>> Narrator: From Las Vegas, it's the Cube, covering IBM Think 2018, brought to you by IBM. >> Welcome back to Las Vegas, everybody. You're watching the Cube, the leader in live tech coverage. My name is Dave Vellante, and this is day three of our wall-to-wall coverage of IBM's inaugural Think conference. Mary Glackin's here, she's the vice president of weather business solutions, public, private partnerships, IBM Watson, and she's joined by Sheri Bachstein as the global head of consumer business at the Weather Company, an IBM company. Ladies, welcome to the Cube, thanks so much for coming on. >> Thank you, you're welcome. >> Thanks. >> Alright, Mary, going to start with the Weather Company. When IBM acquired the Weather Company, a lot of people were like, "What?", and they said, "Okay, data science, I get that.", and then, there was an IoT spin on that. Obviously, you have a lot of data, but, I got to ask you, what business are you in? >> So, what we like to say is we're in, not in the weather business, we're in the decision business. We're really dedicated, everyday, to help businesses, make the best decisions possible, and Sheri works on the consumer end of the business to do exactly the same thing. >> So, talk about your respective roles. Sheri, you're on the consumer side, as Mary just said, what does that entail? >> So, the consumer side is any touchpoint where we're bringing weather and weather insights to our consumers, whether it's on our weather channel app, whether it's on our web platform, mobile web, on wearables, so, it's anywhere where we're connecting with consumers, and, as Mary said, it's really about helping consumers make decisions. In our field, the forecast and some of the weather data has become a commodity almost, and we've actually shared our weather data with a lot of partners, and, so, now, we're using machine learning and data science to really come up with weather insights to help consumers make decisions, and it could be something just as simple as what to wear today, what's going to happen for a big event, or it can be around how do I keep people safe during severe weather. >> Yeah, I mean, we all look at the weather. I mean, I look at it everyday. >> Yeah. >> Of course, when you travel, like, what do I bring, what do I wear? Living in the East Coast these days, a lot of storms that we've >> That's right. >> encountered in the East Coast. I wonder if you could talk about life at IBM. I mean, again, it was a curious acquisition to a lot of people. Have you guys assimilated, how has it changed your business? >> I would say pretty dramatically. So, coming back to IBM acquiring us, they acquired us, really, for two reasons. One is we had some underlying technology that was really of interest to them that they're leveraging today, but the other part was because weather impacts so many businesses. So, as we've come into IBM, we've had alliances with IBM research. We're working on a pretty exciting project in bringing the next generation weather model to market, using high performance computing there. We've had alliances, definitely, through Watson in bringing AI into our products, and then, our product lines marry up with a lot of IBM product lines. So, we've rolled out a really exciting offering in closed captioning, and it really works well with some of the classical media business, weather media business that we have been providing. >> So, how do you guys make money? Maybe we could talk about the consumer side and the business side. A lot of people must ask that question. >> Yeah. >> They're advertising, okay, fine, >> Yeah. >> but that's not the core of what you guys do. >> Yeah, so, on the consumer side, a big majority of our revenue is drive by advertising, but we had to look at that business as well, 'cause as programmatic advertising has kind of taken up the landscape, how did we pivot to really generate more revenue, and, so, we've done that by creating Watson advertising, and that was one of the first implementations of Watson after the acquisition on the consumer side, and what we've done is we've created an open, scalable environment that, now, we can not only sell meaningful insights on our platform, but we can now give that to our partners, that they can go off our property and use the weather insights, we can use different data around location and media to help our partners really have a better experience, not only on our platform, but on any publisher's platform. >> So, that's your customers using Watson for advertising to drive their business. >> That's right. >> It's not like IBM is getting into the advertising business, per se, directly, is that right? >> Right, well, we're leveraging the power of Watson to create these insights. One of the products we created is called Weather FX, and, really, what it's doing, it's taking predictive analytics on the retail side, which is really an underused technology for retailers, but taking our historical weather data, mixing it with their retail data' to come up with insights so we can come up with interesting things that, say, in the northeast, like right now, during the winter, soda sells tremendously