>>live from Boston, Massachusetts. It's the Q covering I f s World Conference 2019. Brought to you by I >>f. S, I say, What a minute. I didn't cash it. Everybody welcome to I f s World 2019. You watching the Cube? The leader in live tech coverage on day Volante with my co host, Paul Galen. Marty Martin is here. She is the president of the service management division of I F s and C e o of work wave. Marty, good to see you. >>Yeah, it's great to be here. I'm so excited. >>A lot of action going on. You guys. Service management, Field Service management particular. You guys had an acquisition today. We're gonna talk about Let's start with your role you came in and 2017 with the >>pretty acting. Actually, >>2018 finalized the acquisition. I think they announce it in 2017. So tell us about how you came in and where you're at today with >>Certainly. So work wave the company. I lied. Join the effects family in 2017. Darren Ruess, who joined I f s in April 2018 recruited me into form a global business unit around service in August of 2018 and the reason why we did this is service isn't only a part of our economies all over the world, but it's a super great growth area that almost every business can go after in in progress both revenue and margins. So we had a lot of great software products, and we really wanted to improve our go to market around this. >>So why, why all of a sudden today, this talk about service management? Why's it becoming so hard? I mean, everybody's always been focused on customer service, but why this service management generally and field service management while the buzz. >>So first off, you've had the evolution of a number of line of business applications and service certainly has been a part of maintenance organizations or break fix where you're going out in repairing thing. What we're realizing now when you talk about service ization, how o E EMS air building what's called aftermarket revenue? There is literally $100 billion of revenue that you can get from that you look, we had Melissa did a nano from Souza. If you think about open source software, they make money from sirve ties, ing, open source software and the products. You look at apple how they're doing APs. So people are starting to realize that service is an engine for brand loyalty, customer experience, not just a cost center. How it used to be, what the >>customers do. Ah, companies do wrong with service one of the areas where they tend to have the greatest inefficiencies where you can help him. >>So first off, I'd say that often in the C suite, unless they're pure place service companies. They don't understand how transformative service is and how important it is to their brand. Many times now, if you have digital enablement of a new customer, the first time they see a face of your brand might be your service technician. So getting the awareness of the C suite is Step one, because we want to start talking about outcomes that grow revenue and profits and getting them to invest in service. So you know, many times will say, Oh, I want to do a C. R M project. I want to do an E r P project. That's certainly things were good at it. Here I a fest, but we can coach them through how you take the market opportunity for your company and service enabled by our technology and transform. Tomorrow I'll be with Accenture, one of our many great partners, and we're talking about adapting the business, the service transformation, sometimes digitally, sometimes with workflow transformation. But that opportunity and service is huge and almost never. There's no company I know of that's taking 100% of their service market share. That's the difference, especially in slower growth. Asset manufacturing are more mature verticals. >>So I was here last night walking the floor, and I went to the extent you Booth, you know, anytime you see, except you're in a show like this. Okay, Censure. You think Large company Global. I was actually quite impressed a little bit surprised to see you know, their presence here because they they go where the money is, right? And so my specific question is, think, except you think big companies. But you guys obviously focused on what range of companies smaller midsize company. So what's the landscape? Looked like? What's the difference is between sort of smaller and larger companies, >>so that's a great question. I'll take it in part So if you think about a neck censure definitely they looked a large. I also have had meetings with the Lloyd McKinsey Cap gem and I dxc etcetera Also tcs Tech Mahindra which a little bit or more telco focused. So if you think about at the very large and you have telco utilities, large manufacturing O e ems that our customers and definitely the customers I'm pursuing Maur with this focus But we also with work with go down to the S and B We had panels also of, for example, female owners of franchises and also males as well that are creating new service businesses and they're starting maybe with one truck in out providing service. So the fact that we can handle not only the breath and depth of complex service needs, but through work wave we also can encourage the small service businesses to reach their full potential is fantastic. And you know that makes me excited every day. And part of why I focused on service specifically is you are delighting customers. You are the face of a brand and you're making a difference. It's not something that s 02 is esoteric. This is about really value that we're delivering, >>always interested in the dynamics of serving the SNB market >>because one of >>these small companies don't really have that. Maybe family owned there found her own. They don't really put a lot of value on technology. How >>do you >>get in the door? How do you convince them that automating the service function is actually worth the investment? >>Well, first off, I'd say that even the big companies are struggling to go paperless. Okay, so, you know, I think some of the challenges we see survive, if you will, big to small, especially when you look globally in different countries. What have you. But the approach we take in the S and B is that we want to be a software as a service provider, and we were to really handle everything they need in their business. So everything from how they grow leads how they have c r m type functionality. How, then they're delivering service, how they're cross selling service, how they're billing service. So at the at the S M B level, we're putting that kind of all in one technology and there's really not that much integration or I T Service is around that right. We want it to be easy and fast, etcetera, as you go more into the mid market and then definitely into the enterprise. Then you start getting more complexity. You get more I t service's integrations, more configurable ity, sometimes even some customized software. So there is a definitely a difference in the complexity. But the fundamentals of what a service business needs really isn't that much different to your >>customers that you mentioned customize and you guys were SAS space. That's one of the text that we'd like to sort of explore a little bit. A lot >>of >>times SAS companies want to avoid, you know, custom mods. But at the same time, you guys are trying to offer a choice. So help us square that circle. How do you What's the conversation like with customers in terms of how you advise them, You guys obviously do a lot of deep functionality, you know? How do you sort of advise them whether or not to go heavily custom or try to go out of the box? >>Certainly. So in the true, I'd say the small business of a medium you start getting some crossover, but in the small business, Absolutely avoid customization because you won't be able to stay evergreen. It's going to be too hard to maintain. You don't have the subject matter experts, et cetera, so that's really a truce. Ask that from a community. A product engagement. We need to be driving the partnership with the customers that they can use a software out of the box in ways that matter to them. As you start getting into the mid market and especially the enterprise, then it becomes more of a choice, right? How much money do you have to spend? How robust is your organization and set trek? And in general, I advise customers if they care about evergreen software, et cetera. If they care about ease of upgrades, don't customize that Being said, we recognize sometimes in the field with your brand experience Custom mobile. You may need to customize a