 Let me check. From Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by IBM. Okay, welcome back everyone. Day two, we are here live in Las Vegas for IBM InterConnect. This is SiliconANGLES, the CUBE coverage of IBM's cloud event. The CEO, Janine Rometti, was just on stage. We're kicking off wall-to-wall coverage for three days. I'm John Furrier with my co-host, Dave Vellante here for all three days. And our next guest is Andy Lin, who's the VP of strategy at Mark III Systems, a 20-plus-year IBM Platinum partner, doing some real cutting-edge work with Cognitive, as Janine Rometti said, Cognitive to the Core as IBM's core strategy. Data first, Enterprise Strong is kind of the buzzwords. Andy, welcome to theCUBE. Appreciate you coming on. Thanks for having me. So obviously, Enterprise Strong, it's kind of a whole other conversation that we can go deep on, but Data First and Cognitive to the Core is really kind of the things that you guys are really getting into, all kinds of data types, and automating it and making it almost frictionless to move insights out. So take a minute to explain what Mark III's doing and what your role is with the company. Sure, absolutely. So I'm vice president of strategy at Mark III, so I work sort of across all our initiatives, especially areas that are emerging. Just a little bit about Mark III, just historically for background purposes. So we're a 22-year IBM Platinum partner, as you pointed out. We actually started out in the mid-90s actually doing IT infrastructure around the IBM stack at that time. So we sort of been with IBM over the last 20 years since the beginning. We've sort of grown up throughout the stack as IBM's evolved over the last two decades. About two and a half years ago, we started a digital development unit called BlueCasm. And what BlueCasm does is it basically builds open digital and cognitive platforms on the IBM cloud that are around a lot of the services you pointed out. And we basically designed it based on use cases that the ecosystem and our clients talk about. And to give you a couple examples, one of the big ones that we're seeing a lot of interest around is called Video Recon. Video Recon is a video analytics platform that's API enabled and open at its core. So regardless of where the video comes from, if it's a content management system, if it's a camera, we're able to basically take in that video, basically watch and listen to the video using Watson and some elements of our own intellectual property, and then basically return insights based on what it sees and hears along with timestamps back to the user to actually take action. I love the name BlueCasm. It brings up, you know, Jeffrey Moore is crossing the chasm, Blue IBM is big blue. So, you know, it's nice, clever play, the BlueCasm opportunity. So in your mind for people watching, squint through some of the trends and extract out where you see these opportunities because you're talking about new opportunities are emerging because of cloud horsepower and compute and storage and all the greatness of cloud. And you got real-time analytics kind of really hitting the mainstream. That's highlighted by Internet of Things. You can't go anywhere these days out here about autonomous vehicles, industrial Internet of Things, AI. Mark Bandyoff was saying, you know, we've seen the movies like Terminator and we've all dreamed about AI. So we can kind of get excited about the prospects. So, but this chasm you're talking about, this is where these things that were ungettable before, unreachable new things, what are some of those things that you guys are doing in that chasm? Yeah, so I think some of the things that we're doing are basically enabling, like I'll use video recart as example, right? We're enabling a client to be able to get new insights using basically computer vision, but in an open and accessible way than they've never had been able to do before. Vision itself I don't think is new or revolutionary. You know, a lot of folks are doing it self-driving cars, et cetera, but I think what is new is being able to make it open and easily accessible to the normal enterprise and the normal service provider. Up to now it's been, you know, you've really had to have your own team of really, really deep AI developers or PhDs to be able to produce it for your own platform. What we're trying to do is basically democratize that. So, to give you an example, some use cases that we're sort of working on today, the ability to do things like read meters and gauges as an example with a camera. That way you can avoid a situation where somebody has to walk around all the time, you know, look at different things. It could be dangerous. There could be issues actually looking at what you see from a metering perspective or to be able to, for instance, for in the media entertainment industry or the video production industry, be able to do things like identify shot type to be able to more quickly allow our enterprise users in that particular space to be able to create video content quickly. And the underlying theme with all this, I think, is really about speed and mark and how quickly can you iterate and please whatever your customer is in that particular space that you're in. So, the video recon, so your videos are searchable, essentially. So, what do you do? Use Watson natural language processing to sort of translate them. And now, so of course, you know, NLP is maybe, I don't know, 75, 80% accurate. How do you close that gap? Yeah, so, video recon does both visual and audio. So, the audio portion, you are correct. There is some degree of trade-off and accuracy relative to what I think the average human can do today. Assuming the human is focused and able to really tag these videos accurately. So, we are able to train it based on things like proper words and things that are enterprise focused because I know there are a lot of different ways that I think you can maybe attack this today from a video analytics perspective, but we're focused primarily just on the enterprise solving business problems with video analytics. So, you know, taking advantage of as Watson improves because we do use speech-to-text at its core on the audio perspective, applying some of our own techniques to basically improve the accuracy of certain words that matter most of the enterprise. One