>>from Las Vegas. It's the Q covering. Next work. 2019 America's Do You buy Juniper Networks? Come back already. Jeffrey here with the Cube were in Las Vegas at Caesar's at the Juniper. Next work event. About 1000 people kind of going over a lot of new cool things. 400 gigs. Who knew that was coming out of new information for me? But that's not what we're here today. We're here for the fourth installment of around the Cube unpacking. I were happy to have all the winners of the three previous rounds here at the same place. We don't have to do it over the phone s so we're happy to have him. Let's jump into it. So winner of Round one was Bob Friday. He is the VP and CTO at Missed the Juniper Company. Bob, Great to see you. Good to be back. Absolutely. All the way from Seattle. Sharna Parky. She's a VP applied scientist at Tech CEO could see Sharna and, uh, from Google. We know a lot of a I happen to Google. Rajan's chef. He is the V p ay ay >>product management on Google. Welcome. Thank you, Christy. Here >>All right, so let's jump into it. So just warm everybody up and we'll start with you. Bob, What are some When you're talking to someone at a cocktail party Friday night talking to your mom And they say, What is a I What >>do you >>give him? A Zen examples of where a eyes of packing our lives today? >>Well, I think we all know the examples of the south driving car, you know? Aye, aye. Starting to help our health care industry being diagnosed cancer for me. Personally, I had kind of a weird experience last week at a retail technology event where basically had these new digital mirrors doing facial recognition. Right? And basically, you start to have little mirrors were gonna be a skeevy start guessing. Hey, you have a beard, you have some glasses, and they start calling >>me old. So this is kind >>of very personal. I have a something for >>you, Camille, but eh? I go walking >>down a mall with a bunch of mirrors, calling me old. >>That's a little Illinois. Did it bring you out like a cane or a walker? You know, you start getting some advertising's >>that were like Okay, you guys, this is a little bit over the top. >>Alright, Charlotte, what about you? What's your favorite example? Share with people? >>Yeah, E think one of my favorite examples of a I is, um, kind of accessible in on your phone where the photos you take on an iPhone. The photos you put in Google photos, they're automatically detecting the faces and their labeling them for you. They're like, Here's selfies. Here's your family. Here's your Children. And you know, that's the most successful one of the ones that I think people don't really think about a lot or things like getting loan applications right. We actually have a I deciding whether or not we get loans. And that one is is probably the most interesting one to be right now. >>Roger. So I think the father's example is probably my favorite as well. And what's interesting to me is that really a I is actually not about the Yeah, it's about the user experience that you can create as a result of a I. What's cool about Google photos is that and my entire family uses Google photos and they don't even know actually that the underlying in some of the most powerful a I in the world. But what they know is they confined every picture of our kids on the beach whenever they whenever they want to. Or, you know, we had a great example where we were with our kids. Every time they like something in the store, we take a picture of it, Um, and we can look up toy and actually find everything that they've taken picture. >>It's interesting because I think most people don't even know the power that they have. Because if you search for beach in your Google photos or you search for, uh, I was looking for an old bug picture from my high school there it came right up until you kind of explore. You know, it's pretty tricky, Raja, you know, I think a lot of conversation about A They always focus the general purpose general purpose, general purpose machines and robots and computers. But people don't really talk about the applied A that's happening all around. Why do you think that? >>So it's a good question. There's there's a lot more talk about kind of general purpose, but the reality of where this has an impact right now is, though, are those specific use cases. And so, for example, things like personalizing customer interaction or, ah, spotting trends that did that you wouldn't have spotted for turning unstructured data like documents into structure data. That's where a eyes actually having an impact right now. And I think it really boils down to getting to the right use cases where a I right? >>Sharon, I want ask you. You know, there's a lot of conversation. Always has A I replace people or is it an augmentation for people? And we had Gary Kasparov on a couple years ago, and he talked about, you know, it was the combination if he plus the computer made the best chess player, but that quickly went away. Now the computer is actually better than Garry Kasparov. Plus the computer. How should people think about a I as an augmentation tool versus a replacement tool? And is it just gonna be specific to the application? And how do you kind of think about those? >>Yeah, I would say >>that any application where you're making life and death decisions where you're making financial decisions that disadvantage people anything where you know you've got u A. V s and you're deciding whether or not to actually dropped the bomb like you need a human in the loop. If you're trying to change the words that you are using to get a different group of people to apply for jobs, you need a human in the loop because it turns out that for the example of beach, you type sheep into your phone and you might get just a field, a green field and a I doesn't know that, uh, you know, if it's always seen sheep in a field that when the sheep aren't there, that that isn't a sheep like it doesn't have that kind of recognition to it. So anything were we making decisions about parole or financial? Anything like that needs to have human in the loop because those types of decisions are changing fundamentally the way we live. >>Great. So shift gears. The team are Jeff Saunders. Okay, team, your mind may have been the liquid on my bell, so I'll be more active on the bell. Sorry about that. Everyone's even. We're starting a zero again, so I want to shift gears and talk about data sets. Um Bob, you're up on stage. Demo ing some some of your technology, the Miss Technology and really, you know, it's interesting combination of data sets A I and its current form needs a lot of data again. Kind of the classic Chihuahua on blue buried and photos. You got to run a lot of them through. How do you think about data sets? In terms of having the right data in a complete data set to drive an algorithm >>E. I think we all know data sets with one The tipping points for a I to become more real right along with cloud computing storage. But data is really one of the key points of making a I really write my example on stage was wine, right? Great wine starts a great grape street. Aye, aye. Starts a great data for us personally. L s t M is an example in our networking space where we have data for the last three months from our customers and rule using the last 30 days really trained these l s t m algorithms to really get that tsunami detection the point where we don't have false positives. >>How much of the training is done. Once you once you've gone through the data a couple times in a just versus when you first started, you're not really sure how it's gonna shake out in the algorithm. >>Yeah. So in our case right now, right, training happens every night. So every night, we're basically retraining those models, basically, to be able to predict if there's gonna be an anomaly or network, you know? And this is really an example. Where you looking all these other cat image thinks this is where these neural networks there really were one of the transformational things that really moved a I into the reality calling. And it's starting to impact all our different energy. Whether it's text imaging in the networking world is an example where even a I and deep learnings ruling starting to impact our networking customers. >>Sure, I want to go to you. What do you do if you don't have a big data set? You don't have a lot of pictures of chihuahuas and blackberries, and I want to apply some machine intelligence to the problem. >>I mean, so you need to have the right data set. You know, Big is a relative term on, and it depends on what you're using it for, right? So you can have a massive amount of data that represents solar flares, and then you're trying to detect some anomaly, right? If you train and I what normal is based upon a massive amount of data and you don't have enough examples of that anomaly you're trying to detect, then it's never going to say there's an anomaly there, so you actually need to over sample. You have to create a population of data that allows you to detect images you can't say, Um oh, >>I'm going to reflect in my data set the percentage of black women >>in Seattle, which is something below 6% and say it's fair. It's not right. You have to be able thio over sample things that you need, and in some ways you can get this through surveys. You can get it through, um, actually going to different sources. But you have to boot, strap it in some way, and then you have to refresh it, because if you leave that data set static like Bob mentioned like you, people are changing the way they do attacks and networks all the time, and so you may have been able to find the one yesterday. But today it's a completely different ball game >>project to you, which comes first, the chicken or the egg. You start with the data, and I say this is a ripe opportunity to apply some. Aye, aye. Or do you have some May I objectives that you want to achieve? And I got to go out and find the >>data. So I actually think what starts where it starts is the business problem you're trying to solve. And then from there, you need to have the right data. What's interesting about this is that you can actually have starting points. And so, for example, there's techniques around transfer, learning where you're able to take an an algorithm that's already been trained on a bunch of data and training a little bit further with with your data on DSO, we've seen that such that people that may have, for example, only 100 images of something, but they could use a model that's trained on millions of images and only use those 100 thio create something that's actually quite accurate. >>So that's a great segue. Wait, give me a ring on now. And it's a great Segway into talking about applying on one algorithm that was built around one data set and then applying it to a different data set. Is that appropriate? Is that correct? Is air you risking all kinds of interesting problems by taking that and applying it here, especially in light of when people are gonna go to outweigh the marketplace, is because I've got a date. A scientist. I couldn't go get one in the marketplace and apply to my data. How should people be careful not to make >>a bad decision based on that? So I think it really depends. And it depends on the type of machine learning that you're doing and what type of data you're talking about. So, for example, with images, they're they're they're well known techniques to be able to do this, but with other things, there aren't really and so it really depends. But then the other inter, the other really important thing is that no matter what at the end, you need to test and generate based on your based on your data sets and on based on sample data to see if it's accurate or not, and then that's gonna guide everything. Ultimately, >>Sharon has got to go to you. You brought up something in the preliminary rounds and about open A I and kind of this. We can't have this black box where stuff goes into the algorithm. That stuff comes out and we're not sure what the result was. Sounds really important. Is that Is that even plausible? Is it feasible? This is crazy statistics, Crazy math. You talked about the business objective that someone's trying to achieve. I go to the data scientist. Here's my data. You're telling this is the output. How kind of where's the line between the Lehman and the business person and the hard core data science to bring together the knowledge of Here's what's making the algorithm say this. >>Yeah, there's a lot of names for this, whether it's explainable. Aye, aye. Or interpret a belay. I are opening the black box. Things like that. Um, the algorithms that you use determine whether or not they're inspect herbal. Um, and the deeper your neural network gets, the harder it is to inspect, actually. Right. So, to your point, every time you take an aye aye and you use it in a different scenario than what it was built for. For example, um, there is a police precinct in New York that had a facial recognition software, and, uh, victim said, Oh, it looked like this actor. This person looked like Bill Cosby or something like that, and you were never supposed to take an image of an actor and put it in there to find people that look like them. But that's how people were using it. So the Russians point yes, like it. You can transfer learning to other a eyes, but it's actually the humans that are using it in ways that are unintended that we have to be more careful about, right? Um, even if you're a, I is explainable, and somebody tries to use it in a way that it was never intended to be used. The risk is much higher >>now. I think maybe I had, You know, if you look at Marvis kind of what we're building for the networking community Ah, good examples. When Marvis tries to do estimate your throughput right, your Internet throughput. That's what we usually call decision tree algorithm. And that's a very interpretive algorithm. and we predict low throughput. We know how we got to that answer, right? We know what features God, is there? No. But when we're doing something like a NAMI detection, that's a neural network. That black box it tells us yes, there's a problem. There's some anomaly, but that doesn't know what caused the anomaly. But that's a case where we actually used neural networks, actually find the anomie, and then we're using something else to find the root cause, eh? So it really depends on the use case and where the night you're going to use an interpreter of model or a neural network which is more of a black box model. T tell her you've got a cat or you've got a problem >>somewhere. So, Bob, that's really interested. So can you not unpacking? Neural network is just the nature of the way that the communication and the data flows and the inferences are made that you can't go in and unpack it, that you have to have the >>separate kind of process too. Get to the root cause. >>Yeah, assigned is always hard to say. Never. But inherently s neural networks are very complicated. Saito set of weights, right? It's basically usually a supervised training model, and we're feeding a bunch of data and trying to train it to detect a certain features, sir, an output. But that is where they're powerful, right? And that's why they basically doing such good, Because they are mimicking the brain, right? That neural network is a very complex thing. Can't like your brain, right? We really don't understand how your brain works right now when you have a problem, it's really trialling there. We try to figure out >>right going right. So I want to stay with you, bought for a minute. So what about when you change what you're optimizing? Four? So you just said you're optimizing for throughput of the network. You're looking for problems. Now, let's just say it's, uh, into the end of the quarter. Some other reason we're not. You're changing your changing what you're optimizing for, Can you? You have to write separate algorithm. Can you have dynamic movement inside that algorithm? How do you approach a problem? Because you're not always optimizing for the same things, depending on the market conditions. >>Yeah, I mean, I think a good example, you know, again, with Marvis is really with what we call reinforcement. Learning right in reinforcement. Learning is a model we use for, like, radio resource management. And there were really trying to optimize for the user experience in trying to balance the reward, the models trying to reward whether or not we have a good balance between the network and the user. Right, that reward could be changed. So that algorithm is basically reinforcement. You can finally change hell that Algren works by changing the reward you give the algorithm >>great. Um, Rajan back to you. A couple of huge things that have come into into play in the marketplace and get your take one is open source, you know, kind of. What's the impact of open source generally on the availability, desire and more applications and then to cloud and soon to be edge? You know, the current next stop. How do you guys incorporate that opportunity? How does it change what you can do? How does it open up the lens of >>a I Yeah, I think open source is really important because I think one thing that's interesting about a I is that it's a very nascent field and the more that there's open source, the more that people could build on top of each other and be able to utilize what what others others have done. And it's similar to how we've seen open source impact operating systems, the Internet, things like things like that with Cloud. I think one of the big things with cloud is now you have the processing power and the ability to access lots of data to be able to t create these thes networks. And so the capacity for data and the capacity for compute is much higher. Edge is gonna be a very important thing, especially going into next few years. You're seeing Maur things incorporated on the edge and one exciting development is around Federated learning where you can train on the edge and then combine some of those aspects into a cloud side model. And so that I think will actually make EJ even more powerful. >>But it's got to be so dynamic, right? Because the fundamental problem used to always be the move, the computer, the data or the date of the computer. Well, now you've got on these edge devices. You've got Tanya data right sensor data all kinds of machining data. You've got potentially nasty hostile conditions. You're not in a nice, pristine data center where the environmental conditions are in the connective ity issues. So when you think about that problem yet, there's still great information. There you got latent issues. Some I might have to be processed close to home. How do you incorporate that age old thing of the speed of light to still break the break up? The problem to give you a step up? Well, we see a lot >>of customers do is they do a lot of training on the cloud, but then inference on the on the edge. And so that way they're able to create the model that they want. But then they get fast response time by moving the model to the edge. The other thing is that, like you said, lots of data is coming into the edge. So one way to do it is to efficiently move that to the cloud. But the other way to do is filter. And to try to figure out what data you want to send to the clouds that you can create the next days. >>Shawna, back to you let's shift gears into ethics. This pesky, pesky issue that's not not a technological issue at all, but right. We see it often, especially in tech. Just cause you should just cause you can doesn't mean that you should. Um so and this is not a stem issue, right? There's a lot of different things that happened. So how should people be thinking about ethics? How should they incorporate ethics? Um, how should they make sure that they've got kind of a, you know, a standard kind of overlooking kind of what they're doing? The decisions are being made. >>Yeah, One of the more approachable ways that I have found to explain this is with behavioral science methodologies. So ethics is a massive field of study, and not everyone shares the same ethics. However, if you try and bring it closer to behavior change because every product that we're building is seeking to change of behavior. We need to ask questions like, What is the gap between the person's intention and the goal we have for them? Would they choose that goal for themselves or not? If they wouldn't, then you have an ethical problem, right? And this this can be true of the intention, goal gap or the intention action up. We can see when we regulated for cigarettes. What? We can't just make it look cool without telling them what the cigarettes are doing to them, right so we can apply the same principles moving forward. And they're pretty accessible without having to know. Oh, this philosopher and that philosopher in this ethicist said these things, it can be pretty human. The challenge with this is that most people building these algorithms are not. They're not trained in this way of thinking, and especially when you're working at a start up right, you don't have access to massive teams of people to guide you down this journey, so you need to build it in from the beginning, and you need to be open and based upon principles. Um, and it's going to touch every component. It should touch your data, your algorithm, the people that you're using to build the product. If you only have white men building the product, you have a problem you need to pull in other people. Otherwise, there are just blind spots that you are not going to think of in order to still that product for a wider audience, but it seems like >>they were on such a razor sharp edge. Right with Coca Cola wants you to buy Coca Cola and they show ads for Coca Cola, and they appeal to your let's all sing together on the hillside and be one right. But it feels like with a I that that is now you can cheat. Right now you can use behavioral biases that are hardwired into my brain is a biological creature against me. And so where is where is the fine line between just trying to get you to buy Coke? Which somewhat argues Probably Justus Bad is Jule cause you get diabetes and all these other issues, but that's acceptable. But cigarettes are not. And now we're seeing this stuff on Facebook with, you know, they're coming out. So >>we know that this is that and Coke isn't just selling Coke anymore. They're also selling vitamin water so they're they're play isn't to have a single product that you can purchase, but it is to have a suite of products that if you weren't that coke, you can buy it. But if you want that vitamin water you can have that >>shouldn't get vitamin water and a smile that only comes with the coat. Five. You want to jump in? >>I think we're going to see ethics really break into two different discussions, right? I mean, ethics is already, like human behavior that you're already doing right, doing bad behavior, like discriminatory hiring, training, that behavior. And today I is gonna be wrong. It's wrong in the human world is gonna be wrong in the eye world. I think the other component to this ethics discussion is really round privacy and data. It's like that mirror example, right? No. Who gave that mirror the right to basically tell me I'm old and actually do something with that data right now. Is that my data? Or is that the mirrors data that basically recognized me and basically did something with it? Right. You know, that's the Facebook. For example. When I get the email, tell me, look at that picture and someone's take me in the pictures Like, where was that? Where did that come from? Right? >>What? I'm curious about to fall upon that as social norms change. We talked about it a little bit for we turn the cameras on, right? It used to be okay. Toe have no black people drinking out of a fountain or coming in the side door of a restaurant. Not that long ago, right in the 60. So if someone had built an algorithm, then that would have incorporated probably that social norm. But social norms change. So how should we, you know, kind of try to stay ahead of that or at least go back reflectively after the fact and say kind of back to the black box, That's no longer acceptable. We need to tweak this. I >>would have said in that example, that was wrong. 50 years ago. >>Okay, it was wrong. But if you ask somebody in Alabama, you know, at the University of Alabama, Matt Department who have been born Red born, bred in that culture as well, they probably would have not necessarily agreed. But so generally, though, again, assuming things change, how should we make sure to go back and make sure that we're not again carrying four things that are no longer the right thing to do? >>Well, I think I mean, as I said, I think you know what? What we know is wrong, you know is gonna be wrong in the eye world. I think the more subtle thing is when we start relying on these Aye. Aye. To make decisions like no shit in my car, hit the pedestrian or save my life. You know, those are tough decisions to let a machine take off or your balls decision. Right when we start letting the machines Or is it okay for Marvis to give this D I ps preference over other people, right? You know, those type of decisions are kind of the ethical decision, you know, whether right or wrong, the human world, I think the same thing will apply in the eye world. I do think it will start to see more regulation. Just like we see regulation happen in our hiring. No, that regulation is going to be applied into our A I >>right solutions. We're gonna come back to regulation a minute. But, Roger, I want to follow up with you in your earlier session. You you made an interesting comment. You said, you know, 10% is clearly, you know, good. 10% is clearly bad, but it's a soft, squishy middle at 80% that aren't necessarily super clear, good or bad. So how should people, you know, kind of make judgments in this this big gray area in the middle? >>Yeah, and I think that is the toughest part. And so the approach that we've taken is to set us set out a set of AI ai principles on DDE. What we did is actually wrote down seven things that we will that we think I should do and four things that we should not do that we will not do. And we now have to actually look at everything that we're doing against those Aye aye principles. And so part of that is coming up with that governance process because ultimately it boils down to doing this over and over, seeing lots of cases and figuring out what what you should do and so that governments process is something we're doing. But I think it's something that every company is going to need to do. >>Sharon, I want to come back to you, so we'll shift gears to talk a little bit about about law. We've all seen Zuckerberg, unfortunately for him has been, you know, stuck in these congressional hearings over and over and over again. A little bit of a deer in a headlight. You made an interesting comment on your prior show that he's almost like he's asking for regulation. You know, he stumbled into some really big Harry nasty areas that were never necessarily intended when they launched Facebook out of his dorm room many, many moons ago. So what is the role of the law? Because the other thing that we've seen, unfortunately, a lot of those hearings is a lot of our elected officials are way, way, way behind there, still printing their e mails, right? So what is the role of the law? How should we think about it? What shall we What should we invite from fromthe law to help sort some of this stuff out? >>I think as an individual, right, I would like for each company not to make up their own set of principles. I would like to have a shared set of principles that were following the challenge. Right, is that with between governments, that's impossible. China is never gonna come up with same regulations that we will. They have a different privacy standards than we D'oh. Um, but we are seeing locally like the state of Washington has created a future of work task force. And they're coming into the private sector and asking companies like text you and like Google and Microsoft to actually advise them on what should we be regulating? We don't know. We're not the technologists, but they know how to regulate. And they know how to move policies through the government. What will find us if we don't advise regulators on what we should be regulating? They're going to regulate it in some way, just like they regulated the tobacco industry. Just like they regulated. Sort of, um, monopolies that tech is big enough. Now there is enough money in it now that it will be regularly. So we need to start advising them on what we should regulate because just like Mark, he said. While everyone else was doing it, my competitors were doing it. So if you >>don't want me to do it, make us all stop. What >>can I do? A negative bell and that would not for you, but for Mark's responsibly. That's crazy. So So bob old man at the mall. It's actually a little bit more codified right, There's GDP are which came through May of last year and now the newness to California Extra Gatorade, California Consumer Protection Act, which goes into effect January 1. And you know it's interesting is that the hardest part of the implementation of that I think I haven't implemented it is the right to be for gotten because, as we all know, computers, air, really good recording information and cloud. It's recorded everywhere. There's no there there. So when these types of regulations, how does that impact? Aye, aye, because if I've got an algorithm built on a data set in in person, you know, item number 472 decides they want to be forgotten How that too I deal with that. >>Well, I mean, I think with Facebook, I can see that as I think. I suspect Mark knows what's right and wrong. He's just kicking ball down tires like >>I want you guys. >>It's your problem, you know. Please tell me what to do. I see a ice kind of like any other new technology, you know, it could be abused and used in the wrong waste. I think legally we have a constitution that protects our rights. And I think we're going to see the lawyers treat a I just like any other constitutional things and people who are building products using a I just like me build medical products or other products and actually harmful people. You're gonna have to make sure that you're a I product does not harm people. You're a product does not include no promote discriminatory results. So I >>think we're going >>to see our constitutional thing is going applied A I just like we've seen other technologies work. >>And it's gonna create jobs because of that, right? Because >>it will be a whole new set of lawyers >>the holdings of lawyers and testers, even because otherwise of an individual company is saying. But we tested. It >>works. Trust us. Like, how are you gonna get the independent third party verification of that? So we're gonna start to see a whole terrorist proliferation of that type of fields that never had to exist before. >>Yeah, one of my favorite doctor room. A child. Grief from a center. If you don't follow her on Twitter Follower. She's fantastic and a great lady. So I want to stick with you for a minute, Bob, because the next topic is autonomous. And Rahman up on the keynote this morning, talked about missed and and really, this kind of shifting workload of fixing things into an autonomous set up where the system now is, is finding problems, diagnosing problems, fixing problems up to, I think, he said, even generating return authorizations for broken gear, which is amazing. But autonomy opens up all kinds of crazy, scary things. Robert Gates, we interviewed said, You know, the only guns that are that are autonomous in the entire U. S. Military are the ones on the border of North Korea. Every single other one has to run through a person when you think about autonomy and when you can actually grant this this a I the autonomy of the agency toe act. What are some of the things to think about in the word of the things to keep from just doing something bad, really, really fast and efficiently? >>Yeah. I mean, I think that what we discussed, right? I mean, I think Pakal purposes we're far, you know, there is a tipping point. I think eventually we will get to the CP 30 Terminator day where we actually build something is on par with the human. But for the purposes right now, we're really looking at tools that we're going to help businesses, doctors, self driving cars and those tools are gonna be used by our customers to basically allow them to do more productive things with their time. You know, whether it's doctor that's using a tool to actually use a I to predict help bank better predictions. They're still gonna be a human involved, you know, And what Romney talked about this morning and networking is really allowing our I T customers focus more on their business problems where they don't have to spend their time finding bad hard were bad software and making better experiences for the people. They're actually trying to serve >>right, trying to get your take on on autonomy because because it's a different level of trust that we're giving to the machine when we actually let it do things based on its own. But >>there's there's a lot that goes into this decision of whether or not to allow autonomy. There's an example I read. There's a book that just came out. Oh, what's the title? You look like a thing. And I love you. It was a book named by an A I, um if you want to learn a lot about a I, um and you don't know much about it, Get it? It's really funny. Um, so in there there is in China. Ah, factory where the Aye Aye. Is optimizing um, output of cockroaches now they just They want more cockroaches now. Why do they want that? They want to grind them up and put them in a lotion. It's one of their secret ingredients now. It depends on what parameters you allow that I to change, right? If you decide Thio let the way I flood the container, and then the cockroaches get out through the vents and then they get to the kitchen to get food, and then they reproduce the parameters in which you let them be autonomous. Over is the challenge. So when we're working with very narrow Ai ai, when use hell the Aye. Aye. You can change these three things and you can't just change anything. Then it's a lot easier to make that autonomous decision. Um and then the last part of it is that you want to know what is the results of a negative outcome, right? There was the result of a positive outcome. And are those results something that we can take actually? >>Right, Right. Roger, don't give you the last word on the time. Because kind of the next order of step is where that machines actually write their own algorithms, right? They start to write their own code, so they kind of take this next order of thought and agency, if you will. How do you guys think about that? You guys are way out ahead in the space, you have huge data set. You got great technology. Got tensorflow. When will the machines start writing their own A their own out rhythms? Well, and actually >>it's already starting there that, you know, for example, we have we have a product called Google Cloud. Ottawa. Mel Village basically takes in a data set, and then we find the best model to be able to match that data set. And so things like that that that are there already, but it's still very nascent. There's a lot more than that that can happen. And I think ultimately with with how it's used I think part of it is you have to start. Always look at the downside of automation. And what is what is the downside of a bad decision, whether it's the wrong algorithm that you create or a bad decision in that model? And so if the downside is really big, that's where you need to start to apply Human in the loop. And so, for example, in medicine. Hey, I could do amazing things to detect diseases, but you would want a doctor in the loop to be able to actually diagnose. And so you need tohave have that place in many situations to make sure that it's being applied well. >>But is that just today? Or is that tomorrow? Because, you know, with with exponential growth and and as fast as these things are growing, will there