little bit, so it's Ah, say, a chicken and an egg. You have to weigh the benefits of the costs, and that's what we work through with our >>customers. Specifically morning. What's the upgrade cycle like? There's a customer having the choice Thio upgrade at a particular time, Or do they have a window? >>So it varies primarily, there's a few exceptions, but in general, with the work way, Family of products is true SAS. So it's almost like you're Apple Phone. We pushed the upgrade and you have to take it. Okay, And that's the true SAS model at I. F. S. And this is something Darren talked about in his keynote. We pride ourselves on offering choice. So even though we do have regular release cycles, we encourage customers to upgrade regularly. They have the choice on when they take upgrades and also how they deploy. We have some markets with things like data, privacy and what have you that they may, for that reason or for other reasons, go on premise even still today. So we give them the choice on how they upgrade as well as where they host. >>I'm fascinated by your product line. You have products for pest control. H V. A. C. Plumbing cleaning service is long and landscape. How different are these industries really in terms of their their automation needs? >>Well, I'll tell you one of the personal factors that Darren wanted to make sure I was comfortable with was multitasking. And that definitely is the case, because an I f s, we serve five key industries. So if you think about manufacturing utilities, telco service providers and Andy Okay, that's more at the enterprise level. If you think then when you go toe work wave. Those verticals that you mentioned are all the ones we service at work wave, and they are different. So you know what? Work wave. It's primarily service industries where you're going into ah, home and a little bit The commercial aspect and I effects were also doing more some heavy industries, some very large asset base, things like that. So I like to think about it as a product I service consumer based service. And then you can also differentiate across verticals with what are called high value assets versus, you know, Mork consumer size assets. >>So what >>are >>the one of the key technology enablers that are driving service management today? I mean, obviously, cloud, we talked about sas a lot of push on you X and customer experience, but what other key ones? >>So all the three that you mentioned mobile is huge. You know, Pete and even today, like I run. I work mainly from my phone, and that's really what people want. They want efficient work flows that are configurable on mobile, tied to the customer, the asset, the business. And that's an area that we're continuing to make investment. We also try to prioritize how we bring in the new technology trends into service. Because every technology trend that you see has applicable ity and service supply chain and how you run spare parts specially globally, you can see applications for Blockchain augmented emerged Reality how you can connect the field tech with an expert resource or remote resource to the consumer. That is obvious, right? So you talked about the enabling technologies like Cloud, how we're thinking about data platforms and Data's the currency. Of all of that, we need to d'oh. His service is really about a an execution engine, right? Because to deliver a customer experience that makes people come back to your brand. To purchase Maur, you need great service, so any time somebody talks about customer experience, but they don't talk about service. I want to say you're really naive because you can just get the customer. You have to delight the customer. >>Uh, the, uh, there's a lot of interesting technology going on now in the area. Fleet Management making fleets more efficient How does that figure into the service is? You offer. >>So Fleet management is an important part, and it's one that you have a very tangible return on investment when you deploy route management route optimization, fleet management. So you have the aspects that are very tangible, relate to how do you get the person or the truck where it needs to be when it needs to be okay, and that's pretty well understood. Then how do you get the most efficient schedule that minimizes miles driven gas, used et cetera? And then, of course, you also are thinking about health and safety. There's some cool things now that you can partner that if you have these fleet technologies installed in a way that is integrated in your service business, you can actually get lower insurance premiums, right? So it's not just the conventional use. Cases were starting to think in this kind of gig economy, how you can also be thinking about bringing in Maura what's called a contingent workforce. So if you have surge capacity in a certain period or you want to just do more third party service, probably your appliances. You know they're not the employees, if you will, of a g e or a world polar and LG right there Probably a contingent workforce. And that's a model that's also evolving. But to do Fleet Management across say, contractors, not just employees is an area that were thinking more and more led by some of the uber ization, if you will, of the of the marketplace >>right up against the clock, Marty. But to last questions You made an acquisition today, Vashti Uh, yeah, uh, I thought of it as a tuck in acquisitions, although Darren essentially sort of said, it's gonna make you the leader now in service management. Um And then I want to understand how you guys differentiate from some of the big whales. >>So, you know, overall, we're on track to be about 700 revenue this year in service management. We're working to get to 200 million, right? So this year will probably be around maybe 1/5 50 ish per se. Don't quote me on that check with our coms team, but the point being is that we have the ability to use these tuck in acquisitions and service to accelerate our lead, not just from a revenue perspective, which is what we were just talking about. But from a product perspective, you might have followed Salesforce acquiring Click. That means we are the only independent. Aye, aye. Optimization engine that is field tested. Battle ready. So that's great. This s t a is how we consolidate our dominance and complex service. So what darren was speaking to is not on Lee the service management segment of our revenue and how we continue to accelerate over the oracles in the S a. P s and the service maxes et cetera of the world. But how we take what we're already dominant in and really put the hammer down. Honesty is part of that. >>Your differentiation then if I infers, is focus. Um, you're you're deep customer customs agent deep >>domain expertise. Yeah, So really, when you think about a i optimization, which drives a ton of business value and the ability to handle the complex service cases that then drive business outcomes and outcomes based service models, we are number one and s dea tucks into that, even though it is very strategic on how we position ourselves with leadership and service. >>All right, Challenger becomes number one, Marty. Thanks very much. All right, Keep it right, everybody. Dave A lot with Paul Galen. You're watching the Cube from Boston Mass. I f s world 2019 right back.

