 Welcome to theCUBE here for special presentation live in San Francisco for General Electric GE's Mines and Machines Conference. I'm John Furrier with SiliconANGLE, host of theCUBE and our guest here is Gladys Kong, who's the CEO of Uber Media, formerly the CTO. Welcome to theCUBE. Thank you very much for having me. Great to see you and talking before we went here live. You're the CTO of the company. Now the CEO, this is a Bill Gross company, he's a legend in the industry, going back to the kind of the invention of paid search, one of the couple guys. I was in the mix with him, Keith Thier at Real Names. But at that time that changed the digital landscape, which became known as paid search. And he's got that DNA. But that at the time was not laughed at. No one even thought they would. Yes. Paid links with you. I used to remember that, yes. That became changed history. Hence Google, now we got fake news that Google was pushing, again disruption. Yes. But he started Uber Media. Okay, now he's working on energy. You took it over as CEO. Yes. Take a minute to describe what is Uber Media. So Uber Media is a data technology company today, helping use mobile data to transform into business insight to help company do marketing, measurement, or just business intelligence. And we've been around since 2010, and in around 2012 we've pivoted into this current business model. And I remember when Bill started the company, he was really enamored with data from day one. Yes. And at that time, in 2010, because we had still started SiliconANGLE, all the data geeks like us and Bill go right to the Twitter fire hose. Yes. And I know that that's evolved now over media because Twitter really didn't have a good developer program, killed everything out there that's a business, but still the data's relevant. Right, so. Take us through how you guys got to today. How does it work? What's the value proposition? Absolutely. So the roots of us being a mobile app developer is really helpful because at the time we were collecting everything to try to improve the user experience of our own apps. We tried to use the signals to learn what people like, what people don't like and target better ads to them. And as a result, we find out the insights of how powerful the potential of such data. So today we're using it to help not only marketing businesses, but businesses all over brick and motor stores and everything, but to help make better informed decisions. Yeah, we have a Twitter implementation where we're talking about what we've done, but we could never sell it because the customers weren't ready for it on this journey of digital transformation. But this notion of data clouds are emerging. You guys have built a significant data presence. And the data's happened, it's happening and will happen. So there's the past, the present and the future. How do customers realize this now? As they start to operationalize, put their toe in the water. I think it's very early stage in terms of using mobile data today in the location data, but businesses are realizing how important the real-time aspect and the abundance of data available for how to help them make decisions. So they're learning a lot. A lot of times we sit down with the customer, we listen to their use cases and then figure out how we can best out, choose crafting solutions together today. I was talking to Dave Vellante, who's not here, he's on the East Coast. He's my co-host on theCUBE. You've seen them in the videos. We're talking about that. And we always joke about the old mindset of a developer was whether you're doing websites, microsites, or apps. Oh, that's easy. The most important thing is the UX. We'll just slap a database on and we're good. That notion of building a database to the app and going down, it's the 10 different apps, 10 different databases with 10 applications is changing the notion of the database. It's been the key disruption. And Amazon Web Services, for instance, is putting a herding on Oracle right now and even an open source. This is changing development. How do customers need to think about the database and data going forward? I think the biggest change is the amount of data. We're talking about terabytes now. We're not starting a hard drive. You have to think about scaling and the real-time aspect and the filtering process, all that. And I think it's just a different scale. It's just a company have to start with that mindset of dealing with large scales of data. Instead of starting with one database, it's really have to really expand quickly and then the cost of it too. So one of the things that you guys do I think is really interesting for the folks watching is you're good at collecting data. Yes. And it's hard for companies, even to grok and get their mind around what it would take to even collect, never mind the mechanisms for collecting the data. That's one of your key value propositions. Talk about that dynamic. This collection, what to collect, and how to collect it. So I think there are multiple facets to that. The source of the data, you first have to identify whether the correct source of the data and then the type of data you're collecting. Even location data, you can look at it. Is it precise? Are you looking at GPS data or are you looking at IP derived data? There's big difference. And then the way you're collecting it is it accurate data. People reporting GPS or are they reporting a static location? So