be a day where you don't necessarily need maybe need the doctor to communicate the news? Maybe there's some second order impacts in terms of how you deal with the family and, you know, kind of pros and cons of treatment options that are more emotional than necessarily mechanical, because it seems like eventually that the doctor has a role. But it isn't necessarily in accurately diagnosing a problem. >>I think >>I think for some things, absolutely over time the algorithms will get better and better, and you can rely on them and trust them more and more. But again, I think you have to look at the downside consequence that if there's a bad decision, what happens and how is that compared to what happens today? And so that's really where, where that is. So, for example, self driving cars, we will get to the point where cars are driving by themselves. There will be accidents, but the accident rate is gonna be much lower than what's there with humans today, and so that will get there. But it will take time. >>And there was a day when will be illegal for you to drive. You have manslaughter, right? >>I I believe absolutely there will be in and and I don't think it's that far off. Actually, >>wait for the day when I have my car take me up to Northern California with me. Sleepy. I've only lived that long. >>That's right. And work while you're while you're sleeping, right? Well, I want to thank everybody Aton for being on this panel. This has been super fun and these air really big issues. So I want to give you the final word will just give everyone kind of a final say and I just want to throw out their Mars law. People talk about Moore's law all the time. But tomorrow's law, which Gardner stolen made into the hype cycle, you know, is that we tend to overestimate in the short term, which is why you get the hype cycle and we turn. Tend to underestimate, in the long term the impacts of technology. So I just want it is you look forward in the future won't put a year number on it, you know, kind of. How do you see this rolling out? What do you excited about? What are you scared about? What should we be thinking about? We'll start with you, Bob. >>Yeah, you know, for me and, you know, the day of the terminus Heathrow. I don't know if it's 100 years or 1000 years. That day is coming. We will eventually build something that's in part of the human. I think the mission about the book, you know, you look like a thing and I love >>you. >>Type of thing that was written by someone who tried to train a I to basically pick up lines. Right? Cheesy pickup lines. Yeah, I'm not for sure. I'm gonna trust a I to help me in my pickup lines yet. You know I love you. Look at your thing. I love you. I don't know if they work. >>Yeah, but who would? Who would have guessed online dating is is what it is if you had asked, you know, 15 years ago. But I >>think yes, I think overall, yes, we will see the Terminator Cp through It was probably not in our lifetime, but it is in the future somewhere. A. I is definitely gonna be on par with the Internet cell phone, radio. It's gonna be a technology that's gonna be accelerating if you look where technology's been over last. Is this amazing to watch how fast things have changed in our lifetime alone, right? Yeah, we're just on this curve of technology accelerations. This in the >>exponential curves China. >>Yeah, I think the thing I'm most excited about for a I right now is the addition of creativity to a lot of our jobs. So ah, lot of we build an augmented writing product. And what we do is we look at the words that have happened in the world and their outcomes. And we tell you what words have impacted people in the past. Now, with that information, when you augment humans in that way, they get to be more creative. They get to use language that have never been used before. To communicate an idea. You can do this with any field you can do with composition of music. You can if you can have access as an individual, thio the data of a bunch of cultures the way that we evolved can change. So I'm most excited about that. I think I'm most concerned currently about the products that we're building Thio Give a I to people that don't understand how to use it or how to make sure they're making an ethical decision. So it is extremely easy right now to go on the Internet to build a model on a data set. And I'm not a specialist in data, right? And so I have no idea if I'm adding bias in or not, um and so it's It's an interesting time because we're in that middle area. Um, and >>it's getting loud, all right, Roger will throw with you before we have to cut out, or we're not gonna be able to hear anything. So I actually start every presentation out with a picture of the Mosaic browser, because what's interesting is I think that's where >>a eyes today compared to kind of weather when the Internet was around 1994 >>were just starting to see how a I can actually impact the average person. As a result, there's a lot of hype, but what I'm actually finding is that 70% of the company's I talked to the first question is, Why should I be using this? And what benefit does it give me? Why 70% ask you why? Yeah, and and what's interesting with that is that I think people are still trying to figure out what is this stuff good for? But to your point about the long >>run, and we underestimate the longer I think that every company out there and every product will be fundamentally transformed by eye over the course of the next decade, and it's actually gonna have a bigger impact on the Internet itself. And so that's really what we have to look forward to. >>All right again. Thank you everybody for participating. There was a ton of fun. Hope you had fun. And I look at the score sheet here. We've got Bob coming in and the bronze at 15 points. Rajan, it's 17 in our gold medal winner for the silver Bell. Is Sharna at 20 points. Again. Thank you. Uh, thank you so much and look forward to our next conversation. Thank Jeffrey Ake signing out from Caesar's Juniper. Next word unpacking. I Thanks for watching.

>> live from Las Vegas. It's the queue covering Dell Technologies. World twenty nineteen. Brought to you by Dell Technologies and its ecosystem partners. >> The one Welcome to the Special Cube Live coverage here in Las Vegas with Dell Technologies World 2019. I'm John Furrier with Dave Vellante breaking down day one of three days of wall the wall Coverage - 2 Cube sets. Uh, big news today and dropping here. Dell Technology World's series of announcements Cloud ability, unified work spaces and then multi cloud with, uh, watershed announced with Microsoft support for VMware with Azure are guests here theCUBE alumni that Seo, senior leader of'Em Where Sanjay *** and such a great to see you, >> John and Dave always a pleasure to be on your show. >> So before we get into the hard core news around Microsoft because you and Satya have a relationship, you also know Andy Jassy very well. You've been following the Clouds game in a big way, but also as a senior leader in the industry and leading BM where, um, the evolution of the end user computing kind of genre,  that whole area is just completely transformed with mobility and cloud kind of coming together with data and all this new kinds of applications. The modern applications are different. It's changing the game on how end users, employees, normal people use computing because some announcement here on their What's your take on the ever changing role of cloud and user software? >> Yeah, John, I think that our vision , as  you know, it was the first job I came to do at VMware almost six years ago, to run and use a computing. And the vision we had at that time was that you should be able to work at the speed of life, right? You and I happen to be on a plane at the same time  yesterday coming here, we should be able to pick our amps up on our devices. You often have Internet now even up at thirty thousand feet. In the consumer world, you don't lug around your CDs, your music, your movies come to you. So the vision of any app on any device was what we articulated with the digital workspace We. had Apple and Google very well figured out. IOS later on Mac,  Android,  later on chrome . The Microsoft relationship in end use the computing was contentious because we overlapped. They had a product, PMS and in tune. But we always dreamed of a day. I tweeted out this morning that for five and a half years I competed with these guys. It was always my dream to partner with the With Microsoft. Um, you know, a wonderful person, whom I respect there, Brad Anderson. He's a friend, but we were like LeBron and Steph Curry. We were competing against each other. Today everything changed. We are now partners. Uh, Brad and I we're friends, we'll still be friends were actually partners  now why? Because we want to bring the best of the digital workspace solution VMware brings workspace one to the best of what Microsoft brings in Microsoft 365 , active directory, E3 capabilities around E. M. S and into it and combined those together to help customers get the best for any device. Apple, Google and Microsoft that's a game changer. >> Tell about the impact of the real issue of Microsoft on this one point, because is there overlap is their gaps, as Joe Tucci used to say, You can't have any. There's no there's no overlap if you have overlapped. That's not a >> better to have overlapped and seems right. A gaps. >> So where's the gaps? Where this words the overlapping cloud. Next, in the end user world, >> there is a little bit of overlap. But the much bigger picture is the complementarity. We are, for example, not trying to be a directory in the Cloud That's azure active directory, which is the sequel to Active Directory. So if we have an identity access solution that connect to active directory, we're gonna compliment that we've done that already. With Octo. Why not do that? Also inactive Directory Boom that's clear. Ignored. You overlap. Look at the much bigger picture. There's a little bit of overlap between in tune and air Watch capabilities, but that's not the big picture. The big picture is combining workspace one with E. M s. to allow Office 365 customers to get conditional access. That's a game, so I think in any partnership you have to look past, I call it sort of these Berlin Wall moments. If the U. S and Soviet Union will fighting over like East Germany, vs West Germany, you wouldn't have had that Berlin wall moment. You have to look past the overlaps. Look at the much bigger picture and I find the way by which the customer wins. When the customer wins, both sides are happy. >> Tearing down the access wall, letting you get seamless. Access the data. All right, Cloud computing housely Multi cloud announcement was azure something to tell on stage, which was a surprise no one knew was coming. No one was briefed on this. It was kind of the hush hush, the big news Michael Delll, Pat Girl singer and it's nothing to tell up there. Um, Safia did a great job and really shows the commitment of Microsoft with the M wear and Dell Technologies. What is this announcement? First, give us your take an analysis of what they announced. And what does it mean? Impact the customers? >> Yeah, listen, you know, for us, it's a further That's what, like the chess pieces lining up of'Em wars vision that we laid up many years for a hybrid cloud world where it's not all public cloud, it isn't all on premise. It's a mixture. We coined that Tom hybrid loud, and we're beginning to see that realize So we had four thousand cloud providers starting to build a stack on VM, where we announced IBM Cloud and eight of us. And they're very special relationships. But customers, some customers of azure, some of the retailers, for example, like Wal Mart was quoted in the press, released Kroger's and some others so they would ask us, Listen, we're gonna have a way by which we can host BMO Workloads in there. So, through a partnership now with Virtue Stream that's owned by Dell on DH er, we will be able to allow we, um, where were close to run in Virtue Stream. Microsoft will sell that solution as what's called Azure V M, where solutions and customers now get the benefit of GMO workloads being able to migrate there if they want to. Or my great back on the on premise. We want to be the best cloud infrastructure for that multi cloud world. >> So you've got IBM eight of us Google last month, you know, knock down now Azure Ali Baba and trying you. Last November, you announced Ali Baba, but not a solution. Right >> now, it's a very similar solutions of easy solution. There's similar what's announced with IBM and Nash >> So is it like your kids where you loved them all equally or what? You just mentioned it that Microsoft will sell the VM wear on Azure. You actually sell the eight of us, >> so there is a distinction. So let me make that clear because everything on the surface might look similar. We have built a solution that is first and preferred for us. Called were MacLeod on a W s. It's a V m er manage solution where the Cloud Foundation stack compute storage networking runs on a ws bare metal, and V. Ember manages that our reps sell that often lead with that. And that's a solution that's, you know, we announced you were three years ago. It's a very special relationship. We have now customer attraction. We announce some big deals in queue, for that's going great, and we want it even grow faster and listen. Eight of us is number one in the market, but there are the customers who have azure and for customers, one azure very similar. You should think of this A similar to the IBM ah cloud relationship where the V C P. V Partners host VM where, and they sell a solution and we get a subscription revenue result out of that, that's exactly what Microsoft is doing. Our reps will get compensated when they sell at a particular customer, but it's not a solution that's managed by BM. Where >> am I correct? You've announced that I think a twenty million dollars deal last quarter via MacLeod and A W. And that's that's an entire deal. Or is that the video >> was Oh, that was an entirely with a customer who was making a big shift to the cloud. When I talked to that customer about the types of workloads, they said that they're going to move hundreds off their APs okay on premise onto via MacLeod. And it appears, so that's, you know, that's the type of cloud transformation were doing. And now with this announcement, there will be other customers. We gave an example of few that Well, then you're seeing certain verticals that are picking as yours. We want those two also be happy. Our goal is to be the undisputed cloud infrastructure for any cloud, any cloud, any AP any device. >> I want to get your thoughts. I was just in the analysts presentation with Dell technology CFO and looking at the numbers, the performance numbers on the revenue side Don Gabin gap our earnings as well as market share. Dell. That scales because Michael Delll, when we interviewed many years ago when it was all going down, hinted that look at this benefits that scale and not everyone's seeing the obvious that we now know what the Amazon scale winds so scale is a huge advantage. Um, bm Where has scale Amazon's got scale as your Microsoft have scales scales Now the new table stakes just as an industry executive and leader as you look at the mark landscape, it's a having have not world you'd have scale. You don't If you don't have scale, you're either ecosystem partner. You're in a white space. How do companies compete in this market? Sanjay, what's your thoughts on I thinkit's >> Jonah's? You said there is a benefit to scale Dell, now at about ninety billion in revenue, has gone public on their stock prices. Done where Dellvin, since the ideal thing, the leader >> and sir, is that point >> leader in storage leader inclined computing peces with Vienna and many other assets like pivotal leaders and others. So that scale VM, Where about a ten billion dollar company, fifth largest software company doing verywell leader in the softer to find infrastructure leader, then use a computing leader and softer, defined networking. I think you need the combination of scale and speed, uh, just scale on its own. You could become a dinosaur, right? And what's the fear that every big company should have that you become ossified? And I think what we've been able to show the world is that V M wear and L can move with scale and speed. It's like having the combination of an elephant and a cheetah and won and that to me special. And for companies like us that do have scaled, we've to constantly ask ourselves, How do we disrupt ourselves? How do we move faster? How do we partner together? How do we look past these blind spots? How do we pardon with big companies, small companies and the winner is the customer. That's the way we think. And we could keep doing that, you'll say so. For example, five, six years ago, nobody thought of VMware--this is going before Dell or EMC--in the world of networking, quietly with ten thousand customers, a two million dollar run rate, NSX has become the undisputed leader and software-defined networking. So now we've got a combination of server, storage and a networking story and Dell VMware, where that's very strong And that's because we moved with speed and with scale. >> So of course, that came to an acquisition with Nice Sarah. Give us updates on the recent acquisitions. Hep C e o of Vela Cloud. What's happening there? >> Yeah, we've done three. That, I think very exciting to kind of walk through them in chronological order about eighteen months ago was Velo Cloud. We're really excited about that. It's sort of like the name, velocity and cloud fast. Simple Cloud based. It is the best solution. Ston. How do we come to deciding that we went to talk to our partners like t other service providers? They were telling us this is the best solution in town. It connects to the data center story to the cloud story and allows our virtual cloud network to be the best softer. To find out what you can, you have your existing Mpls you might