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to Cambridge, Massachusetts. Everybody, You're watching the Cube, the leader in live tech coverage, and we're covering the M I t CDO conference M I t. CDO. My name is David Monty in here with my co host, Paul Galen. Mike Stone breakers here. The legend is founder CTO of Of Tamer, as well as many other companies. Inventor Michael. Thanks for coming back in the Cube. Good to see again. Nice to be here. So this is kind of ah, repeat pattern for all of us. We kind of gather here in August that the CDO conference You're always the highlight of the show. You gave a talk this week on the top 10. Big data mistakes. You and I are one of the few. You were the few people who still use the term big data. I happen to like it. Sad that it's out of vogue already, but people associated with the doo doop it's kind of waning, but regardless, so welcome. How'd the talk go? What were you talking about. >> So I talked to a lot of people who were doing analytics. We're doing operation Offer operational day of data at scale, and they always make most of them make a collection of bad mistakes. And so the talk waas a litany of the blunders that I've seen people make, and so the audience could relate to the blunders about most. Most of the enterprise is represented. Make a bunch of the blunders. So I think no. One blunder is not planning on moving most everything to the cloud. >> So that's interesting, because a lot of people would would would love to debate that, but and I would imagine you probably could have done this 10 years ago in a lot of the blunders would be the same, but that's one that wouldn't have been there. But so I tend to agree. I was one of the two hands that went up this morning, and vocalist talk when he asked, Is the cloud cheaper for us? It is anyway. But so what? Why should everybody move everything? The cloud aren't there laws of physics, laws of economics, laws of the land that suggest maybe you >> shouldn't? Well, I guess 22 things and then a comment. First thing is James Hamilton, who's no techies. Techie works for Amazon. We know James. So he claims that he could stand up a server for 25% of your cost. I have no reason to disbelieve him. That number has been pretty constant for a few years, so his cost is 1/4 of your cost. Sooner or later, prices are gonna reflect costs as there's a race to the bottom of cloud servers. So >> So can I just stop you there for a second? Because you're some other date on that. All you have to do is look at a W S is operating margin and you'll see how profitable they are. They have software like economics. Now we're deploying servers. So sorry to interrupt, but so carry. So >> anyway, sooner or later, they're gonna have their gonna be wildly cheaper than you are. The second, then yet is from Dave DeWitt, whose database wizard. And here's the current technology that that Microsoft Azure is using. As of 18 months ago, it's shipping containers and parking lots, chilled water in power in Internet, Ian otherwise sealed roof and walls optional. So if you're doing raised flooring in Cambridge versus I'm doing shipping containers in the Columbia River Valley, who's gonna be a lot cheaper? And so you know the economies of scale? I mean, that, uh, big, big cloud guys are building data centers as fast as they can, using the cheapest technology around. You put up the data center every 10 years on dhe. You do it on raised flooring in Cambridge. So sooner or later, the cloud guys are gonna be a lot cheaper. And the only thing that isn't gonna the only thing that will change that equation is For example, my lab is up the street with Frank Gehry building, and we have we have an I t i t department who runs servers in Cambridge. Uh, and they claim they're cheaper than the cloud. And they don't pay rent for square footage and they don't pay for electricity. So yeah, if if think externalities, If there are no externalities, the cloud is assuredly going to be cheaper. And then the other thing is that most everybody tonight that I talk thio including me, has very skewed resource demands. So in the cloud finding three servers, except for the last day of the month on the last day of the month. I need 20 servers. I just do it. If I'm doing on Prem, I've got a provision for peak load. And so again, I'm just way more expensive. So I think sooner or later these combinations of effects was going to send everybody to the cloud for most everything, >> and my point about the operating margins is difference in price and cost. I think James Hamilton's right on it. If he If you look at the actual cost of deploying, it's even lower than the price with the market allows them to their growing at 40 plus percent a year and a 35 $40,000,000,000 run rate company sooner, Sooner or >> later, it's gonna be a race to the lot of you >> and the only guys are gonna win. You have guys have the best cost structure. A >> couple other highlights from your talk. >> Sure, I think 2nd 2nd thing like Thio Thio, no stress is that machine learning is going to be a game is going to be a game changer for essentially everybody. And not only is it going to be autonomous vehicles. It's gonna be automatic. Check out. It's going to be drone delivery of most everything. Uh, and so you can, either. And it's gonna affect essentially everybody gonna concert of, say, categorically. Any job that is easy to understand is going to get automated. And I think that's it's gonna be majorly impactful to most everybody. So if you're in Enterprise, you have two choices. You can be a disrupt or or you could be a disruptive. And so you can either be a taxi company or you can be you over, and it's gonna be a I machine learning that's going going to be determined which side of that equation you're on. So I was a big blunder that I see people not taking ml incredibly seriously. >> Do you see that? In fact, everyone I talked who seems to be bought in that this is we've got to get on the bandwagon. Yeah, >> I'm just pointing out the obvious. Yeah, yeah, I think, But one that's not quite so obvious you're is a lot of a lot of people I talked to say, uh, I'm on top of data science. I've hired a group of of 10 data scientists, and they're doing great. And when I talked, one vignette that's kind of fun is I talked to a data scientist from iRobot, which is the guys that have the vacuum cleaner that runs around your living room. So, uh, she said, I spend 90% of my time locating the data. I want to analyze getting my hands on it and cleaning it, leaving the 10% to do data science job for which I was hired. Of the 10% I spend 90% fixing the data cleaning errors in my data so that my models work. So she spends 99% of her time on what you call data preparation 1% of her time doing the job for which he was hired. So data science is not about data science. It's about data integration, data cleaning, data, discovery. >> But your new latest venture, >> so tamer does that sort of stuff. And so that's But that's the rial data science problem. And a lot of people don't realize that yet, And, uh, you know they will. I >> want to ask you because you've been involved in this by my count and starting up at least a dozen companies. Um, 99 Okay, It's a lot. >> It's not overstated. You estimated high fall. How do you How >> do you >> decide what challenge to move on? Because they're really not. You're not solving the same problems. You're You're moving on to new problems. How do you decide? What's the next thing that interests you? Enough to actually start a company. Okay, >> that's really easy. You know, I'm on the faculty of M i t. My job is to think of news new ship and investigate it, and I come up. No, I'm paid to come up with new ideas, some of which have commercial value, some of which don't and the ones that have commercial value, like, commercialized on. So it's whatever I'm doing at the time on. And that's why all the things I've commercialized, you're different >> s so going back to tamer data integration platform is a lot of companies out there claim to do it day to get integration right now. What did you see? What? That was the deficit in the market that you could address. >> Okay, great question. So there's the traditional data. Integration is extract transforming load systems and so called Master Data management systems brought to you by IBM in from Attica. Talent that class of folks. So a dirty little secret is that that technology does not scale Okay, in the following sense that it's all well, e t l doesn't scale for a different reason with an m d l e t l doesn't scale because e t. L is based on the premise that somebody really smart comes up with a global data model For all the data sources you want put together. You then send a human out to interview each business unit to figure out exactly what data they've got and then how to transform it into the global data model. How to load it into your data warehouse. That's very human intensive. And it doesn't scale because it's so human intensive. So I've never talked to a data warehouse operator who who says I integrate the average I talk to says they they integrate less than 10 data sources. Some people 20. If you twist my arm hard, I'll give you 50. So a Here. Here's a real world problem, which is Toyota Motor Europe. I want you right now. They have a distributor in Spain, another distributor in France. They have a country by country distributor, sometimes canton by Canton. Distribute distribution. So if you buy a Toyota and Spain and move to France, Toyota develops amnesia. The French French guys know nothing about you. So they've got 250 separate customer databases with 40,000,000 total records in 50 languages. And they're in the process of integrating