those are all things that you take someone to really dive into, understand, and the filtering process. And also then analytics, how do you turn it into useful business insights? Transforming a set of raw data into insights also take a lot of understanding of the business use cases. So here, G, they're showing obviously things like the twin, which is the digital twin is like an agent of bot. But bots are hot, you're seeing the bot movement, which essentially is just a front end to automation. Of data, it oversimplified. But for the most part, that's kind of the idea. How, I mean, how are companies working with you guys in particular? Because I can see the benefit of saying, you guys know how to collect data. You have access to maybe data or it can help us understand what to collect. But now to put that into motion, to put it into their operations, how does someone get that benefit? And be specific, how do you guys help customers? So every company is looking at how to use that data because they know it helps them. And the wide range of use cases, some of them like auto manufacturer, they like to find targeted customers that are in market already, but not just in market. If you're in market in minivan, they don't want to show you their European car ad. So being able to understand what customers are looking for and also to look at the competitors and to understand that, which is what the mobile data allows them to do. So that's one type of use case, hotels, right? They always look for customers. But if I'm a business hotel, I like to look for business travelers that frequently seen at airports. So that's another type of insights that we could gain from that. So when do they call you guys up? And why do they call you up? Do they say, hey, Gladys, just come in and do everything for me? Or they come in with a specific use case? It's usually is they want to move the needle. Every business want to move the needle. And if our data can help them move the needle, even 1%, 10% is huge to their business. So usually they come in and then we identify what's the biggest opportunity to use the data to move the needle in the business. So you come in with a consultative kind of approach. To start just because every use case is so different now, at some point we would like to offer product suites. That's a lot of problems. Today we've seen what that's it. And you bring data to the table for them? Absolutely. Through apps that you're providing. And then sometimes in conjunction with businesses, a lot of times have their own customers data or a subset of it. And what we augment is competitors data or other types of behavioral data they've seen beyond being at their store. This is where we always talk on theCUBE at every event we go to. When you have siloed data, it's not worth anything. No, I think you have to partner to make it more powerful and look at patterns that in a way that looking at it alone can't do it. So building a data lake is not going to do it. You got to have it flowing through some sort of extraction layer. I think so. I think having raw data is like having a bunch of random musical notes. You need a composer to put it together to make it into beautiful music. And you guys are the composer? We are. I mean, being an expert, we know how to put in this in a way that you can listen to. Beautiful music rather than noise. Let's talk about that. So we love that. Extracting the signal from the noise, extracting the music from the noise. It's like putting the musicians together. There's some synergy around the participants. You can't just say put people up on stage and play great music. There has to be some chemistry around it. So let's take that one step further. How do you do that with data? I mean, what's the best practice you've seen? Is there computer science techniques? Is it much more business process improvement? It's a lot of machine learning to extract insights out of data. And we often look at it as, how can you extract actionable insights? Because if I tell you, your hair look messy. It doesn't help you. But maybe you can use this hair product to help you. There's some specific things you can do to businesses that would help them make decisions. And I think looking at those and extracting actionable insights as well. Well, I'm excited that you came on theCUBE today. And I know that we got you in here because we want to sneak you in because the GE event's going on. But more importantly, you were the CTO of the company. Yes. And now the CEO, which I love because I think CEOs should be very technical and they should understand what's going on, not just be an empty suit or someone who's just a business person. Because there's a lot of tech going on. So I've got to ask you the question. What is, as a technical CEO, how do you look at the landscape and how should other CEOs that are out there look at the landscape? Because a lot of bets are being made at the same time. You've got to build some foundations and then build and iterate on top of it. Open source is a big part of it. Of the new software paradigm. What are your thoughts on being a CEO and being technical? I think every company needs to be a technical company today. And leveraging data, leveraging machine learning, leveraging data science to help make this decision is important. And I think synthesizing data and trying to just gather more data and more informative decision is quite important. And in our