You guys brought that, you brought all that to bear and flexible for the customer to essentially self-serve their network cloud. >> Yes, yeah. Is that the wave? >> And nowadays, from business perspective, agility is the key, right? You have to move at the pace of the business. If you don't, you are losing. >> So, would it be safe to say that you guys have a network supercloud? >> Absolutely, yeah. >> We, pretty much, yeah. Absolutely. >> What does that mean to our customer? What's in it for them? What's the benefit to the customer? I got a network supercloud, it connects, provides SLA, all the capabilities I need. What do they get? What's the end point for them? What's the end? >> Atif, maybe you can talk some examples. >> The IT infrastructure is all like distributed now, right? So you have applications running in data centers. You have applications running in one cloud. Other cloud, public clouds, enterprises are depending on so many SaaS applications. So now, these are, you can call these endpoints. So a supercloud or a network cloud, from our perspective, it's a cloud in the middle or a network in the middle, which provides connectivity from any endpoint to any endpoint. So, you are able to connect to the supercloud or network cloud in one way no matter where you are. So now, whichever cloud you are in, whichever cloud you need to connect to. And also, it's not just connecting to the cloud. So you need to do a lot of stuff, a lot of networking inside the cloud also. So now, as Amir was saying, every cloud has its own from a networking, you know, the concept perspective or the construct, they are different. There are limitations in there also. So this supercloud, which is sitting on top, basically, your platform is sitting into the cloud, but the supercloud is built on top of using your platform. So that abstracts all those complexities, all those limitations. So now your limitations are whatever the limitations of that platform are. So now your platform, that platform is in our control. So we can keep building it, we can keep scaling it horizontally. Because one of the things is that, you know, in this cloud era, one of the things is autoscaling these services. So why can't the network now autoscale also, just like your other services. >> Network autoscaling is a genius idea, and I think that's a killer. I want to ask the the follow on question because I think, first of all, I love what you guys are doing. So, I think it's a great example of this new innovation. It's not obvious until you see it, right? Geographical is huge. So, you know, single instance, global instances, multiple instances, you're seeing global. How do you guys look at that global equation? Because as companies expand their clouds into geos, and then ultimately, you know, it's obviously continent, region and locales. You're going to have geographic issues. So, this is an extension of your network cloud? >> Amir: It is the extension of the network cloud because if you look at this hyperscalers, they're sitting pretty much everywhere in the globe. So, wherever their regions are, the beauty of building a supercloud is that you can by definition, be available in those regions. It literally takes a day or two of testing for our stack to run in those regions, to make sure there are no nuances that we run into, you know, for that region. The moment we bring it up in that region, all customers can onboard into that solution. So literally, what used to take months or years to build a global infrastructure, now, you can configure it in 10 minutes basically, and bring it up in less than one hour. Since when did we see any solution- >> And by the way, >> that can come up with. >> when the edge comes out too, you're going to start to see more clouds get bolted on. >> Exactly. And you can expand to the edge of the network. That's why we call cloud the new edge, right? >> John: Yeah, it is. Now, I think you guys got a good solutions, network clouds, superclouds, good. So the question on the premise side, so I get the cloud play. It's very cool. You can expand out. It's a nice layer. I'm sure you manage the SLAs between latency and all kinds of things. Knowing when not to do things. Physics or physics. Okay. Now, you've got the on-premise. What's the on-premise equation look like? >> So on-premise, the kind of customers, we are working with large enterprises, mid-size enterprises. So they have on-prem networks, they have deployed, in many cases, they have deployed SD-WAN. In many cases, they have MPLS. They have data centers also. And a lot of these companies are, you know, moving the applications from the data center into the cloud. But we still have large enterprise- >> But for you guys, you can sit there too with non server or is it a box or what is it? >> It's a software stack, right? So, we are a software company. >> Okay, so no box. >> No box. >> Okay, got it. >> No box. >> It's even better. So, we can connect any, as I mentioned, any endpoint, whether it's data centers. So, what happens is usually these enterprises from the data centers- >> John: It's a cloud endpoint for you. >> Cloud endpoint for us. And they need highspeed connectivity into the cloud. And our network cloud is sitting inside the or supercloud is sitting inside the cloud. So we need highspeed connectivity from the data centers. This is like multi-gig type of connectivity. So we enable that connectivity as a service. And as Amir was saying, you are able to bring it up in minutes, pretty much. >> John: Well, you guys have a great handle on supercloud. I really appreciate you guys coming on. I have to ask you guys, since you have so much experience in the industry, multiple inflection points you've guys lived through and we're all old, and we can remember those glory days. What's the big deal going on right now? Because you can connect the dots and you can imagine, okay, like a Lambda function spinning up some connectivity. I need instant access to a new route, throw some, I need to send compute to an edge point for process data. A lot of these kind of ad hoc services are going to start flying around, which used to be manually configured as you guys remember. >> Amir: And that's been the problem, right? The shadow IT, that was the biggest problem in the enterprise environment. So that's what we are trying to get the customers away from. Cloud teams came in, individuals or small groups of people spun up instances in the cloud. It was completely disconnected from the on-premise environment or the existing IT environment that the customer had. So, how do you bring it together? And that's what we are trying to solve for, right? At a large scale, in a carrier cloud center (indistinct). >> What do you call that? Shift right or shift left? Shift left is in the cloud native world security. >> Amir: Yes. >> Networking and security, the two hottest areas. What are you shifting? Up or down? I mean, the network's moving up the stack. I mean, you're seeing the run times at Kubernetes later' >> Amir: Right, right. It's true we're end-to-end virtualization. So you have plumbing, which is the physical infrastructure. Then on top of that, now for the first time, you have true end-to-end virtualization, which the cloud-like constructs are providing to us. We tried to virtualize the routers, we try to virtualize instances at the server level. Now, we are bringing it all together in a truly end-to-end virtualized manner to connect any endpoint anywhere across the globe. Whether it's on-premise, home, multiple clouds, or SaaS type environments. >> Yeah. If you talk about the technical benefits beyond virtualizations, you kind of see in virtualization be abstracted away. So you got end-to-end virtualization, but you don't need to know virtualization to take advantage of it. >> Exactly. Exactly. >> What are some of the tech involved where, what's the trend around on top of virtual? What's the easy button for that? >> So there are many, many use cases from the customers and they're, you know, some of those use cases, they used to deliver out of their data centers before. So now, because you, know, it takes a long time to spend something up in the data center and stuff. So the trend is and what enterprises are looking for is agility. And to achieve that agility, they are moving those services or those use cases into the cloud. So another technical benefit of like something like a supercloud and what we are doing is we allow customers to, you know, move their services from existing data centers into the cloud as well. And I'll give you some examples. You know, these enterprises have, you know, tons of partners. They provide connectivity to their partners, to select resources. It used to happen inside the data center. You would bring in connectivity into the data center and apply like tons of ACLs and whatnot to make sure that you are able to only connect. And now those use cases are, they need to be enabled inside the cloud. And the customer's customers are also, it's not just coming from the on-prem, they're coming from the cloud as well. So, if they're coming from the cloud as well as from on-prem, so you need like an infrastructure like supercloud, which is sitting inside the cloud and is able to handle all these use cases. So all of these use cases have to be, so that requires like moving those services from the data center into the cloud or into the supercloud. So, they're, oh, as we started building this service over the last four years, we have come across so many use cases. And to deliver those use cases, you have to have a platform. So you have to have your own platform because otherwise you are depending on somebody else's, you know, capabilities. And every time their capabilities change, you have to change. >> John: I'm glad you brought up the platform 'cause I want to get your both reaction to this. So Bob Muglia just said on theCUBE here at Supercloud, that supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question is, is supercloud a platform or an architecture in your view? >> That's an interesting view on things, you know? I mean, if you think of it, you have to design or architect a solution before we turn it into a platform. >> John: It's a trick question actually. >> So it's a, you know, so we look at it as that you have to have an architectural approach end to end, right? And then you build a solution based on that approach. So, I don't think that they are mutually exclusive. I think they go hand in hand. It's an architecture that you turn into a solution and provide that agility and high availability and disaster recovery capability that it built into that. >> It's interesting that these definitions might be actually redefined with this new configuration. >> Amir: Yes. >> Because architecture and platform used to mean something, like, aight here's a platform, you buy this platform. >> And then you architecture solution. >> Architect it via vendor. >> Right, right, right. >> Okay. And they have to deal with that architecture in the place of multiple superclouds. If you have too many stove pipes, then what's the purpose of supercloud? >> Right, right, right. And because, you know, historically, you built a router and you sold it to the customer. And the poor customer was supposed to install it all, you know, and interconnect all those things. And if you have 40, 50,000 router network, which we saw in our lifetime, 'cause there used to be many more branches when we were growing up in the networking industry, right? You had to create hierarchy and all kinds of things to figure out how to solve that problem. We are no longer living in that world anymore. You cannot deploy individual virtual instances. And that's what approach a lot of people are taking, which is a pure overly network. You cannot take that approach anymore. You have to evolve the architecture and then build the solution based on that architecture so that it becomes a platform which is readily available, highly scalable, and available. And at the same time, it's very, very easy to deploy. It's a SaaS type solution, right? >> So you're saying, do the architecture to get the solution for the platform that the customer has. >> Amir: Yes. >> They're not buying a platform, they end up with a platform- >> With the platform. >> as a result of Supercloud path. All right. So that's what's, so you mentioned, that's a great point. I want to double click on what you just said. 'Cause I like that what you said. What's the deployment strategy in your mind for supercloud? I'm an architect. I'm at an enterprise in the Midwest. I'm an insurance company, got some cloud action going on. I'm mostly on-premise. I've got the mandate to transform the company. We have apps. We'll be fully transformed in five years. What's my strategy? What do I do? >> Amir: The resources. >> What's the deployment strategy? Single global instance, code in every region, on every cloud? >> It needs to be a solution which is available as a SaaS service, right? So from the customer's perspective, they are onboarding into the supercloud. And then the supercloud is allowing them to do whatever they used to do, you know, historically and in the new world, right? That needs to come together. And that's what we have built is that, we have brought everything together in a way that what used to take months or years, and now taking an hour or two hours, and then people test it for a week or so and deploy it in production. >> I want to bring up something we were talking about before we were on camera about the TCP/IP, the OSI model. That was a concept that destroyed the proprietary narcissist. Work operating systems of the mini computers, which brought in an era of tech prosperity for generations. TCP/IP was kind of the magical moment that allowed for that kind of super networking connection. Inter networking is what's called as a category. It feels like something's going on here with supercloud. The way you describe it, it feels like there's this unification idea. Like the reality is we've got multiple stuff sitting around by default, you either clean it up or get rid of it, right? Or it's almost a, it's either a nuance, a new nuisance or chaos. >> Yeah. And we live in the new world now. We don't have the luxury of time. So we need to move as fast as possible to solve the business problems. And that's what we are running into. If we don't have automated solutions which scale, which solve our problems, then it's going to be a problem. And that's why SaaS is so important in today's world. Why should we have to deploy the network piecemeal? Why can't we have a solution? We solve our problem as we move forward and we accomplish what we need to accomplish and move forward. >> And we don't really need standards here, dude. It's not that we need a standards body if you have unification. >> So because things move so fast, there's no time to create a standards body. And that's why you see companies like ours popping up, which are trying to create a common infrastructure across all clouds. Otherwise if we vent the standardization path may take long. Eventually, we should be going in that direction. But we don't have the luxury of time. That's what I was trying to get to. >> Well, what's interesting is, is that to your point about standards and ratification, what ratifies a defacto anything? In the old days there was some technical bodies involved, but here, I think developers drive everything. So if you look at the developers and how they're voting with their code. They're instantly, organically defining everything as a collective intelligence. >> And just like you're putting out the paper and making it available, everybody's contributing to that. That's why you need to have APIs and terra form type constructs, which are available so that the customers can continue to improve upon that. And that's the Net DevOps, right? So that you need to have. >> What was once sacrilege, just sayin', in business school, back in the days when I got my business degree after my CS degree was, you know, no one wants to have a better mousetrap, a bad business model to have a better mouse trap. In this case, the better mouse trap, the better solution actually could be that thing. >> It is that thing. >> I mean, that can trigger, tips over the industry. >> And that that's where we are seeing our customers. You know, I mean, we have some publicly referenceable customers like Coke or Warner Music Group or, you know, multiple others and chart industries. The way we are solving the problem. They have some of the largest environments in the industry from the cloud perspective. And their whole network infrastructure is running on the Alkira infrastructure. And they're able to adopt new clouds within days rather than waiting for months to architect and then deploy and then figure out how to manage it and operate it. It's available as a service. >> John: And we've heard from your customer, Warner, they were just on the program. >> Amir: Yes. Okay, okay. >> So they're building a supercloud. So superclouds aren't just for tech companies. >> Amir: No. >> You guys build a supercloud for networking. >> Amir: It is. >> But people are building their own superclouds on top of all this new stuff. Talk about that dynamic. >> Healthcare providers, financials, high-tech companies, even startups. One of our startup customers, Tekion, right? They have these dealerships that they provide sales and support services to across the globe. And for them to be able to onboard those dealerships, it is 80% less time to production. That is real money, right? So, maybe Atif can give you a lot more examples of customers who are deploying. >> Talk about some of the customer activity. What are they like? Are they laggards, they innovators? Are they trying to hit the easy button? Are they coming in late or are you got some high customers? >> Actually most of our customers, all of our customers or customers in general. I don't think they have a choice but to move in this direction because, you know, the cloud has, like everything is quick now. So the cloud teams are moving faster in these enterprises. So now that they cannot afford the network nor to keep up pace with the cloud teams. So, they don't have a choice but to go with something similar where you can, you know, build your network on demand and bring up your network as quickly as possible to meet all those use cases. So, I'll give you an example. >> John: So the demand's high for what you guys do. >> Demand is very high because the cloud teams have- >> John: Yeah. They're going fast. >> They're going fast and there's no stopping. And then network teams, they have to keep up with them. And you cannot keep deploying, you know, networks the way you used to deploy back in the day. And as far as the use cases are concerned, there are so many use cases which our customers are using our platform for. One of the use cases, I'll give you an example of these financial customers. Some of the financial customers, they have their customers who they provide data, like stock exchanges, that provide like market data information to their customers out of data centers part. But now, their customers are moving into the cloud as well. So they need to come in from the cloud. So when they're coming in from the cloud, you cannot be giving them data from your data center because that takes time, and your hair pinning everything back. >> Moving data is like moving, moving money, someone said. >> Exactly. >> Exactly. And the other thing is like you have to optimize your traffic flows in the cloud as well because every time you leave the cloud, you get charged a lot. So, you don't want to leave the cloud unless you have to leave the cloud, your traffic. So, you have to come up or use a service which allows you to optimize all those traffic flows as well, you know? >> My final question to you guys, first of all, thanks for coming on Supercloud Program. Really appreciate it. Congratulations on your success. And you guys have a great positioning and I'm a big fan. And I have to ask, you guys are agile, nimble startup, smart on the cutting edge. Supercloud concept seems to resonate with people who are kind of on the front range of this major wave. While all the incumbents like Cisco, Microsoft, even AWS, they're like, I think they're looking at it, like what is that? I think it's coming up really fast, this trend. Because I know people talk about multi-cloud, I get that. But like, this whole supercloud is not just SaaS, it's more going on there. What do you think is going on between the folks who get it, supercloud, get the concept, and some are who are scratching their heads, whether it's the Ciscos or someone, like I don't get it. Why is supercloud important for the folks that aren't really seeing it? >> So first of all, I mean, the customers, what we saw about six months, 12 months ago, were a little slower to adopt the supercloud kind of concept. And there were leading edge customers who were coming and adopting it. Now, all of a sudden, over the last six to nine months, we've seen a flurry of customers coming in and they are from all disciplines or all very diverse set of customers. And they're starting to see the value of that because of the practical implications of what they're doing. You know, these shadow IT type environments are no longer working and there's a lot of pressure from the management to move faster. And then that's where they're coming in. And perhaps, Atif, if you can give a few examples of. >> Yeah. And I'll also just add to your point earlier about the network needing to be there 'cause the cloud teams are like, let's go faster. And the network's always been slow because, but now, it's been almost turbocharged. >> Atif: Yeah. Yeah, exactly. And as I said, like there was no choice here. You had to move in this industry. And the other thing I would add a little bit is now if you look at all these enterprises, most of their traffic is from, even from which is coming from the on-prem, it's going to the cloud SaaS applications or public clouds. And it's more than 50% of traffic, which is leaving your, you know, what you used to call, your network or the private network. So now it's like, you know, before it used to just connect sites to data centers and sites together. Now, it's a cloud as well as the SaaS application. So it's either internet bound or the public cloud bound. So now you have to build a network quickly, which caters to all these use cases. And that's where like something- >> And you guys, your solution to me is you eliminate all that work for the customer. Now, they can treat the cloud like a bag of Legos. And do their thing. Well, I oversimplify. Well, you know I'm talking about. >> Atif: Right, exactly. >> And to answer your question earlier about what about the big companies coming in and, you know, now they slow to adopt? And, you know, what normally happens is when Cisco came up, right? There used to be 16 different protocols suites. And then we finally settled on TCP/IP and DECnet or AppleTalk or X&S or, you know, you name it, right? Those companies did not adapt to the networking the way it was supposed to be done. And guess what happened, right? So if the companies in the networking space do not adopt this new concept or new way of doing things, I think some of them will become extinct over time. >> Well, I think the force and function too is the cloud teams as well. So you got two evolutions. You got architectural relevance. That's real as impact. >> It's very important. >> Cost, speed. >> And I look at it as a very similar disruption to what Cisco's the world, very early days did to, you know, bring the networking out, right? And it became the internet. But now we are going through the cloud. It's the cloud era, right? How does the cloud evolve over the next 10, 15, 20 years? Everything's is going to be offered as a service, right? So slowly data centers go away, the network becomes a plumbing thing. Very, you know, simple to deploy. And everything on top of that is virtualized in the cloud-like manners. >> And that makes the networks hardened and more secure. >> More secure. >> It's a great way to be secure. You remember the glory days, we'll go back 15 years. The Cisco conversation was, we got to move up to stack. All the manager would fight each other. Now, what does that actually mean? Stay where we are. Stay in your lane. This is kind of like the network's version of moving up the stack because not so much up the stack, but the cloud is everywhere. It's almost horizontally scaled. >> It's extending into the on-premise. It is already moving towards the edge, right? So, you will see a lot- >> So, programmability is a big program. So you guys are hitting programmability, compatibility, getting people into an environment they're comfortable operating. So the Ops people love it. >> Exactly. >> Spans the clouds to a level of SLA management. It might not be perfectly spanning applications, but you can actually know latencies between clouds, measure that. And then so you're basically managing your network now as the overall infrastructure. >> Right. And it needs to be a very intelligent infrastructure going forward, right? Because customers do not want to wait to be able to troubleshoot. They don't want to be able to wait to deploy something, right? So, it needs to be a level of automation. >> Okay. So the question for you guys both on we'll end on is what is the enablement that, because you guys are a disruptive enabler, right? You create this fabric. You're going to enable companies to do stuff. What are some of the things that you see and your customers might be seeing as things that they're going to do as a result of having this enablement? So what are some of those things? >> Amir: Atif, perhaps you can talk through the some of the customer experience on that. >> It's agility. And we are allowing these customers to move very, very quickly and build these networks which meet all these requirements inside the cloud. Because as Amir was saying, in the cloud era, networking is changing. And if you look at, you know, going back to your comment about the existing networking vendors. Some of them still think that, you know, just connecting to the cloud using some concepts like Cloud OnRamp is cloud networking, but it's changing now. >> John: 'Cause there's apps that are depending upon. >> Exactly. And it's all distributed. Like IT infrastructure, as I said earlier, is all distributed. And at the end of the day, you have to make sure that wherever your user is, wherever your app is, you are able to connect them securely. >> Historically, it used to be about building a router bigger and bigger and bigger and bigger, you know, and then interconnecting those routers. Now, it's all about horizontal scale. You don't need to build big, you need to scale it, right? And that's what cloud brings to the customer. >> It's a cultural change for Cisco and Juniper because they have to understand that they're still could be in the game and still win. >> Exactly. >> The question I have for you, what are your customers telling you that, what's some of the anecdotal, like, 'cause you guys have a good solution, is it, "Oh my god, you guys saved my butt." Or what are some of the commentary that you hear from the customers in terms of praise and and glory from your solution? >> Oh, some even say, when we do our demo and stuff, they say it's too hard to believe. >> Believe. >> Like, too hard. It's hard, you know, it's >> I dont believe you. They're skeptics. >> I don't believe you that because now you're able to bring up a global network within minutes. With networking services, like let's say you have APAC, you know, on-prem users, cloud also there, cloud here, users here, you can bring up a global network with full routed connectivity between all these endpoints with security services. You can bring up like a firewall from a third party or our services in the middle. This is a matter of minutes now. And this is all high speed connectivity with SLAs. Imagine like before connecting, you know, Singapore to U.S. East or Hong Kong to Frankfurt, you know, if you were putting your infrastructure in columns like E-connects, you would have to go, you know, figure out like, how am I going to- >> Seal line In, connect to it? Yeah. A lot of hassles, >> If you had to put like firewalls in the middle, segmentation, you had to, you know, isolate different entities. >> That's called heavy lifting. >> So what you're seeing is, you know, it's like customer comes in, there's a disbelief, can you really do that? And then they try it out, they go, "Wow, this works." Right? It's deployed in a small environment. And then all of a sudden they start taking off, right? And literally we have seen customers go from few thousand dollars a month or year type deployments to multi-million dollars a year type deployments in very, very short amount of time, in a few months. >> And you guys are pay as you go? >> Pay as you go. >> Pay as go usage cloud-based compatibility. >> Exactly. And it's amazing once they get to deploy the solution. >> What's the variable on the cost? >> On the cost? >> Is it traffic or is it. >> It's multiple different things. It's packaged into the overall solution. And as a matter of fact, we end up saving a lot of money to the customers. And not only in one way, in multiple different ways. And we do a complete TOI analysis for the customers. So it's bandwidth, it's number of connections, it's the amount of compute power that we are using. >> John: Similar things that they're used to. >> Just like the cloud constructs. Yeah. >> All right. Networking supercloud. Great. Congratulations. >> Thank you so much. >> Thanks for coming on Supercloud. >> Atif: Thank you. >> And looking forward to seeing more of the demand. Translate, instant networking. I'm sure it's going to be huge with the edge exploding. >> Oh yeah, yeah, yeah, yeah. >> Congratulations. >> Thank you so much. >> Thank you so much. >> Okay. So this is Supercloud 2 event here in Palo Alto. I'm John Furrier. The network Supercloud is here. Checkout Alkira. I'm John Furry, the host. Thanks for watching. (lively music)