have your land infrastructure but there's nobody who does softer to find when, like Philip, they're excited about that cloud health. We're very excited about that because that brings a multi cloud management like, sort of think of it like an e r P system on top of a w eso azure to allow you to manage your costs and resource What ASAP do it allows you to manage? Resource is for materials world manufacturing world. In this world, you've got resources that are sitting on a ws or azure. Uh, cloud held does it better than anybody else. Hefty. Oh, now takes a Cuban eighty story that we'd already begun with pivotal and with Google is you remember at at PM world two years ago. And that's that because the founders of Cuban eighties left Google and started FTO. So we're bringing that DNA we've become now one of the top two three contributors to communities, and we want to continue to become the de facto platform for containers. If you go to some of the airports in San Francisco, New York, I think Keilani and Heathrow to you'LL see these ads that are called container where okay, where do you think the Ware comes from Vienna, where, OK, and our goal is to make containers as container where you know, come to you from the company that made vmc possible of'Em where So if we popularized PM's, why not also popularised the best enterprise contain a platform? That's what helped you will help us do >> talk about Coburn at ease for a minute because you have an interesting bridge between end user computing and their cloud. The service is micro. Services that are coming on are going to be powering all these APS with either data and or these dynamic services. Cooper, Nettie sees me the heart of that. We've been covering it like a blanket. Um, I'm gonna get your take on how important that is. Because back Nelson, you're setting the keynote at the Emerald last year. Who burn it eases the dial tone. Is Cooper Netease at odds with having a virtual machine or they complimentary? How does that evolving? Is it a hedge? What's the thoughts there? >> Yeah, First off, Listen, I think the world has begun to realize it is a world of containers and V ems. If you looked at the company that's done the most with containers. Google. They run their containers in V EMS in their cloud platform, so it's not one or the other. It's vote. There may be a world where some parts of containers run a bare metal, but the bulk of containers today run and Beyonce And then I would say, Secondly, you know, five. Six years ago, people all thought that Doctor was going to obliterate VM where, But what happened was doctors become a very good container format, but the orchestration layer from that has not become daugher. In fact, Cuban Eddie's is kind of taking a little of the head and steam off Dr Swarm and Dr Enterprise, and it is Cooper Navy took the steam completely away. So Senses Way waited for the right time to embrace containers because the obvious choice initially would have been some part of the doctor stack. We waited as Borg became communities. You know, the story of how that came on Google. We've embraced that big time, and we've stated a very important ball hefty on All these moves are all part of our goal to become the undisputed enterprise container platform, and we think in a multi cloud world that's ours to lose. Who else can do multi cloud better than VM? Where may be the only company that could have done that was Red Hat. Not so much now, inside IBM, I think we have the best chance of doing that relative. Anybody else >> Sanjay was talking about on our intro this morning? Keynote analysis. Talking about the stock price of Dell Technologies, comparing the stock price of'Em where clearly the analysis shows that the end was a big part of the Dell technologies value. How would you summarize what v m where is today? Because on the Kino there was a Bank of America customers. She said she was the CTO ran, she says, Never mind. How we got here is how we go floors the end wars in a similar situation where you've got so much success, you always fighting for that edge. But as you go forward as a company, there's all these new opportunities you outlined some of them. What should people know about the VM? We're going forward. What is the vision in your words? What if what is VM where >> I think packed myself and all of the key people among the twenty five thousand employees of'Em are trying to create the best infrastructure company of all time for twenty one years. Young. OK, and I think we have an opportunity to create an incredible brand. We just have to his use point on the begins show create platforms. The V's fear was a platform. Innocent is a platform workspace. One is a platform V san, and the hyper convert stack of weeks right becomes a platform that we keep doing. That Carbonetti stuff will become a platform. Then you get platforms upon platforms. One platforms you create that foundation. Stone now is released. ADelle. I think it's a better together message. You take VX rail. We should be together. The best option relative to smaller companies like Nutanix If you take, you know Veum Where together with workspace one and laptops now put Microsoft in the next. There's nobody else. They're small companies like Citrix Mobile. I'm trying to do it. We should be better than them in a multi cloud world. They maybe got the companies like Red Hat. We should have bet on them. That said, the end. Where needs toe also have a focus when customers don't have Dale infrastructure. Some people may have HP servers and emcee storage or Dell Silvers and netapp storage or neither. Dellery emcee in that case, usually via where, And that's the way we roll. We want to be relevant to a multi cloud, multi server, multi storage, any hardware, any cloud. Any AP any device >> I got. I gotta go back to the red hat. Calm in a couple of go. I could see you like this side of IBM, right? So So it looks like a two horse race here. I mean, you guys going hard after multi cloud coming at it from infrastructure, IBM coming at it with red hat from a pass layer. I mean, if I were IBM, I had learned from VM where leave it alone, Let it blossom. I mean, we have >> a very good partisan baby. Let me first say that IBM Global Services GTS is one about top sai partners. We do a ton of really good work with them. Uh, I'm software re partner number different areas. Yeah, we do compete with red hat with the part of their portfolios. Relate to contain us. Not with Lennox. Eighty percent plus of their businesses. Lennox, They've got parts of J Boss and Open Stack that I kind of, you know, not doing so well. But we do compete with open ship. That's okay, but we don't know when we can walk and chew gum so we can compete with Red Hat. And yet partner with IBM. That's okay. Way just need to be the best at doing containing platform is better than open shifter. Anybody, anything that red hat has were still partner with IBM. We have to be able to look at a world that's not black and white. And this partnership with Microsoft is a good example. >> It's not a zero sum game, and it's a huge market in its early days. Talk >> about what's up for you now. What's next? What's your main focus? What's your priorities? >> Listen, we're getting ready for VM World now. You know in August we want to continue to build momentum on make many of these solutions platforms. So I tell our sales reps, take the number of customers you have and add a zero behind that. OK, so if you've got ten thousand customers of NSX, how do we get one hundred thousand customers of insects. You have nineteen thousand customers of Visa, which, by the way, significantly head of Nutanix. How do we have make one hundred ninety thousand customers? And we have that base? Because we have V sphere and we have the Delll base. We have other partners. We have, I think, eighty thousand customers off and use of computing tens of millions of devices. How do we make sure that we are workspace? One is on billion. Device is very much possible. That's the vision. >> I think that I think what's resonating for me when I hear you guys, when you hear you talk when we have conversations also in Pat on stage talks about it, the simplification message is a good one and the consistency of operating across multiple environments because it sounds great that if you can achieve that, that's a good thing. How you guys get into how you making it simple to run I T. And consistent operating environment. It's all about keeping the customer in the middle of this. And when we listen to customs, all of these announcements the partnership's when there was eight of us, Microsoft, anything that we've done, it's about keeping the customer first, and the customer is basically guiding up out there. And often when I sit down with customers, I had the privilege of talking hundreds of thousands of them. Many of these CEOs the S and P five hundred I've known for years from S athe of'Em were they'LL Call me or text me. They want us to be a trusted advisor to help them understand where and how they should move in their digital transformation and compared their journey to somebody else's. So when we can bring the best off, for example, of developer and operations infrastructure together, what's called DEV Ops customers are wrestling threw that in there cloud journey when we can bring a multi device world with additional workspace. Customers are wrestling that without journey there, trying to figure out how much they keep on premise how much they move in the cloud. They're thinking about vertical specific applications. All of these places where if there's one lesson I've learned in my last ten twenty years of it has become a trusted advisor to your customers. Lean on them and they will lean on you on when you do that. I mean the beautiful world of technology is there's always stuff to innovate. >> Well, they have to lean on you because they can't mess around with all this infrastructure. They'LL never get their digital transformation game and act together, right? Actually, >>= it's great to see you. We'Ll see you at PM, >> Rollo. Well, well, come on, we gotta talk hoops. All right, All right, All right, big. You're a big warriors fan, right? We're Celtics fan. Would be our dream, for both of you are also Manny's themselves have a privileged to go up against the great Warriors. But what's your prediction this year? I mean, I don't know, and I >> really listen. I love the warriors. It's ah, so in some senses, a little bit of a tougher one. Now the DeMarcus cousins is out for, I don't know, maybe all the playoffs, but I love stuff. I love Katie. I love Clay, you know, and many of those guys is gonna be a couple of guys going free agents, so I want to do >> it again. Joy. Well, last because I don't see anybody stopping a Celtics may be a good final. That would be fun if they don't make it through the rafters, though. That's right. Well, I Leonard, it's tough to make it all right. That sounds great. >> Come on. Sanjay Putin, CEO of BM Wear Inside the Cube, Breaking down his commentary of you on the landscape of the industry and the big news with Microsoft there. Other partner's bringing you all the action here Day one of three days of coverage here in the Cubicle two sets a canon of cube coverage out there. We're back with more after this short break.

>> Narrator: Live from Las Vegas, it's the CUBE covering Service Now Knowledge 2018. Brought to you by Service Now. >> Welcome back to Service Now Knowledge 18 this is the CUBE's live coverage. We are the leader in live technology coverage. We extract the signal from the noise. I'm Rebecca Knight your host along with my cohost Dave Vellante. We've got a great panel right now. We have Andrew Wilson who is the CIO of Accenture and Ellen Shook who is the chief leadership in human resources officer at Accenture. Thanks so much for coming on the show. >> Thanks for having us. >> Hello great to be back. >> Good to see you again. >> Before the cameras were rolling we were talking about people driven change. But Accenture not but, and Accenture is a huge organization. 400,000 plus individuals working around the world. How do you drive change in such a large and dispersed organization? >> Well I think the most important thing is that change isn't human driven but humans need to be at the center of all change and I think that's why Andrew and I show up in a lot of places together. Because we do use technology to elevate the human experience at Accenture. And the more digital an organization becomes the more important human connection is and that's what we do is create truly compelling experiences for our people. >> Because we don't have separate agendas at Accenture. The relationship that Ellen and I have I think is one of the most important in our enterprise. Where we're driving digital transformation for our clients and within our own business and it's equal parts technology, talent, and change. And so you have to bring those things together and so what we're doing at Knowledge is talking a lot about the outcomes that we drive. Where we're in an experience rich culture our people, our employees, our citizens, our customers. They demand an experience which is very different to how the old IT posture had to deliver. So if we get the partnership right we create a culture and an environment that they'll have fun in and enjoy and not just have to turn up at work for. >> So Ellen what's the outcome that you're trying to achieve? Let's work backwards from there when you think about your human experience? >> Well really what we're trying to do is create an environment where our people can be successful both professionally and personally. Because you, we really require huge diversity at Accenture because in order to bring innovative solutions to our clients we truly need very broad diversity and in order to discover and inspire diverse base of talent. We need to create world class experiences that really unlock their full potential. >> We're all human beings after all. But human beings whether or not we're delivering services or whether we're consuming them. So under Ellen's leadership we talk about truly human and I think that's really important because we must reflect and understand the community we serve. So if we don't have the diversity, if we don't have the gender mix. If we're not looking like the humans who we need to look after then there's going to be a barrier and I think that's at the heart of a lot of modern transformation. >> Now hang on. I heard you say today you have a lot of nn human workers. >> I do, I do. >> So they're not all humans. Who are they, are they robots? >> Well the future of work and the future workforce is a combination of human and machine. Because you need both and you need both working in a way that compliments each other. So we're often asked does the machine replace the human. No it doesn't it changes the content of the work and frees the human to do more interesting work and we need both in a modern agenda. >> And quite simply we do have a very strong belief that technology elevates humans and does not eliminate humans. >> And I'm an optimist too but when I go to the airport I see kiosks, more kiosks than humans. When I drive down the highway out of Heathrow I see all the billboards and they're neon now or electronic so clearly machines have always replaced humans in jobs and clearly as humans we've always overcome. So I'm an optimist too but it seems different this time around because, it cognitive functions and it seems like a whole new set of skills. You guys are experts at this. What are your thoughts? >> I think we are building a set of skills is the new that's absolutely essential for the modern enterprise. So when you drive down the road from Heathrow you don't see the data scientists, you don't see the design thinkers. You don't see the humans that are listening to and talking with their customers and surfacing insights. We think about applying intelligence in the enterprise. Now the humans wouldn't have time to do that if they had to deal with all the old transactions. Free them up from that and then they can do all of this interesting work and that's the future of work. >> One of the things you were talking about on the main stage Andrew was about the changing role of the CIO and you said I actually think of myself as a chief experience officer. Can you refine that a little bit? >> Well I think Ellen and I both care about the experience of all of our employees, all of our humans, all of our citizens and all of our customers and clients as well. So the days of operating in a data center, of buildings systems are long gone. Accenture is now 90% in the cloud and I have to think about services which are really flexible, agile that deliver outcomes. So if my customers are not enjoying the experience and having fun and feeling at home. They're going to walk away so I care much more and that's why I think I lead with experience as the chief experience officer. >> So one just, to bring that down to an example. We hire about a 100,000 people a year and if you think of kind of the old paradigm when someone starts at your company. They have to get assigned a desk, a computer, a security badge you know get onto payroll and all of that historically has been done very siloed function by function. What Andrew and I are trying to create is an exciting experience when you show up for work on the first day where all of that is frictionless. All of that process goes to the backstage and how you feel about showing up as a new employee on your first day is just a glorious experience. >> So we always talk about people process and technology as a CIO you understand. Well the technology will continue to progress it's the people in process that are hard part. But can you actually achieve that vision without a technology platform that is flexible, that enables that type of work environment? >> The technology problem is really what is the enabler of the experiences we're trying to create. But the most important thing that the technology does for us is enables us to create