during very snowy or rainy winters. We can look at, you know, strawberry Pop-Tarts sell fairly well right before a hurricane, and, so, these are insights that we can bring to retailers, but it helps them with their supply chain, it helps them with their inventory, it can actually even help them with pricing, and, so, this is one of the ways we're taking our weather technology and marrying it with the advertising world to help provide those insights. >> For real, with the strawberry Pop-Tarts? >> For real, yeah, I guess, you know, you don't have to cook 'em or something. I don't know, so, yeah. >> Right, yeah, it's simple if the lights go out, okay. I mean, we want to ask you about your title, public and private partnerships. It's interesting, what is that all about? >> So, it's really about the fact that weather has really been something that's been shared globally around the world for hundreds of years at this point, and, so, the Weather Company and IBM take it very seriously that we be good partners in that community of weather providers. So, one of the things that we feel passionately about is we have a shared safety mission with national meteorological services globally. So, here in the US, we transmit, Sheri's team does, the warnings that come from the National Weather Service unaltered with attribution to the National Weather Service. We feel that it's really important that there's a sole authoritative voice when there's really danger. So, we share that safety mission, and then, we're trying to help in other parts of the world. We've had some partnerships to try to increase the observing in Africa which is really a part of the world that's under-observed. So, some of IBM's philanthropic efforts have been helping to fill in there and work with those national met services. So, it's really one of the really fun parts of my job. >> You know, we talk a lot about digital transformation, and Ginni Rometty was talking about the incumbent disruptors, and we've been riffing on that all week. We've made the observation that companies that are digital have data at their core, and they've organized, sort of, human expertise around that data. Most companies, Fortune 1000, are built around human expertise and built around other assets, the bottling plant or the factory, et cetera. I look at the Weather Company as a data company, that's probably fair. Did you evolve into that data is clearly at your core? Has it always been, and it's very interesting that IBM has acquired this company as it changes its DNA. I wonder if you could address that. >> Go ahead (laughs). >> So, I think there's a couple aspects around our data. There's obviously the weather data which is really powerful, but then, there's also location data. We're one of the largest location data providers besides Google and some of the others, because our weather accuracy starts with location which is really important. We have 250 million users that use our application, and we want to give them the most accurate forecast, and that starts with location. Because we add value, users will opt in to give us that data which is really important to us that we do keep their data private and opt in to that to get that location data. So, that's really powerful, because, now we can deliver products based on time and location and weather, and it just makes for better weather insights for, not only our consumers, but for our businesses. >> Yeah, yeah. >> Do you use, I mean, how do you use social? I mean, you know how Waze tells you where the traffic is and you report back. Do you guys rely heavily on that, or do you more rely on machines to help you with your forecast? Is it a combination? >> So, I could talk a little bit. One of our new market areas we've been going into is ground transportation. So, we do have a partner that's providing us some transportation, traffic information, but what we bring to it is being able to do, the predictive thing, is to take the weather piece and how that's going to influence that traffic. So, as the storm comes through, we know by looking at past events what that will mean and we bring that piece to the table. So, it's an example of how we go, not just giving you a weather forecast, but really forecasting the impacts and giving you insights, so that if you're running a large trucking operation, you can reroute fleets around it and avoid weather like that and keep people safe. >> Talk about, oh, go ahead, please. >> One of the brands within our portfolio is Weather Underground, and what they brought to the table for us is a personal weather station that works. So, we have about 270,000 around the world, and these are people that just really love the weather. They have a personal weather station in their backyard and they provide that data that then goes into Mary's team in helping looking at the forecast. So, that's one of the ways that we're using kind of a social network in sensoring to influence some of the work that we're doing. >> I mean, the weather forecast, for years, have been the butt of many jokes. You guys are data science oriented, data scientists, the data doesn't lie. We just keep iterating >> Yeah. >> and make it better and better and better. What could you tell us about the improvements of the forecast over the last decade? Maybe Bill Belichick makes jokes about the weather and you hear it, you say, "You know, actually "the weather's predictions have gotten much better." You guys measure it, what can you share with us? >> Oh, it's gotten so much better over the course of my career, it's pretty dramatic and it's getting better still. You're going to see some real breakthroughs coming up. So, one of the things that we've really put a lot of bets on in IBM is the internet of things, >> Dave: Right. >> and, so, we are, today, pulling off of cellphones atmospheric pressure data and that's going into our next generation model. So, this'll be more data than anybody has powering that model. So, you're able to augment traditional data sources like, you may or may not know, we still launch weather balloons twice a day to measure through the atmosphere, but, in our technology, we take data off of airplanes, we take data off of cellphones, we'll soon be taking data off of cars which will tell us when the windshield wipers are moving, is it raining or not, when the anti-lock brakes things lock, that roads are icy, all of that. So, all of that will come in to improve forecasting. >> So, this requires partnerships with all that and amazing supply chain. >> Absolutely. >> I presume IBM helps there as well, but did you have a lot of that in motion prior to the acquisition, how does that all work? >> I think we've really been empowered by IBM. >> Yep, absolutely. >> Yeah. >> There's no question about that, and it's about finding the win-win. When we work with car manufacturers they're looking to have safe experiences for their drivers and we can help in that regard, and, as we move into autonomous vehicles, there's just going to be even more demand for very high resolution, accurate weather information. >> Am I correct at all, the weather data from all these devices actually goes back to the IBM cloud, is that right, and that's where the models are iterated and developed, is that correct, or does some of it stay out in the network? >> It's all a cloud-based operation that's here. We do do some, I mentioned before that we're working with IBM research on next generation high-performance computing which is actually, it can be cloud-based, but it's also on Prim-based, because of the very large cores we need for computing these models. We're going to run a very high-resolution model globally at a very high frequency. >> So, thinking about some of the industries that you're helping, I mean, you mentioned retail before. Obviously, government's very interested in this. I would imagine investors are interested in the weather in a big way. >> Yeah. >> Maybe you could talk about some of the more interesting industries, use cases, business models. >> Yeah, there's a lot out there, there's traditional ones we've served for years like energy traders that are very interested in, you know, because they're trying to make decisions about that. The financial services sector is also very interested. When they can get some additional insights through footfall traffic, if they know certain stores are seeing more footfall traffic, that will give them some indication, a little edge up in the marketplace for that. So, we see those kind of things, and other traditional areas as well, agriculture, what you would expect there. >> So people, you know, you hear a lot of talk in the press about artificial intelligence and Elon Musk predictions and the like, but here's an example where machine intelligence, everybody welcomes, keeps getting better and better and better. How far could we take AI and weather? Where do you see this going in the next 10 years? >> So, on the consumer side, I think it's really about transforming the way that we're delivering weather on the digital platform, the new age of the weather app will say, and, really, users want a personalized experience. They want to know how the weather's going to impact me, but they don't want to personalize, right? So, that's where machine learning is coming in, that we can be able to provide those insights. We'll know that, maybe, you're an allergy sufferer or migraine sufferer, and we're going to tell you that the conditions are right for that you might have symptoms related to that around health. So, there's a lot of ways, on the consumer side, more personalized experience, giving you more assurance that you don't have to, necessarily, go to the app to find information. We're going to send it to you more proactively, and, so, machine learning is helping us do that cognitive science as well. So, it's a pretty exciting time to be part of the weather. >> Yeah, that bum knee I have, you know, you might want to get ahead of the pain. >> That's right, with the arthritis, yes, yes, so, definitely. >> Alright, Mary, we'll give you last word on IBM Think and, you know, the whole trend of AI and weather. >> So, I think it's really exciting. I think Ginni says it really well. It's about AI and the person as well. You know, AI doesn't take over. It's really finding the way to AI to really assist decision makers and that's we're going on the business end of things is really sorting through tons and tons of data to really provide the insights that people can make, businesses can make really great decisions. >> Well, it's always been a really fascinating acquisition to me, and, now, just to see how it's evolving is really amazing. So, Sheri and Mary, thanks very much for coming on the Cube >> Thank you. >> and sharing your experiences. >> Thanks so much. >> Great, thank you. >> You're welcome, alright, keep it right there, everybody, you're watching the Cube. We're live from Think 2018 and we'll be right back. (techno beat)

