 From Las Vegas, expecting the signal from the noise. It's theCUBE covering Interconnect 2016. Brought to you by IBM. Now your host, John Furrier and Dave Vellante. Okay, welcome back everyone. We are here live in Las Vegas for IBM Interconnect 2016. This is theCUBE's Silicon Angles flagship program where we go out to the events and extract the signal from the noise. I'm John Furrier with my co-host Dave Vellante. Next guest is Nancy Pearson, Vice President of Cognitive Business at IBM, CUBE alumni. Great to see you again, you look fabulous. Great to see both of you. Hi. Thank you. So the wheel keeps turning on every crank, in innovation, every event, you hear new stuff. Cognitive is a big part of it. Watson's front and center, but you got open technology, you got Apple on stage. All this is teasing out the digital transformation from hold down the fort with VMware and hybrid cloud. Then you got the open technologies, Swift programming language. Then it comes down to the application. The data is a big part of it. So I got to ask you, what is cognitive? What is the 101? For people who hear the term cognitive technology, cognitive business, what is that? Well, first of all, I'll start with, you heard a lot earlier today about disruption. And in fact, it's a topic that continues to permeate a lot of the presentations and keynotes here. It's just still a struggle for our clients. And it's definitely related to the role that cognitive computing and cognitive business plays. So first of all, clients ask us all the time, what is cognitive? What is cognitive business? What is cognitive computing? So first of all, cognitive means learning to learn. So this is about learning and this is about cognition. A cognitive business is a business that really, infuses cognitive technology to help improve their expertise, improve their discovery, improve the use of massive amounts of data, structured and unstructured data. But cognitive computing is really a system that understands reasons and learns. And that's really important and interacts in a very comfortable way with humans. It's actually the combination of human and machine. And these two things really coming together in a way that's very conducive and comfortable and delivering really good outcomes for clients. So you see that a lot on the TV commercials. The Watson is the poster child for learning machine. I love the Bob Dylan one. You see the interface with teens and tennis athletes. Really it's showing that the machine's doing work for you. So the learning is cool. Talk about the role of data in all this because now the data aspect is critical because you need the data to learn how does that factor into your role and your customers' use of the word cognitive? Do they get a brain implant, data implant? Is it internet of things? What is it all about? Well, I think you can break it down like this. So in order for a business to become a cognitive business, the way we're talking to clients about it is, first of all, there's the extreme that is really in a lot of the commercials, which is to build a cognitive system, a branded system that's Watson. And that's really building a capability that can be a physician's assistant and education assistant, a system that you train. You take four months to train it around specific corpuses of data. And so we talk to clients about that but probably maybe 10% of the market will be interested in really building that kind of a system. It takes some time, it's more expensive and you really need to have the business application. It'll transform industries. It'll transform enterprises and it's an investment. We also talk to clients all the way on the other side, which is kind of from the bottom up, about building cognitive apps. You can do that now. You can do that in days, weeks and months. And it's a way that businesses can get started and really infuse innovation into their business. So you heard it this morning on the keynote. We talked about Watson Tone, Watson Vision, Watson Emotion. We have Watson Trend. We have these APIs and these APIs can be infused into a new application. It can be infused into an existing client's business application or into an offering or a service. And so there's three paths we talk about. Build apps with cognitive, infuse cognitive into your business process or pull down a SaaS offering that we have on our marketplace that has cognitive capabilities or all the way on this side, which is I want to build a cognitive system. I'm in an industry like a medical industry and we have some examples where we've been working with clients on building a physician support. So a couple of questions I have for you. So there's a new role, VP Marketing of Cognitive. Now is that a sort of across all the sort of cognitive businesses at IBM? Are you sort of focused on one particular aspect of business? Our chairman in January announced IBM really being focused, her vision for the business. And when she started to talk about cognitive business and cognitive computing. She said we're a cognitive business solutions company and we're a cloud platform company. So those are the two major areas of where innovation is continuing to be brought for IBM. So my mission is in corporate right now and I'm responsible for taking the cognitive capabilities, the messaging that exists, all the beautiful launch materials and pulling them through working with the units so that we introduce cognition and cognitive into all the units within IBM. Now you know we have Watson Health, Watson IoT and the Watson unit. Of course that's the core of their business. But the other units all are either building roadmaps for introducing cognitive. It's internal transformation into infusing these capabilities, taking what was launched and infusing them through all the different units. So let's pick up on that sort of transformation thing. So when I think of the broad category of information management over the years, it's information's generally been a liability. Oh, if somebody finds this smoking gun email, I'm in big trouble, how do I get rid of it? Oh, we'll help you categorize it. And then they say, okay, well, maybe we can extract value out of that. And the problem was, it was just too much data for humans to extract value. So now we enter this cognitive era and you're providing this new super powerful tooling that allows me to actually get value out of that corpus of data that this is too much for me to handle. So, and you gave a couple of examples. One was a big chewy vision, heavy lift, maybe 10% of the people are actually going to go build that out now. Maybe eventually people get there. And the second was the bottoms up