>>From the cube studios in Palo Alto in Boston. It's the cube covering the IBM thing brought to you by IBM. We're back and this is Dave Vellante and you're watching the cube and we're covering wall-to-wall the IBM 2020 I think digital experience. Rob Thomas is here. He's the senior vice president of clouds and data. Right. Warm rub. Always a pleasure to see you. I wish you were face to face, but Hey, we're doing the best we can. As you say, doing the best we can. Great to see you Dave. Hope family safe, healthy, happy as best you can be. Yeah. Ditto. You back out your Robin. Congratulations on on the new role, you and the cube. We've been riding this data wave for quite some time now. It's really been incredible. It really is. And last year I talked to you about how clients, we're slowly making progress on data strategy, starting to experiment with AI. >>We've gotten to the point now where I'd say it's game on for AI, which is exciting to see and that's a lot of what the theme of this year's think is about. Yeah, and I definitely want to dig into that, but I want to start by asking you sort of moves that you saw you're in there seeing your clients make with regard to the cobot night covert 19 crisis. Maybe how you guys are helping them in very interested in what you see as sort of longterm and even, you know, quasi permanent as a result of this. I would first say it this way. I don't, I'm not sure the crisis is going to change businesses as much as it's going to be accelerating. What would have happened anyway, regardless of the industry that you're in. We see clients aggressively looking at how do we get the digital faster? >>How do we automate more than we ever have before? There's the obvious things like business resiliency and business continuity, managing the distributed workforce. So to me, what we've seen is really about, and acceleration, not necessarily in a different direction, but an acceleration on. The thing is that that we're already kind of in the back of their minds or in the back of their plans now that as we'll come to the forefront and I'm encouraged because we see clients moving at a rate and pace that we'd never seen before that's ultimately going to be great for them, great for their businesses. And so I'm really happy to see that you guys have used Watson to really try to get, you know, some good high fidelity answers to the citizens. I wonder if you could explain that initiative. Well, we've had this application called Watson assistant for the last few years and we've been supporting banks, airlines, retailers, companies across all industries and helping them better interact with our customers and in some cases, employees. >>We took that same technology and as we saw the whole covert 19 situation coming, we said, Hey, we can evolve Watson assistant to serve citizens. And so it started by, we started training the models, which are intent based models in Watson assistant on all the publicly available data from the CDC as an example. And we've been able to build a really powerful virtual agent to serve really any citizen that has questions about and what they should be doing. And the response has been amazing. I mean, in the last two weeks we've gone live with 20 organizations, many of which are state and local governments. Okay. Also businesses, the city of Austin children's healthcare of Atlanta. Mmm. They local governments in Spain and Greece all over the world. And in some instances these clients have gotten live in less than 24 hours. Meaning they have a virtual agent that can answer any question. >>They can do that in less than 24 hours. It's actually been amazing to see. So proud of the team that built this over time. And it was kind of proof of the power of technology when we're dealing with any type of a challenge. You know, I had a conversation earlier with Jamie Thomas about quantum and was asking her sort of how your clients are using it. The examples that came up were financial institutions, pharmaceutical know battery manufacturers, um, airlines. And so it strikes me when you think about uh, machine intelligence and AI, the type of AI that you're yeah, at IBM is not consumer oriented AI. It's really designed for businesses. And I wonder if you could sort of add some color to that. Yeah, let's distinguish the difference there. Cause I think you've said it well consumer AI is smart speakers things in our home, you know, music recommendations, photo analysis and that's great and it enriches all of our personal lives. >>AI for business is very different. This is about how do you make better predictions, how do you optimize business processes, how do you automate things that maybe your employees don't want to do in the first time? Our focus in IBM as part of, we've been doing with Watson is really anchoring on three aspects of AI language. So understanding language because the whole business world is about communication of language, trust meaning trusted AI. You understand the models, you understand the data. And then third automation and the whole focus of what we're doing here in the virtual think experience. It's focused on AI for automation. Whether that's automating business processes or the new announcement this week, which is around automating AI opera it operations for a CIO. You, you've talked the years about this notion of an AI ladder. You actually, I actually wrote a book on it and uh, but, but it's been hard for customers to operationalize AI. >>Mmm. We talked about this last year. Thanks. What kind of progress, uh, have we made in the last 12 months? There's been a real recognition of this notion that your AI is only as good as your data. And we use the phrase, there's no AI without IAA, meaning information architecture, it's all the same concept, which is that your data, it has to be ready for AI if you want to too get successful outcomes with AI and the steps of those ladders around how you collect data, how you organize data, how you analyze data, how you infuse that into your business processes. seeing major leaps forward in the last nine months where organizations are understanding that connection and