>> From the Salesforce Tower in downtown San Francisco, it's theCUBE, covering Accenture Tech Vision 2019, brought to you by SiliconANGLE Media. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco with a brand newly open Salesforce Tower, the 33rd floor, the middle of the brand new Accenture Innovation Hub. We're excited to have our next guest, who's been part of the Innovation Labs and the Innovation Hubs and a lot of innovation in the center for years and years and years. You've seen him before, we're at the 30th anniversary, I think last year. All the way from Paris, is Marc Carrel-Billiard. He is the Senior Managing Director for Accenture Labs. Marc, great to see you again. >> Great to see you Jeff again as well, I'm so happy. >> So, what do you think of the new space here? >> I love it, I just love it. I saw it building and everything and now it's ready, and we open it today, I mean it's just amazing. The stairs, did you see the stairs? >> I saw the stairs, yes. >> Really amazing, everything's good there. I think it's not an office, like Paul already said, it's really something better and I think it's a tool for explaining what is innovation at Accenture at play, I mean, how we use it, how we connect the labs, we use the liquid studio, all the ventures and everything, that's great. >> Great. But now it's all brought together, right? You had a couple satellite locations in the Bay Area-- >> Yeah and I think that with the story of putting all this stuff in what we call the Innovation Center, the Innovation Hub, and so putting everything in the same building and have different floors where we can address different talking with our clients. Are we talking about research? Are we talking about more polythiophene? Are we talking about, I mean ideally, it's all about driving innovation at scale. >> Right, right. >> At scale. >> So, we're here for the technology vision-- >> We are. >> Which will be in, in a little bit and then, Paul and they team will present-- >> Yep, they will. >> Five new transfer for 2018. One of the ones they called is DARQ, D-A-R-Q, >> I know. >> Which is distributed ledger technologies, formerly known as blockchain, but we don't want to call it blockchain. AI, extended reality, which is every kind of form, extended, augmented-- >> Mix relating everything, that's right. >> And quantum computer. >> You bet. >> So, from the labs point of view, from an Accenture kind of innovation looking forward, inventing the future, as you like to say, which I think is a great tagline, what are some of your priorities going forward, now that you got this great new space? Which is one of what I think 11 in the United States, right? >> So, my priorities are all of them, I mean, all of the above! Because I was like, do you remember at the time we were talking about SMAC? Like Social Mobility, there was analytics and cloud. I would say that DARQ is the new SMAC. So, we saw that basically, that technology has evolved and, from analytics, we'd like more AI work and everything, but it's still being combined and everything. You can still think about social media, collaborative stuff, we going to go through immersive reality where we going to continue collaborating. Think about cloud. I mean, just like cloud will bring you height, throughput computing power through the cloud. Well, I mean, also quantum computing can give you like amazing capability in terms of computing power. So I would say probably, like, DARQ is a new SMAC and so the lab has been working on it since, I would say, not since day one, but at the very beginning. And so, well obviously distributed ledger, you know that we have a lab in Sophia Antipolis, they're really spending a lot of time in the blockchains. So there's a couple of things that we're doing. I give you a couple of ideas. One is, maybe people talk about blockchains, and there's bunch of blockchains all over, there's like blockchains for manufacturing, there's blockchains for trade finance, there's blockchains for this and that. Problem is there's no very good interoperability between those blockchains. One thing that the lab is going to be working is how we can interoperate between those different blockchains. So you are basically a supply chain, you want to connect to a financial organization, how their blockchain will connect to your blockchain. Number one. The second thing we're going to be working on is the SMAC contract. The lab believes the SMAC contract is not smart enough. So we going to add more artificial intelligence in the SMAC contract to see what we could do better. Think about this SMAC contract as a stock procedure in database. How we make those stock procedure a little bit better. I mean, it's just analogy type of thing. >> Obviously, the blockchain conversation, any kind of demo, talking about DHL-- >> Yeah, DHL, exactly. >> But is that logistics, that merchandise move through their system, as you said, there's a lot of different touch points with a lot of different systems. So it's not an aggregated system, it's a problem, and the other thing is you don't necessarily need all the data for each person, >> You don't. >> Or transaction all along the line, right? >> You're absolutely right. And I talk about interoperability between blockchains, but there's going to be also interoperability between the blockchain that you're implementing and the legacy environment that you have. And this needs to be addressed as well. So lot of thinking about blockchains, I've always said for me that blockchain is the digital right management of your future. That kind of protocol, and we're working with companies that are basically creating movies and stuff like that, and how we leverage blockchain