>> Voiceover: Live from San Francisco, it's The Cube. Covering Samsung Developer Conference 2017. Brought to you by Samsung. >> Okay, welcome back, everyone. Live here in San Francisco, this is The Cube's exclusive coverage of Samsung Developer Conference, SDC 2017. I'm John Furrier, co-founder of SiliconANGLE Media, and co-host of The Cube. My next guest is Dominic Venuto, who is the General Manager of the consumer division of The Weather Channel, and Watson Advertising, which is part of The Weather Company. Welcome to The Cube. >> Thank you for having me. >> Finally, I got the consumer guy on. I've interviewed The Weather Company folks from the IBM side, two different brands. One's the data, big data science operation going on, the whole Weather Company. But Weather Channel, the consumer stuff, Weather Underground, that's your product. >> Yes, you saved the best for last. We touch the consumer. >> So, weather content is good. So obviously, the hurricanes have been in the news over the years. Out here in California, the fires. People are interested in whether the impact, it used to be a unique thing on cable, go to the Weather Channel, check the forecast, read the paper. Now with online apps, weather is constantly a utility for users. So it's not a long-tail editorial product. It's pretty fundamental. >> Yeah, we want to be where our consumers are. Fundamentally we want to help people make better decisions and propel the world. And since weather touches everything, we need to be where the consumers are. So now, with all the digital touchpoints, whether that's your phone, or its a watch, your television, desktop if you still have one and you're still using it, as some of us do. We want to be there, for that very reason. And in fact, what we're aiming for, is to move from a utility, because if we are going to help people make better decisions, a utility only goes so far, would be a platform to anticipate behavior and drive decisions. >> So tell me about the Weather Underground and the weather.com consumer product. They're all one in the same now? Obviously one was very successful, with user generated content. This is not going away. Explain the product side of The Weather Channel consumer division. >> Yeah, so we have two brands in our portfolio, Weather Underground, which is more of a challenger brand. It's very data rich, and visualizes data in a number of different ways, that a certain user group really loves. So if you're a weather geek, as we call them, an avid aficionado of weather, and you really want to really get in there and understand what's happening, and look at the data, then Weather Underground is a platform. >> So for users to tie into, to put up weather stations, and other things that might be relevant. >> Exactly so, we started out in 2001, originally the first IOT implementation at the consumer level, connected devices. Where you could connect a personal weather station, put one in your back yard, and connect it to our platform, and feed hyper-local data into our network. And then we feed that into our forecast, to improve that, and actually validate whether the forecast is right or not, based on what people have at home. And we've hit a recent milestone. We've got over 250,000 personal weather stations connected to the network, which we are super thrilled about. And now, what we are doing is, we are extending that network to other connected devices, and air quality is a big topic right now, in other parts of the world, especially in Asia, where air quality is not always where it should be, that's a big thing we think we can... >> That's a big innovation opportunity for you, I mean, you point out the underground product was part of maker-culture, people do-it-yourself weather stations, evolve now into really strong products. That same dynamic could be used for air control, not just micro-climates. >> Exactly, yeah. >> In California, we had a problem this week. >> Exactly, California is a good example, really topical, where cities may have had great air quality, and all of the sudden the environment changes, and you want to know, what is it like? What is the breathing quality like outside right now? And you can come to our network and see that. And we're growing the air quality sensors every month, it's only been up a few months right now, so that's expanding quite well. >> So for the folks that don't know, The Weather Channel back end, has a huge data-driven product. I don't want to get into that