building apps. So how are beyond that sort of, let's peel the onion on that. How are companies getting started on cognitive? Are they really just primarily building apps and what are they working towards? How are they changing organizationally? I wonder if you could give us some color on it. But it's a combination of things. So Alphamotus was on stage this morning. They're a great example. So they're a financial service company. They built cognition. Robo stock picking. Right, and what they're doing is they're learning, they're understanding those patterns, right? And they're building that capability in so that they can predict or steer in a different direction. That's the future of that business, isn't it? So that's a perfect example. They built an app or they introduced cognitive into an app that they had built with our cloud technology. And then on the other end of the spectrum, I think that a good example would be SoftBank. SoftBank is a bank. You probably saw some of the CES examples when our chairman and a number of people presented there. It's where we have the robot pepper and that robot is a concierge. That's basically building a cognitive system. So clients started different places, but they're all after either competitive, advantage, innovation. They are able to really leverage cognitive to do discovery. And your point about data is really important. The data that people possess today, most CXOs don't feel that they're getting the value out of it. And that's the data you have behind your firewall. Think about the data that's coming, all of the data from news, video, unstructured data, and then you take the weather data and all of the other things, the data from sensors and IoT. This explosion of data makes it impossible for people to, if they're only getting 10% value out of the data they possess and that they can actually process and leverage insights from, can you see what's happening in the tsunami that's coming? The only way they can really capture and gain insight from all of that data and also triangulate it to get insights that they could never get by only looking through one dimension is by leveraging cognitive, cloud and cognitive. It changes the analytics game. We were talking on CrowdChat with some of the thought leaders within IBM and the BIP influencers just this last week around that regression analysis and these old school techniques are actually obsolete now because you don't need to throw away all the data. You don't need to throw away the outliers. The outliers are sometimes the new data that you want to double down on. That may be where the insight is and we've been missing it. So the other thing that I think is pretty important is the systems today are deterministic systems. They're programmed by people with a specific outcome involved. A cognitive system is a probabilistic system. It deals with hypotheses. So the aperture is wide open to discovery way beyond what someone would have programmed a system to do in the past. So that's a big part of the difference between analytics are still very much on. That's why you say unstructured is key because that's the lubricant to get everything going in that engine, if you will. Because you need to have that blending in. Well, you take behavioral and sentiment insights and you couple it with data and you're looking at a different outcome. You got to ask you a trick question, not trick question but since you always have great color commentary on theCUBE. What is the coolest thing you've seen from cognition standpoint? You know, you're across the different groups. You're internally transforming, which by the way I think is great for you guys to do because then you can go to your customers and say, hey, we're doing it too, you should do it. But you see a lot of stuff. What's the coolest thing that you've seen? So first of all, I think the coolest thing that I've seen and I had, I was the fortunate enough to present in November with them on stage in Japan. I love the whole soft bank example with Pepper the robot. I am fascinated by that. And I think that it's just, it's the emotional relationship that people are able to have with that form factor and the psychology that went into building that to me is fascinating. So that's- Creative too. I mean, you look at these creative opportunities. I mean, you're seeing all kinds of new creation coming out of this. It's not so much, oh, build the factory, build the product, people are doing things. Well, and they impact society. I mean, they're doing that too in some cases so that they can deal with an aging community. And that's a way of also leveraging that type of technology in kind of a personal man and machine or human and machine interaction. It's a lot about that. So I wanted to take sort of the two examples. Alpha Modus, they're completely repricing financial services. The impact of Pepper is really, that's the first use case. Is that right? Is to help the aging population? Right. Is it starting in Japan or is it- Yes. That is in Japan. And so this little Pepper's gonna be my assistant. Well, right now Pepper's also, he's a concierge, he or she is a concierge, I'm not really sure whether he or she, but, and then the other cool thing we're doing is we're going through, we built an internal kind of Kickstarter program called Cognitive Build, and we're taking 380,000 employees through our own immersion, where they're gonna ideate where there's gonna be a hackathon and a Kickstarter process, internal, so that we can identify new applications, how to infuse Cognitive into our portfolio, and then also how to- They actually get real cash or is it more budget? No, we're gonna, they're gonna be real money behind the end projects. And they're gonna go outside the company to develop it, or is it inside or- No, it's internal. Oh, okay. Yeah. That's exciting. Because you have a good marketing answer for this, and so I want to sort of, because I'm very excited about Watson. Right, I mean, I see IBM pouring billions of dollars into Watson. I go out into the marketplaces and listen, that's real innovation. People go, wow, no, no, no, Google, Facebook, they have the real innovation. How do you respond to that? Well, you know, we are highly recognized for how unique the technology is with Watson. There are a lot of machine learning, Siri type capabilities out there, but that's not understanding, that's not reasoning and ongoing learning. You know, machine learning is one capability, but the sophistication of our Watson technology and the impact that that is already having on industries and healthcare and education is way beyond anything that's happening out there. So I think that