(upbeat music) >> We're back at AWS reinvent 2021. You're watching The Cube, I'm Dave Vellante with my co-host Dave Nicholson. David Nicholson, I'm Dave he's David. >> We're trying something new here at the cube. A little stand up cube. You've heard of the pop-up cube, maybe. We're going to stand up. I work at a stand, standing desk at my office, so let's try it. Four days, two sets, a hundred plus guests. Why not? So Manish Sood is here, he's the founder and CTO of Reltio, Cube alum. >> Dave: Manish, thank you for standing and good to see you again. >> Dave, It's great to see you again, and David, thank you for having me here. >> So, tell us a little bit about your, yourself, your background. I'm always interested to ask founders why you started your company, but tell us the background. >> Yeah, so a little bit of my background and the company's history. I, most of my background has been in data management and creating products for data management. I was at a company called Informatica, came through an acquisition through Informatica, back in 2010. And Started Reltio in 2011. The reason why we started Reltio was that, if you look at the enterprise space and how things have been evolving, there have been an explosion of applications. There's almost an application for every little business process that you can possibly imagine. Enterprise customers who used to struggle with 12 or 24 different systems, are now coming to us and saying they have 300 or 500 different applications that they use to run their business. And that's at the lower end of the spectrum. Even a business like Reltio today, runs on a hundred plus SAAS applications, end to end. And that it is creating one of the biggest opportunities, as well as one of the biggest friction points in the enterprise. Because in order to create better, efficient business outcomes, you have silos of data and you don't know where the source of truth is. And that is something that we saw early on in 2011. At the same time, we also saw that digital transformation or cloud transformation type of requirements, were going to drive a larger need for this kind of capability, where Reltio type of products could act as that single source of truth to unify all of the multi-source siloed information. So, that's what got us started down this journey. >> So, okay. So, when see people hear single source of truth, they think, oh, database, right? But that's not what you guys do, right? I mean, it's, it's, can I call it master data management? But it's really modern master data management. You're kind of recreating a new or creating a new category that- >> Manish: A little bit. >> solves a similar problem. Maybe you could explain that. >> Yeah. A little bit of background. So the term master data management came about the 1920s. (Dave laughing) You believe that? When during the pandemic, the U.S. government was trying to figure out how to know who is still alive versus, you know, not there anymore. And they created something called the death master. Now a very ominous name, for a concept of just bringing data together and figuring out what's going on in the economy, but that need, or problem hasn't gone away. It has just become a harder problem to solve because now we have so many different systems, to deal with. And both internal as well as third-party data sources that companies have to work with. And that's where the need has been around, but the technical capabilities to really keep solving the problem and delivering the solution in a manner where it can keep pace with the evolving needs, that capability has been missing. And that's where the "aha" moment for us was that we really needed to build it out as a foundation that would continue to grow and scale, with the magnitude of the problem that we were going to see in the future. >> Okay, so this idea of single version of the truth, obviously critically important for reporting, financials, you can't, you can't tell an auditor one thing, you know, your, your customers are another thing, your consumers, it's got to be consistent. And especially in regulated industries. Is there a difference Manish, between sort of that type of data and the data maybe that's in the line of business that doesn't necessarily affect the rest of the business? Can they have their own version of the truth, which is just their version, their, their, their single version? It doesn't necessarily have to affect anything else. Do you, are you seeing that changing data landscape, where things are getting more distributed and ownership is becoming more distributed? >> So, the change in the paradigm that we are seeing is because of the proliferation of the data, there is a need to establish, what is the aggregated view of the information. Aggregated and unified, which means that, you know, if there is a record for Dave Vellante or David Vellante. It's the same person. Establishing that fact as the truth across any number of systems that you have, versus the multiple versions of the truth, where somebody comes in and says, for compliance reasons, I want the entire collection of data versus for marketing reasons, I only want one third the slice of this information. So that's where this concept of aggregate once, unify that information, but then make it ready and available for multiple consumers to partake from that. That's becoming the norm. >> Dave: Got it. >> And you mentioned something, Dave, that analytics, reporting, BI, data science, those have been some of the traditional playgrounds for this kind of information to be unified, because if you're trying to roll up the revenue for, you know, the business that you do with Coke or Coca-Cola, you know, you don't know which name you used, then you have to go back to the analytics warehouse and aggregate all of that information and do the reporting. But the same problem is coming up in real time, digital experiences as well. The only difference is, that instead of having the luxury of a few hours, now you have to make the decision in a few milliseconds. >> So, when you talk about those silos of data and seeking to have a unification of those silos, how has that changed in the era of cloud? Is it that Reltio is integrating those disparate sources that now exist in cloud, or is it that you are leveraging cloud to address the problem that's been with us for a long time? And I have to say that Dave Vellante, take him off the the death master. He's definitely still with us. (Manish and Dave laugh) >> Dave: Another good day. >> I'm pretty sure too. But how, how, how has, how have things changed as you know, with, with the dawn of cloud? >> With the dawn of cloud, there are two things that have become available to us. One is using the power of the cloud compute to solve the problem, so that you can keep growing with the footprint of the problem itself and have a solution that scales along with it. But at the same time, you have systems of record, could be your mainframe systems, could be your SAP, ERP type of deployments that you have. Some of those functional applications, they're not going away anytime soon, they're there to stay. But at the same time, you also need the new digital experiences to be delivered on. The glue between those two worlds is the source of truth data that sits in the middle and the best place for it to sit is the cloud, because you have to open it up to the rest of the ecosystem that sits in the cloud, but you also have to maintain a connection to the on the ground type of systems. Putting it behind the firewall and trying to do that is next to impossible, but doing it in the cloud opens up all the doors that you need for your transformation to take place. >> You know Dave, there was a time when I was part of an industry where coding, not writing code, but coding data to basically say, look, this field here is the person's last name. This field is the address where the mortgage is being held. How much of that is still manual, as opposed to applying some form of AI to the problem? Let's say you have 200 different sources of information, where Dave Vellante's name shows up in a variety of contexts. Are we still having to go in manually and sift through to make those correlations? How much of that has been automated at this point? >> So, there are systems of capture where some of that information, because your loan mortgage application was entered by somebody into a system, will still be captured in those places, but we'll take in that information. That's the starting point, but if there are other sources, then we will apply AIML type of capabilities to bring on those new emerging sources. Because at the same time, think about this equation where, you started with five systems or, you know, a dozen systems. Now you're talking about 300 plus systems. You cannot keep doing this manually for every system possible. And this number is only going to grow as we move forward. So AIML definitely has a role to play and further automate this landscape. >> I had to, I saw an amazing stat the other day, the source was the Sand Hill Econometrics, you know, a Silicon valley company. And the stat was that 70% of the series, A, B and C companies, fail to return at least one X to their investors. So you've made it through that nut hole. Congratulations you just raised $120 million dollar round. That's got to be super exciting for you. >> David: No pressure by the way. >> Dave: Tell us about that. Well, I mean, you'd think the industry would have de-risked by now, right. But anyway, so, tell us about that raise. Where are you, where are you guys are at? Very exciting times for you. >> Yeah, really, really exciting time for us. We just raised $120 million dollars. The company was valued at $1.7 billion dollars. >> Dave: Awesome. Congratulations. >> And the round was, you know, all of our existing investors participated in it. We also had a new investor join in the process, as well. >> Dave: They wanted their pro-rata. (Dave and Manish laugh) >> Everybody, everybody wanted their pro-rata. >> Dave: That's great. >> But you know, one of the things that we have been very careful about in this whole process and journey, is something that you and I were talking about, the step function of scale. We're making sure that we are efficient stewards of capital and applying it in a manner where we are at every turn, looking at what's the next step function that we need to graduate to, because we want to make use of this capital to efficiently grow our business and be a Rule of 40 growth company. And that's something that you don't typically hear these days from a lot of the growth companies, but we are certainly focused on building long-term value and focusing on that Rule of 40 growth efficiency. >> Yeah, so Rule of 40 is growth plus EBITDA, or sometimes they use other metrics, but is that how you look at it? Growth plus EBITDA. >> Yes. Yeah. >> Great. >> And that's the formula that we are driving for. And most of our investments with this round of capital are going to be not only pushing forward with the go-to market strategy, because we have a lot of growth opportunity, we have been North America focused, now we can take this global. At the same time, looking at the verticals where we need to double down and invest more, given that we have been a horizontal platform that is core to our capabilities, that we have built with Reltio. But at the same time, making sure that we are investing in the key verticals that we are present in. >> Yeah. So, you were explaining to me that you, you started in the pharmaceutical industry, that's where you got go to market fit. And then you went to other industries. When you went to those other industries where they're similar patterns, or do you do almost have to start from ground zero again, to get that product market fit? >> No. So from the very beginning, the concept has been that this is a horizontal data problem. And at the heart of it, it's information about people, organizations, product, locations, and most of the businesses run on that type of information. That's the core part of the data that they build their business on. Life sciences was a perfect starting point for us, because it had examples of all of those data. When you start with commercial operations, which is sales and marketing, you have people, organization, product type of information. When you go into clinical trials, you have site investigators and patient type of information. When you go into R and D within that same space, you have drugs, compounds, substances, finished products, type of information, all coming from multiple sources. So it was a perfect place for us to prove out, all of the capabilities end to end, which we like to call multi-domain capabilities. And then we looked at what other verticals have similar patterns. And that's why we went after healthcare, financial services, insurance, retail, high tech. Those are some of the key verticals that we are in right now. >> That's awesome. Great vision. Last question, could you give us a sense of the futures, where you're going? Well, first of all, what are you doing with the money? Is it, you go to market, throwing gas on the fire? And what can we expect in the coming year and years? >> Go to market expansion is a key area of investment, but also doubling down on the customer experience that we deliver, how we invest in the product, what are some of the adjacent capabilities that we need to invest in? Because you know, data is a great starting point and data should not hold businesses back. Data should be the accelerant to the business. And that's our philosophy, that we are trying to bring to life. So making sure that we are making the data, readily available, accessible and usable for all of our customers is the key goal to aim for. And that's where all the investment is going. >> Well, Manish was a pleasure having you on at the AWS startup showcase, and then subsequently you become a unicorn. So congratulations on that. Really excited to watch the continued progress. Thanks for coming back in The Cube. >> Well, thank you so much, Dave and David, thanks for having me. >> David: Thanks for validating that Mr. Vellante is still with us. >> (laughs) He's going to be with us for a long time. >> I hope so, I hope so, I got, I got one more to put through college. Thank you for watching this edition of The Cube, at AWS reinvent. I'm Dave Vellante, for Dave Nicholson. We are The Cube, the leader in high-tech coverage, Be right back. (somber music)

>>From the Bellagio hotel in Las Vegas. It's the cube covering UI path forward for brought to you by UI path. >>Hey, welcome back to Las Vegas. Lisa Martin, with Dave Volante, the cube is here, live at UI path forward for very excited to be here in person. Next topic, the smart factory, a couple of guests here to unpack that for us, Jason Brixton joins us the smart factory lead at Deloitte and Thomas Hanson, the CRO of UI path gentlemen, and welcome to the program. Thank you. Thank you for having us great to have you great to be in person. Let's talk about smart track factory factory Ford auto. What is it from Deloitte perspective and then UI path. >>So if you think about smart factory, it's really that transition from the old kind of analog manufacturing environment to the digital, digital operating type environment that we see today. So technology has really changed in the last three or four years. And as a result of that elevation of technology, we're able to do a lot more on the manufacturing floor than we ever could. So what used to be more analog or hybrid with a little bit of technology is now starting to shift really to end to end integrated manufacturing operations that are based on digital platforms and we're loving it. It's a great place to be >>Great. Tell us what's your perspective? >>Well, first of all, it's great to be here. Thank you for the invite. It's so nice to be away from soon calls or, or other type of, uh, of calls, right. And be in person. Uh, look, we have an amazing partnership with the lights. Um, we have worked together for years. We've done more than 400 joint engagements with the large companies across the world. And in that process, we've really gone deeper from a vertical and industry perspective and smart factory is really the starting point of going super specific and figuring out what does automation or how does automation rather play into, um, to a, to a smart factory, like a beautiful trombone, that music from a beautiful trombone. >>So years ago, we wrote a piece talking about the cloud as an opportunity and how to take advantage of it. And one of the, the premise of the piece was you've got to build ecosystems and maybe it's within an industry or within a practice and build data in different disciplines because the power of many versus the capabilities of one, this smart factory initiative that you guys have going, it feels like an ecosystem play. Can you describe that ecosystem? Who's involved? I know SAP in for AWS, but, but tell us more about the ECOS. >>Yeah, sure. So your, your hunch, there is a great one, right? We, we learned early on that trying to do this as Deloitte or Deloitte plus one just, wasn't going to get it done, right? You really needed to harness the power of the many. And so at the, at the core of what we're doing at the smart factory at Wichita, that you alluded to is about bringing an ecosystem to life. So we have 21 partners that are going to be participating out of the gate with the smart factory. Wichitan the intent is to show a seamless solution and actual end-to-end production facility that showcases 21 amazing technologies and partners. And we're just really thrilled about what we're able to show our clients. So, >>Yep. So Koch industries owns Inforce. So obviously that's the Wichita connection, is that right? So they got to be involved in this. I mean, they were amazing company, but what can you tell us about, uh, their, their involvement? >>Yep. So Coke, obviously the in for connection, uh, Dragos, which is another in four company as a founder within, uh, within the ecosystem, which is fantastic. There they play at the core. They're also an incredibly important client, right? So the Coke business on the whole is critical to how we think about manufacturing across a whole range of industries from discreet production to scale process. Um, they're fantastic partners and we've had a great time working with them. And you guys are just, >>It's about to launch through soft launch. Can you tell us more where you are in the progression? >>Sure. So soft launch started two days ago. Oh wow. So the building, we have the keys, uh, we are doing some visits with a handful of friends and family, that ecosystem partners that you mentioned, there'll be coming out, uh, to see it and to provide some feedback. And then we go live in earnest in January >>At Thomas where's UI path fit. >>Well, we fit in essay as a key part in this initiative. Um, look, we, as a company, we are part the preferred partner. First, we do all our business together with partners and we have right about almost 5,000 partners now, globally. And then there's a few, then there's a few in that 5,000 that are unique that really stand out. And Deloitte of course is one of those very, very special partners that we work with globally, but also locally here in the us, across all the states across all the industries. So we're thrilled to be part of this automation plays a key key part of smart factory. When you think about it, the evolution of work there's so much boring, mundane work on there. Humankind is better served, spending their time and effort on the non mundane on the innovative on the creative. And that's what we try to ensure that the humans in the loop so to speak are focused on the innovative work, the graded work, and we have software robots, RPA automation handle all that boring and mundane work, >>Right? Letting the folks focus on the value, add to themselves a value add to the organization, more strategic investments. Thomas question for you is in terms of you talked about this being horizontal across industries, but I'm curious about what some of the feedback is from some of your customers, 8,000 customers. Now you've got a very large what, 726 million ARR, huge lot of customers over a hundred million ARR. What's been the feedback from some of those guys. >>Well, so first of all, uh, personally, I I've been in enterprise software for more than 20 years. And what I've experienced over the years are most large scale enterprise software projects tends to be multi-year in nature, be rather complex. And the failure rate can be rather high. Then in comes RPA and automation, which is a complete different kettle of fish in the sense that from conceptualization of identifying a process, to getting it built, getting it tested, getting it into production, you're talking days and weeks only. So the path to seeing value is so fast. What I've learned yesterday and today from the 1516 customer meetings I've had so far is the same unique trend or learning across all industries and also from various parts of the world. And that is very fast realization of value, perhaps starting initially with 5, 10 20 processes and then scaling super fast because the find that return on investment incredibly quickly with our solution. So that's what unifies it across geographies and across industries. >>What'd you think about the smart factory? And one of the things we've learned during COVID is there's so much unknown. So sometimes these processes aren't linear like a trombone, you know, going back and forth in and out, but is there unknown in the smart factory processes or is it pretty well known? And you can do the process mining on that known base. What's the dynamic >>Back there. So there's a few different dimensions to it. So yes, it is well known because it's a controlled environment, but one of the things that we're doing is we're actually actively introducing a lot of unknown factors to try to let the bots and the process mining kick into effect. Right? So we're artificially, let's just say injecting opportunity for us to do that. The other thing that we're doing is, and what's really unique about the smart factory at Wichita is it's one of four across the globe for Deloitte. And so we're bringing data in from the other three sites, which is data, that'll be less controlled. We're going to do process mining on that. Just try to take advantage of some of the, some of the capabilities associated with the solutions. >>Okay. So, so w when you think about process mining, do you start there, or do you start with, I sometimes call it paving the cow path, you know, taking what you've known, that linear process that, that hit that as the quick win, and then worry about the process money, or do you step back and say, wait a minute, we have to rethink the entire factory experience. Where do you start? >>I think it depends in the case of the smart factory with that, we've got a few different places, so we're using it to do ingestion of orders. So that's obviously a very controlled environment. We're then using it to do a lot of work around inventory management and optimization as well as month end close plays, which will be a lot more we're learning as we go. Right. So I think on the spectrum, it could be on either end my personal belief. If you look at it more long-term or actually out in the real world is that this is all about learning new things. It's about generating insights from data that frankly, you don't want human beings to have to go do that. And so having the ability to take advantage of an intelligent automation solution, as powerful as UI path is really a great advantage. >>One of the things that's misunderstood, I think about UI path is they look at what happened post let's say 2015, 2016, and say, oh, just like, just like every other Silicon valley company, double, double, triple, triple. And that's not how you guys started. You sort of let things bake for the better part of a decade and then got product market fit and then exploded. Um, and so that's, that to me was a key to your success in scaling this. I feel like you guys are building a new offering here. This is not just doing a one-off the product market fit. It's not like a point product. It's a, it's a big thing. So can you talk about the go to market, your product market fit? You're testing it out now, your goals, are you trying to scale this up? What, what are some of the things that you can share about your aspirations? So >>The partnership from a UI path perspective to Deloitte is a critical partnership. One of the select few on a global level, uh, we have enjoyed tremendous, uh, amount of engagements together. I mentioned early on 400, and I believe we, we now have together right about 1000 developers trained within your organization on your iPod, right? That's right. Yep. So we have a strong base that, of course we want to build full and hopefully put a syrup behind the thousand to 10,000. And over time, we want to make sure that it's globally inclusive, that we can serve all the marketers across the world where we have giant presence. And there's a select number of verticals and industries where we really have had success together that we of course want to go and specifically shoe in on what would have caused now be manufacturing together. And of course, a classic vertical we've been very strong in together as BFSI bank and financial services industry. So those are good areas. >>Well, Jason, you're building a business out of this, right? I mean, you've got a business plan around it and you're going to scale this thing. >>Oh, absolutely. Yeah. That's 100% the case. So we have smart factory at Wichita. That is part of our positioning in the marketplace. What we found is that telling people about tech and about solutions is one thing, showing it to them in a production environment is altogether different, right? Giving clients the opportunity to explore the art of the possible in a real setting like that is incredibly impactful. And so you talked about go to market, we see this relationship with the ecosystem and what we're trying to do in Wichita, that's sort of the epicenter of building an entire business, which ultimately will have huge global potential. >>We talk about speed for a minute. And the growth trajectory that UI path Thomas has been on for the last five years or so. I think I was reading, I think it was analysis that Dave wrote that in 2016 revenue was 1,000,020, 20, 15, 20, 20 600 million. So massive growth very quickly. My question, Jason is for you in terms of the speed. Ha how quickly are you looking to see the smart factory for Dato really impacting organizations around the globe because these guys are on a fast bulleted. >>Yeah. So I wish we had those growth rates. I will say though, selling and delivering these solutions holistically to manufacturers takes more time. So we think of our cycle as be measured, certainly in many months, certainly not years. We are starting to see an acceleration of that entire sales cycle and delivery cycle, just because of things like the pandemic driving organizations to just need to move faster. Frankly, if you're not moving towards digital manufacturing operations right now, you're probably behind. And so we're seeing that urgency from the market start to pick up, but we don't have that kind of growth rate, unfortunately. >>Well, what's it. What's interesting about Deloitte to me is you guys here, I think of you as a virtual company. I mean, I know you got a lot of bodies out there, but it's not like you've got a lot of physical locations. Right. And so now, but now you're just, you're investing in a physical plant essentially, >>Which is extremely exciting. We, we keep telling ourselves when we talk to folks, they own lots of buildings. So just because we're excited about our building doesn't mean they are, but you're exactly right, right. We're obviously a global services and products company. So this is one of a handful of buildings that are going to start to represent us as an organization. And we're really excited about what should we watch? >>It's kind of milestones for progress success. What are the markers that we should be paying attention to is independence. >>I think specifically on this, um, rapid experiment together, I think one of the key learnings we can take away that we can apply to other companies in the manufacturing industry specifically look from a UI perspective. We work with many large scale manufacturers around the world, but we've seen amazing fast progress with Bridgestone. For example, we implemented a smaller set of, uh, uh, bots that help them reduce their paperwork by 85% onto their branches with a Turkish e-commerce retailer called Archer. Lik I think I get the pronunciation correctly. They put 85 processes in place with our bots and are now to date transacting or running. I think it's 3 million e-commerce transactions with our processes. So the impact we can have in manufacturing together with the learnings from this, my factory, I think is just so exciting. Really? >>Yeah. The impact, the potential there is, is unlimited. Guys. Thank you for joining David, me talking to us about smart factory Ford auto, what it means for both businesses, how the partnership is evolving. It sounds like music from a beautiful trombone. Thank you so much for joining Dave and me today. Thank you For Dave Volante. I'm Lisa Martin. The Cubas live in Las Vegas at the Bellagio at UI path forward for we'll be right back.

