 Live from Las Vegas, it's theCUBE. Covering InterConnect 2017, brought to you by IBM. Okay, welcome back everyone. We're live in Las Vegas for theCUBE's coverage of InterConnect 2017. This is three days of wall-to-wall coverage. Stay with us for the entire event. This is day two. I'm John Furrier with my co-host Dave Vellante and our guest is Willy Tejada, who's the IBM Chief Developer Advocate at IBM. Welcome to theCUBE. Thanks you guys, I'm really pleased to be here. So I'd love to have you on because all we do is talk about developers and what's in it for them, who's doing what, who's got the better cloud, who's enterprise-ready, all that good stuff, commentating. But I love Jeanne Rometti's conversation today because we're just at Google Next, cover Amazon events, all the cloud events. And the thing that's been on our agenda, and we've been really looking at this, is cloud readiness in the enterprise. And this is really kind of fundamental what she was talking about. Enterprise strong, data-first, cognitive to the core, which kind of is there are three pillars, but this is where the action is right now. Yeah, you know, for developers that's exactly true. You know, what she outlined is really this idea, basically there's three kind of core architectures, right? It's cloud, number one, followed by data later on top of that, and essentially AI or cognitive on top. And what that means actually for the developer communities is that there's a new set of skill sets that are probably moving faster than we ever seen before, right? And a lot of it's actually driven by the explosion of data. And so one of the things that we think that there's going to be a huge shortage of, and there is a huge shortage of, is data scientists and cognitive developers. Because in those layers, what we've seen is that more and more you operate on a data-first model. And by just that definition, what you need to know about data is pushing towards a practitioner level of data scientists. And the reality is that we think that that type of core skill set's going to be needed across all of the developer community. So take a minute to describe what, and then define a cognitive developer. I mean, what that, and the nuance behind it, because obviously the developers are doing really cool creative things. And then you've got the heart under the hood, production workloads and IT. So where's the cognitive developer fit in those spectrums and what is the core definition from your standpoint? Yeah, you know, the cognitive developer really is a person who's actually participating in actually the generation of a system that's fully cognitive. So, you know, adding a cognitive feature is one thing, but actually building a full cognitive system is something different. You know, if I use a comparison, think about how some of these roles and big data came about. You know, big data came, but we didn't have things like a data scientist, we didn't have a data engineer, and it kind of came after the fact, the roles that were actually defined. Now we're onto these new cognitive systems where everything from you have to train the system, you have to have explicit knowledge of what the APIs actually do, and you have to have infrastructure that actually curates data that continues this training along those lines. So, you know, the cognitive developer is really one that's participating in that particular ecosystem. Now what's really important though about that is that they are usually programming in the language that they're usually programming in, whether it be Java, data scientists are using R, or they're using Python, but the reality is that a cognitive developer is that one that's applying those cognitive properties to their system that they're developing. So this is interesting. You mentioned the cognitive development of new tools and stuff, but there's some really good trends out there that is the wind at the back of the developer right now. Cloud Native is a booming trend that's actually phenomenal. You're seeing container madness continue. You've got microservices, all with the Kubernetes under the hood. So there's some cool, exciting things in the trend lines. Can you unpack that for us, and what this means to the developers? And how does it impact their world? I mean, we hear composability and Lego blocks, and most of us know that API economy's here, but now you've got these new tailwinds, these new trends. Let's see, what are they, add to that, what's the impact of the developer? We talked about a new container service, basically, based on Kubernetes that's allowing us to actually build some tremendous scale, actually, and really simplify that type of development, actually, when you're doing native cloud development. You know, probably the most important things for developers is just the accessibility of all these pieces. Of course, it's driven by open source, but you know, if you want to learn these technologies, if you want to participate in experiment with these technologies, they've never been more available than they actually are today. So, if I may, so Tanmay is a good example of a cognitive developer, right? Absolutely. He's all cloud native, he's all cognitive. Nice shout out from the CEO today. That was awesome, and he's also an algorithmist, you know, self-declared algorithmist. I can't even say that. Okay, so here's Tanmay, he's never going to know anything else, right? But so, now, if you're a sort of mainstream developer, what do you do? You know, where do you get the skills? What do you recommend that that