piece, because we've talked about it. Go to youtube.com/siliconangle, search Weather Company. You'll see all our great videos from the IBM events, that are out, if you want the detail. But I do want to ask you, what's really happening with you guys, there's two things. One is, it's an app and content for devices, like Samsung is using. And two, essentially you're an IOT network. Sensors are sensors, whether they're user-generated, or user-populated, you guys are deploying a serious IOT capability. >> Absolutely, it's one of the reasons that IBM acquired The Weather Company, which houses the brands of Weather Underground and The Weather Channel, is that we have this fantastic infrastructure, this IOT infrastructure, ingesting large amounts of data, processing it, and then serving it back out to consumers at scale globally. >> What are you guys doing there with Samsung? Anything just particular in the IOT side, or? >> We've got a couple of initiatives going on with Samsung, a few I can't mention right now, but stay tuned. Some really cool things in the connect-at-home, that we're excited about, that builds on some of the work... >> Nest competitor? >> Not exactly a Nest competitor. Think more kitchen. >> Kitchen, okay. >> Think more kitchen. >> We had the goods, cooking in the kitchen, from our previous guest. So the question is, IOT personal, I get that. What else is going on with IOT, with you guys, that you can share? Lifestyle, in the home is great, but... >> So again, going back to how do we help people make better decisions, now that we are collecting data from not just personal weather stations, but air quality monitors, we are collecting it from cars, we are collecting it from the cell phone. We are really able to ingest data at scale, and when you're doing that, we've got hundreds of thousands of data sets that we are feeding into our models, when you do that, we've solved the computing challenge, now we are applying machine-learning and artificial intelligence to process this and extract insights. To validate data sets, in our forecast, and then deliver that back to the end user. >> One of the tech geek themes we talk about all of the time is policy-based something. Programming, setting the policy. So, connecting the dots from what you're saying is, I'm driving my car, and I want to know if it's hot, or the road temperature. I might want to know if I'm running too fast, and my sensor device on me wants to impact the weather, for comfortable breathing for me, for instance. The lifestyle impacts, the content of data, is not just watching a video on The Weather Channel. >> No, it's not. >> So this is a new user experience. It's immersive, it's lifestyle-oriented, it's relevant. What are some of the products you're doing with Samsung, that can enable this new user expectation? >> One of the products that we have right now, we we're one of the initial partners for the Made for Samsung program, is, we've got calendar integration in our app. So now we know, if you've got a meeting coming up, and you need to travel to get there, maybe there's a car trip involved, we know, obviously, the forecast. We know what traffic might be, and we can give you heads up, an alert, that says, hey you might want to leave 15 minutes early for that meeting coming up. That's in the Samsung product right now, which is really, again, helping people make better decisions. So we've got a lot of examples like that. But again, the calendar integration in the Made for Samsung app is really exciting. We recently announced, in fact I think it was this morning, we announced integration with Trip Advisor. So similarly, if we see time on your calendar, and the weather is fine for the weekend, we might suggest outdoor activities for you to go and explore, using Trip Advisor's almost one-billion library of events that they have. >> What's the coolest thing you guys are working on right now? >> Oh, that's a very long list. I say that I'm probably the luckiest guy in IBM right now, because I get to work with millions of consumers, we reach 250 million consumers a month, and I'm also bringing Watson to consumers, and artificial intelligence, which is a unique challenge to solve. Introducing consumers to a new paradigm of user interaction and abilities. So, I think the most exciting thing is taking artificial intelligence and machine-learning, and bringing that to consumers at scale, and solving some of the challenges there. >> Well contratulations. I'm a big fan of IBM, what they're doing with weather data, The Weather Company, The Weather Channel. Bringing that data and immersing it into these new networks that are being created, new capabilities, really helps the consumer, so. Hope to see you at the Think conference coming up next year. >> Yes, we are excited about that, and stay tuned, we may have some more exciting stuff to unveil. >> Make sure our writers get ahold of it, break the stories. It's The Cube, bringing you the data. The weather's fine in San Francisco today. I'm John Farrier with The Cube. More live from San Francisco, from the SDC Samsung Developer Conference, after this short break. (electronic music)