Hi everybody, this is Kate Brown, executive producer of the Making Data Simple podcast. As we transition into the new year, we're going to do a couple of repeats. This week, part one is an interview that Al conducted with Rob Thomas on business success. Enjoy. You're listening to Making Data Simple, where we make the world of data effortless, relevant, and yes, even fun.
So welcome to the Making Data Simple podcast. This is Al Martin speaking. Thanks to all our listeners. Our listenership continues to grow, and more than anything, I started this for fun, so that just makes it more fun. You can find us on IBM's Big Data Hub, on YouTube, on SoundCloud, and you can also get us on iTunes, so we pretty much got all the bases covered. Today I've got Rob Thomas, General Manager of Data and AI at IBM, and we're going to get into some great topics today. Hey Rob, how you doing?
Al, thanks for having me. Congratulations on the podcast. I have been following it. You have an amazing audience and a lot of great people on here talking about a variety of topics, so great to see.
Thank you, thank you so much for joining us. We have fun with it. So look, before we get started, still working out? You're still reading excessively? I spend as much time possible reading, absolutely love reading. Try to exercise whenever I can. You know, the start of the year has been a heavy start, a lot of travel, so that always moves things around a bit, but overall good. Yes on both is the short answer. So on the working out piece, what do you think you get, four days a week at least?
I probably get five days a week.
Mix it up, some weights, some running, some biking. I'm thinking about possibly trying to do another marathon later this year, so if I can stay healthy I might do that, which would have me do more running. But yeah, I'd probably get five days.
That's good. Are you doing the Peloton?
I am. I've got the Peloton bike, and for some reason we bought the Peloton tread, which is their treadmill. It's actually quite good.
So is this for you or is this for your wife or for both of you? You guys really use it extensively?
We do, yeah. We use both of them, so yeah, it's both of us. So we've got a working out family. My older son plays football, so he's got to get in shape, so he'll probably start using some as well.
You don't want to get him too thin. He's got to bulk up.
All right, and lastly, any new books that you're writing that are on the way that we should look out for?
Not yet. I have a desire to do a book, which probably won't be a business topic. I just realized last year that I finally got into the age where I now have nephews and nieces, and eventually my children that are getting to graduation of high school and onto other things. So I've been pondering a book that would be relevant to a high school graduate or a college graduate. So something that's a little less of a period piece like a business thing, to something that would have hopefully longer lasting relevance. So I'm thinking about something for nieces and nephews and my children, but more to think about and do on that.
Nice, very nice. All right, well, so this interview I think is going to be good timing because we're well into 2019. IBM recently finished its Think conference, and that's where you get to hear about future innovation from the chairman, Arvin Krishna, who's the SVP of Cloud and Cognitive. We even heard from Joe Montana and Tony Hawk, so we heard from Rob and so you're in good company with Joe Montana and Tony Hawk. So I want to look back at this conference, but the first question I have: I know you changed your focus or your title at least from analytics to data and AI. Can you say a few words about that?
So think about it in the market. I'd like to say data and AI are two sides of the same coin. There was this MIT study about a year and a half ago that said 80% of AI projects fail because of incomplete data or data that can't be found or put to work. We did decide to combine those two units in IBM, so what was our data business and our AI business became one unit as data and AI. It gives us a lot of synergy in product strategy, the investments that we're making, how we go to market. I think it solves the whole lifecycle of problems that clients face, from help me find the data, help me understand the data, help me get new outcomes, build new business models with AI. So it seems like a good decision, and client response has certainly been positive. We often talk about data being the world's new oil. I don't actually get tired of that analogy, and given the amount of data we have right now, we're going to have to use AI or some form of machine learning to get through it all. I know if you feel this way, I got to believe you feel this way, but I don't know if there's a better place to be really. There's no better place to be, that is clear. If you think about it from an IBM perspective, what became clear at Think, I think to everybody, is IBM is anchoring the company strategy on two things: one is multicloud hybrid cloud, the other one is data and AI. I've always believed for anybody in their career, you always want to be where the tide is rising, meaning where the focus is, where is the tip of the company strategy, how is the company aligning resources and investments for the future. There's two places for that: it's multicloud and it's data and AI. So I don't think there's a better place to be. When you think externally, you look outside of IBM, what's the number one thing that every board is talking about, every CEO is talking about, every company is trying to figure out? It's how do I put data and AI to work to drive competitive advantage. So I'm not sure there's a better place to be.
I concur. I agree with you. So let's jump into the IBM Think Conference for a minute, which is our annual event for those of you that don't know. We had it in San Francisco this year, a little bit damp, but I thought the venue was pretty good. This is where we gather our clients, partners, thought leaders, talk about innovations both now and in the future. From your perspective, what do you see as the biggest announcement that came out of Think?
We announced Watson Anywhere, which I think is a huge deal. A guy named Ron Miller, who I know writes for TechCrunch, one of the articles he wrote after it was he said IBM's decision to put Watson anywhere, making it available any cloud, he said this is in his mind akin to when Microsoft decided to make Office available on iOS. Where they separated themselves from the Windows shackle, IBM's decision to make really our crown jewels, everything that we're doing with AI and Watson, available anywhere. He compared the two and I think it's an apropos comparison. It's certainly what clients have been asking about, and I think the decision to do that is a critical one that will not only help IBM but it will also help our clients a lot. The thesis was very simple: it's very hard if every data or AI project starts with 'all right, I've got to move terabytes or petabytes of data somewhere else to where the AI is.' That's a problem. We're enabling the AI to come to the data, whether that's on private cloud, on premise, on any public cloud. I think that's really going to change what's possible for our clients and partners by doing that.