to change those movies between different parties. I mean, there's going to be a lot of cool stuff that we're going to be able to do. So that's blockchain. The D for distributed ledger. A for artificial intelligence. So artificial intelligence obviously is something very beginner labs. We have three labs that are delegated to artificial intelligence. >> Three? >> Yup, out of seven. One here, San Francisco. The other one in Bangalore, and the third one in Dublin, Ireland. And each of them are covering a little part of the things that we want to do with artificial intelligence. It's all about accelerating the artificial intelligence, so how we're going to think about new infrastructure, a new way of doing machine learning, using weak labeling, it's all about explainable AI, how you're going to connect the knowledge graph with machine learning, so that's the probabilistic model will give you an explanation of why they've decided to select this picture, or this information and so forth. And basically the other things we're going to be working on, artificial intelligence, is that human-machine interaction, and one thing that we want to address is what we call the conversational aspect of virtual agents. If you look at virtual agents today, voice comment type of things. >> Right, right. >> You can't really engage in a conversation. I want to look at that. How they're going to understand context, and how you're going to be exchanging better, and how you're going to flow a better conversation with that. One thing that's going to be very important in everything that we're doing is going back to semantic network, knowledge management, knowledge graph. How we combine knowledge graph with all these machine learning capabilities. That's artificial intelligence in the lab. >> Then you get, we'll just work down the list, right, then you've got the extended reality. >> Extended reality. >> So whatever kind of reality it is. >> So we're going to continue doing a lot of stuff for extended reality, immersive learning, we're going to use that, I think what's going to be important for us is that not to look at extended reality just from a vision standpoint, but try to use the combinatorial effect of every immersive sense that you have. So like, basically, hearing, also, smelling, touching the aptic, and how you combine all those senses to change completely, not the vision, but the experience. What you really feel. In fact, if you go to this Innovation Hub, I don't know if you've seen that we have an igloo-- >> We did, I saw the 360. >> That's right the 360, to try to immerse you already in some quantum computing experience, I think it's a good segue way also for quantum. So quantum, is that we've been doing a lot of progress with quantum too, you know, two years ago we started already to work with D-wave and then we have work with this company called 1QBit, so we build a software, so we use their software development kit, to program the quantum computer, and then we work with Biogen to do drug discovery, and changing the way you do that, by accelerating that through quantum computing. But we've continued, we've announced basically some partnership with IBM to look at their platform, we're continuing working with other interesting platform like Fujitsu, their Digital Annealer, and so forth, and what we want to do is that Accenture is very, very agnostic related to all those vendors. What we want to do is that we want to understand more about how you program those different architecture, how you see what type of problems they can solve, and how based you can program them. And so if we use the Abstraction Layer on top of all the others, and we can program on top of that, this is really cool, this is exactly what we want to do. >> So how close is it? How close is it to getting the production ready? I mean, you got it in the new vision for 2019, I mean, what are people just playing with it or is it ready for prime-time. >> No, no, no. >> Where is it these days? >> So first of all, DARQ stuff, all the people, all of our clients-- >> I mean quantum specifically. >> Okay quantum-specific. I think we're talking about three to five years to start to have real solutions. Right now, we have prototype, but we're moving to more pilot, and I think the solution will come soon. Probably in five years time, we're starting to ascend soon. Let me give you another idea. >> So the order of magnitude difference in the way that you can compute, the AI. >> Exactly, and I think that's going to change the game. It's going to change the game on everything. Let me give you maybe a last example that I'm sure you're going to love. And it's all about optimization matchmaking. Our tech vision this year is all about hyper-personalization, plus on-demand delivery, and so that's how at the moment, you know, you're going to change the game. The momentary moment. How you're going to change the reality of people. What you're going to be able to do. I'm going to tell you that, where we're going to use quantum computing. We're going to use quantum computing to do a better matchmaking between a person who is waiting for an organ and an organ that you can transplant to this person. And the moment is the accident that happens on the street. There's going to be someone basically dying on the street, so someone dead and then you need, basically, to get this organ, it could be a kidney, for example, every organs have a time-lapse that you can use basically to transport that to someone else. Now the question is that you have the organ, it's in basically an ice-cubed environment-like box, and then you transplant that to someone, you have like few hours to figure out who are the best