truly world class human experiences. >> Before the cameras were rolling you were talking about how you have five generations of workers at Accenture. How do you cater to them? I mean as you said you want, coming to work everyday whether it's your first day or your, you know you've been there for 20 years to be a glorious experience. How do you make sure you are taking this empathetic people centered approach for each of these different kind of workers? >> I call it with my team sweating the small stuff and that's not worrying about bureaucracy and process. That's worrying about the individual. So we do have five generations working side by side both serving our clients and serving our business and the most important thing is truly understanding what's most important to the human? Not what generation they're coming from or were born during. >> Those five generations have a lot in common before they come to work they typically watch the news. They may have read the Wall Street Journal. They may have consumed content on YouTube. They may have looked at Twitter, they may have subscribed to Netflix. They may have asked Alexa or Cortana for advice and guidance. When they get to work what changes? It has to feel and be exactly like that and Ellen and I will be creating the services that do that so that it feels welcoming and sticky and so I want to stay. Which is really important in the modern enterprise when there's so much opportunity out there for the human. >> And to go back to the question you were asking and talking about driving out of Heathrow and not seeing humans. I think the thing that CEOs really need to understand is that employees are excited about the opportunity that technology is going to bring to their job. In fact we did a piece of research that we launched earlier this year that says over 80% of people are excited about how technology is going to improve their work. Because of the very reason they Google things at home. They use you know Amazon or whatever to go buy their things that they need for themselves. And so they see the opportunity and it's companies and organization's roles to tap into that excitement and really change the future of work. >> Here's a really good example of that. So there is nothing more boring than security training. >> I agree. >> So inside Accenture why don't you subscribe to a TV show that looks like 24. The TV show, the 24 that's episodic. We drop a season that has actors portraying the implications of if you don't get your security rights as a human and as an individual. It gets great ratings, great viewing figures. So it's ratings and viewing figures that tell us we're communicating with our employees. That's what being in the new is about. >> And that's really innovative. I was going to ask you about training and education because the example of Heathrow you don't see the data scientist the person who's putting paper and glue and doesn't have the skill sets of that data scientist. So I know Accenture big on training, education. You guys invest a lot there. My question is as you span five generations is the training regimen... Sort of how do you tailor it to those different needs? >> Well what we're finding frankly is that all of our people really want to stay relevant to their clients and to their people and so what we did was we worked together to democratize our learning platforms. So you no longer have to be tapped on the shoulder and invited to take training. We've enabled our training platform to be available real time and on demand and when you create a culture in which people are hungry to learn. You see some amazing things happen and we can see on our dashboard that Andrew's team has built all of the trending topics on any given day in any day of the week. That our people are doing through self learning. >> And that's shared and open? So there's a little bit of game theory going on here. >> Because transparency builds trust. Absolutely. >> What you want, where you want, when you want it, why you want it and at the rate you want it. Because everybody has different sets of needs. Well they'll stay relevant, they'll stay liquid and they'll be able to keep up with modern technology because we're a technology business in our case. That's wat training is about and they'll be more effective and they'll have fun and they'll have job security and none of that is threatened by other aspects of technology. >> But one point to add to that because I think Andrew's brilliance doesn't always fully come through is that everything that he's built for our people has a social component it. So for example on the learning platform I can recommend different learning experiences that I've gone through to my colleagues, to my peers and when you see the interaction among the people and how you can create real change. With just each other, without driving change top down. That social experience really changes the whole dynamic in an organization. >> I think one of the things that Ellen and I have had a chance to leave our mark on is that we have both democratized training and we socialize training as well and both are really important. >> You talked about, oh sorry. Go ahead please. >> You said you hire a 100,000 people a year and at a time where the skill set is really changing. Because so many of the repetitive automate the task are being automated and so really the skillsets that we need are more empathetic, more creative. How are you finding those people? Particularly at a time we really are in a war for talent? >> We talk about discovering new sources of talent rather than attracting talent to us. So we really try to go digital where the people are. So that's where people are, that's where we go look for them but the most important thing is that we are investing in new skilling our people. So we're not just hiring people in with new skills we're giving all of the 442,000 humans at Accenture the opportunity to continue to keep themselves relevant. >> So rather than coders and testers we now have data scientists and I do think we have new talent sources inside and outside the company. So I'm delighted to say that 54% of my team in China happen to be ladies and there's a really good solid data science gene in them which is helping us with our analytics and surfacing insights in a way that my organization didn't used to do. So we've tapped into new talent, many of them we already had it's just how you free them to do the job that they are very very capable of doing. >> Well Andrew, Ellen thank you so much for coming on the CUBE. It was great to have you here. >> Thanks for having us. >> Great to see you guys. >> I'm Rebecca Knight for Dave Vellante, we will have more from Service Now Knowledge 18 just after this.

>> Announcer: Live from Berlin, Germany, it's theCUBE, covering NetApp Insight 2017. Brought to you by NetApp. (upbeat music) >> Welcome back to theCUBE's live coverage of NetApp Insight 2017, here in Berlin, Germany. I'm your host, Rebecca Knight, along with my co-host, Peter Burris. We are joined by Shelia Fitzpatrick, she is the Chief Privacy Officer of NetApp, and Paul Stringfellow who is a Technical Director at Gardner Systems. Shelia, Paul, thanks so much for joining us. >> Thank you. >> Thank you for inviting us. >> So, I want to talk about data privacy. The general data protection regulation, the EU's forthcoming laws, GDPR, are going to take effect in May of next year. They represent a huge fundamental change about the way that companies use data. Can you just set the scene for our viewers and explain what these changes mean? >> Sure, happy to. As you said, GDPR is the newest regulation, it will replace the current EU directive, goes into effect May 25th of 2018. It has some fundamental changes that are massively different than any other data privacy laws you've ever seen. First and foremost, it is a legal, compliance and business issue as opposed to a technology issue. It's also the first extra-territorial regulation, meaning, it will apply to any organization anywhere in the world, regardless of whether or not they have a presence in Europe. But if they provide goods and services to an EU resident, or they have a website that EU residents would go to to enter data, they are going to have to comply with GDPR, and that is a massive change for companies. Not to mention the sanctions, the sanctions can be equal to 20 million Euro or 4% of a company's annual global turnover, pretty phenomenal sanctions. There are a lot of fundamental changes, but those are probably the biggest right there. >> What are some of the biggest challenges that companies are... I mean, you talked about the threat of sanctions and just the massive implications of what companies need to do to prepare? >> To really prepare, as I'm talking to customers, they really need, unfortunately a lot of companies are just thinking about security. And they're thinking, well as long as we have encryption, as long as we have tokenization, as long as we're locking down that data, we're going to be okay. I'm saying, no. It first and foremost starts with building that legal compliance program. What does your data privacy program look like? What personal data are you collecting? Why are you collecting it? Do you have the legal right to collect it? Part of GDPR requires unambiguous, explicit, freely-given consent. Companies can no longer force or imply consent. A lot of times when you go on to websites the terms and conditions are so impossible to understand that people just tick the box (laughs). Well, under GDPR, that will no longer be valid because it has to be very transparent, very easily understandable, very readable. And people have to know what organizations are doing with their data. And it puts ownership and more control of data back into the hands of the data subject, as opposed to the organizations that are collecting data. SO those are some of the fundamental changes. For the Cloud environment, for instance, for a lot of big hyperscalers, GDPR now puts obligations on data processors which is very different from the current regulation. SO that's going to be a fundamental change of business for a lot of organizations. >> Now, is it just customers or is it customers and employees as well? >> It's customers, employees, suppliers, it's any personal data that an organization collects, regardless of the relationship. >> SO what does it mean? Does it mean that I'm renting your data? Does it mean that I, 'cause you now own it, it's not me owning it. >> I own it, that's right. >> What are some of the implications of how folks are going to monetize some of these resources? >> SO what it actually means is, as an organization that's collecting data, you have to have a legal and valid business reason for needing that data. SO part of GDPR requires what's called, data minimization. You should only be collecting the minimal amount of data you need in order to provide the service you're going to provide, or manage the relationship you're going to manage. And you are never, as an organization, the owner of that data, you're the data steward. I am giving you permission to use my data for a very specific reason. You can't take liberties with that data. You can't do, what I call, scope-creep which is, once you have the data, "Oh, I can do whatever I want "with that data," no you can't. Unless I have consented to it, you cannot use that data. And so, that is going to be a major change for organizations to deal with and it doesn't matter if it's your employee data, your customer data, your partner data, your alternative worker data, your supplier data. Whose ever data you have, you better be transparent about that data. >> Shelia, you haven't once mentioned technology. Paul, what does this mean from a technology perspective? >> I suppose it's my job to mention technology? >> As Shelia will tell you, the GDPR, it should not be driven by IT. Because it's not an IT problem, it's absolutely a legal and compliance issue. However, I think there's a technology problem in there. So for lots of things that Shelia is talking about, in terms of understanding your data, in terms of being able to find data, being able to remove data when you no longer need to use it, that's absolutely a technology problem. And I think, actually, maybe something you won't hear said very often, I'm a real fan of GDPR, I think a it's long overdue it's probably because Shelia's been beating me round the head for the last 12 months >> I have. >> about it. But, I think it's one of those things that's long overdue to all of us within enterprises, within business, who hold and look after data. Because what we've done, traditionally, is that we just collected tons and tons of data and we bought storage 'cause storage could be relatively cheap, we're moving things to the Cloud. And, we've got absolutely no control, no management, no understanding of what the data is, where it is, who has access to it? Does anybody even access it, I'm paying for it, does anybody even use it? And I think what this is, for me, if GDPR wasn't a regulatory thing that we had to do, I think it's a set of really good practices that, as organizations, we should be looking to follow anyway. And technology plays a small part in that, it will enable organizations to understand the data better, it will enable those organizations to be able to find information as and when they need it. When somebody makes a subject access request, how are you going to find that data without appropriate technology? And I think, first and foremost, it's something that is forcing organizations to look at the way they culturally look after data within their business. This is no longer about, "Let me just keep things forever and I won't worry about it." This is a cultural shift that says data is actually an asset in your business. And as Shelia actually mentioned before, and something I'll pinch in future, the data is not mine, I'm just the custodian of that data while you allow me to be so. So I should treat that like anything else I'm looking after on your behalf. SO I think it's those kind of fundamental shifts that will drive technology adoption, no doubt, to allow you to do that, but actually, it's much more of a cultural shift in the way that we think of data and the way that we manage data in our businesses. >> Well you're talking about it as this regulation that is long overdue, and it will cause this cultural shift. So what will be different in the way that companies do business and the way that they treat their customer data, and their customer's privacy? And their employee's privacy, too, as you pointed out? >> Well, and part of the difference is going to be that need for transparency. So companies are going to have to be very upfront about what they're doing with the data, as Paul said. You know, why are they collecting that data, and they need to think differently about the need for data. Instead of collecting massive amounts of data that you really don't need, they need to take a step back and say, "This is the type of relationship "I'm trying to manage." Whether it's an employment relationship, whether it's a customer relationship, whether it's a partner relationship. What is the minimum amount of information I need in order to manage that relationship? So if I have an employee, for instance, I don't need to know what my employee does on their day off. Maybe that's a nice thing to know because I think well, maybe we can offer them a membership to a gym because they like to work out? That's not a must-have, that's a nice-to-have. And GDPR is going to force must-haves. In order to manage the employment relationship I have to be able to pay you, I have to be able to give you a job, I have to be able to provide benefits, I have to be able to provide performance evaluations and other requirements, but if it's not legally required, I don't need that data. And so it's going to change the way companies think about developing programs, policies, even technology. As they start to think about how they're developing new technology, what data do they need to make this technology work? And technology has actually driven the need for more privacy laws. If you think about IoT, artificial intelligence, Cloud. >> Mobile. >> Absolutely. Great technology, but from a privacy perspective, the privacy was never a part of the planning process. >> In fact, in many respects it was the exact opposite. There were a whole bunch of business models, I mean if you think about it in the technology industry, there's two fundamental business models. There's the ad-based business model, which is, "Give us all your data "and we'll figure out a way to monetize it." >> Absolutely. >> And there's a transaction-based business model which says, "We'll provide you a service "and you pay us, and we promise to do something "and only something with your data." >> Absolutely. >> It's the difference between the way Google and Facebook work, and say, Apple and Microsoft work. SO how is this going to impact these business models in ways of thinking about engaging customers at least where GDPR is the governing model? >> Well, it is going to force a fundamental change in their business model. SO the companies that you mentioned, that their entire business model is based on the collection and aggregation of data, and in some cases, the selling of personal data. >> Some might say screwing you. >> Some might definitely say that, especially if you're a privacy attorney, you might say that. They offer fabulous services and people willingly give up their privacy, that's part of the problem, is that they're ticking the box to say, "I want to use Facebook, I want to use Twitter, "I want to use LinkedIn "because these are great technologies." But, it's the scope-creep. It's what you're doing behind the scenes that I don't know how you're using my data. SO transparency is going to become more and more critical in the business model and that's going to be a cultural, as Paul said, a cultural shift for companies that their entire business model's based on personal data. They're