(upbeat music) >> Hello, and welcome back to theCUBE's coverage of Red Hat Summit 2021 Virtual. I'm John Furrier, host of theCUBE. We got a great guest here, Raymond Kok, Senior Vice President Cloud Application Solutions at Siemens Digital Industry Software. Raymond, thanks for remoting in with theCUBE Virtual all the way from the Netherlands. Great to see you. We're in Palo Alto, California. Great to see you. >> All right, thanks for having me. >> Love the international culture of the vibe with virtual, one of the benefits of having remote, which we were in person, but soon the pandemics coming around the corner, but great to see you. Let's get started, let's get into the Digital Industry Software Group that you're involved in, your relationship with Red Hat. But first let's start with, if you could take a minute to give us a brief overview of Siemens and your role there. >> Yeah, so first of all, let me talk a little bit about Siemens because Siemens is obviously a big company. So as you already announced, I'm part of Siemens Digital Industries Software. So Digital Industries is actually the vision at Siemens that is really focused on how to help companies to become a digital enterprise. And so as part of this IoT (faintly speaking) Industrial Internet of Things is obviously an important element of that. And so if you look at my role at Siemens, is really to be the business lead for the cloud part of IoT. And so what I mean with that is specifically a product line called MindSphere. And so Siemens, like I said, is looking at the overall digital transformation of customers, relay product landscape but also how we can support them with new technologies and IoT is very much part of that. >> One of the benefits of doing theCUBE interviews over the years and having the team that we have in the media side, we get to see things early. Industrial IoT, we've been blogging about and reporting for a couple of years now, now it's hard. Because with the pandemic, you still need things to run. And so Industrial IoT, not withstanding, there's still the other edges like consumer edge and other devices, but Industrial IoT is getting all the focus because of security and also because of just critical operations, critical infrastructure and for business and public sector, private sector, everything. This is a huge area. Could you talk about your strategy around Industrial IoT and specifically how you guys are using this analytics, MindSphere as you mentioned, what is that about? How does that help me if I'm a manufacturing organization? >> Yeah, so first of all, maybe it's good to clarify what we mean with Industrial IoT, because there's IoT and there's Industrial IoT. So, when people typically talk about Industrial IoT, it's really three main areas. It's smart grid. So it's really around IoT for energy management and energy usage. There is smart cities. So this is really IoT for smart buildings but also any kind of infrastructure that goes with smart cities. And then the last one is smart factories. And so, we typically, when we say Industrial IoT, we have clients that cover the three main areas that I just mentioned. And so really what it is about is to take advantage of data, right? So IoT is really about how you take advantage of data and how do you actually get insights from this data to run your business better? So maybe to give a specific example, if you look at one of our major customers, like for example, Coke Hellenic, and they just actually presented that (mumbles) last week. They are trying to use IoT to advance how they actually operate the bottling lines of the factories. And so it's really above operational excellence. So, meaning how to get more trooper, how to get more efficiency into how they do production. But in many cases, John, it's also about energy management because data is not just about, okay, operational excellence but also surrounding topics like, how can I better preserve energy as I produce something? And so, yeah. So in many cases, IoT is all about data, getting next levels of insight from the data and then put that to a particular use. So this can be answering the quality of production, getting better performance of your equipment, getting a better use of your equipment when it comes to energy consumption. So there are many use cases typically related to Industrial IoT. >> Yeah, and you got to love the industrial definition to the way you laid it out. That's critical infrastructure and emerging infrastructure and plant and equipment, all those things. But it's also a proxy for (faintly speaking) for business. So this kind of brings me to the kind of connecting the dots. If you don't mind, I'll jump to the convergence question I'd love to bring up, which is the convergence of IT, Information Technology and Operational Technology, OT, which has been discussed before, but you talked about culture clashes, different cultures. Also systems are different, purpose-built, potentially on one side, but they've got to come together, okay? These are both very important software pieces to the puzzle on the platform. How do you see that evolving? What's your take on resolving this dilemma of the priorities, of innovation and security and openness? What's your take on this? >> (Faintly speaking) Topic, John, because the reality is that OT has to ITinice and IT has to OTinice I guess, when we talk about IoT, right? So I think that's why at Siemens, we have kind of a unique viewpoint because Siemens looks at both the OT side of the world through, for example the context of discrete, the process industries look at the automation part of it, so meaning the actual operational automation and then obviously only equipment that comes with it, which is really typically an OT conversation. Then if you look at my business unit, so, Siemens Digital Industries Software, we look at it really from an IT point of view, and so how can we help these customers to become a digital enterprise? And so at Siemens, we're kind of bringing these two views together. And then to your point, we're trying to make the integration as seamless as possible. And to your point actually, it includes also making sure that we actually drive the standards that are going to make this enable, that are going to make this possible, can be open standards like OPC UA, for example, when you look at discrete manufacturing, but can also be standardizing on certain technologies, right? And so what we're seeing is that, for example, back to my word, talking is really Kubernetes and kind of the container technology that is out there, standard technology is helping this conversation as well. >> Yeah, the integration piece, that's the Kubernetes, containers and micro services. These are bringing cloud native integration points. And that's really going to be key, I'm going to get that in a second, but I want to come back to the MindSphere Analytics piece because data is critical as you mentioned. So integration data security and observability means security, monitoring all these things are evolving. You guys earlier this year, announced you expanding this MindSphere reach in partnership with IBM and Red Hat, so consumers could run on on-prem and cloud. That's the topic of this event. The main theme at Red Hat Summit this year is clearly hybrid cloud, in a distributed kind of computing paradigm which we all love. This is what we're talking about here. We're talking about distributed computing edge, Core Cloud. Why is this important for Siemens and your customers? Why did you decide to work with IBM and Red Hat on this initiative? >> Yeah, it kind of was already somewhat in your question, meaning that if we work with our customers, really the cloud conversation that we have with them is a hybrid cloud conversation. And what we mean with that is, yes, there're elements of public clouds, but especially when you talk about critical factory operations, many of these workloads that we're talking about are actually very close to the shop floor or are at least some what near, and therefore any kind of large enterprise OEM that we work with, so whether it's an automotive OEM, whether it's an aerospace and defense OEM, they all have a hybrid cloud strategy. And so what is interesting about IoT is that this is where hybrid cloud kind of comes together. It kind of goes back to your previous question about IT and OT coming together. As you can imagine OT has always been very on-premise because it's near real time critical factory operations. IT obviously much more comfortable with public cloud. So we're trying to bring this together and therefore, many of these conversations that we have with large enterprise OEMs is really a hybrid cloud conversation. So specifically, what we're doing here together with Red Hat is to enable exactly that. So meaning that we can take MindSphere or solution for IoT Analytics, we can bring that not just to a public cloud or make that available as a public cloud solution, but also on-premise private clouds. And I think it's very interesting because it opens a conversation that allows people to really now start talking about value as opposed to being worried about, okay, where is my data going? Is it secure? Is it actually going to be available when I need it for factory operations? So, yeah, I'm pretty excited about this work that we're doing together, because again, it's about value, making sure that our customers actually can fit what we do at Siemens into a landscape that they feel comfortable with. >> It feels to me, I may be a little bit old school but I feel like this is the innovation that we saw in the eighties and nineties as networks got more expansive and inter networking happened and you start to see that life blood of the action and the value get enabled. And I think your point about hybrid and operating around the environment is critical, because this brings up new challenges and new opportunities. For instance, you don't need to bolt on a caching layer to manage a slow database or you can get real time, and you can get better performance and compute. You don't need to move the data around. So, bringing compute and resource and scale to these edges when they need it, focuses more on the solution architect less on putting point technologies in place to solve. >> Yeah, exactly. Maybe to chime in on that, I think what is also interesting is that it allows the customers to optimize where to best place the workloads that they care about. And so maybe to make that a bit more specific, if you think about a use case like energy management. So let's say that I have a production line, 1500 assets that are consuming energy. If you then think about the data that is involved in analytics, you can imagine that if I start sending all this data to public cloud, maybe, maybe not the most efficient setup, because a first level of filtering and analytics, I can very much close do or do that close to a 2D equipment. And then when I get to aggregation of data, and some further filtering to figure out, okay, what is really happening at the line level? What is really happening at a particular production area level? Again, I think you can do that prior to actually sending some of this data to the cloud, meaning public cloud. Where the public cloud becomes interesting is when you want to aggregate, for example across multiple manufacturing facilities. Now you want to look at the KPIs of one factory versus another, you want to aggregate across multiple factories, you want to figure out, okay, why are certain trends happening just in this factory and it's better in this one? But I think that's why, what we're seeing with clients is that they're expecting from us a layered architecture and to your point, the most efficient way of actually dealing with their use cases across the infrastructure that is available to them. So yeah, if you look at Siemens, we're trying to kind of carefully think about all these layers from fields to edge, to on-premise private cloud, to public clouds, and then make sure that along the way each layer has value and that it's there for a purpose and for a real reason, right? And not just for the sake of having it. >> Yeah, or being limited by the architecture that you're stuck with, constrained by the architecture by what the solutions are. You're saying, the script is flipped upside down where you can optimize your business, which by the way will flow up more data to evaluate. So there's a new post analysis mode of post configuration, and you could align your resources best way you see fit to maximize your business model. This is the beautiful thing about this distributed edge concept is the software enablement of the business is there. So the data is critical. So, as more controlled data comes in, it's not just set it up and watch it run. Yeah, there's automation involved in a lot of software but you're getting new data coming in. If you have this new observation space, of new horizontally scalable data, this new data coming in. >> Yeah, exactly, exactly. And I think you said a key point there. We don't want our architecture to constrain. I guess, what kind of value the customer can actually get out of these use cases and therefore, I think it's kind of exciting that in this ecosystem, especially also the interplay between Red Hat and Siemens, that we kind of take it one step further and think about, okay, what is actually truly the most optimal way for customers to go do this? And that we've formed these kinds of partnerships to really help the customer even take another step forward. So I think it's pretty, pretty nice. >> Well, Raymond, I really appreciate it. That's a masterclass, a commentary, nice gems you're dropping here on theCUBE, I appreciate it. The way I look at it, I'd love to get your final reaction to kind of the world we're living in. Just my take on it is that, we have a new operating system of business, and we're kind of getting at, is that you guys now can have an operating model for your customers and software. It's not just another (faintly speaking) For a server and the server is the business, it's the world now. >> Yeah, exactly. And I think from my point of view, I think it's exciting to see us again in this world of complex technology always to find new ways to help the customer to kind of advance their use cases, right? Because the imperatives that, for example discreet manufacturing doesn't really change. They've been there for many, many years. And I think for us to be able to bring out technology closer together and then solve, and I do use use cases in an even more efficient way. I think that's pretty interesting. And yeah, so I see good things and I think ultimately IoT, I think those that can actually bring real value are going to be able to deal like we just talked about, the hybrid scenarios, but the people that are going to matter is the people that can bring the most insights out of this data, right? Because what I always say about IoT is, it's yet more a messy data. So it's only worth actually collecting all this data if you actually get next to levels and new levels of insight from it. And I think, yeah, it has to kind of fit that kind of a mantra, and I think together that we're really trying to figure that out, so- >> I know some people as well would agree with that statement, I do as well, but the other side of that question is, if you don't architect the edge properly or the IoT edge, the data costs could be compelling. You could get hit with some charges because most people have been burned by the idea of moving data around versus say, moving compute. So, back to this value, where's the edge? What're you optimizing for? That's kind of the big question. How do you react to that when someone says, Raymond, what should I be optimizing for as I lay out my architecture for the core to edge, data center cloud edge scenario, what am I optimizing for? >> Yeah, I think you kind of work backwards from what you're trying to achieve. I think it may sound kind of obvious, but quite often I get in discussions with customers where we first start talking technology, obviously it's exciting. I'll be kind of attacking myself. So it's exciting to talk about technology but they forget to start from, okay, what's the return of the invest and what's the use case, right? And so, what are we trying to solve? Who is trying to benefit from it? And what benefit are they looking for? And then if you carefully work backwards from there, you will actually see that as we just talk about data and insights into data are in many cases, leading some elements of the value that a particular person is looking for. And then working backwards from there, you will actually figure out that back to the layer of discussion that we just had, this data doesn't have to be available at every level, right? Every layer adds some value, and so therefore you have to have kind of an open discussion and that's meaning an open discussion about what layers to use. And that's why at Siemens, we kind of follow that approach. So meaning that we work backwards from the use case, then we think about, okay, what is most appropriate at the field and control level? Then what to your point, is the most appropriate at the edge level? Then what is the most appropriate at the cloud level? And then from there, you actually figure out, okay, where do I deploy? What kind of acquisition of data? What kind of insights am I interested in at that level? And then basically, what kind of machine learning am I going to deploy there? And then work all the way from there. And it seems to work. And that's why to your point, it's all about making sure that at every level data is there for a reason and you process it for a reason, because otherwise it's just acknowledging it, interesting still, but it doesn't have any value, right? >> Awesome. Raymond, great insight there. And this is all about engineering. You guys are doing a great job. Engineering, the solutions, this is DevOps, DevSecOps, it's some hybrid cloud, really bringing those that value to the edge, industrial edge. Congratulations for all the great work. Raymond Kok, Senior Vice President, Cloud Application Solutions at Siemens Digital Industries Software. Thanks for coming on theCUBE. >> Okay, yeah. Thanks for having me. >> Okay. >> Thank you. >> I'm John Furrier with theCUBE, Red Hat Summit 2021 Virtual. Thanks for watching. (upbeat music)

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for DataOps. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

>> Narrator: From around the globe, it's "theCUBE" with digital coverage of Smart Data Marketplaces brought to you by Io-Tahoe. >> We're back. We're talking about smart data and have been for several weeks now. Really it's all about injecting intelligence and automation into the data life cycle of the data pipeline. And today we're drilling into Smart Data Marketplaces, really trying to get to that self-serve, unified, trusted, secured, and compliant data models. And this is not trivial. And with me to talk about some of the nuances involved in actually getting there with folks that have experienced doing that. They'd send a series of digital evangelist with Tata Consultancy Services, TCS. And Ajay Vohora is back, he's the CEO of Io-Tahoe. Guys, great to see you, thanks so much for coming on. >> Good to see you, Dave. >> Hey Dave. >> Ajay, let's start with you. Let's set up the sort of smart data concept. What's that all about? What's your perspective? >> Yeah, so I mean, our way of thinking about this is you you've got data, it has latent value, and it's really about discovering what the properties of that data. Does it have value? Can you put that data to work? And the way we go about that with algorithms and machine learning, to generate signals in that data identified patterns, that means we can start to discover how can we apply that data to down stream? What value can we unlock for a customer and business? >> Well, so you've been on this, I mean, really like a laser, why? I mean, why this issue? Did you see a gap in the marketplace in terms of talking to customers and maybe you can help us understand the origin? >> Yeah, I think that the gap has always been there. They've been, it's become more apparent over recent times with big data. So the ability to manually work with volumes of data in petabytes is prohibitively complex and expensive. So you need the different routes, you need different set of tools and methods to do that. Metadata are data that you can understand about data. That's what we at Io-Tahoe focus on, discovering and generating that metadata. That ready, that analogy to automate those data ops processes. So the gap David, is being felt by a business owner prizes and all sectors, healthcare, telecoms, and putting that data to work. >> So Ved, Let's talk a little bit about your role. You work with a lot of customers. I see you as an individual in a company who's really trying to transform what is a very challenging industry. That's sort of ripe for transformation, but maybe you could give us your perspective on this, what kind of signals you're looking for from the data pipeline and we'll get into how you are helping transform healthcare? >> Thanks, David. You know I think this year has been one of those years where we've all realized about this idea of unknown unknowns, where something comes around the corner that you're completely not expecting. And that's really hard to plan for obviously. And I think what we need is the ability to find early signals and be able to act on things as soon as you can. Sometimes, and you know, the COVID-19 scenario of course, is hopefully once in a generation thing, but most businesses struggle with the idea that they may have the data there in their systems, but they still don't know which bit of that is really valuable and what are the signals they should be watching for. And I think the interesting thing here is the ability for us to extract from a massive data, the most critical and important signals. And I think that's where we want to focus on. >> And so, talk a little bit about healthcare in particular and sort of your role there, and maybe at a high level. How Tata and your eco-system are helping transform healthcare? >> So if you look at healthcare, you've got the bit where people need active intervention from a medical professional. And then you've got this larger body of people, typically elderly people who aren't unwell, but they have frailties. They have underlying conditions and they're very vulnerable, especially in the world that we're in now in the post-COVID-19 scenario. And what we were trying to look at is how do we keep people who are elderly, frail and vulnerable? How can we keep them safe in their own homes rather than moving to care homes, where there has been an incredibly high level of infection for things like COVID-19. So the world works better if you can keep people safe in their own homes, if you can see the slide we've got. We're also talking about a world where care is expensive. In most Western countries, especially in Western Europe, the number of elderly people is increasing as a percentage of the population, quite significantly, and resources just are not keeping up. We don't have enough people. We don't have enough funding to look after them effectively. And the care industry that used to do that job has been struggling of late. So it's kind of a perfect storm for the need for technology intervention there. And in that space, what we're saying is the data signal that we want to receive are exactly what as a relative, or a son or daughter you might want from a parent to say, "Everything's okay. "We know that today's been just like every other day "there are no anomalies in your daily living." If you could get the signals that might tell us that something's wrong, something not quite right. We don't need very complex diagnostics. We just need to know something's not quite right, that my dad hasn't woken up as has always at seven o'clock, but till nine o'clock there's no movement. Maybe he's a bit unwell. It's that kind of signal that if we can generate, can make a dramatic difference to how we can look out for these people, whether through professional carers or through family members. So what we're looking to do is to sensor-enable homes of vulnerable people so that those data signals can come through to us in a curated manner, in a way that protects privacy and security of the individual, but gives the right people, which is carers or chosen family members the access to the signals, which is alerts that might tell you there was too much movement at night, or the front door was been left open, things like that that would give you a reason to call him and check. Everybody has spoken to in this always has an example of an uncle or a relative or parent that they've looked after. And all they're looking for is a signal. Even stories like my father's neighbor calls me when he doesn't open his curtain by 11 o'clock, that actually, if you think about it is a data signal that something might be all right. And I think what we're trying to do with technology is create those kinds of data signals because ultimately, the healthcare system works much better if you can prevent rather than cure. So every dollar that you put into prevention saves maybe $3 to $5 downstream. The economic summit also are working our favor. >> And those signals give family members the confidence to act. Ajay, it is interesting to hear what Ved was talking about in terms of the unknowns, because when you think about the early days of the computer industry, there were a lot of knowns, the processes were known. It was like the technology was the big mystery. Now, I feel like it's flipped. We've certainly seen that with COVID. The technology is actually quite well understood and quite mature and reliable. One of the examples is automated data discovery, which is something that you guys have been been focused on at Io-Tahoe. Why is automated data discovery such an important component of a smart data life cycle? >> Yeah. I mean, if we look David at the schematic and this one moves from left to right where right at the outset with that latent data, the value is late because you don't know. Does it have? Can it be applied? Can that data be put to work or not? And the objective really is about driving some form of exchange or monetization of data. If you think about it in insurance or healthcare, you've got lots of different parties, providers, payers, patients, everybody's looking to make some kind of an exchange of information. The difficulty is in all of those organizations, that data sits within its own system. So data discovery, if we drill into the focus itself that, it's about understanding which data has value, classifying that data so that it can be applied and being able to tag it so that it can then be put to use it's the real enabler for that per day drops. >> So maybe talk a little bit more about this. We're trying to get to self-service. It's something that we hear a lot about. You mentioned putting data to work. It seems to me that if the business can have access to that data and serve themselves, that's the way to put data to work. Do you have thoughts on that? >> Yeah, I mean, thinking back in terms of what IT and the IT function in a business could provide, there have been limitations around infrastructure, around scaling, around compute. Now that we're in an economy that is digital driven by API's your infrastructure, your data, your business rules, your intelligence, your models, all of those on the back of an API. So the options become limitless. How you can drive value and exchange that data. What that allows us to do is to be more creative, if we can understand what data has value for what use case. >> Ved, Let's talk a little bit about the US healthcare system. It's a good use case. I was recently at a chief data officer conference and listening to the CDO of Johns Hopkins, talk about the multiple different formats that they had to ingest to create that COVID map. They even had some PDFs, they had different definitions, and that's sort of underscored to me, the state of the US healthcare industry. I'm not as familiar with the UK and Europe generally, but I am familiar with the US healthcare system and the diversity that's there, the duplication of information and the like, maybe you could sort of summarize your perspectives and give us kind of the before and your vision of the after, if you will? >> The use of course, is particularly large and complex system. We all know that. We also know, I think there is some research that suggests that in the US the per-capita spend on healthcare is among the highest in the world. I think it's like 70%, and that compares to what just under 9%, which is going to be European, typical European figure. So it's almost double of that, but the outcomes are still vastly poor. When Ajay and I were talking earlier, I think we believe that there is a concept of a data friction. When you've got multiple players in an eco-system, trying to provide a single service as a patient, you're receiving a single health care service. There are probably a dozen up to 20 different organizations that have to collaborate to make sure you get that top of the line health care service. That kind of investment deserves. And what prevents it from happening very often is what we would call data friction, which is the ability to effectively share data. Something as simple as a healthcare record, which says, "This is Dave, this is Ved, this is Ajay." And when we go to hospital for anything, whatever happens, that healthcare record can capture all the information and tie to us as an individual. And if you go to a different hospital, then that record will follow you. This is how you would expect that to be implemented, but I think we're still on that journey. There are lots and lots of challenges. I've seen anecdotal data around people who suffered because they weren't carrying a card when they went into hospital, because that card has the critical elements of data, but in today's world, should you need to carry a piece of paper or can the entire thing be a digital data flow that can easily be, can certainly navigate through lack of paper and those kinds of things. So the vision that I think we need to be looking at is an effective data exchange or marketplace back with a kind of a backbone model where people agree and sign off a data standard, where each individual's data is always tied to the individual. So if you were to move States, if you would move providers, change insurance companies, none of that would impact your medical history, your data, and the ability to have the other care and medical professionals to access the data at the point of need and at the point of healthcare delivery. So I think that's the vision we're looking at, but as you rightly you said that there are enormous number of challenges, partly because of the history, of healthcare, I think it was technology enablement of healthcare started early. So there's a lot of legacy as well. So we shouldn't trivialize the challenges that the industry faces, but that I think is the way we want to go. >> Well, privacy is obviously a huge one, and a lot of the processes are built around non-digital processes and what you're describing as a flip for digital first. I mean, as a consumer, as a patient, I want an app for that. So I can see my own data. I can see price, price transparency, give access to people that I think need it. And that is a daunting task, isn't it? >> Absolutely. And I think the implicit idea and what you just said, which is very powerful is also on the app you want to control. >> Yes. >> And sometimes you want to be able to change access on data at that point. Right now, I'm at the hospital. I would like to access my data. And when I walk away or maybe three days later, I want to revoke that access. It's that level of control. And absolutely, it is by no means a trivial problem, but I think that's where you need the data automation tools. If you try to do any of this manually, we'd be here for another decade trying to solve this, but that's where tools like Io-Tahoe come in because to do this, a lot of the heavy lifting behind the scenes has to be automated. There has to be a machine churning that and presenting the simpler options. And I know you were talking about it just a little while ago Ajay. I was reminded of the example of a McDonald's or a Coke, because the sales store idea that you can go in and you can do your own ordering off a menu, or you can go in and select five different flavors from a Coke machine and choose your own particular blend of Coke. It's a very trivial example, but I think that's the word we want to get to with access of data as well. If it was that simple for consumers, for enterprise, business people, for doctors, then that's where we ultimately want to be able to arrive. But of course, to make something very simple for the end-user, somebody has to solve for complexity behind the scenes. >> So Ajay, it seems to me Ajay there're two major outcomes here. One is of course, the most important I guess, is patient outcomes, and the other is cost. I mean, they talked about the cost issues, we all, US especially understand the concerns about rising costs of healthcare. My question is this, how does a Smart Data Marketplace fit into achieving those two very important outcomes? >> When we think about how automation is enabling that, where we've got different data formats, the manual tasks are involved, duplication of information. The administrative overhead of that alone and the work, the rework, and the cycles of work that generates. That's really what we're trying to help with data is to eliminate that wasted effort. And with that wasted effort comes time and money to employ people to work through those siloed systems. So getting to the point where there is an exchange in a marketplace just as they would be for banking or insurance is really about automating the classification of data to make it available to a system that can pick it up through an API and to run a machine learning model and to manage a workflow, a process. >> Right, so you mentioned backing insurance, you're right. I mean, we've actually come a long way and just in terms of, know the customer and applying that to know the patient would be very powerful. I'm interested in what you guys are doing together, just in terms of your vision. Are you going to market together, kind of what you're seeing in terms of promoting or enabling this self-service, self-care. Maybe you could talk a little bit about Io-Tahoe and Tata, the intersection at the customer? >> Sure. I think we've been very impressed with the TCS vision of 4.0, how the re-imagining traditional industries, whether it's insurance, banking, healthcare, and bringing together automation, agile processes, robotics, AI, and once those enablers, technology may have brought together to re-imagine how those services can be delivered digitally. All of those are dependent on data. So we see that there's a really good fit here to enable understanding the legacy, the historic situation that has built up over time in