that. It was single customer database so that they can Duke custom. They could do the customer service we expect when you cross cross and you boundary. I've never seen an e t l system capable of dealing with that kind of scale. E t l dozen scale to this level of problem. >> So how do you solve that problem? >> I'll tell you that they're a tamer customer. I'll tell you all about it. Let me first tell you why MGM doesn't scare. >> Okay. Great. >> So e t l says I now have all your data in one place in the same format, but now you've got following problems. You've got a d duplicated because if if I if I bought it, I bought a Toyota in Spain, I bought another Toyota in France. I'm both databases. So if you want to avoid double counting customers, you got a dupe. Uh, you know, got Duke 30,000,000 records. And so MGM says Okay, you write some rules. It's a rule based technology. So you write a rule. That's so, for example, my favorite example of a rule. I don't know if you guys like to downhill downhill skiing, All right? I love downhill skiing. So ski areas, Aaron, all kinds of public databases assemble those all together. Now you gotta figure out which ones are the same the same ski area, and they're called different names in different addresses and so forth. However, a vertical drop from bottom to the top is the same. Chances are they're the same ski area. So that's a rule that says how to how to put how to put data together in clusters. And so I now have a cluster for mount sanity, and I have a problem which is, uh, one address says something rather another address as something else. Which one is right or both? Right, so now you want. Now you have a gold. Let's call the golden Record problem to basically decide which, which, which data elements among a variety that maybe all associated with the same entity are in fact correct. So again, MDM, that's a rule's a rule based system. So it's a rule based technology and rule systems don't scale the best example I can give you for why Rules systems don't scale. His tamer has another customer. General Electric probably heard of them, and G wanted to do spend analytics, and so they had 20,000,000 spend transactions. Frank the year before last and spend transaction is I paid $12 to take a cab from here here to the airport, and I charged it to cost center X Y Z 20,000,000 of those so G has a pre built classification system for spend, so they have parts and underneath parts or computers underneath computers and memory and so forth. So pre existing preexisting class classifications for spend they want to simply classified 20,000,000 spent transactions into this pre existing hierarchy. So the traditional technology is, well, let's write some rules. So G wrote 500 rules, which is about the most any single human I can get there, their arms around so that classified 2,000,000 of the 20,000,000 transactions. You've now got 18 to go and another 500 rules is not going to give you 2,000,000 more. It's gonna give you love diminishing returns, right? So you have to write a huge number of rules and no one can possibly understand. So the technology simply doesn't scale, right? So in the case of G, uh, they had tamer health. Um, solve this. Solved this classification problem. Tamer used their 2,000,000 rule based, uh, tag records as training data. They used an ML model, then work off the training data classifies remaining 18,000,000. So the answer is machine learning. If you don't use machine learning, you're absolutely toast. So the answer to MDM the answer to MGM doesn't scale. You've got to use them. L The answer to each yell doesn't scale. You gotta You're putting together disparate records can. The answer is ml So you've got to replace humans by machine learning. And so that's that seems, at least in this conference, that seems to be resonating, which is people are understanding that at scale tradition, traditional data integration, technology's just don't work >> well and you got you got a great shot out on yesterday from the former G S K Mark Grams, a leader Mark Ramsay. Exactly. Guys. And how they solve their problem. He basically laid it out. BTW didn't work and GM didn't work, All right. I mean, kick it, kick the can top down data modelling, didn't work, kicked the candid governance That's not going to solve the problem. And But Tamer did, along with some other tooling. Obviously, of course, >> the Well, the other thing is No. One technology. There's no silver bullet here. It's going to be a bunch of technologies working together, right? Mark Ramsay is a great example. He used his stream sets and a bunch of other a bunch of other startup technology operating together and that traditional guys >> Okay, we're good >> question. I want to show we have time. >> So with traditional vendors by and large or 10 years behind the times, And if you want cutting edge stuff, you've got to go to start ups. >> I want to jump. It's a different topic, but I know that you in the past were critic of know of the no sequel movement, and no sequel isn't going away. It seems to be a uh uh, it seems to be actually gaining steam right now. What what are the flaws in no sequel? It has your opinion changed >> all? No. So so no sequel originally meant no sequel. Don't use it then. Then the marketing message changed to not only sequel, So sequel is fine, but no sequel does others. >> Now it's all sequel, right? >> And my point of view is now. No sequel means not yet sequel because high level language, high level data languages, air good. Mongo is inventing one Cassandra's inventing one. Those unless you squint, look like sequel. And so I think the answer is no sequel. Guys are drifting towards sequel. Meanwhile, Jason is That's a great idea. If you've got your regular data sequel, guys were saying, Sure, let's have Jason is the data type, and I think the only place where this a fair amount of argument is schema later versus schema first, and I pretty much think schema later is a bad idea because schema later really means you're creating a data swamp exactly on. So if you >> have to fix it and then you get a feel of >> salary, so you're storing employees and salaries. So, Paul salaries recorded as dollars per month. Uh, Dave, salary is in euros per week with a lunch allowance minds. So if you if you don't, If you don't deal with irregularities up front on data that you care about, you're gonna create a mess. >> No scheme on right. Was convenient of larger store, a lot of data cheaply. But then what? Hard to get value out of it created. >> So So I think the I'm not opposed to scheme later. As long as you realize that you were kicking the can down the road and you're just you're just going to give your successor a big mess. >> Yeah, right. Michael, we gotta jump. But thank you so much. Sure appreciate it. All right. Keep it right there, everybody. We'll be back with our next guest right into the short break. You watching the cue from M i t cdo Ike, you right back

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to M I. T. In Cambridge, Massachusetts. Everybody. You're watching the cube. The leader in live tech coverage. This is M I t CDO I Q the chief data officer and information quality conference. Someday Volonte with my co host, Paul Galen. Professor Dr Stewart, Mad Nick is here. Longtime Cube alum. Ah, long time professor at M i. T soon to be retired, but we're really grateful that you're taking your time toe. Come on. The Cube is great to see you again. >> It's great to see you again. It's been a long time. She worked together and I really appreciate the opportunity to share our spirits. Hear our mighty with your audience. Well, it's really been fun >> to watch this conference evolved were full and it's really amazing. We have to move to a new venue >> next year. I >> understand. And data we talk about the date explosion all the time, But one of the areas that you're focused on and you're gonna talk about today is his ethics and privacy and data causes so many concerns in those two areas. But so give us the highlight of what you're gonna discuss with the audience today. We'll get into >> one of things that makes it so challenging. It is. Data has so many implications. Tow it. And that's why the issue of ethics is so hard to get people to reach agreement on it. We're talking people regarding medicine and the idea big data and a I so know, to be able to really identify causes you need mass amounts of data. That means more data has to be made available as long as it's Elsa data, not