struggling because they're the companies that, no matter what they do, they're going to have to change. They can't just make a simple, change their policy or procedure, they have to change their entire business model to meet the GDPR obligations. >> And I think from, like Shelia says there, and obviously GDPR's very much around, kind of, private data. Well, the conversation we're having with our customers is, is a much wider scope than that, it is all of the data that you own. And it's important, I think, organizations need to stop being fast and loose with the information that they hold because not only is the private information about those people there that, you know, me and you, and that we don't want that necessarily leaked across the well to somebody who might look to exploit that for some other reason. But, that might be, business confidential information, that might be price list, it might be your customer list. And, at the moment, I think in lots of organizations we have a culture where people from top to bottom in an organization don't necessarily understand that. SO they might be doing something where, we had a case in UK recently where some records, security arrangements for Heathrow Airport were found on a bus. So somebody copied them to a USB stick, no encryption, somebody copied it to a USB stick, thought it was okay to take home and leave in the back of, probably didn't think it was okay to leave in the back of the taxi, but certainly thought it was okay to take that information home. And you look at that and think, well, what other business asset that that organization held would they have treated with such disdain, almost to say "I just don't care, this is just ones and zeroes, "why would I care about it?" It's that shift that I think we're starting to see. And I think it's that shift that organizations should have taken a long time ago. We talk to customers, and you hear of events like this all the time, data is the new gold, data is the new precious material of your choice. >> Which it really isn't. It really isn't, here's why I say that because this is the important thing and leads to the next question I was going to ask you. Every asset that's ever been conceived follows the basic laws in economic scarcity. Take gold, you can apply to that purpose, you can make connectors for a chip, or you can use it as a basis for making jewelry or some other purpose. But, data is fungible in so many ways. You can connect it and in many respects, we talked about it a little bit earlier, the act of making it private is, in many respects, the act of turning it into an asset. SO one of the things I want to ask you about, if you think about it, is that, there will still be a lot of net new ways to capture data that's associated with a product or service in a relationship. SO we're not saying that GDPR is going to restrict the role that data plays, it's just going to make it more specific. We're still going to see more IoT, we're still going to see more mobile services, as long as the data that's being collected is in service to the relationship or the product that's being offered. >> Yeah, you're absolutely right. I mean, one of the things that I always say is that, GDPR's intent is not stop organizations from collecting data, data is your greatest asset, you need data to manage any kind of relationship. But, you're absolutely right in what it's going to do is force transparency, so instead of doing things behind the scenes where nobody has any idea what you're doing with my data, companies are going to have to be extremely transparent about it and think about how it's being used. You talked about data monetization, healthcare data today is ten times more valuable than financial data. It is the data that all hackers want. And the reason is, is because you take even aggregate and statistical information through, say trial clinics, information that you think there's no way to tie it back to a person, and by adding just little elements to it, you have now turned that data into greater value and you can now connect it back to a person. SO data that you think does not have value, the more we add to it and the more, sort of, profiling we do, the more valuable that data is going to become. >> But it's even more than that, right? Because not only are you connecting it back to a person, you're connecting it back to a human being. Whereas financial data is highly stylized, it's defined, it's like this transaction defining, and there's nothing necessarily real about it other than that's the convention that we used to for example, do accounting. But, healthcare data is real. It ties back to, what am I doing, what drugs am I taking, why am I taking them, when am I visiting somebody? This is real, real data that provides deep visibility into the human being, who they are, what they face, and any number of other issues. >> Well, if you think about GDPR, too, they expanded the definition of personal data under GDPR. SO it now includes data, like biometric and genetic information that is heavily used in the healthcare industry. It also includes location data, IP information, unique identifiers. SO a lot of companies say, "Well, we don't collect personal data "but we have the unique identifiers." Well, if you can go through any kind of process to tie that back to a person, that's now personal data. SO GDPR has actually the first entry into the digital age as opposed to the old fashioned processing. Where you can now take different aspects of data and combine it to identify a human being, as you say. >> So, I got one more question. This is something of a paradox, sorry for jumping in, but I'm fascinated by this subject. Something of a paradox. Because the act of making data private, at least to the corporation, is an act of creating an asset, and because the rules of GDPR are so much more specific and well thought through than most rules regarding data, does it mean that companies that follow GDPR are likely, in the long run, to be better at understanding, taking advantage of, and utilizing their data assets? That's the paradox. Most people say, "I need all the data." Well, GDPR says, "Maybe you need to be more specific "about how you handle your data assets." What do you think, is this going to create advantages for certain kinds of companies? >> I think it absolutely is going to create advantages in two ways. One, I see organizations that comply with GDPR as having a competitive advantage. Because, number one it goes down to trust. If I'm going to do business with Company A or Company B, I'm going to do business with the company that actually takes my personal data seriously. But, looking' at it from your point of view, absolutely. As companies become more savvy when it comes to data privacy compliance, not just GDPR, but data privacy laws around the world, they're also going to see more of that value in the data, be more transparent about it. But, that's also going to allow them to use the data for other purposes, because they're going to get very creative in how having your data is actually going to benefit you as an individual. SO they're going to have better ways of saying, "But, by having your data I can offer you these services." >> GDPR may be a catalyst for increased data maturity. >> Absolutely. >> Well, I wanna ask you about the cultural shift. We've been talking so much about it from the corporate standpoint, but will it actually force a cultural shift from the customer standpoint, too? I mean, this idea of forcing transparency and having the customer understand why do you need this from me, what do you want? I mean, famously, Europeans are more private than Americans. >> Oh much so. As you've said, "Just click accept, okay, fine, "tell me what I need to know, "or how can I use this website?" >> Well, the thing is that, it's not necessarily from a consumer point of view, but I do think it's from a personal point of view from everybody. SO whether you work inside an organization that keeps data, that's starting to understand just how valuable that data might be. And just to pick up on something, that just to pop at something you were saying before, I think one of the other areas where this has business benefit is that that better and increased management and maturity, actually I think is actually a great way, that better maturity around how we look after our data, has huge impact. Because, it has huge impact in the cost of storing' it, if we want to use Cloud services why am I putting things there that nobody looks at? And then, looking at maintaining this kind of cultural shift that says, "If I'm going to have data in my organization, "I'm no longer going to have it on a USB stick "and leave it in the back of a cab "when it's got security information "of a global major airport on it. "I'm going to think about that "because I'm now starting to understand." And this big drive about, people starting to understand how the information that people keep about you has a potential bigger impact, and it has a potential bigger impact if that data, yeah, we've seen data breach, after data breach after data breach. You can't look at the news any day of the week without some other data breach and that's partly because, a bit like health and safety legislation, GDPR's there because you can't trust all those organizations to be mature enough with the way that we look after our data to do these things. SO legislation and regulations come across and said, "Well, actually this stuff's really important "to me and you as individuals, "so stop being fast and loose with it, "stop leaving it in the back of taxis, "stop letting it leak out your organization "because nobody cares." And that's driving a two-way thing, here, it's partly we're having to think more about that because actually, we're not trusting organizations who are looking after our data. But, as Shelia said, if you become an organization that has a reputation for being good with the way they lock their data, and look after data, that will give you a competitive edge alongside, actually I'm being much more mature, I'm being much more controlled and efficient with how I look after my data. That's got big impact in how I deliver technology and certainly, within a company. Which is why I'm enthusiastic about GDPR, I think it's forcing lots and lots of long-overdue shift in the way that we, as people, look after data, architect technology, start to think about the kind of solutions and the kind of things that we do in the way that we deliver IT into business and enterprise across the globe. >> I think one of the things, too, and Paul brought it up, is he mentioned security several times. And, as Paul knows, one of my pet peeves is when companies say, "We have world-class security, "therefore we're compliant with GDPR." And I go, "Really, so you're basically locking down data "you're not legally allowed to have? That's "what you're telling me." >> Like you said earlier, it's not just about having encryption everywhere. >> Exactly, and it's funny how many companies say "Well, we're compliant with GDPR "because we encrypt the data." And I go, "Well, if you're not legally allowed "to have that data, that's not going to help you at all." And, unfortunately, I think that's what a lot of companies think, that as long as we're looking at the security side of the house, we're good. And they're missing the whole boat on GDPR. >> It's got to be secure. >> It's got to be secure. >> But-- >> You got to legally have it first. >> Exactly. The chicken and the egg. >> But, what's always an issue with security, around data and the stuff that Shelia talked about is quite a lot, is that one of the risks you have, is you can have all the great security in the world but, if the right person with the right access to the right data has all the things that they should have, that doesn't mean that they can't steal that data, lose that data, do something with that data that they shouldn't be doing, just because we've got it secured. SO we need to have policies and procedures in place that allow us to manage that better, a culture that understands the risk of doing those kinds of things, and maybe, alongside technologies that identify, unusual use of data are important within that. >> Well, Paul, Shelia, thank you so much for coming on the show, it's been a fascinating conversation. >> Thank you very much, appreciate it. >> Yeah, thanks for having us on, appreciate it. >> I'm Rebecca Knight for Peter Burris, we will have more from NetApp Insight here in Berlin in just a little bit. (upbeat music)

(clicking) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. It looks like they're letting the general session out. We're here at the Professional Business Women of California Conference; 6,000 women, about 5% men really talking about, it's amazing, the 28th year. I've never been to this show about how women can get more inclusive and diversity and taking, executing on steps to actually make it happen as somebody said in the key note. It's not a strategy problem, it's an execution problem. So, we've got a great story here and we're really excited to have CUBE alumni, Andrea Ward. She's now the CMO of Magento Commerce. Welcome back, Andrea. >> Thank you so much, it's great to be here and great to be at this conference. The buzz is amazing and I was here two years ago and it's grown so much, just in the two years. >> How many people were there, they say it's 6,000, now. >> I mean, it looks like it's about doubled. I don't know what the numbers were two years ago but the participation is amazing and it's such a great opportunity for local businesses to bring employees from their companies, have them have a chance just to talk and learn from such powerful women. So, it's been a really great conference. >> And, it's also a cross of so many kind of verticals if you will, because you know we go to a lot of tech conferences. This is more kind of a cross industry with banking and insurance and, you know, United Airlines we talked to earlier. And so, it's a much more diverse kind of set. >> Absolutely, I mean the women on the panels this morning spanned legal professions, government, entertainment, business, really diverse issue and it's fantastic that women are coming together to support each other to help make a difference. >> So last we saw you, I think we were on the street on Howard Street a couple years back which was pretty exciting as well, but now your new company, Magento Commerce. So, for people who aren't familiar with the company, give them kind of the four-one-one. >> Yeah great, well Magento Commerce is a leading commerce technology platform for mid-size businesses. We have recently separated from Ebay about 15 months ago and are now a privately held company and we power about a third of the world's commerce, believe it or not. >> That is amazing. Yeah. >> A third of the world's eCommerce. >> That's right. So, it's a fantastic company. We're growing and a part of that growth is absolutely growing a more diverse workforce and we've been putting into place some initiatives since last year. >> Yeah, part of the key note conversations were, obviously, that you need to put goals down on paper and you need to measure them and I think it was Bev Crair from Intel talked about, you know, doing it across all the pay grades. It's not just in engineering or just on the board or just the executive ranks, but really all the way across and it sounds like you guys are executing that to really help you just grow the company generically. >> Well, we're in a very lucky position in that we're experiencing growth and so that gives us room to really go out and look for amazing talent across the board. And so, we put a focus on diversity and inclusion and by doing that, we've increased the percentage of women in all roles across the company by 50% and that's since last June. So I think, you know, really just what you said earlier about execution and putting some numbers and goals against that can really make a difference. >> Right, and if you hadn't had those, that execution detail you probably couldn't have grown that fast because let's face it, it's hard to get good talent. If you're not including a broader base of talent, you're not going to be able to achieve your goals. >> Well, that's right and I think that some of that is, I don't know if you want to call it unconscious bias or unintentional, we're used to hiring people that look like us, have experience like us. And so, by encouraging that diversity, it really has made us expand the pool of applicants, make sure that we're not going for the easiest choice or the simplest choice but really considering a wide range of candidates to fill those positions. >> You know, I don't the birds of a feather conversation comes up enough, it's just easy to go with what you're familiar with. So whether it's unconscious or not, it's just easy, people are busy, you want to check the box and get off to your next task. So, you have to take a step back and consciously do the extra work, take the extra effort. >> Well, in the industry we support, the industries we support are going through digital transformation, I mean, commerce is key and central to digital transformation. And, transformation and change means that you have to consider other perspectives. You need to learn from new ideas and I think, you know, diversity plays a big part in that as well. So, I think bringing that into our own company because we're supporting that broader industry has been very important. >> Right. So, I want to take that opportunity to pivot on what you just said about in terms of the changing role of commerce. You know, I often think of like banks because in a bank, you know, your relationship was with your local branch; maybe you knew the banker, maybe you knew a couple of the tellers whatever, but you had a personal connection. Now, most people's engagement with the brands they interact with is electronic and via their phone and it's interesting that you say that. And, it's the commerce around those engagements, that the