of the things we've noticed is it's entirely a collaborative relationship with our enterprise clients, but really partners, because what works well for one may not work well for another. The one thing about Cognitive is it really depends on the end user as to if this is a good idea or not, or if this will work for their use case just based on error as you pointed out. So, to your point, you're identifying enterprise use cases and then tuning the system, building solutions essentially for those use cases. Absolutely. You said 22-year IBM Platinum partner, so he obviously started well before this so-called digital transformation. Yes. You see digital transformation as revolutionary or is it more of an evolution of your business? I would definitely say it's an evolution. I think a lot of the industry buzzwords out there are all around transformation or transition, but for us it's been completely additive. At the end of the day, we're just doing what our clients want, and we're still continuing the core part of our business around modernizing and optimizing IT infrastructure, the tech stacks in the data center, also infrastructure service in the cloud, also up through the middleware is still really as strong as ever. And in fact, that business has actually been very much reinforced by some of these capabilities that we brought in on the digital development side, because at the end of the day, clients may have a digital unit and they may have IT, but they're really viewed sort of all in the same. A lot of people try to put them in two different buckets by modal or whatever you want to use, but inevitably, clients just see a business problem they want to address, and they're saying, how can I address it the fastest and the most effectively as relative to what their stakeholders want? And we just realized early on that we had to have that development capability be able to build platforms, but also guide our clients. If they don't want one of our platforms, if they don't want video recon or cognitive call center platform, that's perfectly fine. We're more than happy to guide them on how to build something similar for their developers with our developers relative to their tech stack, hopefully on the IBM Cloud. Andy, one of the things you're pointing out that I think is worth highlighting is the digital transformation buzzword, which has been around for a few years now, really is in mainstream right now. People are really working hard to figure this out. We're seeing the disruption on the business model side. You mentioned speed and time to market. That's agility. That's not just a technical development term anymore. It's actually business model. It's business related. But there's two axes of thing going on. There's the under the hood heavy lifting stuff that goes on around getting stuff digitally to work. That's IT, security, and you know, Ginny Ramay talks about a lot on stage. That's being enterprise-grade or enterprise-strong. The other one is this digitization of the real world, right? So that's creative. That requires insights. That requires kind of a different, it's actually probably maybe more fun for some people, but I mean to me it's not who your profile is, but you have kind of two spectrums. Cool and relevant, exciting and intoxicating, creative, user experience driven. You mentioned reading meters. That's the analog world. That's actually space. That's the world. You got the sky, you got the meter, you got physical impressions. This is the digitization of our world. What's your perspective? How do you talk to customers when they say, hey, I want to digitize my business? How does it go? What do you say? I mean, do you break it down into those axes? Do you go, do they see it that way? Can you share some color on this digital transformation of digitizing business? Yeah, so I mean it really depends on, I think normally it has to do with interacting with some other stakeholders in a certain way. I think from our perspective, it really is about how they want to interface, and most of the time you pointed out speed. Speed I think is the number one reason why people are doing the digital transformation. It's not really about cost or these other factors. How quickly can I adjust my business model so I can win in the marketplace? And I think I pointed this earlier, but IOT is huge now. It covers what I call three of the five senses in my mind, it covers basically touch, smell, and taste in many ways. And for us, I think we're basically trying to help them even get beyond IOT with video. Video really covers site and hearing as well. It covers all the five senses. And then you take that and figure out how do I digitize that experience and be able to allow you to interact with your stakeholders, whether it be your customers or suppliers or your partners out in the marketplace. And then based on that, we'll take these building blocks on how we extend the experience and work with them on the specific use case. You got to ingest the data, which is the images or data coming in. Then you got to prep it and make it available for insights and then produce them really fast. That's hard. It's not trivial. No, it is not. It's not a trivial problem. Yeah, absolutely. I think there's a lot of opportunity here in the space over the next two to five years, but you're absolutely right. I mean, it is a challenge. And I want to get your thoughts too. And if you can share your reaction to some of the trends around machine learning, for instance, that's really kind of fueling this democratization you mentioned and the old days was really hard. There's kind of a black art to machine learning or unique specialties and even data science at one level was really, really hard. Now you have common people doing things with visualization. What's the same with machine learning? I mean, you've got more data sets coming in. Do you see that trend relevant to what you guys are working on than blue chasm? Yeah, absolutely. I think at the core of it, and this wasn't our plan initially three years ago, we didn't realize that this would happen, but every single one of the platforms or prototypes or apps we built, they all incorporate some degree of machine learning, deep learning within its core. And this is primarily just driven by, I think, to give a client a unique platform or