mine. Well, not my backyard. If he really So you have this issue where on the one hand, people are concerned about sharing the data. On the other hand, there's so many valuable things would gain by sharing data and getting people to reach agreement is a challenge. Well, one of things >> I wanted to explore with you is how things have changed you back in the day very familiar with Paul you as well with Microsoft, Department of Justice, justice, FTC issues regarding Microsoft. And it wasn't so much around data was really around browsers and bundling things today. But today you see Facebook and Google Amazon coming under fire, and it's largely data related. Listen, Liz Warren, last night again break up big tech your thoughts on similarities and differences between sort of the monopolies of yesterday and the data monopolies of today Should they be broken up? What do you thought? So >> let me broaden the issue a little bit more from Maryland, and I don't know how the demographics of the audience. But I often refer to the characteristics that millennials the millennials in general. I ask my students this question here. Now, how many of you have a Facebook account in almost every class? Facebook. You realize you've given away a lot of nation about yourself. It it doesn't really occurred to them. That may be an issue. I was told by someone that in some countries, Facebook is very popular. That's how they cordoned the kidnappings of teenagers from rich families. They track them. They know they're going to go to this basketball game of the soccer match. You know exactly what I'm going after it. That's the perfect spot to kidnap them, so I don't know whether students think about the fact that when they're putting things on Facebook than making so much of their life at risk. On the other hand, it makes their life richer, more enjoyable. And so that's why these things are so challenging now, getting back to the issue of the break up of the big tech companies. One of the big challenges there is that in order to do the great things that big data has been doing and the things that a I promises do you need lots of data. Having organizations that can gather it all together in a relatively systematic and consistent manner is so valuable breaking up the tech companies. And there's some reasons why people want to do that, but also interferes with that benefit. And that's why I think it's gonna be looked at real Kim, please, to see not only what game maybe maybe breaking up also what losses of disadvantages we're creating >> for ourselves so example might be, perhaps it makes United States less competitive. Visa VI China, in the area of machine intelligence, is one example. The flip side of that is, you know Facebook has every incentive to appropriate our data to sell ads. So it's not an easy, you know, equation. >> Well, even ads are a funny situation for some people having a product called to your attention that something actually really want. But you never knew it before could be viewed as a feature, right? So, you know, in some case of the ads, could be viewed as a feature by some people. And, of course, a bit of intrusion by other people. Well, sometimes we use the search. Google, right? Looking >> for the ad on the side. No longer. It's all ads. You know >> it. I wonder if you see public public sentiment changing in this respect. There's a lot of concerns, certainly at the legislative level now about misuse of data. But Facebook user ship is not going down. Instagram membership is not going down. Uh, indication is that that ordinary citizens don't really care. >> I know that. That's been my I don't have all the data. Maybe you may have seen, but just anecdotally and talking to people in the work we're doing, I agree with you. I think most people maybe a bit dramatic, but at a conference once and someone made a comment that there has not been the digital Pearl Harbor yet. No, there's not been some event that was just so onerous. Is so all by the people. Remember the day it happened kind of thing. And so these things happen and maybe a little bit of press coverage and you're back on your Facebook. How their instagram account the next day. Nothing is really dramatic. Individuals may change now and then, but I don't see massive changes. But >> you had the Equifax hack two years ago. 145,000,000 records. Capital one. Just this week. 100,000,000 records. I mean, that seems pretty Pearl Harbor ish to me. >> Well, it's funny way we're talking about that earlier today regarding different parts of the world. I think in Europe, the general, they really seem to care about privacy. United States that kind of care about privacy in China. They know they have no privacy. But even in us where they care about privacy, exactly how much they care about it is really an issue. And in general it's not enough to move the needle. If it does, it moves it a little bit about the time when they show that smart TVs could be broken into smart. See, TV sales did not Dutch an inch. Not much help people even remember that big scandal a year ago. >> Well, now, to your point about expects, I mean, just this week, I think Equifax came out with a website. Well, you could check whether or not your credentials were. >> It's a new product. We're where we're compromised. And enough in what has been >> as head mind, I said, My wife says it's too. So you had a choice, you know, free monitoring or $125. So that way went okay. Now what? You know, life goes >> on. It doesn't seem like anything really changes. And we were talking earlier about your 1972 book about cyber security, that many of the principles and you outlined in that book are still valid today. Why are we not making more progress against cybercriminals? >> Well, two things. One thing is you gotta realize, as I said before, the Cave man had no privacy problems and no break in problems. But I'm not sure any of us want to go back to caveman era because you've got to realize that for all these bad things. There's so many good things that are happening, things you could now do, which a smartphone you couldn't even visualize doing a decade or two ago. So there's so much excitement, so much for momentum, autonomous cars and so on and so on that these minor bumps in the road are easy to ignore in the enthusiasm and excitement. >> Well and now, as we head into 2020 affection it was. It was fake news in 2016. Now we've got deep fakes. Get the ability to really use video in new ways. Do you see a way out of that problem? A lot of people looking a Blockchain You wrote an article recently, and Blockchain you think it's on hackable? Well, think again. >> What are you seeing? I think one of things we always talk about when we talk about improving privacy and security and organizations, the first thing is awareness. Most people are really small moment of time, aware that there's an issue and it quickly pass in the mind. The analogy I use regarding industrial safety. You go into almost any factory. You'll see a sign over the door every day that says 520 days, his last industrial accident and then a sub line. Please do not be the one to reset it this year. And I often say, When's the last time you went to a data center? And so assign is at 50 milliseconds his last cyber data breach. And so it needs to be something that is really front, the mind and people. And we talk about how to make awareness activities over companies and host household. And that's one of our major movements here is trying to be more aware because we're not aware that you're putting things at risk. You're not gonna do anything about it. >> Last year we contacted Silicon Angle, 22 leading security experts best in one simple question. Are we winning or losing the war against cybercriminals? Unanimously, they said, we're losing. What is your opinion of that question? >> I have a great quote I like to use. The good news is the good guys are getting better than a firewall of cryptographic codes. But the bad guys are getting batter faster, and there's a lot of reasons for that well on all of them. But we came out with a nautical talking about the docking Web, and the reason why it's fascinating is if you go to most companies if they've suffered a data breach or a cyber attack, they'll be very reluctant to say much about unless they really compelled to do so on the dock, where they love to Brent and reputation. I'm the one who broke in the Capital One. And so there's much more information sharing that much more organized, a much more disciplined. I