receiver. And this is hyper-personalization, because you need to understand the variable of all the body that is going to receive that but all the variables of the organ, until now is all main front to do the matchmaking. We're rethinking that using quantum computing. >> It's just wild, you know, what the cloud really enabled to concept. If you had infinite compute, infinite store, and infinite networking, at basically free, asymptotically approaching free, what would you build? And that's a very different way to think about problems. >> Not only will we build some amazing things, but I think we would change the reality of every people. Every people will have their own reality that they could use product and service the way they want it, and this will be a completely different, not a world, but a game set, that would be completely different. >> Marc, we're almost out of time, but I just want to ask you about Pierre, former CEO of Accenture passed away recently, and I was really struck by the linked investors. So many people, you know, I follow you, I follow Paul, a lot of people posted, what a special man, and what an impact he had, sounds really personally with most of the leadership here in Accenture. I was wondering if you could share a few thoughts. >> Well obviously, I mean, everyone's been very sad that we lost Pierre. I mean, he was just an amazing person. He was really a role model, not only in business, but in life. And he was so fun about fun of innovations, he loved the labs, he loved what we could do in it, I think he was really thinking about better future for the people, better future for the world, and everything, and it was really amazing for that. Everyone was struck really to see that. But I think there was so many testimonials pouring from our people, but what I was even more amazed was our clients. He really moved clients. And his visions is an amazing legacy for Accenture, and we're going to, I mean, this is so precious what he left us and I think that I really want the lab, every day that we're inventing something, I'm always thinking about Pierre and what he would have thought about these things. He was always enthusiastic reading our research paper and everything, so definitely the lab's going to continue to innovate, and I hope that Pierre, wherever he is, will be watching. >> I'm sure he's smiling down. >> And will be happy with that. >> Alright, well Marc, thanks a lot for taking a few minutes and congratulations on this continual evolution of what you guys are doing with labs and Innovation Centers, and now the Innovation Hub here in downtown San Francisco. >> Thanks, Jeff. >> Alright. He's Marc, I'm Jeff, you're watching theCUBE. We're at downtown San Francisco at the Accenture Innovation Hub as part of the Accenture Technology Vision 2019 presentation. Thanks for watching. See you next time. (light electro music)

>> Hey, welcome back everybody Jeff Frick here with theCUBE, we're downtown San Francisco, the Hotel Nikko, it's International Women's Day, March 8th, there's stuff going on all around the world, but we're excited to be here at the Accenture event, about 400 people, a lot of great panels, some familiar faces, some new faces, and one of those familiar faces joins us in the next segment. He's Marc Carrel, from Accenture, great to see you. >> Great to see you too. >> And a new face, Mary Hamilton, managing director also from Accenture Labs. Mary, great to see you. >> Great to see you too. >> So, first things, just kind of impressions of this event. I don't know if you did it last year, we weren't here, you know, there's a lot of energy, kind of, initial takeaways from some of the early panels. >> I mean, the energy is there, I mean, definitely last year we were here, I mean we do that every year for sure, and last year it was amazing as well, but I think this year is even bigger than we had last year. We have a kind of a hub and spokesmen of our organization where we have also our top leadership to go from different cities and then we celebrate all over the world. So this year the hub is here, and that's the reason why there's so much buzz and so much excitement. So that's pretty cool. >> Yeah, all of our leadership is here, and just phenomenal guests, um, from, yeah, we really aim for diversity, even not just gender diversity but diversity across all of our different panelists, you know, kind of thing they're thinking about, the way they're thinking about diversity, um, and you know, for me just some of those takeaways, you know, Vivian Ming, her point was when she showed up um, and, is there a difference between how men and women are treated? When she showed up as herself, as she is today, as a woman, she said she's never been asked a math question since. And that just blew me away that it's so black and white and they're really you know, from someone who's lived on both sides, there really is a difference. >> Right, right. So what are the topics? You guys are involved in Labs, is innovation, right? So there's digital transformation, yeah yeah yeah yeah yeah, but really innovation is kind of a more concrete thing that people are trying to achieve. And you guys are a big part of that at Labs, diversity is a big part of being more innovative. >> It's critical. >> So how do you guys see it in your customer base, and how do you see it within the work that you guys do within your own department at the Labs group? >> Well, I'll start, just, you know, you think about innovation that taps diversity is stronger innovation. Right? Our clients are delivering products and services to a diverse audience. And as we serve our clients and try to help them transform and be more digital, we have to