we have an opportunity here. First of all, a lot of people are jumping into the space. If you look at the competition, whether it's Google, I think Salesforce just made an announcement about purchasing AI technology and machine learning technology, it's happening every single day. So people are really ramping up. Watson is very different. That is something that we built, took years to build and very, very highly sophisticated and with a level of human interaction that is unprecedented. But there's a lot of people out there who are racing to get to the same endpoint because they see the opportunity. Well, I think too, the use cases that you have in place now, I mean, it took a while. I remember when we first saw the grand challenge, it was like, okay, now what? And you guys are probably doing a lot of that internally. But you've poured so much effort, development, technology, customer interactions, and now the use cases are starting to emerge. They're really forming. So, you know, we'll be starting to talk about Airbus. You know, we've got a number of clients there that are already leveraging cognitive technology and we've got a number of use cases now. So it's not a few. In fact, we're working on, you know, this hero storytelling approach with Cognitive. I'll talk about it this afternoon at our lightning, the lightning talks that we're having. But we've got, you know, 30, 40, 50 really excellent stories that we're going to start to tell through social media. It's exciting. So, talk about this hero concept. Can you explain a little bit further on what that's about? Well, it really takes the customer example and instead of it being like a talking head, you really interview throughout the whole process and really understand what is the motivation of the client, of the user and how does this technology actually change the lives of people? So, it goes way beyond being a reference. And we do, we do- You get immersed into the use case and the person. You get immersed in the story, the use case, the people that are affected by it and then we can tell back stories. I call them derivative stories about, well, what was a developer thinking? What motivated them to create this application or this solution? And so you get ongoing a drum beat of story, different facets of the story. So, we're really accelerating our hero's storytelling capabilities with Cognitive. So, what's the customer imperative? You sit down with the customer and say, hey, I'm really interested in this stuff. I'm not really sure how to apply it. Where do I start? Well, that's where the three paths come in. Are you just kind of dipping your toe in the water and you want to develop an app? Because you can do that immediately. And I think it's really important because when you see Bob Dylan and Watson singing on TV, you think, oh my God, you know, that's not me. Or people say all the time, I'm not curing cancer. You don't have to. You can get started by building an application and then you really understand what it's about and that grows. So, or you can pull down a SaaS service on our marketplace. So, those are ways in which you can get started today and tomorrow and then some people are really thinking big and they're going to get started and it's a multiple year journey. Well, they're going to take the first step. I mean, you can think big now. You have the data, you have the reasoning capability, the cognition as you say. But you can start small. You can take a baby step, it doesn't matter. That's right. If you don't take that step, you'll never get there. I think that's the most important message. So, do I start with my data? Is that the starting point? Absolutely. You definitely need to start with your data and then also to identify the data that is out there. You know, the data space, you'll see us doing a lot of acquisition in data models like the weather company. The data space is really big and that's what's really going to accelerate the capabilities and the value to clients because they would never be able to address that data on their own. They wouldn't be able to access it. They wouldn't be able to process it and get insight from it. We got to do some real time consulting. We need your help because you're awesome. We'd love to interview you because you just get great stories. We have a lot of data. A lot, a lot of energy. Help us. How does theCUBE get our own cognition engine? What do we do? So, we have a lot of data. We get the Twitter stuff. What do we do? How can theCUBE get infused with more Watson? What should we do? Well, you should look at all that data and say what would make your business model different? What, you know, where is the innovation? Where could the innovation be? And see what you can do with that data to actually maybe even determine the personality of the different people. So, if you're Watson, what would you say to me and Dave? If you'd look at all of our interviews, what would the profile us as? You know, I would take, well, I don't know about your own personality profile, but we can take that offline. I think we can do that on the side. Watson would say. But you can probably do take all the data and take all of your interviews and understand exactly what makes a compelling interview. The personality traits, you know, do something like tone analyzer and you'd get insights from it that you can actually feedback to the people coming in and doing interviews. When you do this, this, and this, you know, the interview really spikes. Right, and help people discover the real nuggets, the gold nuggets that are in these interviews. The insights, exactly. And then do something with them. And he certainly will have the beacon technology and say, John, you were out late last. I can tell by your tone. Exactly. That's where you can get into a little bit of trouble of your time. It's having a little sluggish right now. I would love to interview Watson. That would be a great cube segment to interview Watson. Well, Nancy, thanks so much for coming on. Well, thank you for having me. All the videos will be on SiliconANGLE.tv. Of course, Wednesday is our Women in Wednesday podcast, featured guests of the week. Go to SiliconANGLE.tv and go to Twitter and search hashtag cube gems. That's hashtag cube gems, G-E-M-S. You will see all the short sound bites, the snackable content. Nancy's video's up there right now. Variety of cube gems, certainly, from this interview. Thanks so much for spending the time with us again. Thank you. Good to see you guys. Nancy Pearson, vice president of Cognitive here at IBM. And we're trying to get our cognition on here in the cube. We'll be right back for it to the short break.