mean, the criminal ecosystem is so much more superior than the chaotic mess we have here on the good guys side of the table. >> Do you see any hope for that? There are service's. IBM has one, and there are others in a sort of anonymous eyes. Security data enable organizations to share sensitive information without risk to their company. You see any hope on the collaboration, Front >> said before the good guys are getting better. The trouble is, at first I thought there was an issue that was enough sharing going on. It turns out we identified over 120 sharing organizations. That's the good news. And the bad news is 120. So IBM is one and another 119 more to go. So it's not a very well coordinated sharing. It's going just one example. The challenges Do I see any hope in the future? Well, in the more distant future, because the challenge we have is that there'll be a cyber attack next week of some form or shape that we've never seen before and therefore what? Probably not well prepared for it. At some point, I'll no longer be able to say that, but I think the cyber attackers and creatures and so on are so creative. They've got another decade of more to go before they run out of >> Steve. We've got from hacktivists to organized crime now nation states, and you start thinking about the future of war. I was talking to Robert Gates, aboutthe former defense secretary, and my question was, Why don't we have the best cyber? Can't we go in the oven? It goes, Yeah, but we also have the most to lose our critical infrastructure, and the value of that to our society is much greater than some of our adversaries. So we have to be very careful. It's kind of mind boggling to think autonomous vehicles is another one. I know that you have some visibility on that. And you were saying that technical challenges of actually achieving quality autonomous vehicles are so daunting that security is getting pushed to the back burner. >> And if the irony is, I had a conversation. I was a visiting professor, sir, at the University of Niece about a 12 14 years ago. And that's before time of vehicles are not what they were doing. Big automotive tele metrics. And I realized at that time that security wasn't really our top priority. I happen to visit organization, doing really Thomas vehicles now, 14 years later, and this conversation is almost identical now. The problems we're trying to solve. A hider problem that 40 years ago, much more challenging problems. And as a result, those problems dominate their mindset and security issues kind of, you know, we'll get around him if we can't get the cot a ride correctly. Why worry about security? >> Well, what about the ethics of autonomous vehicles? Way talking about your programming? You know, if you're gonna hit a baby or a woman or kill your passengers and yourself, what do you tell the machine to Dio, that is, it seems like an unsolvable problem. >> Well, I'm an engineer by training, and possibly many people in the audience are, too. I'm the kind of person likes nice, clear, clean answers. Two plus two is four, not 3.94 point one. That's the school up the street. They deal with that. The trouble with ethic issues is they don't tend to have a nice, clean answer. Almost every study we've done that has these kind of issues on it. And we have people vote almost always have spread across the board because you know any one of these is a bad decision. So which the bad decision is least bad. Like, what's an example that you used the example I use in my class, and we've been using that for well over a year now in class, I teach on ethics. Is you out of the design of an autonomous vehicle, so you must program it to do everything and particular case you have is your in the vehicle. It's driving around the mountain and Swiss Alps. You go around a corner and the vehicle, using all of senses, realize that straight ahead on the right? Ian Lane is a woman in a baby carriage pushing on to this onto the left, just entering the garage way a three gentlemen, both sides a road have concrete barriers so you can stay on your path. Hit the woman the baby carriage via to the left. Hit the three men. Take a shop, right or shot left. Hit the concrete wall and kill yourself. And trouble is, every one of those is unappealing. Imagine the headline kills woman and baby. That's not a very good thing. There actually is a theory of ethics called utility theory that says, better to say three people than to one. So definitely doing on Kim on a kill three men, that's the worst. And then the idea of hitting the concrete wall may feel magnanimous. I'm just killing myself. But as a design of the car, shouldn't your number one duty be to protect the owner of the car? And so people basically do. They close their eyes and flip a coin because they don't want anyone. Those hands, >> not an algorithmic >> response, doesn't leave. >> I want to come back for weeks before we close here to the subject of this conference. Exactly. You've been involved with this conference since the very beginning. How have you seen the conversation changed since that time? >> I think I think it's changing to Wei first. As you know, this record breaking a group of people are expecting here. Close to 500 I think have registered s o much Clea grown kind of over the years, but also the extent to which, whether it was called big data or call a I now whatever is something that was kind of not quite on the radar when we started, I think it's all 15 years ago. He first started the conference series so clearly has become something that is not just something We talk about it in the academic world but is becoming main stay business for corporations Maur and Maur. And I think it's just gonna keep increasing. I think so much of our society so much of business is so dependent on the data in any way, shape or form that we use it and have >> it well, it's come full circle. It's policy and I were talking at are open. This conference kind of emerged from the ashes of the back office information quality and you say the big date and now a I guess what? It's all coming back to information. >> Lots of data. That's no good. Or that you don't understand what they do with this. Not very healthy. >> Well, doctor Magic. Thank you so much. It's a >> relief for all these years. Really Wanna thank you. Thank you, guys, for joining us and helping to spread the word. Thank you. Pleasure. All right, keep it right, everybody. Paul and >> I will be back at M I t cdo right after this short break. You're watching the cue.

>>The cube at IBM. Impact 2014 is brought to you by headline sponsor. IBM. Here are your hosts, John furrier and Paul Gillin. >>Hey, welcome back everyone. This is Silicon angle's the cube. It's our flagship program. We go out to the events district as soon from the noise. We're ending out day two of two days of wall to wall coverage with myself and Paul Galen. Uh, 10 to six 30 every day. I'm just, we'll take as much as we can just to get the data. Share that with you. Restrict the signal from the noise. I'm John furrier the bonus look at angle Miko is Paul Gilliam and our special guests, Holger Mueller, Mueller from constellation research analyst covering the space. Ray Wang was here earlier. You've been here for the duration. Um, we're going to break down the event. We'll do a wrap up here. Uh, we have huge impact event for 9,000 people. Uh, Paul, I want to go to you first and get your take on just the past two days. And we've got a lot of Kool-Aid injection attempts for Kool-Aid injection, but IBM people were very, very candid. I mean, I didn't find it, uh, very forceful at all from IBM. They're pragmatic. What's your thoughts on it? >>I think pragmatism is, is what I take away, John, if it gets a good, that's a good word for it. Uh, what I saw was a, uh, not a blockbuster. Uh, there was not a lot of, of, uh, of hype and overstatement about what the company was doing. I was impressed with Steve mills, but our interview with him yesterday, we asked about blockbuster acquisitions and he said basically, why, why, I mean, why should we take on a big acquisition that is going to create a headache, uh, for us in integrating into your organization? Let's focus on the spots where we have gaps and let's fill those. And that's really what they've, you know, they really have put their money where their mouth is and doing these 150 or more acquisitions over the last, uh, three or four years. Um, I think that the, the one question that I would have, I don't think