reflect, the consumers or the buyers, for their products. And if we don't have that diversity, we're not going to deliver the right kinds of innovation. >> Right. >> I think Mary is absolutely right. And then what's very important to us is that we absolutely demonstrate that through numbers. So, you know, we have like seven labs, two of our leaders are women from those labs, we have five research domains, out of the five research domains, three out of the five are lead by women. >> Right. >> And I think that's pretty amazing. Now you see that from an organization's perspective. But I think if you look at who are the researchers, the most prolific that we have in the labs, from the few hundred people that we have, they're women. Hands down. And I'm going to give you some numbers which is again amazing, we are again publishing about 2,000 patents. I mean from the labs, since we exist. More than thirty eight percent have been driven by women. And then our most prolific labber is a woman. She has many of her, 124 applications and patents. How about that? I mean, she's amazing. >> Well drive is such an important piece, which is one of my favorite quotes. "In God we trust, but everybody else better bring data." Right? So if you don't apply data, if you don't measure the data, and you don't actually put in processes to specifically address the problem, it's just conversation, right? It's just interesting words. >> Absolutely, Jeff. And I think Mary will share with you, I mean also we're putting a process and an approach, a culture that is really changing the mind. >> Yeah. We focus on programs, not just at the junior level of recruiting, we do spend a lot of time and effort on getting out where women are, so we do things like Grace Hopper. We invest a lot to go to Grace Hopper and meet those technical women, we do things with women who code, with girls who code, what's the pipeline going to look like? But then once we have them in, how do we retain them? And so we've created a community and a network where we do a number of things. We mentor them, we create external networks, we create internal networks, we create kind of a social space, a safe social space, where you can bring up questions like "what should I wear to International Women's Day?", without having to feel awkward about asking those kind of things. We create a community that empowers and makes people feel comfortable. >> And do the clients get now that for whatever good, bad or otherwise they just need more good people. I mean we can't just not pull from the greatest population of good people that you can pull from. >> Absolutely, you're absolutely right. And I think another aspect from what I see what's happening in the lab, and I think Mary is a great example of that, we're looking at raw morals. Like, amazing woman like Mary, that is going to be driving, basically striving, and showing our people that you can really have a fantastic capacity as a technology person in the lab and in the Accenture organization overall. And that is very, very important for us. >> Yeah, and for me I'm not just a technologist but I'm also a mother of three small kids and I try to bring that to work, right? I try to show people, you know, I'm not just taking the hardcore path, I'm balancing a family I'm doing all these things that probably the rest of you are trying to do too and I let it show. Right? This is hard, how can I help you, here's what I'm going through, here are the challenges I'm facing, and try to bring others along too. >> So funny I did an interview years ago at an IBM event and there was a great women who was from an HR kind of consultative background, and she said, "You know, we spent all this time trying to find these great people, that have all these great attributes, and then we bring them in and then we just like give them the compliance manual, now you need to not be you, the mom, you've just got to be this little machine." And that's really not the way anymore, not at all. >> And credit to our leadership, to Marc, to Paul, Ellen, all the way up, right? There's true support for being truly human, bringing yourself to the workplace, and they do support it, they encourage it, right? And I think that that culturally seeps in to how we bring diversity to innovation too, right? It's bring your whole self to how you think about innovation. When we're hiring, I mean, I have a great example, I had a client come visit us, and he's been a strong supporter of us within his client space, and he came in and we were talking about you know, his work, and then I took him out to meet the team that was building the proof of concept for him, some tangential areas, and he met people from not just men and women, you know, diverse, but also different backgrounds, engineers, researchers, businessfolks, he met people from all kinds of backgrounds around the world. And he was able to have conversations about sports science, cricket, extended reality, and bring all those conversations back and at the end of his meeting he said "I was just floored at how many engaged conversations I was able to have with different people and the diversity of your workforce." And it's not just male female, right? You need that broad spectrum diversity to fuel innovation. >> Right. >> So -- >> Go ahead. >> Go ahead, Mark. Oh, I was just going to say, so, you know obviously it's a feel-good day today, it's feel-good place right here, but what are some of the significant, is it just execution or are there still some big hurdles that we have to overcome? Let's see, Mary, from your perspective. Marc's got it all figured out so we don't have to worry about him. >> Well, yeah, I mean there absolutely are, right? There