commerce is becoming the central point of gravity if you will and the relationship is spawning all from that. >> Well, I mean, personal connections are still very important and commerce I feel is like the moment where a conversation really turns into a relationship. So, it's important that those digital experiences, the customer experiences really make up the right connection with the brand. And so, that seamless interaction between what happens at the branch, for example in the financial example, on what you can do at home, that needs to be very cohesive. It needs to be trustworthy, it needs to be authentic and that means businesses need to create individual experiences that really reflect their brand. And, our company specifically has really helped businesses create those experiences, seamless experiences and translated them from digital to in-store or in the branch. I think the biggest change now is how that's starting to impact business-to-business relationships, I think. >> In what way? In the consumer world, we're used to that now right? We're all doing that in our everyday experiences. Now, we're starting to see that also come into a business-to-business relationship. So, just like the seamless conveniences that you have online in your day to day life, people want to see that in the workplace, too. And so, we're seeing the biggest change now in those types of business models. >> They're rocking in the background, if you can't hear them. >> Yeah! We are here. >> Yeah! You know, it's funny, I just saw, something come across the feed talking about that annoying business-to-business add in Instagram, but then aren't you glad you saw it? >> Yeah. >> So, it's interesting how, you know, the B to C norms, you know, continue to help define what's going on in the B to B space and we've seen it in Enterprise Software Applications and Cloud and the flexibility and speed of innovation. It just continues to really drive the business-to-business relationship. >> Yeah, and I think just like in the business-to-consumer world, it has started with content in business-to-business. But, now people want to move from just learning and knowledge to actually transacting which means that companies need to enable specialized price list, account management, things like that and that's starting to surface in the commerce world as well. So, we're really excited about that and we're going to be sharing some of that at our conference next week; Imagine, in Las Vegas. >> Okay yeah, it's amazing how fast. It was not that long ago, we were just trying to get the 360 view. Right? We were just trying to pull from all the various desperate systems to know who that customer was for a given system. Now, it's a segmentation to want, a very different challenge. >> Right, I mean it's that change from thinking about trying to attract your customer to come to your business to really bringing the business to the customer. I mean, I think that's what some of this digital technology is allowing us to do. We're going to them rather than trying to draw them in to come to us, if that makes sense. This idea of commerce coming to you, right? >> And, it's got to come to you with something that's relevant, that's topical, that's timely. >> That's easy to execute, that can mirror a real experience. I mean, you hear a lot of things about, things like virtual reality, artificial intelligence. I mean, all of that's just gimmicks unless you can actually think about how you make that real for your brand. So, for example, we have a customer in Mexico City who is selling eyewear, right. And so, everybody when they buy glasses, they want to try them on, so we need to help them give their customers that virtual experience. If they can't come into the store and try them on, we want to be able to let them try them on at home. So, that's a natural extension of the brand and a way to use virtual reality and I think businesses are still trying to figure that out. But, if those customers didn't have that experience, it'd be less likely that they actually would buy or, you know, make a commerce transaction. >> But, if I'm hearing you, instead of it really kind of being in a marketing effort that then it's completed with a transaction, you're kind of coming at that which you just described from the transaction first and this is really a supporting or an enabling activity. >> That's right, it all starts with the customer understanding what is going to help them make their decisions. Giving them experiences that feel seamless, giving them options. So, if they want to come in-store but see what's maybe available at another store for pick-up or if they want to come in-store and order online or if they want to order from home and then go into the store and pick it up. It's really about giving the customer the right options for them. >> Right. >> Another great story we had is, I mean, how many of us travel, I know you travel a lot. >> Right. >> I travel a ton. >> Especially, to Vegas. (chuckling) >> Especially, to Vegas! And, you know, my kids are always expecting something when I come home but who has time? So, you know, one of our partners worked with the Frankfurt Airport and created an application where on the way to the airport, you can go shopping at all of their stores in the airport and have your package waiting for you at the gate on the way to the plane. So now, you know, they've figured out what their customers want to do first by creating this great shopping experience at the airport. Now, they know people are running through the airport, how can we extend that shopping experience for them while they're sitting in the taxi (chuckling) on the way, have it waiting for them at the gate? And so, for me personally, working for a company that's helping customers to do those kinds of things has really been fun. >> Right, because they always have the liquor for ya ready to go at the gate but never the kids', you know, t-shirts or a little tchotchke or, I can remember running through Heathrow time and time again trying to find something quickly. >> Yeah, and now with two kids and a husband that all want something different, (laughing) you know, it makes it much easier for me. >> Alright, Andrea, well you've been doing this marketing thing for a long time. I'll give you the last word both on the conference and kind of, you know, as a marketer to see where we're going with A.I. and really the ability to actually segment to one. You know, how exciting is that for you? >> Yeah, I mean, it's fantastic. I think, you know, marketers want to create relationships with their brand and all of these tools are giving us better access, better chance to create that fantastic experience. So, it's a great time to be a marketer. (chuckling) And, it's a great time to be at this conference, too so. >> Alright. Thanks very much. >> Thanks for stopping by, Andrea Ward. I'm Jeff Frick, you're watching theCUBE from the Professional Business Women's Conference in San Francisco. Thanks for watching. (upbeat electronic music)

>> Narrator: Live from Dublin, Ireland. It's theCUBE, covering Hadoop Summit Europe 2016. Brought to you by Hortonworks. Now your host, John Furrier and Dave Vellante. >> Okay, welcome back here, we are here live in Dublin, Ireland, it's theCUBE SiliconANGLEs flagship program where we go out to the events and extract the signal from the noise, I'm John Furrier, my cohost Dave Vellante, our next guest is Emer Coleman who's with Disruption Limited, Open Data Governance Board in Ireland and Transport API, a growing startup built self-sustainable, growing business, open data, love that keynote here at Hadoop Summit, very compelling discussion around digital goods, digital future. Emer, welcome to theCUBE. >> It's great to be here. >> So what was your keynote? Let's just quickly talk about what you talked about, and then we can get in some awesome conversation. >> Sure. So the topic yesterday was we need to talk about techno ethics. So basically, over the last couple of months, I've been doing quite a lot of research on ethics and technology, and many people have different interpretations of that, but yesterday I said it's basically about three things. It's about people, it's about privacy, and it's about profits. So it's asking questions about how do we look at holistic technology development that moves away from a pure technocratic play and looks at the deep societal impacts that technology has. >> One of the things that we're super excited about and passionate about is this new era of openness going to a whole another level. Obviously, open source tier one software development environment, cloud computing allows for instant access to resources, almost limitless at this point, as you can project it forward with Moore's Law and whatnot. But the notion that digital assets are not just content, it's data, it's people, it's the things you mentioned about, create a whole new operating environment or user experience, user expectations with mobile phones and Internet of Things and Transport API which you have, if it moves, you capture it, and you're providing value there. So a whole new economy is developing around digital capital. Share your thoughts around this, because this is an area that you're passionate about, you've just done work here, what's your thoughts on this new digital economy, digital capital, digital asset opportunity? >> I think there's huge excitement about the digital economy, isn't there? And I think one of the things I'm concerned about is that that excitement will lead us to the same place that we are now, where we're not really thinking through what are the equitable distribution in that economy, because it seems to me that the spoils are going to a very tiny elite at the tops. So if you look at Instagram, 13 employees when it was purchased by Facebook for a billion dollars, but that's all our stuff, so I'm not getting any shares in the billion, those 13 people are. That's fantastic that you can build a business, build it to that stage and sell, but you have to think about two things, really: what are we looking at in terms of sustainable businesses into the future that create ethical products, and also the demands from citizens to get some value for their data back, because we're becoming shadow employees, we're shadow employees of Google, so when we email, we're not just corresponding, we're creating value for that company. >> And Facebook is a great example. >> And Facebook, and the thing is, when we were at the beginning of that digital journey, it was quite naive. So we were very seduced by free, and we thought, "This is great," and so we're happy with the service. And then the next stage of that, we realize what if we're not paying for the service, we're the product? >> John: Yeah. >> But we were too embedded in the platform to extricate ourselves. But now, I think, when we look at the future of work and great uncertainty that people are facing, when their labor's not going to be required to the same degree, are we going to slavishly keep producing capital and value for companies like Google, and ask for nothing more than the service in return? I don't think so. >> And certainly, the future will be impacted, and one of the things we see now in our business of online media and online open data, is that the data's very valuable. We see that, I'll say data is the new capital, new oil, whatever phrases of the day is used, and the brand marketers are the first ones to react to it, 'cause they're very data driven. Who are you, how do I sell stuff to you? And so what we're seeing is, brand marketers are saying, "Hey, I'm going to money to try to reach out to people, "and I'm going to activate that base and connect with, "engage with them on Facebook or other platform. "I'm going to add value to your Facebook or Google platform, "but yet I'm parasitic to your platform for the data. "Why just don't I get it directly?" So again, you're starting to see that thinking where I don't want to be a parasite or parasitic to a network that the value's coming from. The users have not yet gotten there, and you're teasing that out. What's your thoughts there, progression, where we're at, have people realized this? Have you seen any movement in the industry around this topic? >> No, I think there's a silence around... Technology companies want to get all the data they can. They're not going to really declare as much as they should, because it bends their service model a bit. Also, the data is emergent. Zuckerberg didn't start Facebook as something that was going to be a utility for a billion people, he started it as a social network for a university. And what grew out of that, we learned as we went along. So I'm thinking, now that we have that experience, we know that happens, so let's start the thinking now. And also, this notion of just taking data because you can, almost speculatively getting data at the point of source, without even knowing what you want it for but thinking, "I'm going to monetize this in the end." Jaron Lanier in his book Who Owns The Future talks about micro licensing back content. And I think that's what we need to do. We start, at the very beginning, we need to start baking in two things: privacy by design and different business models where it's not a winner takes all. It's a dialog between the user and the service, and that's iterated together. >> This idea that it's not a zero sum game is very important, and I want to go back to your Instagram and Facebook example. At its peak, I think Eastman Kodak had hundreds of thousands of employees, maybe four or five hundred, 450,000 employees, huge. Facebook has many many more photos, but maybe a few thousand employees? Wow, so all the jobs are gone, but at the same time, we don't want to be protecting the past from the future, so how do you square that circle? >> Correct, but I think what we know is that the rise of robotics and software is going to eat jobs, and basically, there's going to be a hollowing out of the middle class. You know, for sure, whether it's medicine, journalism, retail, exactly. >> Dave: It's not future, it's now. (laughs) >> Exactly. So we maybe come into a point where large swaths of people don't have work. Now, what do you do in a world where your labor is no longer required? Think about the public policy implications of that. Do we say you either fit in this economy or you die? Are we going to look at ideas which they are looking at in Europe, which is like a universal wage? And all of these things are a challenge to government, because they're going to have a citizenry who are not included in this brave new world. So some public policy thinking has to go into what happens when our kids can't get jobs. When the jobs that used to be done by people like us are done by machines. I'm not against the movement of technology, what I'm saying is there are deep societal implications that need some thinking, because if we get to a point where we suddenly realize, if all of these people who are unemployed and can't get work, this isn't a future we envisioned where robots would take all the crap jobs and we would go off to do wonderful things, like how are we going to bring the bacon home? >> It seems like in a digital world that the gap is creativity to combine technologies and knowledge. I find that it's scary when you talk about maybe micromanaging wages and things like that, education is the answer, but that's... How do you just transfer that knowledge? That's sort of the discussion that we're having in the United States anyway. >> I think some of the issue is that the technology is so, we're kind of seduced by simplicity. So we don't see the complexity underneath, and that's the ultimate aim of a technology, is to make something so simple, that complexity is masked. That's what the iPhone did wonderfully. But that's actually how society is looking now. So we're seduced by this simplicity, we're not seeing the complexity underneath, and that complexity would be about what do we do in a world where our labor is no longer required? >> And one of the things that's interesting about the hollowing of the middle class is the assumption is there's no replacements, so one of the things that could be counter argued is that, okay, as the digital natives, my daughter, she's a freshman in high school, my youngest son's eighth grade, they're natives now, so they're going to commit. So what is the replacement capital and value for companies that can be sustained in the new economy versus the decay and the darwinism of the old? So the digital darwinism aspect's interesting, that's one dilemma. The other one is business models, and I want to get your thoughts on this 'cause this is something we were teasing out with this whole value extraction and company platform issue. A company like Twitter. Highly valuable company, it's a global network of people tweeting and sharing, but yet is under constant pressure from Wall Street and investors that they basically suck. And they don't, they're good, people love Twitter, so they're being forced to behave differently against their mission because their profit motive doesn't really match maybe something like Facebook, so therefore they're instantly devalued, yet the future of someone connecting on Twitter is significantly high. That being said, I want to get your thoughts on that and your advice to Twitter management, given the fact it is a global network. What should they do? >> It's the same old capitalism, just it's digital, it's a digital company, it's a digital asset. It's the same approach, right? Twitter has been a wonderful thing. I've been a Twitter user for years. How amazing, it's played a role in the Arab Spring, all sorts of things. So they're really good, but I think you need as a company, so for example, in our company, in Transport API, we're not really looking to build to this massive IPO, we're trying to build a sustainable company in a traditional way using digital. So I think if you let yourself be seduced by the idea of phenomenal IPO, you kind of take your eye off the