an organization, a business and to help shine a light on what's meaningful in that to migrate to the cloud or to drive a digital twin, data science project. >> Ved, anything you can add to that? >> Sure. I mean, we do take the business 4.0 model quite seriously in terms of a lens with which you look at any industry, and what I talked about in healthcare was an example of that. And for us business 4.0, means a few very specific things. The technology that we use in today's verse should be agile, automated, intelligent, and cloud-based. These have become kind of hygiene factors now. On top of that, the businesses we build should be mass customized. They should be risk embracing. They should engage ecosystems, and they should strive for exponential value, not 10% growth year on year, but doubling, tripling every three, four years, because that's the competition that most businesses are facing today. And within that, the Tata group itself, is an extremely purpose-driven business. We really believe that we exist to serve communities, not just one specific set, i.e. shareholders, but the broader community in which we live and work. And I think this framework also allows us to apply that to things like healthcare, to education and to a whole vast range of areas where, everybody has a vision of using data science or doing really clever stuff at the gradients. But what becomes clear is, to do any of that, the first thing you need is a foundational piece. And as a foundation isn't right, then no matter how much you invest in the data science tools you won't get the answers you want. And the work we're doing with the Io-Tahoe really, for me, is particularly exciting because it sorts out that foundational piece. And at the end of it, to make all of this, again, I will repeat that, to make it simple and easy to use for the end user, whoever that is. And I realized that I'm probably the first person who's used fast food as a shining example for healthcare in this discussion, but you can make a lot of different examples. And today, if you press a button and start a car, that's simplicity, but someone has solved for that. And that's what we want to do with data as well. >> Yeah, that makes a lot of sense to me. We talk a lot about digital transformation and a digital business, and I would observe that a digital business puts data at the core. And you can certainly be the best example. There is, of course, Google is an all digital business, but take a company like Amazon, Who's got obviously a massive physical component to its business. Data is at the core. And that's exactly my takeaway from this discussion. Both of you are talking about putting data at the core, simplifying it, making sure that it's compliant, and healthcare it's taking longer, 'cause it's such a high risk industry, but it's clearly happening, COVID I guess, was an accelerant. Guys, Ajay, I'll start with you. Any final thoughts that you want to leave the audience with? _ Yeah, we're really pleased to be working with TCS. We've been able to explore how we're able to put dates to work in a range of different industries. Ved has mentioned healthcare, telecoms, banking and insurance are others. And the same impact they speak to whenever we see the exciting digital transformations that are being planned, being able to accelerate those, unlock the value from data is where we're having a purpose. And it's good that we can help patients in the healthcare sector, consumers in banking realize a better experience through having a more joined up marketplace with their data. >> Ved, you know what excites me about this conversation is that, as a patient or as a consumer, if I'm helping loved ones, I can go to the web and I can search, and I can find a myriad of possibilities. What you're envisioning here is really personalizing that with real time data. And that to me is a game changer. Your final thoughts? >> Thanks, David. I absolutely agree with you that the idea of data centricity and simplicity are absolutely forefront, but I think if we were to design an organization today, you might design it very differently to how most companies today are structured. And maybe Google and Amazon are probably better examples of that because you almost have to think of a business as having a data engine room at its core. A lot of businesses are trying to get to that stage, whereas what we call digital natives, are people who have started life with that premise. So I absolutely agree with you on that, but extending that a little bit. If you think of most industries as eco-systems that have to collaborate, then you've got multiple organizations who will also have to exchange data to achieve some shared outcomes. Whether you look at supply chains of automobile manufacturers or insurance companies or healthcares we've been talking about. So I think that's the next level of change we want to be able to make, which is to be able to do this at scale across organizations at industry level or in population scheme for healthcare. >> Yeah, Thank you for that. Go ahead Ajay. >> David that's where it comes back to again, the origination where we've come from in big data. The volume of data combined with the specificity of individualizing, personalizing a service around an individual amongst that massive data from different providers is where is exciting, that we're able to have an impact. >> Well, and you know Ajay, I'm glad you brought that up because in the early days of big data, there were only a handful of companies, the biggest financial institutions. Obviously, the internet giants who had all these engineers that were able to take advantage of it. But with companies like Io-Tahoe and others, and the investments that the industry has made in terms of providing the tools and simplifying that, especially with machine intelligence and AI and machine learning, these are becoming embedded into the tooling so that everybody can have access to them, small, medium, and large companies. That's really, to me, the exciting part of this new era that we're entering. >> Yeah, and we have placed those, take it down to the level of not-for-profits and smaller businesses that want to innovate and leapfrog into, to growing their digital delivery of their service. >> And I know a lot of time, but Ved, what you were saying about TCS's responsibility to society, I think is really, really important. Large companies like yours, I believe, and you clearly do as well, have a responsibility to society more than just a profit. And I think, Big Tech it's a better app in a lot of cases, but so thank you for that and thank you gentlemen for this great discussion. I really appreciate it. >> Thanks David. >> Thank you. >> All right, keep it right there. I'll be right back right after this short break. This is Dave Vellante for theCUBE. (calm music)

>> From The Cube Studios in Palo Alto and Boston, bringing you data driven insights from The Cube and ETR, this is Breaking Analysis with Dave Vellante. >> Despite it's faster growth and infrastructure as a service, relative to AWS and Azure, Google Cloud platform remains a third wheel in the race for cloud dominance. Google begins its Cloud Next online event starting July fourteenth in a series of nine rolling sessions that go through early September. Ahead of that, we want to update you on our most current data on Google's cloud business. Hello everyone, this is Dave Vellante, and welcome to this week's Wikibon Cube insights, powered by ETR. In this session, we'll review the current state of cloud, and Google's position in the market. We'll drill into the ETR data and share fresh insights from our partner and the Cube community. So let's get right into it. You know, Google, if you think about it, was actually very early into the cloud game. Google's 2004 IPO was a milestone event for the tech industry, and in you know many ways, it really marked the end of the post-dotcom malaise. It signaled the beginning of a new era of innovation. During this time, Google was busy building out its massive, global cloud infrastructure, probably the largest in the world, with undersea cables, global data centers, and tools like the Google file system, and of course Bigtable. But it took many years for Google to pull its head out of its ad serving butt and realize the opportunity to sell its cloud services to global enterprises. Bigtable, Google's no-sequel database, for example, was released in 2005, but it wasn't until 2015 that Google made this service available to its customers. That was the same year Google brought in VMware founder, Diane Greene to begin its enterprise journey in earnest. Now Google, they have a dizzying array of services in compute, storage, database, networking, IT ops, dev tools, machine learning, AI, analytics, big data, security, on and on and on. Name a category and it's likely that Google has something in it as a cloud service. But Google, to this day, still hasn't figured out how to sell to the enterprise. It really struggles to find the right formula. So, as you know, Google brought in Thomas Kurian from Oracle, to figure this out. Of course Kurian is, he's going to go with Google's strengths like analytics and database, but it has to have differentiation, so it comes up with unique pricing models like sustained discounts, which automatically apply discount for heavy usage, as opposed to forcing users to buy reserved instances such as what AWS does. You know Google is more aggressive partnering around multi-cloud, for instance, with Anthos, and it's smartly open-sourced Kubernetes really to minimize the importance of, physically, where workloads run. The bottom-line, however, is that these moves are necessary for Google to compete because it lags behind the leaders. And it has a long way to go before it's going to be satisfied with its cloud business. Let's look at the IaaS market in context. Now, I don't want to say it's all gloom and doom for Google. Far from it. Earnings for Q2, they're going to start rolling out later this month, but this chart shows our latest estimates of IaaS and PaaS for the big three cloud players. Now, I got to caution you, as I did before, other than AWS, which reports very clean numbers each quarter on IaaS and PaaS, we have to estimate Azure and GCP revenue because they bundle in other things. I'll give an example. Google reports its overall cloud numbers which include G Suite. Microsoft reports a category they call intelligent cloud. Now that includes public, private clouds, hybrid, sequel server, Windows server, system center, GitHub, enterprise support and consulting services. And Azure, the IaaS and PaaS numbers are also in there too. So what we have to do is to squint through the earnings reports and the 10 Ks and try to get a clean IaaS and PaaS figure for these players, and that's what we show here. Now there's really two points that we want to stress with this data. First, on a trailing 12 month basis, the big three cloud players now account for nearly 60 billion dollars in IaaS and PaaS revenue. And this 60 billion dollars, on a weighted average basis, is growing in the mid 40% range. So well on its way to being a 100 billion dollar business. Just for these three firms. And as we've reported, that's eating directly into the on-premises infrastructure install base, which is a flat to declining market. And that trend is going to play out in a big way this decade. We've predicted that public cloud is going to out pace on-prem infrastructure by more that 1800 basis points over the next 10 years, from a spending standpoint. Now the second point that I want to make relates to Google IaaS and PaaS growth. We peg it at greater than 70%, based on public statements, reading the 10 Ks and ETR data, which we'll discuss in a moment. So, very healthy growth, but from a much smaller install base than, or base than AWS and Azure. But in our view it's not enough, because AWS and Azure are so large and strong still, growth wise, that we feel Google is going to remain a distant third, really indefinitely. Nonetheless, a lot of companies would be thrilled to have a four billion dollar cloud business and there's certainly good news in the data for Google. So let's look at some of that survey data. Now, as we've reported in the past, Google pushes G Suite very hard, as part of its cloud story, and it leads often times with G Suite in its messaging. You know, but to us that's never really been that compelling. So let me start with some anecdotal data from ETR. ETR runs a regular program, they call it VENN, and in the VENN they invite clients into a private session to listen to named CIOs talk about their experience with vendors and overall spending intentions. It's a facilitated session. And we've had ETR's Eric Bradley on as a guest who directs the VENN program, and does much of the facilitation, and here's a statement from a recent VENN session quoting a CIO at a midsize Telco, that I think sums it up nicely. He says Google's G Suite is fine and dandy, but I don't see that truly as an enterprise solution. And frankly, it's still not of the quality of an Office application, talking about Microsoft. All in all I really like the infrastructure-as-a-service and the platform-as-a-service components that GCP had. And I thought they were coming along very very well in that space. Now, the reason that I share this is because the IT buyers that we speak with, you know they're very serious about exploring Google. They want options other than Azure and AWS and they see Google as having great tech and as a viable alternative. So let's talk about GCP and the enterprise. We looking, when we look into the ETR data for the most recent survey, which ran in June and early July, GCP is showing strength in one really important bellwether category, the giant public and private companies. These are the largest firms in the ETR dataset and often point to secular trends. Now, before we get into that, let's look at the picture for GCP using ETR's net score up methodology. This is fundamental to the ETR approach, and remember, each quarter ETR goes out and asks its respondents, are you planning to spend more or less? In its July survey, ETR focuses on second half spending. The next chart captures results across Google's entire portfolio. So here's the breakdown for, for Google across all sectors. 14% of the respondents are adopting new, that's the lime green. 39% plan to increase spending in the second half versus the first half, that's the forest green. Then there's a big fat middle, that's flat, and you see that in the gray area. And the 7% are spending less, with 2% replacing, that's the pinkish and dark red, respectively. So, I would say this result is mixed, in my opinion. Yeah, it's not bad, don't get me wrong, and we've, we'll see once ETR comes out of its quite period, how this compares to Azure and AWR, so remember, I can only share limited data until ETR clients get the data and have time to act on it. But this calculates out to a net score of 44%, which is respectable, but frankly not overly inspiring. So let's look across the GCP portfolio using the ETR taxonomy and see what it looks like. This chart shows the net score comparisons across three different surveys, October 19, April 20, and July 20. So reading the bars left to right, you can see Google's strong suit really is machine learning and AI. Container platforms are also very strong, as are functions, or server-less, and databases, very solid, we'll talk more about that in a minute. You know, video conferencing was just added by ETR and sure it pops up with the work from home. Cloud is actually holding firm when compared to October of last year. But surprisingly, analytics is looking a bit softer. And ETR for the first time added G Suite with, it shows a 26% net score, first time out, which is pretty tepid. I mean not very impressive at all. But overall, the picture looks pretty good for Google. So let's dig further into the giant public and private sector, that bellwether I talked about. And let's peal the onion a bit and look closer at the results from the largest companies in the dataset. So this chart shows the giant public, plus private organizations. So it would include like monster public companies but also large companies like a Cargill or a Coke Industries, if in fact they responded in this survey. And you can see, in that all important sector, it's a story of a lot of green with hardly any red, so quite a positive sign for Google within those bellwethers. Here's what I think is happening here. Is these large, and often far flung organizations, have realized that they have multiple cloud vendors, and they're asking their senior IT leadership to bring some consistency and sanity to their cloud strategies. So they look at the big three and say, okay, what's the best strategic fit for each workload? So they might say for instance let's use AWS for core IaaS, let's use Azure for productivity workloads, and we'll sprinkle some Google in for machine learning and related projects. So we do see some real strength in some of the larger strongholds for Google, although interestingly ETR sort of tells me that there's softness in the midsize and smaller companies that have powered AWS for so many years. And of course this, with Google's base, but compare that to AWS and AWS is much stronger in those smaller companies, start-ups and the like, and of course COVID's the wild car in all this. You know, we have to take that into account, and we will with Sagar Kadakia, who's ETR's director of research in the coming weeks. But I want to look at Google in the all important database category. So before we wrap, let's look at database. You remember, Google's playing catch up in the cloud and its marketing takes a more open posture around partners and things like multi-cloud and you know you can contrast that with AWS for example, but look, make no mistake, Google wants you data in their cloud, and that's why database is so strategic and so important. Look, it's the mother of all lock specs. All you got to do is look at Oracle and their success. Now, as we've reported many times, there's a new workload emerging in the cloud around this idea of the modern data warehouse. I mean I don't even like that term anymore, data warehouse, because it sounds just so static. But anyway, any rate, I'm talking about workloads that bring database, machine learning, AI, data science, compute and storage along with visualization tools to deliver real-time insights and operational analytics. Database is at the heart of everything here. Win the database and everything else falls into place. Now, Google has six or seven database products and one of the most impressive, in my opinion, is BigQuery. I mean, for those who have followed me over the years you know I love the technology behind Google's banner, but BigQuery is where much of the action is around this new workload that I'm talking about. So, let's look at, deeper at Google's position in database. This chart shows one of my favorite views. On the Y axis is the net score, or spending momentum, and on the X axis is market share or pervasiveness in the ETR dataset. The chart plots various database companies and their position within the all important giant public plus private sector. So these are the companies in the ETR survey that are the largest, and oftentimes, again, are a bellwether. And you can see Microsoft and Oracle and AWS have very strong presence on the horizontal axis. Mongo, MongoDB looms large, MemSQL, they just raised 50 million dollars this past May, MariaDB just raised another 25 million this month. You can see Couchbase and Redis, they show up, and they're on my radar. I'm learning more about those companies. Folks, database is hot. VC's are pouring money in and it's something that's very important to the Cube community to look at. And of course you see Google in the chart, with a strong net score, you know, but not the type of market presence that you see from the other big cloud players. In fact, they've pulled back a little somewhat in this last ETR survey. So despite some bright spots in the enterprise in terms of spending momentum, just not quite enough presence yet. Oh, by the way, look who's right there with Google. I know I sound like a broken record, but Snowflake is everywhere. You'll find them in AWS, you'll find them in Azure and on GCP. Now remember, Snowflake is only about one tenth the size of Google's IaaS and PaaS business. But it has stronger spending momentum than all the big guys, and it continues to creep its way to the right in terms of market share or presence. You know, but Google has great database tech and BigQuery is at the heart of its strategy to support analytics at scale, and automate the data pipeline. BigQuery's very well designed, it started as a cloud native database, it's based on server-less, it's highly scalable, and it's very cost-effective. In fact, ESG, enterprise strategy group, wrote a report comparing the TCO of the cloud databases. Let me pull that up and show you. Now the report was commissioned by Google, so I got to caution you there. But it was very well done in my opinion by a guy named Aviv Kaufmann, and you can see here it compares BigQuery with the other cloud databases, and of course, you know, BigQuery wins, got the lowest TCO, but again I thought the report was really detailed and well researched. I have no doubt that Snowflake has an answer for the big brown bar, which is on-demand cloud cost. I think ESG was making certain assumptions, maybe worst case assumptions, about the need to over-provision resources for Snowflake, which I'm sure ESG can defend, but I'll bet dollars to donuts that Snowflake, you know, has an answer to that or a comeback. I'm going to ask them. But the point I want to make here is that BigQuery was designed from day one, again, as a cloud-native database. We've been talking about that a lot. It's very efficient and is going to be competitive. So you can see, there are some bright spots in the enterprise, for Google. Okay, let's wrap up. Now, having called out some of the positives, and there are many, Google is still not getting it done in the enterprise, in my opinion. I certainly would not say too little too late, but I would say they spotted the competition a huge lead, and the only reason is Google just didn't act on the opportunity staring them in the face, within the enterprise, fast enough, and they finally woke up. But enterprise sales are, they're really hard. Thomas Kurian, for all his experience, is coming from way, way behind with regard to the enterprise go to market, systems and processes, pricing, partnerships, special deals for the enterprise. Google's still learning how to sell the business outcomes and is relying far too much on its technology chops, which, while impressive, are not going to win the day without better enterprise sales, marketing, and ecosystem integration. Now I feel like for years, Google has said to the enterprise market, give me heat and I'll add the wood. Meaning we have the best tech, go ahead and use it. That strategy just doesn't work in the enterprise. Kurian knows it and I suspect that's why Google's showing some strength within these large, giant public and private companies. They're probably applying focused sales resources to nail customer success with some of its top accounts where they have a presence, and then once they nail that they'll broaden to the market. But they got to move fast. We'll learn more about Google's intentions and its progress over the next few, next few months as they try their online event experiment, and of course we'll be there providing our wall to wall coverage. Remember, these Breaking Analysis episodes, they're all available as podcasts. ETR is shortly exiting its quiet period, this week, and will be rolling out the data, so check out etr.plus. I publish weekly on wikibon.com and siloconeangle.com and as always please comment on my LinkedIn posts, I really appreciate the feedback. This is Dave Vellante for the Cube Insights, powered by ETR. Thanks for watching everyone. We'll see you next time.

>>LA Las Vegas. It's the cube hovering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back everyone. This is the cubes live covers Las Vegas anus. Re-invent. I'm John furrier with Dave Alante extracting the signal from the noise sponsored by Intel and AWS. They put the stage together, two big stages. Day two, we're here day Jew, I rapid fire a devil's execs coming on. Dave McCann, cube alumni, VP of ADAS migration marketplace and control services known most for the marketplace and a lot of stuff going on. That's exciting in the marketplace. It's where all the ecosystem actions happening. Congratulations on you six. I know you're busy, you've got new stuff, but the marketplace seems to be changing the procurement and the consumption of software and solutions, whether it's SAS or images and technology, your demand on the marketplace. So great to be back, Kimberly. It's another reinvent. This is my sixth. Um, so lots going on. Marketplace has got a lot bigger in the last year. >>We're up to 260,000 customers, so not substantial growth from last year. And we're adding thousands of customers every month. Um, big headline I have to start with is marketplace has been a marketplace for software for the last seven years. And two weeks ago we launched a marketplace for data and it's a new service that we call AWS data exchange. And instead of allowing you to point, click subscribe to software, and if you're a data consumer and a bank and you're an analyst or you're a researcher and a pharma company, you actually buy data from hundreds of companies, you know, you can go into the new console, find the product and market, please go over to this console called data exchange. And you can go buy research data or you can buy healthcare data from change healthcare. You can buy news data from Thomson Reuters, you can buy consumer data from Experian. >>And we've launched 1400 products from 19 data providers and we've made it available globally. So it's a whole new class of intellectual property data sources in there as well. There's some open source public sources as well. And we're adding literally dozens of products every day. So really easy API. And the cool thing is that after you subscribe, you copy it right into your S three bucket, moves into your VPC and then you move it into your project and you can actually create a Lambda function with the next version of the data. The next day gets updated and know the data just gets updated. And the use case here is like, if I'm a retail outlet, I could buy or go and get weather data and do some things. Is that kind of the model? Exactly. Right. I mean companies all over the world by $150 billion worth of data, but it's all delivered thousands of different EPA. >>Dave, we got cube data, we put all of our advanced data out there, which might be an opportunity. But seriously, Q three 65 is our new listing on the market place. So we have a Q cloud service, little plug for the cube cube three 65 on the marketplace and we're, we're happy. But I want to ask you because one of the things that's coming up is, um, from your team in the marketplace, the industry is this notion of buying through the marketplace. The trend is increasing private offers is a hot feature that you guys have put in place. And there's some news there. Could you explain how private offers is changing the game in the marketplace? I'd love to show you, if you think about it, a lot of our customers are developers and builders and they're working on something on test and it's a pilot and you use it for a few hours or a week. >>But once a company contracts for software and if you're contracting for a lot of software, procurement, one's best price, legal one's best terms, and there's going to be in negotiation and we call that negotiation of private offer. And so that involves salespeople. And so our top software vendors like a Splunk and new Relic of trend micro, uh, Palo Alto, their sales guys, or negotiate our sales ladies and negotiating with the customer for a couple hundred thousand dollars and there's a price and terms. When are you going to pay? What clauses do you agree? How many of you buying? Where are you going to deploy? All of that's negotiated and no, we have a portal for the sailor. We've had it for a year, we've made some really good changes and the central, they arose the seller to automate that price court rate into your account and then the buyer subscribes, and this is allowing our sailors to do quotations in the hundreds of thousands, the millions and sometimes in the tens of millions on a contract rate through marketplace, you're doing millions of dollars of business with with private offers today we've seen vendors write contracts for over $10 million, Peter over three years SAS contracts. >>So we've had that program available for the last year and we'd be working on a lot of features with the help of people at Splunk and new Relic today, we've made it available for all ISBNs and marketplace. You say all the iterations get to take place in the market place, so it's all those informations. I should just speak, just make sure I get it right before private offers were invite only kind of thing. Now you're making it available to all ASVs. Correct. We've got one. As of today, we've over 1,500 ASVs in the marketplace. You're one of them. And with those 1500 vendors within our go into marketplace, there's a new button and the seller portal and it says create Piper offer and any over ISV can note create a private. So I'm going to put my little seller hat on. I have a SAS application. Look at, I don't have a big Salesforce. >>How can you guys help me? How do I, how do I get more sales? Is there a, there's the money just following my bank account. Oh, are you overstaffed to do marketing? You have to do some discussions. You know, we had a company in the UK called Matilda MAF last year on, on the cube. Medallian Staffan was 17 engineers and new salespeople and now they're like 300 people, two runs of venture and everything's through marketplace. Big booth here. Well, congratulations to those guys. We love them. And to come Mytilene again, they engage rafted with you guys. It is all the sales and go to market through AWS complete everything goes through marketplace. Okay. We've made it available to 1,500 vendors today. Okay. So changing procurement. I love that trend. You kind of modernizing the procurement process with the marketplace. What about um, resellers? What's the update there? >>So the big update there is, you know, for the first six years of marketplace we couldn't handle the resaler. We didn't conceive of the VAR or the consulting partner and we got a lot of feedback that we had to do work. And so we've taken private offers and we've designed consulting partner, private offers and no, we've saved up over a hundred top consulting partner resellers, the likes of an OCT of an Ashi, a Rackspace in Europe computer center and Softcat and they were working with all of the world's top resellers and know if you are a Splunk or trend micro, you can authorize computer center to offer private prices to their customers and you can actually authorize a wholesale price from Splunk directly to computer and get paid for. Well, they could actually set the price. Mark it up. I got to ask you, Dave, what's your vision for marketplace? >>Because you're doing a great job. It seems like you're paddling as fast as you can constantly improving the service. I know you've got a big to do list, you want to make it easy or make it faster, all that good stuff, but what's the vision? Where do you see marketplace evolving? You know, Jeff Bezos says it's only day one. We're seven years old. We've barely scratched the surface. Global software is 450 billion growing 8% data is 150 billion growing at 3% you've got a $600 billion industry. Marketplace has not touched a tiny percentage. We want all of our customers to be able to find, discover, provision, and run all of their software and their data out of marketplace and it's gonna take us another 10 years and you get a lot of teen. How big is the team? We never publish JFK K but just let's say the Andy Jassy continues to invest in the business and as we add engineers and we add business people and development people, you know we work well with our partners. >>We cool market. Yeah, we grew up well, as Andy always says, you know, and you always say this, the customer needs come first. That's kind of a vetting process. Then working backwards documents, we know all about that history. What is the number one customer need that you're hearing, that you're addressing, that you see coming up around the corner, you're constantly working on and new potentially new requests that are coming in that are relevant to your business. There's two or three big customer needs. The number one is governance. So while engineers are going fast, innovating, legal, finance and procurement need to be confident that the contracts are being written well and is the spend under control. And so we're doing a lot of work around tagging or the resources so that it's tagged to the right project. Did you overspend on the project? And then on the contracting inside we launched this thing called enterprise contract and we're continuing to work with customers. >>We just integrated into the leading procurement system called ACP a Reebok and we launched that last week. And so we know have a procurement workflow that says procurement's happy it finances happy legal needs to be happy because the engineers want to go quick, but we can't leave the it finance legal professionals behind because they protect the risks for the kinda, the contracts too are all there. So you're modernizing procurement. We are transforming the supply chain for data and for software, you know big. You know I'm a big fan of what you do and I know you got a lot of hard work, a lot of demand, there's a lot of money to be made there, water customers to make happy and you know we've got great customers that BP or shell or Coca Cola, Coke industries that are using marketplace on a regular basis and we have customers now with over a foes and subscriptions from over 50 vendors and that's a single customer. >>Dave, thank you so much for coming on. I know you're super busy and making the time for wrestling the cube means a lot. You've been with us the entire journey for the Ravens, our seventh reinvent. You've been a great one. I missed one but usually patients man it's just you. You saw it working backwards and it's happening. It's working well and you know we learn from our customers and I'm having a dinner tonight with 40 more and I'm sure they'll hit us with more requirements. I'll check my email for the invite. I'm sure it's in there somewhere. Dave McKenna inside the cube. Good friend of the cube, hardworking, billable in the next generation, the next gen marketplace. Check it out. Of course, the cube three 65 our new offering is up there as of Monday. It's kind of a soft launch, but we're telling you now, I'm John Freud. Dave Volante. Thanks for watching back with more. Thanks and have a short break.