there's any doubt about IBM's commitment to cloud as the future about their investment in big data analytics. They certainly have put their money where their mouth is. They're over $25 billion invested in big data analytics. One question I have coming out of this conference is about power and about the decision to exit the x86 market and really create confusion in a part of their business partners, their customers about about how they're going to fill that gap and where are they going to go for their actually needs and the power. Clearly power eight clearly is the future. It's the will fill that role in the IBM portfolio, but they've got to act fast. >>Do you think there's a ripple effect then so that that move I'll see cause a ripple effect in their ecosystem? >>Well, I was talking to a, I've talked to two IBM partners today, fairly large IBM partners and both of them have expressed that their customers are suffering some whiplash right now because all of a sudden the x86 option from IBM has gone away. And so it's frozen there. Their purchasing process and some of them are going to HP, some of them are looking at other providers. Um, I don't think IBM really has has told a coherent story to the markets yet about how >>and power's new. So they've got to prop that up. So you, so you're saying is okay, HP is going to get some new sales out of this, so frozen the for IBM and yet the power story's probably not clear. Is that what you're hearing? >>I don't think the power story is clear. I mean certainly it was news to me that IBM is taking on Intel at the, at this event and I was surprised that, that, >>that that was a surprise. Hold on, I've got to go to you because we've been sitting here the Cuban, we've been having all the execs come here and we've been getting briefed here in the cube. Shared that with the audience. You've been out on the ground, we've bumped into you guys, all, all the other analysts and all the briefings you've been in, the private sessions you've been in the rooms you've been, you've been, you've been out, out in the trenches there. What have you, what are you finding, what have you been hearing and what are the, some of the soundbites that you could share with the audience? It's not the classic God, Yemen, what are the differences? >>The Austin executives in cloud pedal, can you give me your body language? He had impact one year ago because they didn't have self layer at a time, didn't want to immediately actionable to do something involving what? A difference things. What in itself is fine, but I agree with what you said before is the messaging is they don't tell the customers, here's where we are right now. Take you by the hand. It's going to be from your door. And there's something called VMs. >>So it's very interesting. I mean I would consider IBM finalized the acquisition only last July. It's only been nine months since was acquired. Everything is software now. It leads me to think of who acquired who IBM acquired a software or did soflar actually acquire IBM because it seems to, SoftLayer is so strategic. IBM's cloud strategy going forward. >>Very strategic. I think it's probably why most transformative seemed like the Nexans agenda. And you've heard me say assault on a single thing. who makes it seven or eight weeks ago? It's moving very far. >>What do you think about the social business? Is that hanging together, that story? Hang on. It's obviously relevant direction. It's kind of a smarter planet positioning. Certainly businesses will be social. Are you seeing any meat on the bone there? On the collaboration side, >>one of the weakest parts, they have to be built again. Those again, they also have an additional for HR, which was this position, this stuff. It's definitely something which gives different change. >>I have to say, John, I was struck by the lack of discussion of social business in the opening keynote in particular a mobile mobile, big data. I mean that that came across very clear, but I've been accustomed to hearing that the social business rugby, they didn't, it didn't come out of this conference. >>Yeah. I mean my take on that was, is that >>I think it's pretty late. I don't think there's a lot of meat in the bone with the social, and I'll tell you why. I think it's like it's like the destination everyone wants to go to, but there's no really engine yet. Right. I think there's a lot of bicycle riding when they need a car. Right? So the infrastructure is just not is too embryonic, if you will. A lot of manual stuff going on. Even the analytics and you know you're seeing in the leaderboard here in the social media side and big data analytics. Certainly there are some core engine parts around IBM, but that social engine, I just don't see it happening. You risk requires a new kind of automation. It's got some real times, but I think that this is some, some nice bright spots. I love the streams. I love this zone's concept that we heard from Watson foundations. >>I think that is something that they need to pull out the war chest there and bring that front and center. I think the thinking about data as zones is really compelling and then I'll see mobile, they've got all the messaging on that and to give IBM to the benefit of the doubt. I mean they have a story now that they have a revenue generating story with cloud and with big data and social was never a revenue generating story. That's a software story. It's not big. It's not big dollars. And they've got something now that really they're really can drive. >>I'll tell you Chris Kristin from mobile first. She was very impressive and, and I'll tell you that social is being worked on. So I put the people are getting it. I mean IBM 100% gets social. I think the, the, it's not a gimmick to them. It's not like, Oh, we got some social media stuff. I think in the DNA of their soul, they, they come from that background of social. So I give them high marks on that. I just don't see the engine yet. I'm looking for analytics. I'm looking for a couple of eight cylinders. I just don't see it yet. You know, the engine, the engines, lupus and she wants to build the next generation of education. Big data, tons of mobile as the shoulder equivalent to social. I'm skeptical. I'm skeptical on Bloomix. I'll tell you why. I'm not skeptical. I shouldn't say that. >>It's going to get some plane mail for that. Okay. I'll say I'll see what's out there. I'll say it. I'm skeptical of Blumix because it could be a Wright brothers situation. Okay, look, I'm wrong guys building the wrong airplane. So the question is they might be on the wrong side of history if they don't watch the open source foundations because here's the problem. I have a blue mix, gets rushed to the market. Certainly IBM has got muscle solutions together. No doubt debting on cloud Foundry is really a risk and although people are pumping it up and it's got some momentum, they don't have a big community, they have a lot of marketing behind it and I know Jane's Wars over there is doing a great job and I'm Josh McKinsey over there with piston cloud. It'll behind it. It has all the elements of open collaboration and architecture or collaboration. However, if it's not a done deal yet in my mind, so that's a, that is a risk factor in my my mind. >>We've met a number of amazing, maybe you can help to do, to put these in order, a number of new concepts out there. We've got Bloomex the soft player, and we've got the marketplace, and these are all three concepts that approval, which is a subset of which, what's the hierarchy of these different platforms? >>That's hopefully, that's definitely at the bottom. The gives >>us visibility. You talk about the CIO and CSI all the time. Something you securities on every stupid LCO one on OCS and the marketplace. Basically naming the applications. Who would folded? IBM. IBM would have to meet opensource platform as a service. >>Well, it's not, even though it's not even open source and doing a deal with about foundries, so, so they've got, I think they're going in the middle. Where's their angle on that? But again, I like, again, the developer story's good, the people are solid. So I think it's not a fail of my, in my mind that all the messaging is great. But you know, we went to red hat summit, you know, they have a very active community, multiple generations in the data center, in the Indiana prize with Linux and, and open, you know, they're open, open shift is interesting. It's got traction and it's got legit traction. So that's