individual does, and how do they get up to ramp? So, you know, lots of times, you know, as you know, the developer's learnings is not like kind of a linear pattern, right? You know, they go to blogs, basically, they go and pull basically a library for them, the environment they're in. They figure it out. Just kind of mess around in it, along those lines. They go to a meetup or a hack from that standpoint that's based on cognitive development. And, you know, so they should just go about what they normally do, kind of along those lines. And then, you know, and then I think basically there's an advancement, because ultimately, we're publishing these things called journeys, which are really kind of use cases in a cognitive-based environment. So, as an example, we might publish a journey on a cognitive retail chatbot, and it will combine a variety of these microservices that Watson's actually built on, but give them exploration into how they use a chatbot, how they use a service called Discovery, and how they use persistence, basically, so that essentially they can learn from the data that they actually have. And then, ultimately, if they want to do is to actually get deeper into it, there's organizations that we partner with where we give them cognitive curriculum that allows them to experience these pieces, like TopCoder. You can go on and do a cognitive challenge right on TopCoder, or you can go to a cognitive course designed by Galvanize, one of our partners in relation to skills development. So, it's interesting about that journey. So, when you think about big data, we're talking about big data before, the sort of point at which a company like IBM would engage in that journey is somebody who's exploring and maybe kicking the tires a little bit, or somebody who had a data warehouse that was killing them. Where is, obviously, there's a part of that in the cognitive world, which is experimental. Is there another sort of analog to the data warehouse sort of disaffection, if you will? Yeah, now, one of the things that we spend a lot of time on is that every organization that's going to build a cognitive system is looking for cognitive developers and data scientists. So, essentially, mess around with... Across all industries, by the way, cyber security to... Absolutely. So, one of the key pieces is what kind of tools do you actually give that data scientist to mess around with that data set? We provide something called a data science experience. And the idea there is essentially, how do you give them an environment that allows them, essentially, to look into the data very quickly, actually have these data sets, and really kind of explore the data in a way that they never were capable of actually doing that. Those are the types of things that we're actually trying to do that a data scientist, so that you can bridge over if you're a data engineer or you're a business analyst and you're looking to actually get into data science, you can actually play with some of these big data sets and actually explore with things you can do. Well, I couldn't agree with you more on the whole how developers learn. It's really not a courseware online in the physical classroom. Yeah, it may be there if they're in college, but it's the practitioner world of nonlinear learning through experience. And these journeys are super valuable. And just for a tactical question, where do they find the journeys or URL? What you'll find basically in, come April 1st, we're going to launch a number of them on developer.ibm.com slash accelerate. So they'll be focused on several different categories. Number one will be just developing in the cloud, cloud native. What's the journeys basically that, they're kind of like common setups that you actually need. We'll do next ones on cognitive and analytics where you pull together a set of services along those lines. And as you heard Ginny talk about, it's really important that a cloud have knowledge about a domain or an industry. And so we'll create some journeys that are actually very industry specific. You know, we announced. Like they're like templates basically. They are. People jumpstarted not so much a reference implementation. Exactly. But you know, what it's all about is, you mentioned this nonlinear journey that kind of developers on to actually learn. You know, fundamentally they have a core thing that they're trying to actually get done with just, can you help me get my stuff done faster? Right. And fundamentally when you talk about cognitive or data science, we're trying to actually deliver them tool sets or examples that do that. So I now got to go to the next level with that question. Because first of all, it's awesome. Now, how do you intersect that with community? Because now that's super important because you might want to take a minute to just do a plug for IBM in terms of the open source goodness you guys are doing because you guys do a great job with open source. We just hosted a very large, what we believe is one of the largest open tech meetups right before basically Interconnect actually started and we had one of the ballroom's actually full. And you know, we talked about our nurse service. We had Jim Basic from the Linux foundation actually come. You know, he stated a stat which was really interesting in open source which IBM is a large contributor to, that I think the stat that he said was Linux basically as a project now, there's 10,800 new lines of code and 1,800 lines of code that are modified every day, right? And that's the community. It's only going to get