>>from Las Vegas. It's the Q covering. Next work. 2019 America's Do You buy Juniper Networks? Come back already. Jeffrey here with the Cube were in Las Vegas at Caesar's at the Juniper. Next work event. About 1000 people kind of going over a lot of new cool things. 400 gigs. Who knew that was coming out of new information for me? But that's not what we're here today. We're here for the fourth installment of around the Cube unpacking. I were happy to have all the winners of the three previous rounds here at the same place. We don't have to do it over the phone s so we're happy to have him. Let's jump into it. So winner of Round one was Bob Friday. He is the VP and CTO at Missed the Juniper Company. Bob, Great to see you. Good to be back. Absolutely. All the way from Seattle. Sharna Parky. She's a VP applied scientist at Tech CEO could see Sharna and, uh, from Google. We know a lot of a I happen to Google. Rajan's chef. He is the V p ay ay >>product management on Google. Welcome. Thank you, Christy. Here >>All right, so let's jump into it. So just warm everybody up and we'll start with you. Bob, What are some When you're talking to someone at a cocktail party Friday night talking to your mom And they say, What is a I What >>do you >>give him? A Zen examples of where a eyes of packing our lives today? >>Well, I think we all know the examples of the south driving car, you know? Aye, aye. Starting to help our health care industry being diagnosed cancer for me. Personally, I had kind of a weird experience last week at a retail technology event where basically had these new digital mirrors doing facial recognition. Right? And basically, you start to have little mirrors were gonna be a skeevy start guessing. Hey, you have a beard, you have some glasses, and they start calling >>me old. So this is kind >>of very personal. I have a something for >>you, Camille, but eh? I go walking >>down a mall with a bunch of mirrors, calling me old. >>That's a little Illinois. Did it bring you out like a cane or a walker? You know, you start getting some advertising's >>that were like Okay, you guys, this is a little bit over the top. >>Alright, Charlotte, what about you? What's your favorite example? Share with people? >>Yeah, E think one of my favorite examples of a I is, um, kind of accessible in on your phone where the photos you take on an iPhone. The photos you put in Google photos, they're automatically detecting the faces and their labeling them for you. They're like, Here's selfies. Here's your family. Here's your Children. And you know, that's the most successful one of the ones that I think people don't really think about a lot or things like getting loan applications right. We actually have a I deciding whether or not we get loans. And that one is is probably the most interesting one to be right now. >>Roger. So I think the father's example is probably my favorite as well. And what's interesting to me is that really a I is actually not about the Yeah, it's about the user experience that you can create as a result of a I. What's cool about Google photos is that and my entire family uses Google photos and they don't even know actually that the underlying in some of the most powerful a I in the world. But what they know is they confined every picture of our kids on the beach whenever they whenever they want to. Or, you know, we had a great example where we were with our kids. Every time they like something in the store, we take a picture of it, Um, and we can look up toy and actually find everything that they've taken picture. >>It's interesting because I think most people don't even know the power that they have. Because if you search for beach in your Google photos or you search for, uh, I was looking for an old bug picture from my high school there it came right up until you kind of explore. You know, it's pretty tricky, Raja, you know, I think a lot of conversation about A They always focus the general purpose general purpose, general purpose machines and robots and computers. But people don't really talk about the applied A that's happening all around. Why do you think that? >>So it's a good question. There's there's a lot more talk about kind of general purpose, but the reality of where this has an impact right now is, though, are those specific use cases. And so, for example, things like personalizing customer interaction or, ah, spotting trends that did that you wouldn't have spotted for turning unstructured data like documents into structure data. That's where a eyes actually having an impact right now. And I think it really boils down to getting to the right use cases where a I right? >>Sharon, I want ask you. You know, there's a lot of conversation. Always has A I replace people or is it an augmentation for people? And we had Gary Kasparov on a couple years ago, and he talked about, you know, it was the combination if he plus the computer made the best chess player, but that quickly went away. Now the computer is actually better than Garry Kasparov. Plus the computer. How should people think about a I as an augmentation tool versus a replacement tool? And is it just gonna be specific to the application? And how do you kind of think about those? >>Yeah, I would say >>that any application where you're making life and death decisions where you're making financial decisions that disadvantage people anything where you know you've got u A. V s and you're deciding whether or not to actually dropped the bomb like you need a human in the loop. If you're trying to change the words that you are using to get a different group of people to apply for jobs, you need a human in the loop because it turns out that for the example of beach, you type sheep into your phone and you might get just a field, a green field and a I doesn't know that, uh, you know, if it's always seen sheep in a field that when the sheep aren't there, that that isn't a sheep like it doesn't have that kind of recognition to it. So anything were we making decisions about parole or financial? Anything like that needs to have human in the loop because those types of decisions are changing fundamentally the way we live. >>Great. So shift gears. The team are Jeff Saunders. Okay, team, your mind may have been the liquid on my bell, so I'll be more active on the bell. Sorry about that. Everyone's even. We're starting a zero again, so I want to shift gears and talk about data sets. Um Bob, you're up on stage. Demo ing some some of your technology, the Miss Technology and really, you know, it's interesting combination of data sets A I and its current form needs a lot of data again. Kind of the classic Chihuahua on blue buried and photos. You got to run a lot of them through. How do you think about data sets? In terms of having the right data in a complete data set to drive an algorithm >>E. I think we all know data sets with one The tipping points for a I to become more real right along with cloud computing storage. But data is really one of the key points of making a I really write my example on stage was wine, right? Great wine starts a great grape street. Aye, aye. Starts a great data for us personally. L s t M is an example in our networking space where we have data for the last three months from our customers and rule using the last 30 days really trained these l s t m algorithms to really get that tsunami detection the point where we don't have false positives. >>How much of the training is done. Once you once you've gone through the data a couple times in a just versus when you first started, you're not really sure how it's gonna shake out in the algorithm. >>Yeah. So in our case right now, right, training happens every night. So every night, we're basically retraining those models, basically, to be able to predict if there's gonna be an anomaly or network, you know? And this is really an example. Where you looking all these other cat image thinks this is where these neural networks there really were one of the transformational things that really moved a I into the reality calling. And it's starting to impact all our different energy. Whether it's text imaging in the networking world is an example where even a I and deep learnings ruling starting to impact our networking customers. >>Sure, I want to go to you. What do you do if you don't have a big data set? You don't have a lot of pictures of chihuahuas and blackberries, and I want to apply some machine intelligence to the problem. >>I mean, so you need to have the right data set. You know, Big is a relative term on, and it depends on what you're using it for, right? So you can have a massive amount of data that represents solar flares, and then you're trying to detect some anomaly, right? If you train and I what normal is based upon a massive amount of data and you don't have enough examples of that anomaly you're trying to detect, then it's never going to say there's an anomaly there, so you actually need to over sample. You have to create a population of data that allows you to detect images you can't say, Um oh, >>I'm going to reflect in my data set the percentage of black women >>in Seattle, which is something below 6% and say it's fair. It's not right. You have to be able thio over sample things that you need, and in some ways you can get this through surveys. You can get it through, um, actually going to different sources. But you have to boot, strap it in some way, and then you have to refresh it, because if you leave that data set static like Bob mentioned like you, people are changing the way they do attacks and networks all the time, and so you may have been able to find the one yesterday. But today it's a completely different ball game >>project to you, which comes first, the chicken or the egg. You start with the data, and I say this is a ripe opportunity to apply some. Aye, aye. Or do you have some May I objectives that you want to achieve? And I got to go out and find the >>data. So I actually think what starts where it starts is the business problem you're trying to solve. And then from there, you need to have the right data. What's interesting about this is that you can actually have starting points. And so, for example, there's techniques around transfer, learning where you're able to take an an algorithm that's already been trained on a bunch of data and training a little bit further with with your data on DSO, we've seen that such that people that may have, for example, only 100 images of something, but they could use a model that's trained on millions of images and only use those 100 thio create something that's actually quite accurate. >>So that's a great segue. Wait, give me a ring on now. And it's a great Segway into talking about applying on one algorithm that was built around one data set and then applying it to a different data set. Is that appropriate? Is that correct? Is air you risking all kinds of interesting problems by taking that and applying it here, especially in light of when people are gonna go to outweigh the marketplace, is because I've got a date. A scientist. I couldn't go get one in the marketplace and apply to my data. How should people be careful not to make >>a bad decision based on that? So I think it really depends. And it depends on the type of machine learning that you're doing and what type of data you're talking about. So, for example, with images, they're they're they're well known techniques to be able to do this, but with other things, there aren't really and so it really depends. But then the other inter, the other really important thing is that no matter what at the end, you need to test and generate based on your based on your data sets and on based on sample data to see if it's accurate or not, and then that's gonna guide everything. Ultimately, >>Sharon has got to go to you. You brought up something in the preliminary rounds and about open A I and kind of this. We can't have this black box where stuff goes into the algorithm. That stuff comes out and we're not sure what the result was. Sounds really important. Is that Is that even plausible? Is it feasible? This is crazy statistics, Crazy math. You talked about the business objective that someone's trying to achieve. I go to the data scientist. Here's my data. You're telling this is the output. How kind of where's the line between the Lehman and the business person and the hard core data science to bring together the knowledge of Here's what's making the algorithm say this. >>Yeah, there's a lot of names for this, whether it's explainable. Aye, aye. Or interpret a belay. I are opening the black box. Things like that. Um, the algorithms that you use determine whether or not they're inspect herbal. Um, and the deeper your neural network gets, the harder it is to inspect, actually. Right. So, to your point, every time you take an aye aye and you use it in a different scenario than what it was built for. For example, um, there is a police precinct in New York that had a facial recognition software, and, uh, victim said, Oh, it looked like this actor. This person looked like Bill Cosby or something like that, and you were never supposed to take an image of an actor and put it in there to find people that look like them. But that's how people were using it. So the Russians point yes, like it. You can transfer learning to other a eyes, but it's actually the humans that are using it in ways that are unintended that we have to be more careful about, right? Um, even if you're a, I is explainable, and somebody tries to use it in a way that it was never intended to be used. The risk is much higher >>now. I think maybe I had, You know, if you look at Marvis kind of what we're building for the networking community Ah, good examples. When Marvis tries to do estimate your throughput right, your Internet throughput. That's what we usually call decision tree algorithm. And that's a very interpretive algorithm. and we predict low throughput. We know how we got to that answer, right? We know what features God, is there? No. But when we're doing something like a NAMI detection, that's a neural network. That black box it tells us yes, there's a problem. There's some anomaly, but that doesn't know what caused the anomaly. But that's a case where we actually used neural networks, actually find the anomie, and then we're using something else to find the root cause, eh? So it really depends on the use case and where the night you're going to use an interpreter of model or a neural network which is more of a black box model. T tell her you've got a cat or you've got a problem >>somewhere. So, Bob, that's really interested. So can you not unpacking? Neural network is just the nature of the way that the communication and the data flows and the inferences are made that you can't go in and unpack it, that you have to have the >>separate kind of process too. Get to the root cause. >>Yeah, assigned is always hard to say. Never. But inherently s neural networks are very complicated. Saito set of weights, right? It's basically usually a supervised training model, and we're feeding a bunch of data and trying to train it to detect a certain features, sir, an output. But that is where they're powerful, right? And that's why they basically doing such good, Because they are mimicking the brain, right? That neural network is a very complex thing. Can't like your brain, right? We really don't understand how your brain works right now when you have a problem, it's really trialling there. We try to figure out >>right going right. So I want to stay with you, bought for a minute. So what about when you change what you're optimizing? Four? So you just said you're optimizing for throughput of the network. You're looking for problems. Now, let's just say it's, uh, into the end of the quarter. Some other reason we're not. You're changing your changing what you're optimizing for, Can you? You have to write separate algorithm. Can you have dynamic movement inside that algorithm? How do you approach a problem? Because you're not always optimizing for the same things, depending on the market conditions. >>Yeah, I mean, I think a good example, you know, again, with Marvis is really with what we call reinforcement. Learning right in reinforcement. Learning is a model we use for, like, radio resource management. And there were really trying to optimize for the user experience in trying to balance the reward, the models trying to reward whether or not we have a good balance between the network and the user. Right, that reward could be changed. So that algorithm is basically reinforcement. You can finally change hell that Algren works by changing the reward you give the algorithm >>great. Um, Rajan back to you. A couple of huge things that have come into into play in the marketplace and get your take one is open source, you know, kind of. What's the impact of open source generally on the availability, desire and more applications and then to cloud and soon to be edge? You know, the current next stop. How do you guys incorporate that opportunity? How does it change what you can do? How does it open up the lens of >>a I Yeah, I think open source is really important because I think one thing that's interesting about a I is that it's a very nascent field and the more that there's open source, the more that people could build on top of each other and be able to utilize what what others others have done. And it's similar to how we've seen open source impact operating systems, the Internet, things like things like that with Cloud. I think one of the big things with cloud is now you have the processing power and the ability to access lots of data to be able to t create these thes networks. And so the capacity for data and the capacity for compute is much higher. Edge is gonna be a very important thing, especially going into next few years. You're seeing Maur things incorporated on the edge and one exciting development is around Federated learning where you can train on the edge and then combine some of those aspects into a cloud side model. And so that I think will actually make EJ even more powerful. >>But it's got to be so dynamic, right? Because the fundamental problem used to always be the move, the computer, the data or the date of the computer. Well, now you've got on these edge devices. You've got Tanya data right sensor data all kinds of machining data. You've got potentially nasty hostile conditions. You're not in a nice, pristine data center where the environmental conditions are in the connective ity issues. So when you think about that problem yet, there's still great information. There you got latent issues. Some I might have to be processed close to home. How do you incorporate that age old thing of the speed of light to still break the break up? The problem to give you a step up? Well, we see a lot >>of customers do is they do a lot of training on the cloud, but then inference on the on the edge. And so that way they're able to create the model that they want. But then they get fast response time by moving the model to the edge. The other thing is that, like you said, lots of data is coming into the edge. So one way to do it is to efficiently move that to the cloud. But the other way to do is filter. And to try to figure out what data you want to send to the clouds that you can create the next days. >>Shawna, back to you let's shift gears into ethics. This pesky, pesky issue that's not not a technological issue at all, but right. We see it often, especially in tech. Just cause you should just cause you can doesn't mean that you should. Um so and this is not a stem issue, right? There's a lot of different things that happened. So how should people be thinking about ethics? How should they incorporate ethics? Um, how should they make sure that they've got kind of a, you know, a standard kind of overlooking kind of what they're doing? The decisions are being made. >>Yeah, One of the more approachable ways that I have found to explain this is with behavioral science methodologies. So ethics is a massive field of study, and not everyone shares the same ethics. However, if you try and bring it closer to behavior change because every product that we're building is seeking to change of behavior. We need to ask questions like, What is the gap between the person's intention and the goal we have for them? Would they choose that goal for themselves or not? If they wouldn't, then you have an ethical problem, right? And this this can be true of the intention, goal gap or the intention action up. We can see when we regulated for cigarettes. What? We can't just make it look cool without telling them what the cigarettes are doing to them, right so we can apply the same principles moving forward. And they're pretty accessible without having to know. Oh, this philosopher and that philosopher in this ethicist said these things, it can be pretty human. The challenge with this is that most people building these algorithms are not. They're not trained in this way of thinking, and especially when you're working at a start up right, you don't have access to massive teams of people to guide you down this journey, so you need to build it in from the beginning, and you need to be open and based upon principles. Um, and it's going to touch every component. It should touch your data, your algorithm, the people that you're using to build the product. If you only have white men building the product, you have a problem you need to pull in other people. Otherwise, there are just blind spots that you are not going to think of in order to still that product for a wider audience, but it seems like >>they were on such a razor sharp edge. Right with Coca Cola wants you to buy Coca Cola and they show ads for Coca Cola, and they appeal to your let's all sing together on the hillside and be one right. But it feels like with a I that that is now you can cheat. Right now you can use behavioral biases that are hardwired into my brain is a biological creature against me. And so where is where is the fine line between just trying to get you to buy Coke? Which somewhat argues Probably Justus Bad is Jule cause you get diabetes and all these other issues, but that's acceptable. But cigarettes are not. And now we're seeing this stuff on Facebook with, you know, they're coming out. So >>we know that this is that and Coke isn't just selling Coke anymore. They're also selling vitamin water so they're they're play isn't to have a single product that you can purchase, but it is to have a suite of products that if you weren't that coke, you can buy it. But if you want that vitamin water you can have that >>shouldn't get vitamin water and a smile that only comes with the coat. Five. You want to jump in? >>I think we're going to see ethics really break into two different discussions, right? I mean, ethics is already, like human behavior that you're already doing right, doing bad behavior, like discriminatory hiring, training, that behavior. And today I is gonna be wrong. It's wrong in the human world is gonna be wrong in the eye world. I think the other component to this ethics discussion is really round privacy and data. It's like that mirror example, right? No. Who gave that mirror the right to basically tell me I'm old and actually do something with that data right now. Is that my data? Or is that the mirrors data that basically recognized me and basically did something with it? Right. You know, that's the Facebook. For example. When I get the email, tell me, look at that picture and someone's take me in the pictures Like, where was that? Where did that come from? Right? >>What? I'm curious about to fall upon that as social norms change. We talked about it a little bit for we turn the cameras on, right? It used to be okay. Toe have no black people drinking out of a fountain or coming in the side door of a restaurant. Not that long ago, right in the 60. So if someone had built an algorithm, then that would have incorporated probably that social norm. But social norms change. So how should we, you know, kind of try to stay ahead of that or at least go back reflectively after the fact and say kind of back to the black box, That's no longer acceptable. We need to tweak this. I >>would have said in that example, that was wrong. 50 years ago. >>Okay, it was wrong. But if you ask somebody in Alabama, you know, at the University of Alabama, Matt Department who have been born Red born, bred in that culture as well, they probably would have not necessarily agreed. But so generally, though, again, assuming things change, how should we make sure to go back and make sure that we're not again carrying four things that are no longer the right thing to do? >>Well, I think I mean, as I said, I think you know what? What we know is wrong, you know is gonna be wrong in the eye world. I think the more subtle thing is when we start relying on these Aye. Aye. To make decisions like no shit in my car, hit the pedestrian or save my life. You know, those are tough decisions to let a machine take off or your balls decision. Right when we start letting the machines Or is it okay for Marvis to give this D I ps preference over other people, right? You know, those type of decisions are kind of the ethical decision, you know, whether right or wrong, the human world, I think the same thing will apply in the eye world. I do think it will start to see more regulation. Just like we see regulation happen in our hiring. No, that regulation is going to be applied into our A I >>right solutions. We're gonna come back to regulation a minute. But, Roger, I want to follow up with you in your earlier session. You you made an interesting comment. You said, you know, 10% is clearly, you know, good. 10% is clearly bad, but it's a soft, squishy middle at 80% that aren't necessarily super clear, good or bad. So how should people, you know, kind of make judgments in this this big gray area in the middle? >>Yeah, and I think that is the toughest part. And so the approach that we've taken is to set us set out a set of AI ai principles on DDE. What we did is actually wrote down seven things that we will that we think I should do and four things that we should not do that we will not do. And we now have to actually look at everything that we're doing against those Aye aye principles. And so part of that is coming up with that governance process because ultimately it boils down to doing this over and over, seeing lots of cases and figuring out what what you should do and so that governments process is something we're doing. But I think it's something that every company is going to need to do. >>Sharon, I want to come back to you, so we'll shift gears to talk a little bit about about law. We've all seen Zuckerberg, unfortunately for him has been, you know, stuck in these congressional hearings over and over and over again. A little bit of a deer in a headlight. You made an interesting comment on your prior show that he's almost like he's asking for regulation. You know, he stumbled into some really big Harry nasty areas that were never necessarily intended when they launched Facebook out of his dorm room many, many moons ago. So what is the role of the law? Because the other thing that we've seen, unfortunately, a lot of those hearings is a lot of our elected officials are way, way, way behind there, still printing their e mails, right? So what is the role of the law? How should we think about it? What shall we What should we invite from fromthe law to help sort some of this stuff out? >>I think as an individual, right, I would like for each company not to make up their own set of principles. I would like to have a shared set of principles that were following the challenge. Right, is that with between governments, that's impossible. China is never gonna come up with same regulations that we will. They have a different privacy standards than we D'oh. Um, but we are seeing locally like the state of Washington has created a future of work task force. And they're coming into the private sector and asking companies like text you and like Google and Microsoft to actually advise them on what should we be regulating? We don't know. We're not the technologists, but they know how to regulate. And they know how to move policies through the government. What will find us if we don't advise regulators on what we should be regulating? They're going to regulate it in some way, just like they regulated the tobacco industry. Just like they regulated. Sort of, um, monopolies that tech is big enough. Now there is enough money in it now that it will be regularly. So we need to start advising them on what we should regulate because just like Mark, he said. While everyone else was doing it, my competitors were doing it. So if you >>don't want me to do it, make us all stop. What >>can I do? A negative bell and that would not for you, but for Mark's responsibly. That's crazy. So So bob old man at the mall. It's actually a little bit more codified right, There's GDP are which came through May of last year and now the newness to California Extra Gatorade, California Consumer Protection Act, which goes into effect January 1. And you know it's interesting is that the hardest part of the implementation of that I think I haven't implemented it is the right to be for gotten because, as we all know, computers, air, really good recording information and cloud. It's recorded everywhere. There's no there there. So when these types of regulations, how does that impact? Aye, aye, because if I've got an algorithm built on a data set in in person, you know, item number 472 decides they want to be forgotten How that too I deal with that. >>Well, I mean, I think with Facebook, I can see that as I think. I suspect Mark knows what's right and wrong. He's just kicking ball down tires like >>I want you guys. >>It's your problem, you know. Please tell me what to do. I see a ice kind of like any other new technology, you know, it could be abused and used in the wrong