organization, innovation, innovation is what stays, keep us up top. We were talking before you came on that we both have CES undergraduate degrees. I got an MBA. I got a master's from UCLA, which by the way that's where the internet was founded. So they have a great department as we all know. So you have a dual CES degree, undergraduate and a master's degree. What's changed now? I mean, because right now you're seeing a lot of people going after computer science. Obviously more women and a lot of diversity, not enough, but we hope more. It's changing a lot because of the role of data, because of the cloud, because it's easy to build applications. Your thoughts on the role of computer science, what's changing? Good bet on the ugly. Your thoughts? It's good. It's evolving for sure. Just like when I graduated, the language I learned in school is no longer applicable, but it's the problem solving skills. It's looking at a problem, analyzing it and coming up with a solution. I think that applies no matter what role you're in. And I think that's what helps me the most in my CX background is analyzing a problem and finding a solution to it. Do you still code now? No, I haven't coded in many years, but I still believe that I could. It's just a matter of learning the syntax. You must miss it. I'm looking at how easy it is now. It's so easy to code now. But I love how we could do something. When we coded, we didn't have shoes. We didn't have shoes. We had to walk on the snow. We had to write in machine language. Of course, we're all kind of can say that, but no, in all seriousness, it's a lot easier with open source now, open source is tier one, and getting stronger every day. Yes. What's the coolest thing that you're working on right now that your company's working on that kind of gets the tech juices flowing? The coolest thing I think is using data to help break and mortar shopic decisions. A lot of times we help with online marketing, but how do you apply that to stores that are not maybe not even having online presence? So it's to transform, connect online to offline business. It's what we do. So machine learning, you guys doing a lot of machine learning? Yes, and then looking at location where people physically are going and if they're visiting the store or what interests they are and helping drive that type of decision making. So the big theme here at GE, mind and machines, and started out two years ago, around big data, obviously cloud, the head cloud boundaries involved, pivotal. But now you're starting to see AI as the face of the value where people can say, okay, I want to automate. It's going to help me drive my business. How do you define AI from your perspective now? Because you see GE as an industrial company. They coined the term industrial cloud. Now they changed it to IIoT. But they're bringing an analog world in with digital for the first time. Yes. So that's life. That's what's going on in our world, right? Yes, yes. You're bringing retailers. Yeah. Before it gets more powering life. Yes. Absolutely. It's analog and digital coming together. Right. Your thoughts on that vision in your commentary of AI. Yeah, just when you look around your house, right? You have a nest that control you. I mean, you have all this kind of AI already in your house. Today, when we talk about AI, it's really around you. I mean, 10, 20 years of your AI is like in a sci-fi fiction movie, right? So today, I think it's already surrounding us and it's just soon we'll have self-driving cars. We'll have a lot of things that are programmed and in an intelligent way where you don't have to use human anymore to do that type of chores and tasks. And we interviewed an awesome professor at Santa Clara University at our last event. We're talking about the impact of AI and cognitive, the IBM event. And we need an algorithm to police the algorithms. Yes. I mean, look at Facebook with the fake news. Yes. Google with the fake news impacted the election. So like, who, how does this all get reconciled? That's the open question. I think that's where the evolution has to come in as you always, you open the flag gate where everybody's innovating, then you have to find out how to control the innovation into a way that is positive and helpful. Gladys Kong with Ubermedia, CEO of Ubermedia, formerly the CTO now running the show based in LA in Pasadena. That's right. I'll give you the final word. What's the vision? What's next for you guys? What's your preferred vision? What are you guys going to do? Well, we like to think every company in the near future will use data to make all their marketing, all their planning decisions because that's how you stay ahead. That's how you stay informed. So we like to push it that way to use data in a lot more companies with a lot more companies in the industries. Hey, how many employees you guys have? 62. Okay, so you guys are going to get some openings? Hope, hope, yes. Some tech, the machine learning coders, good luck finding them. Yes. It's more machine learning opportunity. Well, thanks for stopping by on theCUBE. Thank you very much for having me here. We appreciate it. I know you're in San Francisco for the day. I'm glad you can come down and visit us and join us here on theCUBE. Here are the GE minds and machines. I'm John Furrier. You're watching theCUBE. We'll be back with more live action here in San Francisco after this short break. You're watching theCUBE.