is a pipeline problem, there is pipeline problem both from girls in STEM, coming up, right, what culturally we're telling girls and then there's a pipeline problem for, you know, we need to hire today. And I'm actually on the board of Women Who Code because I'm so passionate about their mission is, let's get women to understand that technology is approachable. That it is for all of us. >> Right. >> There's so many, the spectrum of what you can do with technology is so broad and so really if you think about it it's so appealing to so many women if you hit the right focus for them, then I think we can bring more women into tech even now, right? We don't have to wait for the pipe, we have to work on the pipeline, but we don't have to wait for it. We can start now. >> It's great, we do stuff with girls in tech and girls who code and obviously your Grace Hopper too. So you saw, just basing on her name, the gal that got the keynote, from uh, from the UK, who was basically, you know, at her last nickel with her kids, the poorest, homeless, and she learned how to code. And I dunno how old she was but she wasn't -- >> And we have so many stories of women who code. It turns their life around. And maybe the Tech For Good. >> Yeah, I think that's interesting, I mean also the nature of some of the projects we're doing also are driving women to be involved in this project. Do you know what is Tech For Good? I think I discussed that with you for some of these interviews. >> Yes. >> Where we're using technology and innovation to bring change to the world and the society and everything. We really believe, and we're not the only ones who believe that, you know, I mean, there are CEOs from other organizations that believe that, like, women are really on track today to build solutions or projects, with meaningful projects that really have purpose. That are meaningful to the society. And so Tech For Good, that we have launched, first of all got an incredible success, not only within the firm but outside of the firm, and the second thing is that it attracted tons of women talents. They love these kind of things. And then because they loved that, they want to stick with Accenture, and they, you couldn't describe it. >> Yeah, I mean, you get both sides of the coin. You're doing things that are empowering women in many cases, a lot of the projects we're doing. >> Right, right. And then that's also attracting women because we're excited about betterment of society and humanity and -- >> It's interesting, you know I got to give a lot of credit to kind of the younger generation coming up in terms of the prioritization of purpose within their hierarchy in deciding what to do, what companies to work for, how to spend their time, you know, it's very different than when we were, we didn't think about purpose, was trying to get a good job. Pay off the mortgage and then get a car. They don't want a car, they don't want a mortgage, they just want to do good. >> Absolutely, and I'll tell you something Jeff, I mean it's just like the Tech For Good I was just discussing with Mike Sutcliff before that, our chief officer of Accenture, and I was telling him that Tech For Good, the reason why we decided to do the Tech For Good and lab, talking to my leaders and everything is just like because my kids come to me and say "Hey Dad, you have the best job in the firm now, I mean, you need to do something with it." And so obviously we had to do some Tech For Good things. That's it. >> I love it. Alright, we're running out of time so I'll give you the last word, if when we come back a year from now, I'll probably see you in a month since I see you all the time. But a year from now at International Women's Day what are you working on, what are your priorities, how does this integrate into what you guys are doing at Labs, in your brand new space, by the way. >> Yeah, yeah. I mean part of the mission in that brand new space is to create these accidental collisions, right? >> Accidental collisions? >> Collaborative collisions I should say. (laughter) >> I was like, I love that term. >> No, we're not just colliding with each other. We're collaborating in these collisions. >> When atoms collide big things happen, right? >> Exactly. >> I'm sorry, knocked your train of thought. >> No, no, no, that's perfect. Um, and I think that whole mission is about how to create that diversity of thought. How do we bring people together that wouldn't have collaborated in the past? So my mission as we're moving into that new space, is to get my labbers, who are, you know, we're on our own little floor doing our own little thing, to expand our horizons, right? To think about diversity across the spectrum, how are we going to work with other groups, how are we going to bring different pieces to the innovation? So I hope we can reflect than even as we come back next year to this program. >> Great, alright. >> And my job is really to, I mean, as a, to pile on what Mary says, like, I'm going to continue stretching the limit of others' research. Because I think that there's nothing better than to do that hard research to solve that hard problem to elevate our people. And to be honest whether it's woman or man, they're all labbers, they're all part of our family, and there's no better, basically, reward for you to see these people, basically shining and explaining their passion to our clients, changes society and everything. That's what we got to do. >> Love the passion Marc, Mary, it's always great to catch up. >> It's great to see you. (soft music)