faster if you think about like just the physical media like SSDs in memory with Spark. The kernel, the quantum Linux is going to evolve in a radical killer way and this is the beginning. And to your point about the community, you know, when you think about that advancement and the pace by which basically that kind of software is actually going to move, there's not one organization that can outpace that type of community in the way they actually do it. It doesn't matter what the services actually are. Well, the other interesting thing is the impact on humankind. You heard Benioff and Ginny talking about it this morning and they were both really emphasizing, you know, machine augmented, right? But it's like a Pac-Man device. I mean, there's so much, you know, human interaction that's being automated today. Yeah, absolutely. So, and I know IBM obviously a big believer in augmentation, but it's hard to predict what things humans are going to be do that machines can't do. Any insight on that? Yeah, you know, I think we use the word cognitive assisted. You know, so when you think about it, I'll give one example, let's say for example in the medical professional. So, you know, if you look at in that healthcare industry about 90% of the data in there is not like structured data. Right, it's all unstructured data. A lot of it is images. So if you take a look at someone basically that's in oncology work, taking a look at things like melanoma. You know, the amount of time, I think the data set said the amount of time he needed to watch or get trained on to look at all the new papers that were ever published was probably three weeks basically. You know, if he's thinking about that in a month. You know, the amount of time that that person actually allocates to actually keeping up with all these particular trade journals is a few hours a week. And so he's constantly behind. This is where something like a Watson enabled or a cognitive enabled type of application can help him actually keep up to date with all the new findings based on research papers in his particular field and do something like ingest millions of documents and understand them, but actually apply it to his work. So you know, what you find is that doctor is actually utilizing a cognitive assistant powered by Watson to help him do better diagnosis. Well, you're an advocate for the chief developer advocate for IBM. Talk about for the last couple of minutes we have, what's on your plan? We just saw the news yesterday, the $10 million investment to get education out there and bring this cognitive developer category and kind of lift that up and with Galvanize, which we've supported some of those signature moment events with theCUBE. Where are you going to be out in the field? What's some of your go-to-market activities? How are you going to do this? And then talk about the patterns you've seen in the developer makeup. Just over the past year, what's changed? What's notable? Yeah, so you know what, you know, some of the things that we're actually doing is number one, we're taking out very large presidents in probably nine cities around the world with a very big emphasis on building on data science and cognitive developers. So, you know, there's kind of the usual suspects, the San Francisco's, the New York's, the Tokyo's, the London's, some presidents in Sao Paulo. We're doing Beijing. We recently just basically announced a partnership of how we can actually get presidents actually there. And through that, we're looking actually to bring this presence basically into those communities. So this idea that we actually help actually put forth these journeys. But in many cases, actually be right in the presence of things. We have these, you know, in some cases, we have some programs that we're actually spinning up that are all about essentially how we actually do things like IOT Thursdays or cognitive Tuesdays where they can actually see, you know, actual experts in those particular areas and just come actually do office science. You throw back Thursdays and you hack on a mainframe? That's it, that's it, that's what we're actually looking at from that standpoint. So yeah, you know, a lot of the stuff basically is just actually getting to some of those folks in a very, very intimate way. And like you said, actually kind of populating these folks were kind of where they are. And really what that's all about is essentially actually getting the tools and tool sets in the communities that they find and the peer learning that they do. Which is really fun. We'll see you at some of the galvanized events you guys got going on. We'll certainly see you at DockerCon. We got a lot of cube lineups for the spring tour in the fall. Ton of developer activity. The cloud native stuff is really an intersection point with big data colliding with cloud. IoT and AI is just really this cognitive is just an accelerant for the cloud. It's like the perfect storm is a good opportunity. There's never been a more available time in terms of technology and the technology's never moved as fast. I was just saying at 10 May when he was on yesterday, I wish I could be 13 again, coding so much more fun now than it was when we were doing it. Well, great to have you on, Willie. Hey, thanks very much. Thanks for sharing. It was actually good visiting with you guys. Great insight. Insight from the chief developer advocate here at IBM. I'm John Furrier, Dave Vellante. Stay with us for more coverage. Great interviews all day today and tomorrow. Here live in Las Vegas. We'll be right back.