ball. >> Or in case this, in case you got IPOed, now you're under pressure to produce-- >> Emer: Absolutely, yeah. >> Which changes your behavior. But in Twitter's management defense, they see the value of their product. Now, they got there by accident and everyone loves it, but now they're not taking the bait to try to craft a short term solution to essentially what is already a valuable product, but not on the books. >> Yes, and also I think where the danger is, we know that their generation shifts across channel. So teenagers probably look at Facebook, I think one of them said, like an awkward family dinner they can't quite leave. But for next gen, they're just not going to go there, 'cause that's where your grandmother is. So the same is true of Twitter and Snapchat, these platforms come and go. It's an interesting phenomenon then to see Wall Street putting that much money into something which is essentially quite ephemeral. I'm not saying that Twitter won't be around for years, it may be, but that's the thing about digital, isn't it? Something else comes in and it's well, that becomes the platform of choice. >> Well, it's interesting, right? Everybody, us included, we criticize the... Michael Dell calls it the 90 day shock clock. But it's actually worked out pretty well, I mean, economically, for the United States companies. Maybe it doesn't in the future. What are your thoughts on that, particularly from a European perspective? Where you're reporting maybe twice a year, there's not as much pressure, but yet from a technology industry standpoint, companies outside the Silicon Valley in particular seem to be less competitive, why? >> For example, in our company, in Transport API, we've got some pretty heavyweight clients, we have a wonderful angel investor who has given us two rounds of investment. And it isn't that kind of avaricious absolutely built this super price. And that's allowed us to build from starting off with 2, now to a team of 10, and we're just about coming into break even, so it's doable. But I think it's a philosophy. We didn't want necessarily to build something huge, although we want to go global, but it was let's do this in a sustainable way with reasonable wages, and we've all put our own soul and money into it, but it's a different cultural proposition, I think. >> Well, the valuations always drive the markets. It's interesting too, to your point about things come and go channels, kind of reminds me, Dave and I used to joke about social networks like nightclubs, they're hot and then it's just too crowded and nobody goes there, as Yogi Bear would say. And then they shift and they go out of business, some don't open with fanfare, no one goes 'cause it's got different context. You have a contextual challenge in the world now. Technology can change things, so I want to ask you about identity 'cause there was a great article posted by the founder of the company called Secret which is one of these anonymous apps like Yik Yak and whatnot, and he shut it down. And he wrote a post, kind of a postmortem, saying, "These things come and go, they don't work, "they're not sustainable because there's no identity." So the role of identity in a social global virtual world, virtual being not just virtual reality, is interesting. You live in a world, and your company, Transport API, provides data which enables stuff and the role of identity. So anonymous versus identity, thoughts there, and that impact to the future of work? If you know who you're dealing with, and if they're present, these are concepts that are now important, presence, identity, attention. >> And that's the interesting thing, isn't it? Who controls that identity? Mark Zuckerberg said, "You only have one identity," which is what he said when he set up Facebook. You think, really? No, that's what a young person thinks. When we're older, we know. >> He also said that young people are smarter than older people. >> Yeah, right, okay. (John laughs) He could be right there, he could be right there, but we all have different identities in different parts of our lives. Who we are here, the Hadoop summit is different from what we're at home to when we're with friends. So identity is a multifaceted thing. But also, who gets to determine your identity? So I have 16 years of my search life and Google. Now, who am I in that server, compared to who I am? I am the sum total of my searches. But I'm not just the sum total of my searches, am I? Or even that contextualized, so I'll give you an example. A number of years ago I was searching for a large, very large waterproof plastic bag. And I typed it in, and I thought, "Oh my god, that sounds like I'm going to murder my husband "and try to bury him." (John and Dave laugh) It was actually-- >> John: Into the compost. >> Right, right. And I thought, "Oh my god, what does this look like "on the other side?" Now, it was actually for my summer garden furniture. But the point is, if you looked at that in an analytic way, who would I be? And so I think identity is very, you know-- >> John: Mistaken. >> Yeah, and also this idea of what Frank Pasquale calls the black box society. These secret algorithms that are controlling flows of money and information. How do they decide what my identity is? What are the moral decisions that they make around that? What does it say if I search for one thing over another? If I search constantly for expensive shoes, does that make me shallow? What do these things say? If I search for certain things around health. >> And there's a value judgment now associated with that that you're talking about, that you do not control. >> Absolutely, and which is probably linked to other things which will determine things like whether I get credit or not, but these can almost be arbitrary decisions, 'cause I have no oversight of the logic that's creating that decision making algorithm. So I think it's not just about identity, it's about who's deciding what that identity is. >> And it's also the reality that you're in, context, situations. Dark side, bright side of technology in this future where this new digital asset economy, digital capital. There's going to be good and bad, education can be consumed non-linear, new forms of consumptions, metadata, as you're pointing out, with the algorithms. Where do you see some bright spots and where do you see the danger areas? >> I think the great thing is, when you were saying software is the future. It's our present, but it's going to be even more so in our future. Some of the brightest brains in the world are involved in the creation of new technology. I just think they need to be focusing a bit more of that intellectual rigor towards the impact they're having on society and how they could do it better. 'Cause I think it's too much of a technocratic solution. Technologists say, "We can do this." The questions is, should they? So I think what we need to do is to loop them back into the more social and philosophical side of the discussion. And of course it's a wonderful thing, hopefully technology is going to do amazing things around health. We can't even predict how amazing it's going to be. But all I'm saying is that, if we don't ask the hard questions now about the downsides, we're going to be in a difficult societal position. But I'm hoping that we will, and I'm hoping that raising issues like techno ethics will get more of that discussion going. >> Well, transparency and open data make a big difference. >> Emer: Absolutely. >> Well, and public policy, as you said earlier, can play a huge role here. I wonder if you could give us your perspective on... Public policy, we're in the US most of the time, but it's interesting when we talk to customers here. To hear about the emphasis, obviously, on privacy, data location and so forth, so in the digital world, do you see Europe's emphasis and, I think, leading on those types of topics as an advantage in a digital world, or does it create friction from an economic standpoint? >> Yeah, but it's not all about economics. Friction is a good thing. There are some times when friction is a good thing. Most technologists think all friction is bad. >> Sure, and I'm not implying that it's necessarily good or bad, I'm curious though, is it potentially an economic advantage to have thought through and have policy on some of those issues? >> Well, what we're seeing here-- >> Because I feel like the US is a ticking time bomb on a lot of these issues. >> I was talking to VCs, some VC friends of mine here in the UK, and what they said they're seeing more and more, VCs asking what we call SMEs, small to medium enterprises, about their data policies, and SMEs not being able to answer those questions, and VCs getting nervous. So I think over time it's going to be a competitive advantage that we've done that homework, that we're basically not just rushing to get more users, but that we're looking at it across the piece. Because, fundamentally, that's more sustainable in the longer term. People will not be dumb too forever. They will not, and so doing that thinking now, where we work with people as we create our technology products, I think it's more sustainable in the long term. When you look at economics, sustainability is really important. >> I want to ask you about the Transport API business, 'cause in the US, same thing, we've seen some great openness of data and amazing innovations that have come out of nowhere. In some cases, unheard of entrepreneurs and/or organizations that better society for the betterment of people, from delivering healthcare to poor areas and whatnot. What has been the coolest thing, or of things you've seen come out of your enablement of the transport data. Use cases, have you seen any things that surprised you? >> It's quite interesting, because when I worked for the mayor of London as his director of digital projects, my job was to set up the London data store, which was to open all of London's public sector data. So I was kind of there from the beginning as a lobbyist, and when I was asking agencies to open up their data, they'd go, "What's the ROI?" And I'd just say, "I don't know." Because government's one and oh, I'm saying that was a chicken and egg, you got to put it out there. And we had a funny incident where some of the IT staff in transport for London accidentally let out this link, which is to the tracker net feed, and that powers the tube notice boards that says, "Your next tube is in a minute," whatever. And so the developer community went, "Ooh, this is interesting." >> John: Candy! >> Yeah, and of course, we had no documentation with it because it kind of went out under the radar. And one developer called Mathew Somerville made this map which showed the tubes on a map in real time. And it was like surfacing the underground. And people just thought, "Oh my god, that is amazing." >> John: It's illuminating. >> Yeah. It didn't do anything, but it showed the possibility. The newspapers picked it up, it was absolutely brilliant example, and the guy made it in half a day. And that was the first time people saw their transport system kind of differently. So that was amazing, and then we've seen hundreds of different applications that are being built all the time. And what we're also seeing is integration of transport data with other things, so one of our clients in Transport API is called Toothpick, and they're an online dental booking agency. And so you can go online, you can book your dental appointment with your NHS dentist, and then they bake in transport information to tell you how to get there. So we have pubs using them, and screens so people can order their dinner, and then they say, "You've got 10 minutes till the next bus." So all sorts of cross-platform applications. >> That you never could've envisioned. >> Emer: Never. >> And it's just your point earlier about it's not a zero sum game, you're giving so many ways to create value. >> Emer: Right, right. >> Again, I come back to this notion of education and creativity in the United States education system, so unattainable for so many people, and that's a real concern, and you're seeing the middle class get hollowed out. I think the stat is, the average wage in the United States was 55,000 in 1999, it's 50,000 today. The political campaigns are obviously picking at that scab. What's the climate like in Europe from that standpoint? >> In terms of education? >> No, just in terms of, yes, the education, middle class getting hollowed out, the sentiment around that. >> I don't think people are up to speed with that yet, I really don't think that they're aware of the scale. I think when they think robots or automation, they don't really think software. They think robots like there were in the movies, that would come, as I say, and do those jobs nobody wanted. But not like software. So when I say to them, look, E-discovery software, when it's applied retrospectively, what it shows is that human lawyers are only 60% accurate compared to it. Now, that's a no-brainer, right? If software is 100% accurate, I'm going to use the software. And the ratio difference is 1 to 500. Where you needed 500 lawyers before you need 1. So I don't think people are across the scale of change. >> But it's interesting, you're flying to Heathrow, you fly in and out, you're dealing with a kiosk. You drive out, the billboards are all electronic. There aren't guys doing this anymore. So it's tangible. >> And I think, to your point about education, I'm not as familiar with the education system in the US, but I certainly think, in Europe and in the UK, the education system is not capable of dealing even with the latest digital natives. They're still structuring their classrooms in the same way. These kids, you know-- >> John: They have missed the line with the technology. >> Absolutely. >> So reading, writing and arithmetic, fine. And the cost of education is maybe acceptable. But they may be teaching the wrong thing. >> Asynchronous non-linear, is the thing. >> There's a wonderful example of an Indian academic called Sugata Mitra, who has a fabulous project called a Hole in the Wall. And he goes to non-English speaking little Indian villages, and he builds a computer, and he puts a roof over it so only the children can do it. They don't speak English. And he came back, and he leaves a little bit of stuff they have to get around before they can play a game. And he came back six months later, and he said to them, "What did you think?" And one of the children said, "We need a faster CPU and a better mouse." Now, his point is self-learning, once you have access to technology, is amazing, and I think we have to start-- >> Same thing with the non-linear consumption, asynchronous, all this, the API economy enabling new kinds of expectation and opportunities. >> And it was interesting because the example, some UK schools tried to follow his example. And six months later, they rang him up and they said, "It's not working," and he said, "What did you do?" And they said, "Well, we got every kid a laptop." He said, "That's not the point." The point was putting a scarce resource that the children had to collaborate over. So in order to get to the game, they had figure out certain things. >> I think you're right on some of these (mumbles) that no one's talking about. And Dave and I are very passionate on this, and we're actually investing in a whole new e-learning concept. But it's not about doing that laptop thing or putting courseware online. That's old workflow in a new model. Come on, old wine in a new bottle. So that's interesting. I want to get your thoughts, so a personal question to end this segment. What are you passionate about now, what are you working, outside of the venture, which is exciting. You have a lot of background going back to technology entrepreneurship, public policy, and you're in the front lines now, thought leading on this whole new wide open sea of opportunity, confusion, enabling it. What are you passionate about, what are you working on? Share with the folks that are watching. >> So one of the main things we're trying to do. I work as an associate with Ernst & Young in London. And we've been having discussions over the past couple of months around techno ethics, and I've basically said, "Look, let's see if we can get EY "to build to build an EY good governance index." Like, what does good governance look like in this space, a massively complex area, but what I would love is if people would collaborate with us on that. If we could help to draw up an ethical framework that would convene the technology industry around some ethical good governance issues. So that's what I'm going to be working on as hard as I can over the next while, to try and get as much collaboration from the community, because I think we'd be so much more powerful if the technology industry was to say, "Yeah, let's try and do this better "rather than waiting for regulation," which will come, but will be too clunky and not fit for purpose. >> And which new technology that's emerging do you get most excited about? >> Hmm. Drones. (laughter) >> How about anything with bitcoin, block chains? >> Absolutely, absolutely, block chain. Yeah, block chain, you have to say, yeah. I think, 'cause bitcoin, you know, it's worth 20 p today, it's worth 200,000 tomorrow. >> Dave: Yeah, but block chain. >> Right, right. I mean, that is incredible potentiality. >> New terms like federated, that's not a new term, but federation, universal, unification. These are the themes right now. >> Emer: Well, it's like the road's been coated, isn't it? And we don't know where it's going to go. What a time we live in, right? >> Emer Coleman, thank you so much for spending your time and joining us on theCUBE here, we really appreciate the conversation. Thanks for sharing that great insight here on theCUBE, thank you. It's theCUBE, we are live here in Dublin, Ireland. I'm John Furrier with Dave Vellante. We'll we right back with more SiliconANGLEs, theCUBE and extracting the signal from the noise after this short break. (bright music)