>> Hey welcome back everybody, Jeff Frick here, with theCUBE. We're at the Accenture Technology Vision 2018, it's actually the preview event, a couple of days before the report comes out. We came last year, it's really Accenture querying all their customers and partners, as to what are the hot topics for 2018? We're excited to have a return, from Accenture Labs, he's Marc Carrel-Billiard, the Global Lead for Accenture Labs. Last we saw you at the 30th anniversary. So, Marc, great to see you. >> Great to see you too, very happy to be here. >> Absolutely, and we saw you a year ago at this event as well. So, as you look at this Vision compared to last year's Vision, what really jumps out at you as being so different? >> I think what really jumps is just the fact that what we say here is that, you remember last year, it was all about technology for people, technology by people. What we see is that we move forward into, not just technology for people, by people, but how technology basically is shaping the society. And what people, basically I mean, like technology is changing their life, the way they work and everything. What we say to all this technology is that they're going to be a major impact in the society itself, and then companies need to work with people, need to work with society basically to change, basically, the new models. What we say also is that, something which is very important is that there's a transparency that needs to be brought out by this technology. I mean, it's like if you look at companies and everything they will have to build a social contract with these people. Bring in the technology. It's a two-way street now. >> Right, right. >> Like, you build a lot of technology, and people adopt this technology, and then need to bring back feedback. So what are you going to do about it? And it's not going to be about selling products, selling services, but building partnership. Partnership with the people, partnership to the society that you're going to build around them. That's very important. >> But it's kind of weird, because it's kind of bifurcated. On one hand, there's a personal level of connection that you've never had before. On the other hand, we're trying to automate, with software and data, as many processes as we can, which we've seen in Martek, probably on the cutting edge of that. And that sometimes can cause issues. So we're kind of bifurcating. Automate as much as you can, on the other hand, there's a personal touch and trust and a relationship that I never had before. >> I love this discussion, because I'll tell you this, I completely agree. But I think that people need to recognize that artificial intelligence, we've made tons of progress there. And you remember, we had so many winters along the way and everything. I think there will still be winters for artificial intelligence. Machines can do things very very well. >> Jeff: Right. >> But they still can't do what people can do. You know, for example, common sense learning. It's very difficult to explain to a machine what is common sense learning. You know what is common sense. For example, if I would like to build a robot that comes in your office, and picks, for example, a cup of coffee, and decide whether they want to throw it in the bin or basically reserve it for you, it's very difficult. You need to weigh the cup of coffee. You need to understand if it's warm or not warm. I mean, there's so many things that come to play. A robot would not be able to do that. You can do that, even your kids could do that. >> Pretty interesting. >> I know! >> So there's like five big things, I want to jump into a couple with you. One is, and you guys have twisted kind of common phrases-- >> We did, yeah >> A little bit of Accenture branding, of course, right? So one of them is the Internet of Thinking. So rather than the Internet of Things, which is very popular, and then, of course, we hear about the industrial Internet of Things. You talked about the Internet of Thinking. What do you mean by that? >> Okay, so Internet of Thinking is all about to recognize that every product in the world today will be very intelligent. We talk about artificial intelligence. We're baking the intelligence into systems. They all have matched learning, they all learn about what you're doing. So what we need to do is that, when we're going to build a new environment and everything, we need to understand exactly where all the processing power for this intelligence going to be sitting. Is it going to be, for example, if you have to reinvent the car of the future, where it's going to be driverless. You need to re-think about the cockpit of the future and the experience. There needs to be a lot of matched learning, intelligence, to understand exactly how they want to interact with you. Should sudoers sudo-vise? To recognizing your face when you're frowning, and stuff like that. I mean there's going to be so many things, so there's lot of processing power to put. Where do you put all this processing power? In the chip in the car? >> Right. >> Do you want to split it between the chip in the car and some other chip in the cloud? Where do you put all the data related to what you're going to be doing in this car? You want to look at all these data only in the platform in the car or you want to put a little bit in the cloud so you're going to be able to crunch all the data? You going to be sitting in a seat. American people spend on average, 500 hours per year in the car. Can you imagine what we can do there? Imagine we have sensors in the seats. We're going to be able to collect a lot of data about your wellness your well-being and everything. We want to make you more healthy. What are we going to do with all this data? Are we going to crunch the data basically in the car? Or in the cloud? So, what we want to say is that the