one area. The other area I liked with Steve mills was he's very candid about this turf. They're staking out. Clearly the cloud game is up, is there is hardcore for them and in the IBM flavor enterprise cloud, they want to win the enterprise cloud. They clearly see Amazon, they see Amazon and its rhetoric and Grant's narrative and rhetoric against Amazon was interesting saying that there's more links on SoftLayer and Amazon. Now if you count links, then I think that number is skewed. So it's, you know, there's still a little bit of gamification going to have to dig into that. I didn't want to call him out on that, but know there's also a hosting business versus, you know, cloud parse the numbers. But what's your take on Amazon soft layer kind of comparison. >>It's, it's fundamentally different, right? Mustn't all shows everything. Why did see retailers moves is what to entirely use this software, gives them that visibility machine, this accommodation more conservatively knowing that I buy them, I can see that I can even go and physically touch that machine and I can only did the slowly into any cloud virtualization shed everything. >>Oh, Paul, I gotta say my favorite interview and I want to get your take on this. It was a Grady food. She was sat down with us and talk with us earlier today. IBM fell up, walks on water with an IBM Aussie legend in the computer industry. Just riveting conversation. I mean, it was really just getting started. I mean, it felt like we were like, you know, going into cruising altitude and then he just walked away. So they w what's your take on that conversation? >>Well, I mean, certainly he, uh, the gritty boujee interview, he gave us the best story of, of the two days, which is, uh, they're being in the hospital for open heart surgery, looking up, seeing the equipment, and it's going to be used to go into his chest and open his heart and knowing that he knows the people who program that, that equipment and they programmed it using a methodology that he invented. Uh, that, that, that's a remarkable story. But I think, uh, uh, the fact that that a great igloo can have a job at a company like IBM is a tribute to IBM. The fact that they can employ people like that who don't have a hard revenue responsibility. He's not a P. and. L, he's just, he's just a genius and he's a legend and he's an IBM to its crude, finds a place for people like that all throughout his organization. >>And that's why they never lost their soul in my opinion. You look at what HP and IBM, you know, IBM had a lot of reorganizations, a lot of pivots, so to speak, a lot of battleship that's turned this in way. But you know, for the most part they kept their R and D culture. >>But there's an interesting analogy too. Do you remember the case methodology was mutual support of them within the finance language that you mailed something because it was all about images, right? You would use this, this methodology, different vendors that were prior to the transport itself. Then I've yet to that credit, bring it together. bring and did a great service to all for software engineering. And maybe it's the same thing at the end, can play around diversity. >>You've got to give IBM process a great point. Earlier we, Steve mills made a similar reference around, it wasn't animosity, it was more of Hey, we've helped make Intel a big business, but the PC revolution, you know, where, what's in it for us? Right? You know, where's our, you know, help us out, throw us a bone. Or you know, you say you yell to Microsoft to go of course with the licensing fee with Gates, but this is the point, the unification story and with grays here, you know IBM has some real good cultural, you know industry Goodwill, you agree >>true North for IBM is the Antal quest customer. They'll do what's right where the money and the budget of the enterprise customers and press most want compatibility. They don't want to have staff, of course they want to have investment protection >>guys. I'd be able to do a good job of defining that as their cloud strategy that clearly are not going head to head with Amazon. It's a hybrid cloud strategy. They want to, they see the enterprise customers that legacy as as an asset and it's something they want to build on. Of course the risk of that is that Amazon right now is the pure play. It has all the momentum. It has all the buzz and and being tied to a legacy is not always the greatest thing in this industry, but from a practical revenue generating standpoint, it's pretty good. >>Hey guys, let's go down and wrap up here and get your final thoughts on the event. Um, and let's just go by the numbers, kind of the key things that IBM was promoting and then our kind of scorecard on kind of where they, where they kind of played out and new things that popped out of the woodwork that got your attention. You see the PO, the power systems thing was big on their messaging. Um, the big data story continues to be part of it. Blue mix central to the operations and the openness. You had a lot of open, open openness in their messaging and for the most part that's pretty much it. Um, well Watson, yeah, continue. Agents got up to Watson. >>Wow. A lot of news still to come out of Watson I think in many ways that is their, is their ACE in the hole and then that is their diamond. Any other thoughts? >>Well, what I missed is, which I think sets IBM apart from this vision, which is the idea of the API. Everybody else at that pure name stops the platform or says, I'm going to build like the org, I'm going to build you. That's a clear differentiator on the IBM side, which you still have to build part. They still have to figure out granularity surface that sets them apart that they have to give one. >>Yeah, and I think I give him an a plus on messaging. I think they're on all the right fault lines on the tectonic shifts that we're seeing. Everyone, I asked every every guest interview, what's the game changing moment? Why is it so important? And almost consistently the answers were, you know, we're living in a time of fast change data, you know, efficiency spare or you're going to be left behind. This is the confluence of all these trends, these fall lines. So I think IBM is sitting on these fall lines. Now the question is how fast can they cobbled together the tooling from the machineries that they have built over the years. Going back to the mainframe anniversary, it's out there. A lot of acquisitions, but, but so far the story and the story >>take the customer by the hand. That's the main challenge. I see. This wasn't often we do in Mexico, they want zero due to two times or they're chilling their conferences. It's the customer event and you know, and it's 9,000 people somehow have to do something to just show, right? So why is my wave from like distinguished so forth and so and so into? Well Lou mentioned, sure for the cloud, but how do we get there, right? What can we use, what am I SS and leverage? How do I call >>guys, really appreciate the commentary. Uh, this is going to be a wrap for us when just do a shout out to Matt, Greg and Patrick here doing a great job with the production here in the cube team and we have another cube team actually doing a simultaneous cube up in San Francisco service. Now you guys have done a great job here. And also shout out to Bert Latta Moore who's been doing a great job of live tweeting and help moderate the proud show, which was really a huge success and a great crowd chat this time. Hopefully we'll get some more influencers thought leaders in there for the next event and of course want to thank Paul Gillen for being an amazing cohost on this trip. Uh, I thought the questions and the and the cadence was fantastic. The guests were happy and hold there. Thank you for coming in on our wrap up. >>Really appreciate it. Constellation research. Uh, this is the cube. We are wrapping it up here at the IBM impact event here live in Las Vegas. It's the cube John furrier with Paul Gillen saying goodbye and see it. Our next event and stay tuned if it's look at angel dot DV cause we have continuous coverage of service now and tomorrow we will be broadcasting and commentating on the Facebook developer conference in San Francisco. We're running here, Mark Zuckerberg and all Facebook's developers and all their developer programs rolling out. So watch SiliconANGLE TV for that as well. Again, the cube is growing with thanks to you watching and thanks to all of our friends in the industry. Thanks for watching..