waste. I think legally we have a constitution that protects our rights. And I think we're going to see the lawyers treat a I just like any other constitutional things and people who are building products using a I just like me build medical products or other products and actually harmful people. You're gonna have to make sure that you're a I product does not harm people. You're a product does not include no promote discriminatory results. So I >>think we're going >>to see our constitutional thing is going applied A I just like we've seen other technologies work. >>And it's gonna create jobs because of that, right? Because >>it will be a whole new set of lawyers >>the holdings of lawyers and testers, even because otherwise of an individual company is saying. But we tested. It >>works. Trust us. Like, how are you gonna get the independent third party verification of that? So we're gonna start to see a whole terrorist proliferation of that type of fields that never had to exist before. >>Yeah, one of my favorite doctor room. A child. Grief from a center. If you don't follow her on Twitter Follower. She's fantastic and a great lady. So I want to stick with you for a minute, Bob, because the next topic is autonomous. And Rahman up on the keynote this morning, talked about missed and and really, this kind of shifting workload of fixing things into an autonomous set up where the system now is, is finding problems, diagnosing problems, fixing problems up to, I think, he said, even generating return authorizations for broken gear, which is amazing. But autonomy opens up all kinds of crazy, scary things. Robert Gates, we interviewed said, You know, the only guns that are that are autonomous in the entire U. S. Military are the ones on the border of North Korea. Every single other one has to run through a person when you think about autonomy and when you can actually grant this this a I the autonomy of the agency toe act. What are some of the things to think about in the word of the things to keep from just doing something bad, really, really fast and efficiently? >>Yeah. I mean, I think that what we discussed, right? I mean, I think Pakal purposes we're far, you know, there is a tipping point. I think eventually we will get to the CP 30 Terminator day where we actually build something is on par with the human. But for the purposes right now, we're really looking at tools that we're going to help businesses, doctors, self driving cars and those tools are gonna be used by our customers to basically allow them to do more productive things with their time. You know, whether it's doctor that's using a tool to actually use a I to predict help bank better predictions. They're still gonna be a human involved, you know, And what Romney talked about this morning and networking is really allowing our I T customers focus more on their business problems where they don't have to spend their time finding bad hard were bad software and making better experiences for the people. They're actually trying to serve >>right, trying to get your take on on autonomy because because it's a different level of trust that we're giving to the machine when we actually let it do things based on its own. But >>there's there's a lot that goes into this decision of whether or not to allow autonomy. There's an example I read. There's a book that just came out. Oh, what's the title? You look like a thing. And I love you. It was a book named by an A I, um if you want to learn a lot about a I, um and you don't know much about it, Get it? It's really funny. Um, so in there there is in China. Ah, factory where the Aye Aye. Is optimizing um, output of cockroaches now they just They want more cockroaches now. Why do they want that? They want to grind them up and put them in a lotion. It's one of their secret ingredients now. It depends on what parameters you allow that I to change, right? If you decide Thio let the way I flood the container, and then the cockroaches get out through the vents and then they get to the kitchen to get food, and then they reproduce the parameters in which you let them be autonomous. Over is the challenge. So when we're working with very narrow Ai ai, when use hell the Aye. Aye. You can change these three things and you can't just change anything. Then it's a lot easier to make that autonomous decision. Um and then the last part of it is that you want to know what is the results of a negative outcome, right? There was the result of a positive outcome. And are those results something that we can take actually? >>Right, Right. Roger, don't give you the last word on the time. Because kind of the next order of step is where that machines actually write their own algorithms, right? They start to write their own code, so they kind of take this next order of thought and agency, if you will. How do you guys think about that? You guys are way out ahead in the space, you have huge data set. You got great technology. Got tensorflow. When will the machines start writing their own A their own out rhythms? Well, and actually >>it's already starting there that, you know, for example, we have we have a product called Google Cloud. Ottawa. Mel Village basically takes in a data set, and then we find the best model to be able to match that data set. And so things like that that that are there already, but it's still very nascent. There's a lot more than that that can happen. And I think ultimately with with how it's used I think part of it is you have to start. Always look at the downside of automation. And what is what is the downside of a bad decision, whether it's the wrong algorithm that you create or a bad decision in that model? And so if the downside is really big, that's where you need to start to apply Human in the loop. And so, for example, in medicine. Hey, I could do amazing things to detect diseases, but you would want a doctor in the loop to be able to actually diagnose. And so you need tohave have that place in many situations to make sure that it's being applied well. >>But is that just today? Or is that tomorrow? Because, you know, with with exponential growth and and as fast as these things are growing, will there be a day where you don't necessarily need maybe need the doctor to communicate the news? Maybe there's some second order impacts in terms of how you deal with the family and, you know, kind of pros and cons of treatment options that are more emotional than necessarily mechanical, because it seems like eventually that the doctor has a role. But it isn't necessarily in accurately diagnosing a problem. >>I think >>I think for some things, absolutely over time the algorithms will get better and better, and you can rely on them and trust them more and more. But again, I think you have to look at the downside consequence that if there's a bad decision, what happens and how is that compared to what happens today? And so that's really where, where that is. So, for example, self driving cars, we will get to the point where cars are driving by themselves. There will be accidents, but the accident rate is gonna be much lower than what's there with humans today, and so that will get there. But it will take time. >>And there was a day when will be illegal for you to drive. You have manslaughter, right? >>I I believe absolutely there will be in and and I don't think it's that far off. Actually, >>wait for the day when I have my car take me up to Northern California with me. Sleepy. I've only lived that long. >>That's right. And work while you're while you're sleeping, right? Well, I want to thank everybody Aton for being on this panel. This has been super fun and these air really big issues. So I want to give you the final word will just give everyone kind of a final say and I just want to throw out their Mars law. People talk about Moore's law all the time. But tomorrow's law, which Gardner stolen made into the hype cycle, you know, is that we tend to overestimate in the short term, which is why you get the hype cycle and we turn. Tend to underestimate, in the long term the impacts of technology. So I just want it is you look forward in the future won't put a year number on it, you know, kind of. How do you see this rolling out? What do you excited about? What are you scared about? What should we be thinking about? We'll start with you, Bob. >>Yeah, you know, for me and, you know, the day of the terminus Heathrow. I don't know if it's 100 years or 1000 years. That day is coming. We will eventually build something that's in part of the human. I think the mission about the book, you know, you look like a thing and I love >>you. >>Type of thing that was written by someone who tried to train a I to basically pick up lines. Right? Cheesy pickup lines. Yeah, I'm not for sure. I'm gonna trust a I to help me in my pickup lines yet. You know I love you. Look at your thing. I love you. I don't know if they work. >>Yeah, but who would? Who would have guessed online dating is is what it is if you had asked, you know, 15 years ago. But I >>think yes, I think overall, yes, we will see the Terminator Cp through It was probably not in our lifetime, but it is in the future somewhere. A. I is definitely gonna be on par with the Internet cell phone, radio. It's gonna be a technology that's gonna be accelerating if you look where technology's been over last. Is this amazing to watch how fast things have changed in our lifetime alone, right? Yeah, we're just on this curve of technology accelerations. This in the >>exponential curves China. >>Yeah, I think the thing I'm most excited about for a I right now is the addition of creativity to a lot of our jobs. So ah, lot of we build an augmented writing product. And what we do is we look at the words that have happened in the world and their outcomes. And we tell you what words have impacted people in the past. Now, with that information, when you augment humans in that way, they get to be more creative. They get to use language that have never been used before. To communicate an idea. You can do this with any field you can do with composition of music. You can if you can have access as an individual, thio the data of a bunch of cultures the way that we evolved can change. So I'm most excited about that. I think I'm most concerned currently about the products that we're building Thio Give a I to people that don't understand how to use it or how to make sure they're making an ethical decision. So it is extremely easy right now to go on the Internet to build a model on a data set. And I'm not a specialist in data, right? And so I have no idea if I'm adding bias in or not, um and so it's It's an interesting time because we're in that middle area. Um, and >>it's getting loud, all right, Roger will throw with you before we have to cut out, or we're not gonna be able to hear anything. So I actually start every presentation out with a picture of the Mosaic browser, because what's interesting is I think that's where >>a eyes today compared to kind of weather when the Internet was around 1994 >>were just starting to see how a I can actually impact the average person. As a result, there's a lot of hype, but what I'm actually finding is that 70% of the company's I talked to the first question is, Why should I be using this? And what benefit does it give me? Why 70% ask you why? Yeah, and and what's interesting with that is that I think people are still trying to figure out what is this stuff good for? But to your point about the long >>run, and we underestimate the longer I think that every company out there and every product will be fundamentally transformed by eye over the course of the next decade, and it's actually gonna have a bigger impact on the Internet itself. And so that's really what we have to look forward to. >>All right again. Thank you everybody for participating. There was a ton of fun. Hope you had fun. And I look at the score sheet here. We've got Bob coming in and the bronze at 15 points. Rajan, it's 17 in our gold medal winner for the silver Bell. Is Sharna at 20 points. Again. Thank you. Uh, thank you so much and look forward to our next conversation. Thank Jeffrey Ake signing out from Caesar's Juniper. Next word unpacking. I Thanks for watching.

>> From the Silicon Angle Media Office in Boston, Massachusetts, it's The Cube. Now, here's your host Dave Vellante. >> Hi everybody. Welcome to this Cube Insights powered by ETR. In this breaking analysis we're going to look at recent spending data from the ETR Spending Intentions Survey. We believe tech spending is slowing down. Now, it's not falling off a cliff but it is reverting to pre-2018 spending levels. There's some concern in the bellwethers of specifically financial services and insurance accounts and large telcos. We're also seeing less redundancy. What we mean by that is in 2017 and 2018 you had a lot of experimentation going on. You had a lot of digital initiatives that were going into, not really production, but sort of proof of concept. And as a result you were seeing spending on both legacy infrastructure and emerging technologies. What we're seeing now is more replacements. In other words people saying, "Okay, we're now going into production. We've tried that. We're not going to go with A, we're going to double down on B." And we're seeing less experimentation with the emerging technology. So in other words people are pulling out, actually some of the legacy technologies. And they're not just spraying and praying across the entire emerging technology sector. So, as a result, spending is more focused. As they say, it's not a disaster, but it's definitely some cause for concern. So, what I'd like to do, Alex if you bring up the first slide. I want to give you some takeaways from the ETR, the Enterprise Technology Research Q4 Pulse Check Survey. ETR has a data platform of 4,500 practitioners that it surveys regularly. And the most recent spending intention survey will actually be made public on October 16th at the ETR Webcast. ETR is in its quiet period right now, but they've given me a little glimpse and allowed me to share with you, our Cube audience, some of the findings. So as I say, you know, overall tech spending is clearly slowing, but it's still healthy. There's a uniform slowdown, really, across the board. In virtually all sectors with very few exceptions, and I'll highlight some of the companies that are actually quite strong. Telco, large financial services, insurance. That's rippling through to AMIA, which is, as I've said, is over-weighted in banking. The Global 2000 is looking softer. And also the global public and private companies. GPP is what ETR calls it. They say this is one of the best indicators of spending intentions and is a harbinger for future growth or deceleration. So it's the largest public companies and the largest private companies. Think Mars, Deloitte, Cargo, Coke Industries. Big giant, private companies. We're also seeing a number of changes in responses from we're going to increase to more flat-ish. So, again, it's not a disaster. It's not falling off the cliff. And there are some clear winners and losers. So adoptions are really reverting back to 2018 levels. As I said, replacements are arising. You know, digital transformation is moving from test everything to okay, let's go, let's focus now and double-down on those technologies that we really think are winners. So this is hitting both legacy companies and the disrupters. One of the other key takeaways out of the ETR Survey is that Microsoft is getting very, very aggressive. It's extending and expanding its TAM further into cloud, into collaboration, into application performance management, into security. We saw the Surface announcement this past week. Microsoft is embracing Android. Windows is not the future of Microsoft. It's all these other markets that they're going after. They're essentially building out an API platform and focusing in on the user experience. And that's paying off because CIOs are clearly more comfortable with Microsoft. Okay, so now I'm going to take you through some themes. I'm going to make some specific vendor comments, particularly in Cloud, software, and infrastructure. And then we'll wrap. So here's some major themes that really we see going on. Investors still want growth. They're punishing misses on earnings and they're rewarding growth companies. And so you can see on this slide that it's really about growth metrics. What you're seeing is companies are focused on total revenue, total revenue growth, annual recurring revenue growth, billings growth. Companies that maybe aren't growing so fast, like Dell, are focused on share gains. Lately we've seen pullbacks in the software companies and their stock prices really due to higher valuations. So, there's some caution there. There's actually a somewhat surprising focus given the caution and all the discussion about, you know, slowing economy. There's some surprising lack of focus on key performance indicators like cash flow. A few years ago, Splunk actually stopped giving, for example, cash flow targets. You don't see as much focus on market capitalization or shareholders returns. You do see that from Oracle. You see that last week from the Dell Financial Analyst Meeting. I talked about that. But it's selective. You know these are the type of metrics that Oracle, Dell, VMware, IBM, HPE, you know generally HP Inc. as well will focus on. Another thing we see is the Global M&A across all industries is back to 2016 levels. It basically was down 16% in Q3. However, well and that's by the way due to trade wars and other uncertainties and other economic slowdowns and Brexit. But tech M&A has actually been pretty robust this year. I mean, you know take a look at some examples. I'll just name a few. Google with Looker, big acquisitions. Sales Force, huge acquisition. A $15 billion acquisition of Tableau. It also spent over a billion dollars on Click software. Facebook with CTRL-labs. NVIDIA, $7 billion acquisition of Mellanox. VMware just plunked down billion dollars for Carbon Black and its own, you know, sort of pivotal within the family. Splunk with a billion dollar plus acquisition of SignalFx. HP over a billion dollars with Cray. Amazon's been active. Uber's been active. Even nontraditional enterprise tech companies like McDonald's trying to automate some of the drive-through technology. Mastercard with Nets. And of course the stalwart M&A companies Apple, Intel, Microsoft have been pretty active as well as many others. You know but generally I think what's happening is valuations are high and companies are looking for exits. They've got some cool tech so they're putting it out there. That you know, hey now's the time to buy. They want to get out. That maybe IPO is not the best option. Maybe they don't feel like they've got, you know, a long-term, you know, plan that is going to really maximize shareholder value so they're, you know, putting forth themselves for M&A today. And so that's been pretty robust. And I would expect that's going to continue for a little bit here as there are, again, some good technology companies out there. Okay, now let's get into, Alex if you pull up the next slide of the Company Outlook. I want to start with Cloud. Cloud, as they say here, continues it's steady march. I'm going to focus on the Big 3. Microsoft, AWS, and Google. In the ETR Spending Surveys they're all very clearly strong. Microsoft is very strong. As I said it's expanding it's total available market. It's into collaboration now so it's going after Slack, Box, Dropbox, Atlassian. It's announced application performance management capabilities, so it's kind of going after new relic there. New SIM and security products. So IBM, Splunk, Elastic are some targets there. Microsoft is one of the companies that's gaining share overall. Let me talk about AWS. Microsoft is growing faster in Cloud than AWS, but AWS is much, much larger. And AWS's growth continues. So it's not as strong as 2018 but it's stronger, in fact, much stronger than its peers overall in the marketplace. AWS appears to be very well positioned according to the ETR Surveys in database and AI it continues to gain momentum there. The only sort of weak spot is the ECS, the container orchestration area. And that looks a little soft likely due to Kubernetes. Drop down to Google. Now Google, you know, there's some strength in Google's business but it's way behind in terms of market share, as you all know, Microsoft and AWS. You know, its AI and machine learning gains have stalled relative to Microsoft and AWS which continue to grow. Google's strength and strong suit has always been analytics. The ETR data shows that its holdings serve there. But there's deceleration in data warehousing, and even surprisingly in containers given, you know, its strength in contributing to the Kubernetes project. But the ETR 3 Year Outlook, when they do longer term outlook surveys, shows GCP, Google's Cloud platform, gaining. But there's really not a lot of evidence in the existing data, in the near-term data to show that. But the big three, you know, Cloud players, you know, continue to solidify their position. Particularly AWS and Microsoft. Now let's turn our attention to enterprise software. Just going to name a few. ETR will have an extensive at their webcast. We'll have an extensive review of these vendors, and I'll pick up on that. But I just want to pick out a few here. Some of the enterprise software winners. Workday continues to be very, very strong. Especially in healthcare and pharmaceutical. Salesforce, we're seeing a slight deceleration but it's pretty steady. Very strong in Fortune 100. And Einstein, its AI offering appears to be gaining as well. Some of the acquisitions Mulesoft and Tableu are also quite strong. Demandware is another acquisition that's also strong. The other one that's not so strong, ExactTarget is somewhat weakening. So Salesforce is a little bit mixed, but, you know, continues to be pretty steady. Splunk looks strong. Despite some anecdotal comments that point to pricing issues, and I know Splunk's been working on, you know, tweaking its pricing model. And maybe even some competition. There's no indication in the ETR data yet that Splunk's, you know, momentum is attenuating. Security as category generally is very, very strong. And it's lifting all ships. Splunk's analytics business is showing strength is particularly in healthcare and pharmaceuticals, as well as financial services. I like the healthcare and pharmaceuticals exposure because, you know, in a recession healthcare will, you know, continue to do pretty well. Financial services in general is down, so there's maybe some exposure there. UiPath, I did a segment on RPA a couple weeks ago. UiPath continues its rapid share expansion. The latest ETR Survey data shows that that momentum is continuing. And UiPath is distancing itself in the spending surveys from its broader competition as well. Another company we've been following and I did a segment on the analytics and enterprise data warehousing sector a couple weeks ago is Snowflake. Snowflake continues to expand its share. Its slightly slower than its previous highs, which were off the chart. We shared with you its Net Score. Snowflake and UiPath have some of the highest Net Scores in the ETR Survey data of 80+%. Net Score remembers. You take the we're adding the platform, we're spending more and you subtract we're leaving the platform or spending less and that gives you the Net Score. Snowflake and UiPath are two of the highest. So slightly slower than previous ties, but still very very strong. Especially in larger companies. So that's just some highlights in the software sector. The last sector I want to focus on is enterprise infrastructure. So Alex if you'd bring that up. I did a segment at the end of Q2, post Q2 looking at earning statements and also some ETR data on the storage spending segment. So I'll start with Pure Storage. They continue to have elevative spending intentions. Especially in that giant public and private, that leading indicator. There are some storage market headwinds. The storage market generally is still absorbing that all flash injection. I've talked about this before. There's still some competition from Cloud. When Pure came out with its earnings last quarter, the stock dropped. But then when everybody else announced, you know, negative growth or, in Dell's case, Dell's the leader, they were flat. Pure Storage bounced back because on a relative basis they're doing very well. The other indication is Pure storage is very strong in net app accounts. Net apps mix, they don't call them out here but we'll do some further analysis down the road of net apps. So I would expect Pure to continue to gain share and relative to the others in that space. But there are some headwinds overall in the market. VMware, let's talk about VMware. VMware's spending profile, according to ETR, looks like 2018. It's still very strong in Fortune 1000, or 100 rather, but weaker in Fortune 500 and the GPP, the global public and private companies. That's a bit of a concern because GPP is one of the leading indicators. VMware on Cloud on AWS looks very strong, so that continues. That's a strategic area for them. Pivotal looks weak. Carbon Black is not pacing with CrowdStrike. So clearly VMware has some work to do with some of its recent acquisitions. It hasn't completed them yet. But just like the AirWatch acquisition, where AirWatch wasn't the leader in that space, really Citrix was the leader. VMware brought that in, cleaned it up, really got focused. So that's what they're going to have to do with Carbon Black and Security, which is going to be a tougher road to hoe I would say than end user computing and Pivotal. So we'll see how that goes. Let's talk about Dell, Dell EMC, Dell Technologies. The client side of the business is holding strong. As I've said many times server and storage are decelerating. We're seeing market headwinds. People are spending less on server and storage relative to some of the overall initiatives. And so, that's got to bounce back at some point. People are going to still need compute, they're still going to need storage, as I say. Both are suffering from, you know, the Cloud overhang. As well, storage there was such a huge injection of flash it gave so much headroom in the marketplace that it somewhat tempered storage demand overall. Customers said, "Hey, I'm good for a while. Cause now I have performance headroom." Whereas before people would buy spinning discs, they buy the overprovision just to get more capacity. So, you know, that was kind of a funky value proposition. The other thing is VxRail is not as robust as previous years and that's something that Dell EMC talks about as, you know, one of the market share leaders. But it's showing a little bit of softness. So we'll keep an eye on that. Let's talk about Cisco. Networking spend is below a year ago. The overall networking market has been, you know, somewhat decelerating. Security is a bright spot for Cisco. Their security business has grown in double digits for the last couple of quarters. They've got work to do in multi-Cloud. Some bright spots Meraki and Duo are both showing strength. HP, talk about HPE it's mixed. Server and storage markets are soft, as I've said. But HPE remains strong in Fortune 500 and that critical GPP leading indicator. You know Nimble is growing, but maybe not as fast as it used to be and Simplivity is really not as strong as last year. So we'd like to see a little bit of an improvement there. On the bright side, Aruba is showing momentum. Particularly in Fortune 500. I'll make some comments about IBM, even though it's really, you know, this IBM enterprise infrastructure. It's really services, software, and yes some infrastructure. The Red Hat acquisition puts it firmly in infrastructure. But IBM is also mixed. It's bouncing back. IBM Classic, the core IBM is bouncing back in Fortune 100 and Fortune 500 and in that critical GPP indicator. It's showing strength, IBM, in Cloud and it's also showing strength in services. Which is over half of its business. So that's real positive. Its analytics and EDW software business are a little bit soft right now. So that's a bit of a concern that we're watching. The other concern we have is Red Hat has been significantly since the announcement of the merger and acquisition. Now what we don't know, is IBM able to inject Red Hat into its large service and outsourcing business? That might be hidden in some of the spending intention surveys. So we're going to have to look at income statement. And the public statements post earnings season to really dig into that. But we'll keep an eye on that. The last comment is Cloudera. Cloudera once was the high-flying darling. They are hitting all-time lows. They made the acquisition of Hortonworks, which created some consolidation. Our hope was that would allow them to focus and pick up. CEO left. Cloudera, again, hitting all-time lows. In particular, AWS and Snowflake are hurting Cloudera's business. They're particularly strong in Cloudera's shops. Okay, so let me wrap. Let's give some final thoughts. So buyers are planning for a slowdown in tech spending. That is clear, but the sky is not falling. Look we're in the tenth year of a major tech investment cycle, so slowdown, in my opinion, is healthy. Digital initiatives are really moving into higher gear. And that's causing some replacement on legacy technologies and some focus on bets. So we're not just going to bet on every new, emerging technology, were going to focus on those that we believe are going to drive business value. So we're moving from a try-everything mode to a more focused management style. At least for a period of time. We're going to absorb the spend, in my view, of the last two years and then double-down on the winners. So not withstanding the external factors, the trade wars, Brexit, other geopolitical concerns, I would expect that we're