Internet of Things is going to evolve to Internet of Thinking because we're going to have to be smarter. Not only to implement smart product in the car or something else, but to decide about our fixture. Where are we going to put all that stuff? Which process are we going to use? CPU, FPGA, GPU, even quantum computing? People need to think about where they're going to put the architecture. What type of flavor of architecture they want to have. All these things need to come into play. >> I know, I know! >> Marc we could go and go and go, unfortunately we're getting the hook, they're going to start their program so maybe we'll get you back after the program. >> Sure. >> Thanks for taking a few minutes, they're going to start the program behind us. I'm Jeff Frick, he's Marc, you're watching theCUBE at the Accenture Technology Vision 2018. We'll be right back after the presentation. >> Alright, sure. >> Thanks Marc. Alright, welcome back everybody! We are still the Accenture Tech Vision 2018 free event, the autonomous band is playing, very loudly. But it's good. So we've got Marc back, Marc Carrel-Billiard, and again he is Accenture Labs' Global Lead and he is also all on top of Extended Reality. >> Extended Reality. >> So Marc, we could talk about OR, VR, AR. >> Optics, olfactives, everything. >> Now it's ER? >> That's right. >> Extended reality. >> Extended reality's VR, I mean it's like, I think it takes every type of sensors or immersion, feeling and everything you can have because it's all about combinatory effect. If I combine the augmented reality with the audio, as well with the smell, as well as with the touch then you feel that something is happening. In fact-- >> How long until you just pass all the sensors and just go right to the wires? That's what I'm waiting for. (laughing) These things are not built to look at googles, right? >> I know, I know, I know. But it's coming. >> It's coming but what's interesting though, you guys put a play on it about distance. >> Marc: That's right. >> You guys are, you're positioning this as really a way to break down distance. >> Absolutely, I mean-- >> Jeff: How does that work? >> Well, we call that the end of distance because I think the feeling that we have is that what you're going to be doing is that, you know what I mean it's always the same stuff that you're looking for talent. You're looking for skill. You're looking for people. You're looking for information. Here. Where it's out there. How how are you going to bridge that? How are you going to reduce the distance? To bring people to you, to bring the skills you need, to build the information you need. Extended reality, virtual reality, that can help you out to do that. I'll give you an example, Komatsu, it's a Japanese company. >> Big tractors and things. >> That's right, big tractors and everything. Sometimes, I mean it's a lot of investment and everything, you want to try them out, you want to test them, but it's snowing, it's pouring, it's raining. You're not going to do it. What are you going to do? Why, you're going to use the vehicle a bit in virtual >> They're all autonomous though, and they all drive themselves around. >> But not now, there's some not there. But eventually you can use that in your office. You're going to be training in your office and when it stops raining, basically you're going to be there and you're going to be able to drive that and you're going to be able to use them. We see that in the oil and gas industry. We are building very complex platforms. It takes 10 years to build them, maybe less. The question is that, do you want to wait for five years, 10 years until the platform is delivered, to start training your people? No. I'm going to bring basically that to them directly. It's not only end of distance, it's end of time. I can reduce the time that this stuff is delivered, virtually, to train the people onboard and when they're going to be there. So they're going to be using virtual reality, to be trained on the platform, and then when they're going to be on the platform, they know how it works. But even more, then you go to augmented reality, When they can do maintenance on equipment by augmenting information, to make them more efficient. >> So what's the killer app going to be? Is it a killer app problem? Is it a hardware problem, right, we're still wearing the clunky goggles. What's the breakthrough? >> So the breakthrough is really new devices because right now, if you look at the market today in AR, VR, we're talking about $14 billion, one-four. The billion dollars-- >> Today? >> Yeah, today. Which is a lot. >> Yeah, it's a real number. >> But most of it is on the devices. Most of it is on gaming devices. You know, the stuff that you find on Xbox, the stuff that you find on the PlayStation, very consumer-driven. The big business is really enterprise business which is how you're going to use these devices in oil and gas industry, in automotive industry, in very toxic environments. Where the device needs to be lightweight, with long battery-life, it needs to be intrinsically safe as well. Safe in the-- >> Jeff: Environment, right. >> The devices are coming, and then by 2020 the estimate is that, that whole business is going to shift from $14 billion to $143, one forty three. >> By 2020? >> Yeah. >> Two years from now? That's right, two-three years, because the devices are there. And then, right now 70% of this business is consumer-driven, and 30% is enterprise. We're going to flip that. 70% is going to be enterprise, and 30% will be consumer. >> In 2020? >> Yes. >> Just right around the corner. >> Right around the corner. I mean, I met with a couple of companies, this company called