a unique service on the market, because much of the base digitization, I mean, Jenny likes to talk a lot about the key to differentiating yourself in the digital world is being cognitive. And we've seen this really play out in practice. And I think what's changed, as you pointed out, is that it's easily accessible now to sort of the common man, as I put it. In years past, you really had to have people that are highly specialized. You build your own product, but now through open source. This building blocks out there, you can just take it up to such library and say, hey, and then tweak the machine learning. Absolutely, and the ramp up time has come down dramatically, even for our developers, just watching them work. I mean, the prototype to video recon was built over the course of the weekend by one of our developers. He just came in one Monday and said, is this interesting? Exactly, and we were like, yes, I think this is interesting. Well, this is the whole inspiration thing that I talk about the creativity. I mean, this is the two accesses, right? You try to do that in the old days. I got to get a server provision. I'm done, I'm going to go have a beer, whatever. I mean, there's almost an abandonment going on. We talked to Indiegogo yesterday about how they're funding companies. You have this new creative action. So you guys are seeing that. Any other examples you can share in terms of color around this kind of innovation? Yeah, so we, at Blue Chasm, we try to let our developers sort of have free reign over what they like to create. So video recon was spawned literally by on a side project, as with a lot of companies. It was a platform that sort of evolved into a commercial product, almost by accident, right? And we've had others that have been anchored by what clients have done, but around the Cognitive Call Center, which basically takes phone calls that are recorded and then basically transcribes and make them easily searchable for audit reasons, training reasons, et cetera. Same kind of idea. We built things around like cognitive drones. A lot of folks are trying to do things with drones. Drones themselves aren't really novel anymore, but being able to utilize them to collect data in unique ways. I think that industry is definitely evolving. We've built other things like what I call the Minority Report Board after the scene in the movie where the board sort of looks at you and then based on what it sees of you, of different data points, it shows you an ad or shows you some piece of visual content to allow you to interact. I mean, these are examples. We have others, but we've just seen, like in this organization, if we allow creativity to sort of have free reign, we're able to sort of bring it back in along with some of the strengths of CoreMark 3 about being able to use it. I mean, cognitive is really interesting. It's a programmatic approach to life, and if you think about it, it's like if you have this collective intelligence with the data, you can offer an augmented reality experience to anybody now based upon what you're doing. Absolutely. So I mean, I think that the toughest part, I think right now is figuring out which of the opportunities to pursue because there are so many out there and everyone has some interest in some degree. You have to figure out how to prioritize about which of the ones you want to address first and in what order, because what we've noticed is that a lot of these are building blocks that lead to other greater and greater platform concepts and part of the challenge is figuring out what order you want to actually build these into. And through microservices, through containerization, all these awesome evolutions as far as like with cloud infrastructure technology, you're really able to piece together these pieces to build amazing things. The cloud native stuff is booming right now. It's really fun to watch microservices, Kubernetes, this orchestration, composability is just kicking ass. And all your clients are basically becoming software companies. They're taking your services and building out their own SaaS capabilities. Right, without a doubt. I mean, the cloud native container revolution has been significant for us. I mean, we added the audio component to Video Recon based on some of the work we've been doing on the call center side. It was almost by accident and we were able to really put them together in a day because we were able to basically easily compose the overall platform at that time or the prototype of the platform at that time just by linking together those services. So we see this as a pattern. Andy, thanks for coming on theCUBE. Really appreciate it in the quick 30 seconds. What are you doing here at the show? What are you guys talking about? What's some of the activity? Coolest thing you're seeing? Share some insight, what's going on here in Las Vegas? Share some perspective. Yeah, absolutely. So we have a booth here in Vegas. We're demoing some of the platforms we talked about, Video Recon Cognitive Call Center. We're at booth 687, which is toward the center back to the Expo Center. We have four breakouts that we'll be doing as well, talking about some of these concepts, as well as some of our projects that involve modernization of the data center as well. So the true, what I call IBM full stack. And for the folks that aren't here watching, is there a website address? Where can they go to get more information? Yeah, absolutely. You can go to mark3sys, M-A-R-K-I-S-Y-S.com, which is our website. If you want to learn a little bit more about Video Recon, you can go to videorecons.io. We have a very simple demo page, but if you're interested in learning more or you want to explore if we can accommodate your specific use case, please feel free to reach out to me. Also mark3systems, M-A-R-K-I-I-S-Y-Sys. At Twitter as well. And I can- Well you know, we're going to follow up with you. We're going to get all of our CUBE videos into the cognitive era. You'll be seeing us pinging you online for that. Love the Video Recon. Just great blue cats, so great, great initiative. Congratulations on that. Thank you. Thanks for coming on. This is theCUBE, live here in Las Vegas, day two of coverage, Wall-to-Wall. I'm John Furrier with Dave Vellante. Stay with us. More great interviews after this short break. You