then they're using that to really drive initiatives around AI. So let's talk about that a little bit more. This notion of AI ops, I mean it's essentially the take the concept of dev ops and apply it to the data pipeline if you will. >>Everybody, you know, complains, you know, data scientists complained that all, they spent all their time wrangling data, improving data quality, they don't have line of sight across their organization with regard to other data specialists, whether it's data engineers or even developers. Maybe you could talk a little bit more about that announcement and sort of what you're doing in that area. Sure. So right. Let me put a number on it because the numbers are amazing. Every year organizations lose 2016 point $5 billion of revenue because of outages in it system. That is a staggering number when you think about it. And so then you say, okay, so how do you break down and attack that problem? Well, do you have to get better at fixing problems or you have to get better at avoiding problems altogether. And as you may expect, a little bit of both. You, you want to avoid problems obviously, but in an uncertain world, you're always going to deal with unforeseen challenges. >>So the also the question becomes how fast can you respond and there's no better use of AI. And then to do, I hope you like those tasks, which is understanding your environment, understanding what the systems are saying through their data and identifying issues become before they become outages. And once there is an outage, how do you quickly triage data across all your systems to figure out where is the problem and how you can quickly address it. So we are announcing Watson AI ops, which is the nervous system for a CIO, the manager, all of their systems. What we do is we just collect data, log data from every source system and we build a semantic layer on top that. So Watson understands the systems, understands the normal behavior, understands the acceptable ranges, and then anytime something's not going like it should, Watson raises his hand and says, Hey, you should probably look at this before it becomes a problem. >>We've partnered with companies like Slack, so the UI for Watson AI ops, it's actually in Slack so that companies can use and employees can use a common collaboration tool too. Troubleshoot or look at either systems. It's, it's really powerful. So that we're really proud of. Well I just kind of leads me to my next question, which I mean, IBM got the religion 20 years ago on openness. I mean I can trace it back to the investment you made and Lennox way back when. Um, and of course it's a huge investment last year in red hat, but you know, open source company. So you just mentioned Slack. Talk about open ecosystems and how that it fits into your AI and data strategy. Well, if you think about it, if we're going to take on a challenge this grand, which is AI for all of your it by definition you're going to be dealing with full ecosystem of different providers because every organization has a broad set of capabilities we identified early on. >>That means that our ability to provide open ecosystem interoperability was going to be critical. So we're launching this product with Slack. I mentioned with box, we've got integrations into things like PagerDuty service now really all of the tools of modern it architecture where we can understand the data and help clients better manage those environments. So this is all about an open ecosystem and that's how we've been approaching it. Let's start, it's really about data, applying machine intelligence or AI to that data and about cloud for scale. So I wonder what you're seeing just in terms of that sort of innovation engine. I mean obviously it's gotta be secure. It's, it seems like those are the pillars of innovation for the next 10 plus years. I think you're right. And I would say this whole situation that we're dealing with has emphasized the importance of hybrid deployment because companies have it capabilities on public clouds, on private clouds, really everywhere. >>And so being able to operate that as a single architecture, it's becoming very important. You can use AI to automate tasks across that whole infrastructure that makes a big difference. And to your point, I think we're going to see a massive acceleration hybrid cloud deployments using AI. And this will be a catalyst for that. And so that's something we're trying to help clients with all around the world. You know, you wrote in your book that O'Reilly published that AI is the new electricity and you talked about problems. Okay. Not enough data. If your data is you know, on prem and you're only in the cloud, well that's a problem or too much data. How you deal with all that data, data quality. So maybe we could close on some of the things that you know, you, you talked about in that book, you know, maybe how people can get ahold of it or any other, you know, so the actions you think people should take to get smart on this topic. >>Yeah, so look, really, really excited about this. Paul's the capitalists, a friend of mine and a colleague, we've published this book working with a Riley called the a ladder and it's all the concepts we talked about in terms of how companies can climb this ladder to AI. And we go through a lot of different use cases, scenarios, I think. Yeah. Anybody reading this is going to see their company in one of these examples, our whole ambition was to hopefully plant some seeds of ideas for how you can start to accelerate your journey to AI in any industry right now. Well, Rob, it's always great having you on the cube, uh, your insights over the years and you've been a good friend of ours, so really appreciate you coming on and, uh, and best of luck to you, your family or wider community. I really appreciate it. Thanks Dave. Great to be here and again, wish you and the whole cube team the best and to all of our clients out there around the world. We wish you the best as well. All right. You're watching the cubes coverage of IBM think 20, 20 digital, the vent. We'll be right back right after this short break. This is Dave Volante.