going to have a period of absorption. Obviously it's October, so the Stock Market is always nervous in October. You know, we'll see if we get Santa Claus rally going into the end of the year. But we'll keep an eye on that. This is Dave Vellante for Cube Insights powered by ETR. Thank you for watching this breaking analysis. We'll see you next time. (upbeat tech music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Hey, welcome back here and live here in Mosconi North. The Emerald 2019 Cube Live coverage on Shopping Day Volante Jr Jr. Who's here? EVP general manager, Telco and Edge of Cloud for Vienna. Where Thanks for coming on. Thanks for having me. I know you're super busy. We don't have a lot of time. Get right to it. Um five g a big part of the key. No discussion that's gonna enable a whole bunch of Pakal the pregame show pre gaming not even talk about that. Also. Telco on the Edge Computing Big part Michael Dell said, Edges the future Now these air to emerging areas for you guys. What's the positioning? What's the update? >> No, absolutely. I mean, if you look a tw telecom infrastructure. For the longest time, telcos have played a role just as pure basic connectivity providers. And with five g coming on board, they finally have an opportunity to break out of that and redefine the cloud off the future. So for us the big opportunity around five g is not just the better provisioning off like Higher Man With Service is to consumer for voice and data buy the whole set off new enterprise service is that can be provided on top of this five g network. And in order to be able to do that, you really need to go in with a virtualized telco Cloud architecture. Underneath that, and so we are working with carriers globally now preparing them for five G with an architecture that's going to help them deploy. New service is faster for both their consumer as well as enterprise. >> Going to be the white knight at, so to speak. For these telcos because they've been struggling for years over the top and any kind of differentiates service is even in the network layer. Exactly. I've had tons of rack and stack machine, so they're after their well, well stacked up in terms of computer storage. Also connectivity to the edge. That's the back hall. So you have back haul, which is connectivity. Companies that have massive expertise in scale but fumbling in operational cloud natives that >> by not just that, but I also think that having the idea off on application platform that allows them to go and deploy service is faster and then decide whether they're just going to play at the network connectivity level or at the application tear or a full SAS tear. These are all options that are open to them now with this notion off. Telco five G coupled with an NFI and cloud telco cloud infrastructure. Underneath that and never before have they had this option to doing that. And this is now open to them >> and the cloud native is there greenfield for AP supporter having applications on top of it. Exact icing on the cake, right? >> Exactly, Exactly. And so they're all looking at core architectures and then, potentially, their radio architectures now all being opened up toe deploying new service is that are much faster to provisions and then extending that to EJ and >> five G's deploying. So we know it's out there. So it is pre game is Pat, Guzman said. You know, not even an inning Yet in the metaphor of baseball innings, I >> gotta ask you get my phone. That's not that's fake ill. I know it >> did that with four g to >> skeptic e stands for evolution, which is coming soon. >> That's vaporware for tell Coke language. The surface area is going to radically get bigger with this capability. Yeah, security's gonna be baked in. This is the number one concern for io ti. And more importantly, industrial I ot We've been reporting on silicon angle dot com. This is a national security issue because we're under cyber attacks. Town's getting locked out with ransomware critical infrastructure exposed. We're free country, and I want to be free. We don't lock down. So you have security built into this new promiscuous landscape that is called the coyote Edge. Because you wanna have no perimeter. You want the benefits of cloud. But one whole malware is in there. One take over physical device could cost lives. >> Yeah, there's a big concern. Yeah. What's your thoughts? Yeah, No. So I think there >> are two ways of looking at it. One is the way you looked at it in terms of the security perimeter expanding and then us making sure that we have the right level off infrastructure security baked in to enable this to be an easier, manageable security architecture. This is sort of the pitch you heard from Mia Mary, even in the context of our acquisition of carbon black and how we're thinking about baking security into the infrastructure, the other way of looking at this is if you think about some of the concerns around providers off telecom infrastructure today and how there might be or might not be security back doors. This is happening in today's hardware infrastructure. Okay, so in fact, I would argue that a sick software defined architecture, er, actually ends up providing you greater levels of security. Because what you now have is the option off running all of these network functions as secured as software workloads in a policy envelope that you can introspect. And then you can decide what kind of security you want to deploy on what kind of workload. >> That's an innovative approach. But it doesn't change much, really, from an infrastructure standpoint, does it? Or does it? >> No, it does, >> because now, instead of having a hardware box where you have to worry, I mean, if it's a close, hard red box and you don't quite know what is happening there, the question is, is that more secure than a infrastructure radio running the software that you can actually introspect. I would argue that the software defined approach is more secure than having a hardware box that you don't know. >> I would buy the premise that certainly we know that supply chain concerned. You know the speculation Super Micro, which never was proved. >> It doesn't matter who the vendor is or what the country is. It really is a concern in terms of not being able to introspect what has happened Going inside >> for my tea shop. I'm running VM where operating I want developers. So now you're going to tell Coz you revitalize their business model? They had a rule out appy. Now what did you see? That connecting is gonna be connective tissue between >> I'll think about it. I didn't feel goto a telco. We look at really three stakeholders in there. One is I t the second Is there be to be or enterprise facing business and then the 3rd 1 is their core and access network or the CTO. We're now have a value proposition of having a uniform architecture across all three stakeholders with the uniform ability to create applications and drop it on top of each of these infrastructures with the ability to manage and secure these again in a uniform way, not just that, but also make this work well with other cloud infrastructures private, hyper scale, public as well as EJ. >> That's table stakes. You have to do that. These jokers have to operate whatever >> well it is, But it's not. I mean, if you think about what the infrastructure off a tailcoat today is, it's far from that, because it's it's sort of a closed environment. You can't access anything from a telco environment in order to go build an application to it, and it does not resemble anything like any club >> you could enable Telco. Just I'm just kind of thinking connecting the dots here real time in the Cube. If I'm a telco, hell, I'll take that VM wear on a deli and see model. Make me a cloud and I'll sell Cloud Service is to markets that kind of >> it is. Actually it's a very important part of our business model because most telcos would not move their own infrastructure from a network standpoint onto a public cloud. But they are eagerly awaiting the ability to operate their own network as a cloud, and if they can have somebody manage that for them, then that is very much within the >> you're enabling. An increase in the number of cloud service provides potentially the paint on the makeup of the telco tier one tier two tier three size. Pretty much >> potentially. I mean, it's taking an existing operator and having them operate in a more agile way and potentially increasing anew form off a cloud service >> provided telcos wouldn't move into the public cloud because of they want to control. And the cost is that right or it's >> mostly control. It's not about cost. It's about taking What is your sort of coordinating for, ah, packet corps or for a radio network? Yeah, and there is also an angle around competition, I think telcos our what in about the Amazons of the world and the azure eyes of the world potentially becoming a service provided >> themselves. And that's what I wanted to ask you about the business impact of all this discussion you guys were having is, you know, the cost for bits coming down. The amount of data is increasing faster. You got over the top providers just, you know, picking off the telcos. Telcos can't compete their infrastructures of so hardened. Will this all change that? >> Absolutely So. I think that it has the potential to changing all that. I don't think all the telcos will take advantage of it. Some off them might end up being more traditional and sort of sticking to where they were. But for those that are willing to make the leap, I mean, as an example, Vodafone is a customer that has actually gone in with this architecture with us. A. T and T is working with us with the Vela Cloud software from via Mary bringing a new form off branch computer branch connectivity through SD man. So these are all examples of telcos that are actually leading the >> charter. But if they don't lean in, they have this vision there either. Well, it's either because they're protected by their local government or they're going to go out of business. No, I would >> agree. I mean, it's sort of silly from our standpoint to be talking about five G and not thinking about this as the architecture for five, right? I mean, if you only focus on radio waves and your wireless network that's like a part of the problem, but you really need to have the ability to deploy these agile service's. Otherwise, you could get killed by >> the O. T. T. So how do you compete against the competition? What's the business plan that you have? C. Five G? We see that in the horizon that's evolving its evolution, so to speak. Pun intended on edge is certainly very relevant for enterprises, whether it's manufacturing or industrial or just people. Yeah, >> I'd say there are two things. One is a CZ. I'm sure you heard from folks at GM, where our vision is this notion of any any anywhere. We've talked about any cloud at any application that any device. So that becomes one of the strongest different chaining factors in terms of what V Amir can bring. Tow any of our customers compared to the competition, right? Nobody can actually make it really across these dimensions. If you then take that architecture and use that to deploy a telco cloud, we're now making investments that are telco specific that allow the tailcoat than take this and make the most out of it. As an example, we're investing in open stack we're investing in container ization. We just bought a company called Johanna and Johanna essentially allows the operator to go and provide metrics from their radio access networks. Use at that to train a learning engine and then feed that back so that the operator can tune their network to get like fewer dropped calls in the region. So if you combined technology like that with this, any cloud infrastructure that we have underneath that that's the best in class deployment methodology for any. Tell Cho to deploy >> five. Your business model metrics for you internally is get Maur deployments. What stage of development five G certainly is in a certain stage, but you know, edges there. Where is the Progress bar? If you're the kind of oh, >> it's actually mold phenomenally. I mean, every time we have conversations like this, we're moving about further in terms off. How many carriers are deploying on via mare on a telco cloud Architecture? How many subscribers are basically being serviced by an architectural like this? And then how many network functions are being deployed? Two of'em air architecture. So we are over 100 carriers now we are over. We have about 800 million subscribers, or so that about globally are being serviced by a V M Air supported network. On then, we have essentially over 120 network functions that >> are operating on top of you. Usually bring in all the same stuff that's announced that the show that stuff's gonna fold into the operating platform or Joe Chuckles have different requirements. Off course. It's >> both. We take the best of what is there from the sort of overall vehement factory and then as a team. My team then builds other widgets on top that are telco specific. >> How big is your your tam up Terry for you? >> Well, so the best way to look at it as telcos globally spend about a trillion dollars in capital investment and then probably to X that in terms of their operating expenditure over the course off all of the things that they do right? And out of that, I would say probably a tent off that. So if you take about $100 billion opportunity, opens itself up toe infrastructure investment in terms off the kinds of things that we're talking about now, they're not gonna move from like 0 200 of course. So if you take some period of time, I would say good subset off that $100 billion opportunity is gonna open itself up >> to it. This kind of business cases, eliminating that two x factor, at least reducing it. Is that exactly? That's not just that Service is that's, >> ah, cost reduction alternative. But then you have the ability to go deploy. Service is faster, so it's really a combination off both sort of carrot and the stick, right? I mean, the character here is the ability to go monetize More new service is with five G faster. The stick is that if you don't do it, Ortiz will get there faster and your costs off. Deploying your simple service is will increase his >> telcos, in your opinion, have what they have to do to get the DNA chops to actually be able to compete with the over to top OT T providers and be more agile. I mean, it's obviously sort of new skills that they have to bring in a new talent. Yeah, >> well, first and foremost, they need toe get to a point where their infrastructure is agile and they get into a business model off knowing how to monetize that agile infrastructure. So, for example, they could offer network as a service on a consume as you go basis. They could offer a platform as a service on top off that network in order for or titties to go build applications so they can do Rev shares with the forties. Or they could have offer. Full service is where they could go in and say, We are the conferencing provider for videoconferencing for enterprises. I mean, these are all models that >> the great conversation love to do. Your Palo Alto? Yes. Have you in our studio want to do more of a deep dive? We love the serious, super provocative, and it's important Final question for you. Though Pat Sr here on the Cube, lay asked him, Look back in the past 10 years. Yeah, look back in the next 10 years. What waves should everyone be riding? He said three things that working security and kubernetes humans being number one actually promoting convinced everyone for the ride, for obvious reasons, clouded. I get that, but networking Yeah, that's your world. That's changing. Which which events do you go to where you meet your audience out there in the telco because networking is a telco fundamental thing. Sure moving packets around. This is a big thing, >> eh? So far, operator networking related stuff, I would say. I mean the biggest shows that for us would be Mobile World Congress as an example, right? It's where many operators are. But I would also say that when we do our own events like this is the ember. But the movie forums in in Asia packers an example. A lot of the telco conversations I find they are best done one on one before. Yeah, the forums are our forums, but we will goto have one on one conversations or small group conversations >> with our telco customers. Locals Shakaar Thanks for spending. You get a hard stop. Very busy. >> Thank you. Thanks for having me >> here, Sugar Yaar, Who's here inside the Cube bringing down five G, which is still pregame. A few winning something first thing is gonna come up soon, but edges super hot. A lot of telco customers be back with more live coverage of the emerald after this short break

(upbeat music) >> Welcome back, everybody, Jeff Frick here with theCube. We are at Oracle Park, formerly AT&T Park, recently named Oracle Park. Right on the shores of McCovey Cove, in downtown San Francisco. We haven't been here since Sport's Data, I think 2014. I can't believe it's been five years. So maybe now the Giants' situation will turn as we make a run for the pennant. We're here at a really interesting event, it's called Sports Tech Tokyo World Demo Day. And we're here with kind of the master of ceremonies, if you will, he's Mike Proman, the Managing Director of Scrum Ventures. Mike, great to see you. >> Great to be here. Thanks again for the time. >> Absolutely. So what is this day all about? Give us the low down. >> Yeah so, start up frenzy, right? Sports tech community's just in it's infancy right now. There's a lot of fragmentation though, in this world. And how do we best connect start ups to best-in-class companies, right? Japanese companies, there's a lot of excitement in Japan right now. We have Rugby World Cup coming up next month, we have the Olympics next year. How do we enable the start up community to realize those opportunities from a partnership perspective? So, we set out on this journey about a year ago. Bringing together companies of all different stages, all different geographic regions, and all different areas of focus within sports tech. And our job was to connect them to opportunities in Japan. What we kind of uncovered along the journey right, is that this is a community. And that we're building a platform here that transcends Asia, right. We want to help this community, and whether it's connecting them with the venture audience, or otherwise, we feel this is a great reflection of innovation coming in to this industry. >> Now you took kind of an interesting tact. You've called them, before we turned the cameras on, kind of a cohort, kind of an incubator, not really an incubator. So how is this thing structured, how do people get involved? What are some of the benefits of being part of this group versus out there slogging it on your own? >> Well, absolutely, and I think everyone's first reaction is, oh, this is just another accelerator, right? And we've really made a point of not identifying ourselves as an accelerator, for a variety of reasons. Number one, it's a stage-agnostic cohorts, right. So a lot of the companies that are representative here today, the 159 in our cohort, they've raised 10, 20, 30, $40 million. In many respects, they're all grows up, right. They don't need a quote unquote, a traditional accelerator. But our reality is, everybody needs acceleration. And particularly in Asia, Japan in particular, right? You need allies, you need advocates, you need facilitators. And people who are going to help revenue optimization, as well as just breaking the door in some cases. There's a lot of high profile content coming to that region, and if we can help people, it all comes back to us, long term. >> Right, right. And then the other piece, obviously, is the investment piece. 'Cause you work with a number of Japanese investment firms, so that's really kind of part of the, you know, we're sitting in San Franscisco, the event's called Tokyo, the Olympics are a year way, and you're from the Mid-West. So, you're kind of bringing it all together here in San Franscisco. >> You know, sport is the great unifier, right. So this is a great opportunity for us to speak to other industries, and bring the venture community into this conversation. Because, as you know, it's about top-line growth for a lot of these startups, but in many cases, they need capital to be able to accelerate into that growth. And so, you know, it's a very exciting time, and we're here to help support everybody. Our DNA, we're investors, right. We're a venture capital firm. But at the end of the day, what ends up happening is, these companies needs advocacy and connections, and that's what we're here to provide. >> Right, so, you said 100 plus companies in cohort. So, there's a lot of things going on in sports tech, but what are some of the really oddball ones that you're seeing a little further out than maybe most people aren't thinking about. >> Yeah, you know, the trends to me that I'm really excited about personally, are those opportunities that transcend the industry, right. Where is there opportunity for us to democratize things, from just a lead athletes, right, into things that you and I both need. So look at athlete performance. Look at recovery health, as an industry focus, right. Hydration, you look at mental health, sleep health, dietary health, you know. Players of the Giants, they need that, right? But you and I need that too. So where are those technologies that are innovators or thought leaders and leading the way in those spaces? The nice thing about Sports Tech Tokyo is we focus in athlete performance, stadium experience, and fan engagement, right. And there are 13 sub-categories, so it's a very broad based cohort, a lot of different areas of expertise. But bringing them all together is what's most rewarding. >> What's your favorite piece of it? I mean, it's hard to pick your favorite kid, but a couple of interesting companies in the portfolio that you'd like to highlight. >> Everyone's always saying, oh, you put me on the spot. No, absolutely not, Jeff. But in reality, my background is, I've been an entrepreneur for 10 plus years before this. And I've worked with brands like Coca Cola, and the NBA. What excites me most-- >> So we framed you up with a Coke bottle, by the way. >> Thank you very much. That was a nice product placement there. The nice thing is, I'm seeing technology today that didn't fundamentally exist a year or two ago. So I could tell you my favorite right now, in 2 weeks that might be entirely different, right. You're going to meet somebody from Misapplied Sciences, and they are doing some of the most breakthrough, cutting edge tech that, it's mind boggling, in terms of what they can do. And what's great about a company like Misapplied, is that they're doing it in sports, but they're also doing it in retail, and other high-dense environments. And so to me, those are the winners in this cohort. The ones that can transcend sport, and add value to so many other places. >> Right, so, before I let you go, you got a busy day ahead. What's the run of the day, what should people expect who are coming through the gates here at Oracle today? >> Well I said this is not your traditional accelerator. Well, this is not your traditional demo day, by any means, right. Traditionally, demo day is a bunch of company pitches, and then there's maybe some conversation afterwards. To us, this is a celebration of a broader cohort, right. Our 100 plus mentors that make up the Sports Tech Tokyo community. And we wanted to celebrate those individuals, right. The 100 mentors, the 400 plus attendees we have here today. So, think of it as an extended cocktail party, right. We want people to connect, and connect at scale. And so that's the back half of the day. The front half of the day is more content oriented. We have a lot of industry experts, again, common theme is transcending the vertical. Looking at opportunities to bring the venture community into the conversation. >> All right, well Mike, good luck and have a great and very busy day. >> Yeah, thank you so much. Appreciate it Jeff. >> He's Mike, I'm Jeff, you're watching theCube. We're at Oracle Park in San Francisco on the shores of McCovey Cove, thanks for watching. We'll see you next time. (upbeat digital music)

>> live from Las Vegas. It's the Cube covering magenta. Imagine twenty nineteen. Brought to you by Adobe. >> Hey, welcome back to the Cube. Lisa Martin at Imagine, twenty nineteen from the Wynn Las Vegas. It's happy hour here, but I really wish I had a Coke. I don't have one. But I do have a gentleman from Coca Cola, please doing me and welcoming a couple of guests to the Cube. We have Enrique no great day. The director of Direct to Consumer for Coca Cola Mexico. Enrique, Thank you for joining us. >> Thanks, Lisa. Nice to meet you. >> And we have from forty for Raghu Kerala managing partner. Welcome to >> the Cube. You nailed the name. There you go. Talk >> to >> that interview. I did my best. All right, so here we are in imagine, twenty nineteen with about thirty, five hundred or so people. This show is one that has a tremendous amount of energy. It's like you gave everybody a cook when they walked in the door. Didn't really need it, But we've heard a tremendous amount of positivity people very excited for being able to leverage the power of data to deliver really impactful experiences and as consumers of any product. We want a brand to know us. We want them to help us make our lives better. Before we dig into that with Coca Cola, argue, let's start with you. Forty four is one of magenta owes partners. Give us a little bit of a history there on what you guys do, together with the Gento and four customers like Coca Cola, Mexico. >> Thank you, Lisa, and thank you for inviting us here today. Well, when we put together forty four, we ask yourself some questions like, How do we aspire to be great? And one of the things was to surround ourselves with great partners and adobes definitely been a great partner for us, because what we want to do is bring tea to our customers. A not just a sight but an experience for their consumers. They can live on and grow and invest in a platform. And what we found with Adobe and the Magenta Commerce cloud was a way that we could start building something in an array, tours greatness by using data and insights to build upon our knowledge. And luckily, way found a great partner in Coca Cola that we could aspire to be great together to the end. Consumer e commerce is still in this early days, and what we wanted to say is that a great brand could start and start looking at e commerce in a way to improve their customers. Lives be available in moments that of need and moments of want. And that's something we started doing with North America about four years ago and brought that to Western Europe. And now Lat Ham in the last year has been a great experience partnering with you. >> CocaCola is a brand that everybody knows globally. It's one of those almost feel good brands, right? I mean, you just can't help but get a smile on your face when somebody asked If you want a cup full, of course, who would say no to that? Give me a little lemon twist and I'm very happy, but something that you guys are doing together with Coca Cola. Mexico was really inspirational, and it's really helping to transform and improve people's lives. And we could talk to us about the program that you're building with forty four and how it's actually making giving people access to things that they don't just want that they actually need, like, quality of life, type of sure products. >> So thanks. Thanks a lot, Lisa, for the invitations. So first of all, you know, we have a big challenge, because way No, we have a great brand way, actually have a lot of brands, and that's the challenge. So how can we create this? The solution where we can access people to this? Never. It's for life. So it's not only Coke way have a lot of different products, and Wei have in Mexico is that it's, ah, project that we are calling Coca Cola. It's Coke at home on what we do there is. We are providing the consumers a subscription model where we are enabling the access to multiple beverage products any time on everywhere. So that's that's That's the ambition we have we launched last year in the city of Monterrey. It's It's our first city. We are planning to scale this business into the whole country and probably Latin America. First on, why not probably the states on some foreseeable future. >> So this is more than on demand. I live in Silicon Valley, where we're pretty, you know, we have high expectations and I want to order something, whether it's on door dash or through Google expressed our Amazon that I wanted to show up within an hour. But that's, you know, I might be lazy, that I don't actually want to get in my car and driver walk somewhere. But what you're talking about this is this is not just I want Coca Cola products on demand. This is actually reaching people that really have a strong and need for this type of service. Talk to us about that human interaction and what you guys are really enabling there for your consumers. >> Sure, so So, yeah, United. So the thing is, what we see, the big opportunity here is way. Want to be closer to our consumers? We went to understand them. We want to to hear from them, to receive feedback directly back the way we are used to working Coca Cola in the past one hundred and thirty three years that that's a history of cardiac alights way have the customers that interact with consumers, and then we get some information from the consumers. We've been great doing marketing campaigns, you know. But right now the challenge that we're facing is we want to have direct feedback from them. So we're creating this eco system where we are getting feedback. We're getting knowledge from them, and we know exactly what what's their their needs. The pain points, their suffering, Andi the way what we can solve them and probably eventually some future products. But we can create for them with the specific necessities that they have. So that's what we're creating there. That's a big thing. >> And so we're gonna talk to us about the opportunity to work with a brand like Coca Cola that's been around for over one hundred thirty years, talk about transformation and be able to enable them to really kind of not just delight customers. But there's an emotional connection that people >> have this products. So we always say, like ideally done way can add value from the state of desire to the state of consumption, and in between is a transaction. It's fulfillment, its operations and perhaps unique to most clients of, um, Magenta and Adobe. Coca Cola in Mexico owns a full relationship, and it's a full branded piece from creating that desire in your heart in your mind in your taste buds, but then owning that all the way through the delivery trucks and the people delivering it to your door. And that's something that a CPD firm just actually, I'm not sure of any other CPV firm does in the US or in Mexico at this point. And but then what is the excellence mean? We haven't untidy of excellence of what Coke means to us, the nostalgia and what it means today. But that also raises the high bar because we're not allowed to not be excellent at any other touch point of the brand. But definitely it's fun, right? It's a challenge, you know, making money online. That's the easy part, Being really proud of what you're doing online. That's kind of what makes you go to work every day. >> Being relevant for consumers is what, yeah, >> being relevant? Absolutely, especially because there's a lot of choice with most products and services that are available to us as consumers these days. And if you think of you know, we've been talking a lot at this event about the customer experience and customer experience management, and how can Adobe Inn Magenta enable their customers to use data to understand what delivering what my customer wants to improve. Whether it's, you know, we talked to HP Inc this morning allowing me to order a new PC or printed or ink and have it delivered specifically exactly the way that I wanted to. Whether it's, you know, getting a Coca Cola. I want whoever I'm interacting with to give you a seamless experience. But use the data that you're collecting about me to make my life better. Make my life easier, more seamless. Frictionless. How are you guys at forty for helping Enrique and team utilize that data too crude to really enhance this consumer experience and maybe even create more brand loyalty? Yeah, it's >> interesting. I think data is a tool, but then your hypothesis, where you go from has to be endemic to the brand and for Coca Cola. On the internal, we think of it as a portfolio portfolio of different products in different needs states from hydration to enjoyment from special moments to everyday moments. But then that allows you to start thinking, How do I be part relevant part of more moments and then you could say, Where does data fit into that and now I can understand how there's a new moments being made because people's lives change and the youth always find different ways in different ways of living in different way from being. How can we be relevant to them through our throughout all of that, from the moment you wake up in what you need state is there to special moment of happiness, and they have a company that has products that could live up to. All of that is great and you know you need a portfolio. But you also need to being desire and wanted need all together in one thing, because one person has all of that and one company came, fulfill it if you think about it from a idea of moment. But then what data? Khun, Due to bring those to life >> so soon being relevant, continuing to be relevant is challenging. It's going to require you to really look at trends across a spectrum of, say, consumer behaviors. Enrique, what are some of the trends that you guys are seeing with this project that you've launched in Mexico, and how were you going to be using those trends to expand this globally? >> Sure, Yeah, So? So first of all, as you, as you know, probably e commerce in Mexico is is quite a small right now. So the thing is, it's growing in, you know, very aggressive rates on DH. It happens the same in the rest of Latin America countries. So what What other retailers are looking at is they want to create this this big business right now because they know that in the future it's going to be the competitive advantage for them. So So I think that's something that not many sippy jeez are looking at. There's a lot off are things that must happen inside the companies to enable this on DH. In my experience, the most challenging things and it's not a trend, but it's it's a challenge that we face us as a big city. Gee, Cos is how can we change the culture inside the company? Because this is the main barrier we have. We face when we see and I I'm going to give you the example of Mexico when we see the digital sales of the beverage in Mexico, it comes about two point five percent of the total sales that we have so its its really small if you compare it to the rest of the retail. So whenever we go to the to the rest of the corporation and the rest of the building in Mexico, we say that we want in best, and we want to do there's there's a lot of barriers, you know on the challenge, the main challenge that we face right now. The's companies that want to go direct ical Sumer is this is happen. We changed the mindset, change the culture, and I think that's the most relevant. It's no trend, but it's It's the most relevant challenge that we're facing right now, >> a big challenge because not just for for every convict, but a company with the history that Coca Cola has to be able to start leveraging that data to start to change mindsets and ship cultures. Where are you guys on that journey? And how is your partnership with forty four may be a facilitator of that cultural change? >> Yeah, sure, So it's to be really honest. We're we're beginning this journey way have some countries that are ahead of us. We have some examples in China, For example, curriculum, China's great things cortical in North America is doing very big things in Mexico and Latin America. We're starting the journey on the thing. What we realized is that we need to get together with people that know of this matter. Way are really good at marketing. We're really good at a commercial approach. Operational approach ware not the best at the commerce, but we. That's why we are partnering with guys that no one, we're partnering with platforms like Adobe Magenta, too. To achieve this, that's that's the thing, right? >> Yeah, >> Rookie will finish with you. What are some of the things that you have seen and heard at? Imagine twenty nineteen from a technology innovation perspective that give you the confidence that adobe in Magenta Technologies are going to be able to deliver, what it is that Enrique and his team need to make that barrier change internal evaporate. Yeah, >> I mean, I think when you think of technology right now, even within adobes, it's what the combination of different products that adobe has and how they're going to come together. So the roadmap is a critical piece of it. I think there's been a great announcement of Sensei's coming in and being part of the core offering to make each interaction a little smarter, but also really see the payoff and save what's the real need that trying to be solved, then back that into the products that you see to cut between the different between a press release and a road map? And I think when you come to a summit like this, you hear things from Adobe. But then you also hear the reactions from the customers. And if you hear those both at the same time, you find that great thing in the middle >> of >> what's actionable. And I think if you think of only customer opinions or the what the platform says individually, I think they're less relevant than finding that really time reaction to trends and say, Honestly, sometimes you're drowning in technology and you wantto move the business forward and react to that weak sales that month's numbers. But then you say, Well, let me take a step back and look at the road map or vice versa, and I think everybody's in different stages of where they're going. So until you get that wisdom from everybody else, anyone announcement might be might take you off course. But then you start saying other people are in my boat. Other people are filling my opportunity, sent my sense of opportunity, and other people are feeling my sense of pain. And it's great to see a community come together. It's five thousand people that all want to accomplish something different things, but they want to accomplish success. Whatever. However, they personally define it. >> And it is to your point. It's a very, very strong community here. But we thank you both so much for taking the time to share with us what you guys are doing together with Coca Cola run that everybody knows and loves. So I say we go get a cookie cola and wrap this segment. What do you think you're all right? >> Moment is coming. >> Fantastic. You're watching the Cube. I'm Lisa Martin from Imagine, twenty nineteen from the Wynn Las Vegas. Thanks for watching

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by extension for interactive. >> Hey, welcome back it when Cube live coverage here in Las Vegas are doubly. Summit twenty nineteen. I'm John Murray with Jeffrey, my coz this week. Two days of wall to wall coverage. Our next guest is Glenn Hartman. North America lied for a censure Interactive. Thanks for joining us. Hey, thanks for having me. Great beer. So you guys are doing some great stuff around the creativity, peace, doing great customer experience. Implement taste. We have a great walk through from a lot of the folks from your organization. You're designing up ideas and products, delivering them and then operating them. Nice model. Yeah, thanks. Is that your business model that has network, What century? Interactives business model. I mean center and >> really about one thing. It's about creating, delivering and running the best experiences on the planet. We help our clients do that for their own customers. And when >> we talk about experience, a lot of people have different definitions for that, especially at the conference here. It's not necessarily an experience of a website or a mobile app or u X is people use it. It's really anyway, a brand engages with a customer. It's not just marketing. Either it could be sales or customer service loyalty. Anything anyway. A brand promise can be delivered. Teo to customers. One of things that I've noticed with you guys is that it's a talk track and thought leaders around a new creative and new creativity. And Toby honestly with software that they haven't now the cloud you're seeing in the marketplace. We saw this at Sundance two years ago. A new kind of creative is, um, organically coming into the marketplace with more channels to direct to consumer, whether it be to be or be to see you and now have new kinds of mechanisms to take product, whether it's APS or content or movies, You start to see this democratization really starting to happen. How is that changing? How you guys helped us is because now they now have new capability. They can tell their story in a different way. They have access to new kinds of channels that weren't there before. How is that changing the business, in your opinion, die in a profound way? So I mean, everybody knows that marking is inextricably linked >> to technology and data. Everybody knows that. But when >> we are thinking about the new, creative and own ways that you can tell stories and create experiences. We look at experience very differently. I mentioned before that it was all about all the different touch points in the ways people interact with the brand. But when we look at experience, we call it the Big E. And the biggie actually stands for empathy. And it's understanding how to define what a brand experience means to that customer and defining success in terms of that customer. And you know, Jeff and John, you guys air not to find by your data set or what you bought last week. You could be very different types of people in different situations and understanding ways to empathize with you in the moment and having experiences change in the moment and having creative play, a part of that and data play. A part of that is the big hot. It's a new way of looking at things, and the last part of that, too. And the big is about emotion. So when you have a big brand that has some emotional connection, you know you love this brand for an automotive or you love this hotel chain or there's some brand a connection you have. How do you have that connection flow through every touch? Point and data and technology can enable that. But it's really empathy and emotion. That's the driver. How do you get empathy and creativity to work together? Because you now have an accelerant with data you mentioned getting to know people's empathizing with them in the moment it's contextual. I could be having a great day or a bad day or driving my kids to school of whatever's going on with me. It certainly there might be some data out. How do you get the creativity and the empathy to work together in your mind? You see that appointment? That's the nice parties. More than ever, we have different data sets that can help us do that. Just give you a couple of examples. Um, instead of understanding how to market >> to someone so they'LL buy the next product on basing. That may be on their demographic, maybe basing it on their preferences. You've hear all these terms and marketing for years, and you can understand what they bought. >> Instead of understanding that, why don't we try and look and use data which you could easily do today to understand why they bought something so it could be something as simple as like a I don't know, Cpg example. Maybe have shampoo and you could say, Well, they bought these kinds of things before, So maybe they'LL buy that champion. But if they know that, you know, maybe Jeff is equal friendly are John. Maybe you're more into things that maybe you buy that shampoo because you care about animals and they know they don't test them on animals. Or maybe it's something more about experience that that particular shampoo won't make your daughter cry when you ship your her hair. And it helps that experience that that's the reason why it actually helps me. You're empathizing in the moment with something that is meaningful that you care >> about. It's not about a better deal or >> better price or some kind of feature. It's something actually about you more meaningful, much very meaningful interaction. Data set is that because there's no data before, is it more? There's more signals, potentially to get exposed to that, because that's a hard data points to get. I mean, to find the why is a holistic kind of perspective. It's true, but I mean, I think it's more of a mind set. The date is there, but the mind set has been different. Over time, people were looking to technology every buzz word in the world use big data and personalization. Aye, aye. And then now it's a I and machine learning and like, Well, that's great. And they're all wonderful enablers, as I said, but it has to be driven by empathy first. So it all starts. >> I mean, we've been saying this forever customer, centrist city and a customer >> concerts. But really, I mean, for real. If you start to use those data sets, aunt have the mindset has to be a c M. O. R. A brand manager is someone who actually it's advocating for the customer, and they're willing to say, No, I don't need big data. I don't need all the data. I need this gold nugget part so I can speak to John. >> It's interesting plate, as you say, the emotional part of the biggie. Also, I think it is the old Coke commercial, right raw one world together, and we all cry and there's some great McDonald's commercials, right when you talk about you think beyond that to the to the empathy. I can't help but think of kind of the whole purpose. Purpose driven, mission driven companies. You know, kids coming out of college want to work for mission driven, cos we heard it over and over. And the key notes, you know, we're not a product company, not even really a service company. But we're committed to two, an ideal to the mission. Beep. Be partners with us, be our customer. Let's have a relationship that goes so much deeper and longer than any particular transaction is that kind of that tied it, that that is a part of it? >> Absolutely. Now, the interesting thing of what you said is that people are >> tied to a purpose and maybe something that's meaningful in a broad sense, absolutely. And that's a wonderful place to start. And you can start to align products and services in that way, >> the way he talked about, like, shampoo and, you know, animal testing, right? Well, >> it's a good one, but the next one is really getting a little bit Mohr down to you. So I think all that is great, but really understand what you need in the moment, because what happens is it. Some of those things may change if you are shopping at a grocery store every >> Saturday for your family and you're used to doing down your attitude. There might be different then when >> you're shopping, when your kid is sick and you got pulled out of work and you got to get there to get the prescription, you're into speed and your stress in the moment they're versus. Maybe >> on Saturday you're like all try some new coupons and try some new things and go by. The little tasting >> station is actually behaviors that you want to understand in the moment. That is a big part of that as well. But the key thing to hear is, let's think of this when you deal with empathy. It's not just getting to know all those things. Even if it gets to that level, it's actually changing the way marketers think about talking to communicating and relating to customers even the language that they use. I mean, think of it >> today. I mean, >> still, people use marketers are their marketing to people. It's, uh, that's acquire customers. Let's convert wind developers over good. We don't win their helpers over. And what was the last time you guys were real excited about getting converted? Okay, it's not a fun experience, right? So if you even changed, I might send you say, Let's market with someone or let's let's help them. You actually create experiences that are useful and helpful not about conversion and not a business metric. But success is defined by the customer. How are you guys playing this? Because this is really kind of ties on multiple threads. I mean, the whole nother community angle to people belong to communities in context to their life. And they engage. And when they engage his emotional connection to a group of this and some cohorts is the worker. Thank you. Okay, groups. But they're friends and colleagues, or whatever could be you guys were. The point is, with customers, take us through a use case day in the life of empathy, deployed into how you guys do business with the big Branson and one of the success. How do you make it happen? What's the engagement look like? How does someone do this? So they just wake up one morning, say Okay, I'm gonna have more empathy. They also call you guys up. What happens? Like what? Take us through What? Certain evidence was made in the slide. I could give you >> a little bit of it. An example of how stars we've been talking a little bit more dramatically about sick kids and testing on pets and animals and things like that. Not testing the pets. Can you imagine? I'd really be >> horrible. But single graphic of the users individual personal things is hard, right? So? Well, I mean, the whole point of this is that when you really get into the mechanics of how this works, I'll give you an >> example. It's a little bit less dramatic. OK, so it's a telecommunications company. Telco company. That's selling. You guys know what? Triple play? Yeah. Okay, So you have It's >> a cable and a phone, right? All it's it's like a commodity product writers. There's no emotional thing necessarily. But in that game, if you can just optimize certain parts of the journey, you can make a big difference, right so way got a benign request from a marketer. Teo say, Listen, we do a lot of paid search. Can you help us with this one product? Just if you move it even like one percent, it would be significant to the company. But when? So okay, we'LL do that, >> and it worked out. We go in and help them do their >> search. But because we're thinking about experience in a broader sense for so well, let's let's do it more. Let's make them be able to transact or engage in multiple ways. Well, you could. You could sign up for the service to email. Or maybe there's click to call or click to chat. Or you could even walk into a branch and do it there. Maybe through the call centre, right? It's what's all that's working together on the channel, though fun words you want easy. You're leveraging >> different technologies to do it and people, >> so the way this worked was you were coming in through search and then eventually a lot of them were converting in the call center. So it was all working. And you think that's great? Well, it wasn't great to the company at all. They were very upset. The people that we're buying the media, we're really bummed because they couldn't get the attribution of the credit for the thing was in the call center. So they came over the great idea. They said, OK, take the phone number off and take the the click to call off and will force the >> customer to convert in. Our channel, of >> course, is a brilliant company with great people and rational thinking prevailed and they didn't do that. But they said, Well, what do we do? I said, Well, you're going to eat and multi attribution model to be able to help you do that, Okay, but that's not enough because you also need a new sales incentive and commission structure inside the call center because those people are getting pit on that. But since it's such a low commodity product, that's not gonna work to change. That's that's a new sales kind of thing, then you wait. They can't talk for another three seconds to that person because you'LL bring the margins on. You got to get him back. All the turtleneck just screwed up. That's right. So there's a new business process is now a new operating model whose skills to get him back into the general. So all of a sudden it's benign. Request from a marketing team taken, you optimize my paint search becomes new business transformation. Okay, now, because that brand manager had the guts to say I'm going to advocate for this customer. This customer wants to come in through this channel. They want to convert over here, and we're gonna actually change the operating model, the sales structure to call the sales lead. I had to call the CFO on the CEO, and we're gonna make this happen, Gonna change the way we do business on behalf of that customer. That is weight world, I could tell you we see this all the time and marketers all the time that there's so married to their website analytics funnel that that's all about who gets credit coded earls and the customer experience is a brutal. It's like I'm not here on other sites are all over the place. I don't really need to go the site every day, right? Somebody only go there when Otto and the thing we were talking about before. If you're grocery shopping >> and Europe's have set on Tuesday and you want to get off >> for your kid at versus the nice leisurely thing we talked about on the weekend, there's a whole nother set of outcomes in Cape Yas you have to deal with. If you went into that supermarket on Tuesday and they figured out a way to get you in and out fast and just get those two or three autumns, you need it for your kid. That's a failed trip. According to the grocery industry. You need to be in there longer they want, so you stay in the back. That's right. Totally. That breaks the whole model, but it's wonderful for you. You'LL shop there forever because of that experience, what you're getting at the Morrises air, changing the business models of cos that's the bottom line. You're at the center. That could be a driver for the transformation. That's it. Empathy. Is the driver Absolutely no. You need to have the emotional connection to all that stuff to help also internally see emos. I don't need to just be relevant and customers that need to be relevant to the enterprise. They need to be relevant to the CEO, Doc in seconds and hear the screaming and kicking and screaming right now. Glenn, that's great. But man, that's a heavy lift way could do it. How do you How do you get it? Because now I can see a cultural reaction. The antibodies will come out and attack that notion because it's scary because now, like, whoa, yeah, well, I mean, it is hard, but the good news is, is that we see, even at this conference, and a lot of our clients are coming over to do that this incremental ways to get there. But I'll make it simple. So the advantages are we said this new technology, new data that allow you to do some of this stuff right? That's great. And you can see a lot of them consolidating, right? A lot of the stacks all now have content and analytics and commerce and all that, and in this nice ways that they come together and that consolidation can help, and there's other ones that can handle different data sets, and that helps to his automation. And but the thing is that what people miss is one of the ways to accelerate this is add a human centered approach to how you actually create the experience internally. And what I mean is, it's not enough to consolidate the data and figure out that Gold nugget and not enough to do with technology have to do with humans. It's a human centered approach, so we're bringing in integrated teams of humans that are pulling all the stuff together. It's someone who understands strategy. Maybe someone understands creative when it hit me in the club, basically their prime in the pump getting it. But they will sit together. They sent to get the analytics. People sit next to the creative people. It's in next you people. They work on it as they designed the experience. You don't do a strategy project and then do a A road map and then do an R P for technology enabled Waterfall does not work, but it's beyond even waterfall versus algebra. This is actually taking humans and consolidate that thinking New skill sets at the center in like an incubator way to do pilots to do prototyping to do things. If you want to create that new experience that we're talking about in any of these cases, you gotta hand CMO some kind of thing that can bring to the team and say, Look, here's an app that would enable this or he has a pilot We could try without boiling the ocean toe, actually create an experience that would move the needle or whatever. Lame corporate analogy. Just make more money and get some decent results in Get a beachhead, just small eatery through it. Glenn. Great Insights. This is a great time. We'd love to get you back on the Cuban girl down, and it's kind of design thinking, combined with execution on the front lines with customers. Center the value proposition. Great conversation before we and just give a quick plug for the business. What's going on with a sensor Interactive? How's the business going? What are your goals? How many people are working there? What's the geography is looked like? Give us enough. Thanks for asking So essential Interactive is enjoying its third year as being listed by at H magazine, is the largest digital agency in the world on the fastest growing Wei have coverage and a truly integrated global delivery model that hits every part of the of every market. And we're so excited. Tio have this growth because it's a way to show that the market is truly interested and being experienced lead and the way we're defining experience. We're seeing more and more clients moving from some of these incremental changes to really >> try to put the customer at the center of what they're doing. And, you know, X Ensure Interactive believes in this model it is. It's very much in some ways way. Call it a new kind of provider, like an experience agency for lack of a better term. TTO help companies drive that transformation, and it's >> done with people and technology, and we're been on a tear recently. Most are growth is organic, but we also do lots and lots of acquisitions to make these capabilities come together. All the creativity and the design and the strategy and the techniques and the run of it is all in one integrated team, and that is very, very helpful when you're trying to do some of the things we've been talking about and you're you guys. I think I'm the right way. This customer wave is really, really because with digital customers air in charge, they control their data. They're now going to shift is happening. We're starting to see some visibility into it. It was going to impact the economics process and business models, so I think it's just beginning. Congratulations really is thanks. And we're so excited because some of the >> client successes it's truly transformational somethings. You got it. Carnival or Marriott or or Subway. I >> mean, it's a whole different >> kind of way of looking at experience, and it's >> really helping people. It's not just for its good for the business, but we're really changing people's lives and helping have experiences be meaningful. It's been wonderful and fun for us. Glenn, Thanks so much for sharing this insights here in the Cube. Hey, thanks for going the data Here live adobe summat. Twenty nineteen, Jumper, jefe Rick, Stay tuned for more coverage after this short break

>> 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)