RealWear, they doing amazing device. It's a device you wear, you can put that on the helmet, very very light. You can drop it from 10 meters, it bounce back. It works. And then basically you have bots with cognition in the very noisy environment, like this one, you can speak, you recognize everything. It can provide you with augmented reality information about what you need to do and everything. That's the typical device that we need. You can use it in toxic environments. It has other certification. I mean it's IPv6 and everything, you can run on it and it doesn't do anything, and that's exactly what we need to develop the new use case, that's going to drive these further. >> Yeah, cause we're still a long way from there but two years is not very long, >> It's not long. >> for the devices. >> I mean, it's acceleration. >> Right, right. Alright Marc, well we're excited. What's your favorite AR-VR-ER application? >> You and I, we go to Venice tomorrow, always virtual reality, and so with the combination of the olfactive, the sound, the sun and everything. You can be sitting there on the terrace, you can hear the Vaporetto passing by, you eat the bread, and I fake your brain with the olfactive stuff, you believe it's a pizza, and you drink the water and it's Chianti. That's what it's going to be. >> See I think the device is going to be when it plugs into your head. Again, avoid all these things and go straight in. And then it begs the question, did you really do it? >> I know, I know. Or not? That's way deep, we don't have time Marc. >> It was great to see you. >> Thanks for stopping by. He's Marc, I'm Jeff, you're watching theCube, Accenture Technology Vision preview party, thanks for watching. (bright music)

>> Announcer: From the Computer History Museum in Mountain View, California, it's the Cube. On the ground with Accenture Labs 30th Anniversary Celebration. >> Hello and welcome back to our special on the ground coverage of Accenture Labs 30 year celebration. Here's to the next 30 years is their slogan and I'm John Ferry with the Cube and I'm here with Marc Carrel-Billiard who's the Senior Manger that runs R&D Global for Accenture Labs. Welcome to the Cube conversation. Thanks for joining me. >> Marc: Thanks, John. >> So, I got to ask you, Accenture 30 years, they weren't called Accenture back then, it was called Arthur Anderson or Anderson Consulting and then it became Accenture, now you got Accenture Lab. But you have had labs all throughout. >> You're right. I mean, it's pretty amazing. And I think this is absolutely right. So we had this organization for 30 years, believe it or not. And that organization is doing applied research. So what we do is we leverage new technology innovations and everything to really solve business challenges or societal pacts and social changes and everything. >> State of the art back then, if I remember correctly my history was converting an S&A gateway to a technet to a TCP/IP network. >> Yeah we just improved a little bit. We went to quantum computing, to Blockchain, to different type of things like that. >> What a magical time it is right now >> It is magic. >> Share some color on today's culture, the convergence of all this awesomeness happening. Open source, booming. Cloud, unlimited compute. You have now more developers than ever, Enterprise is looking more and more like consumers. So a lot of action. What's the excitement? Share the cutting edge lab's activity. I think you said something absolutely right. I mean, I think there's a combinatorial effect of two different technology working very well together, and is a compression on time, all those technology waves that are maturing very fast. So one thing that we been doing is a great example for that, is quantum computing. You heard about quantum computing, you know? >> Of course. >> That's the new Paradigm of computing power. Leveraging like, quantum mechanics, you know? I mean it's really amazing stuff. And believe it or not, we've been working with D-Wave, they have a quantum computer in Vancouver, and a companies called 1QBit, it's a software company, and we've built, on top of that, an algorithm that has molecule comparison. And we worked with Biogen, a pharmaceutical company, to work on this. Now, the really staggering thing about it, is that we talked about it like six months ago, we build the pilot in two months time. Done. And then now, I mean, it's already made. >> Well, this is amazing. This is what highlights to me what's exciting. What you just described is a time frame that's really short. >> That's right! >> Back in the old days, it was these projects were months and months, and potentially years. >> Absolutely. >> What is the catalyst for that? Is it the technology leverage? Is it the people? Is it the process? All three? What's the take? >> I think it's all three. I would say that definitely the technology, as I said, get combined faster. You said very right, there's a lot of capability in term of high performance computing we can get through the Cloud, the storage as well. The data that we're going to be accessing, and then I think the beauty is that, putting all the people together for the quantum work. We had mathematicians, we have from Biogen, we have our own labs, and all people together, they make the magic happen. >> 30 years ago, just a little history 'cause I'm old enough to actually talk about 30 years ago, the Big Six Accounting Firms, accounting firms, ran all the big software projects. How ironic is that, that today Blockchain disrupts the even need for an accounting firm, because with Smart Contracts, Blockchain is turning out to be a very, very disruptive operation in technology, because you don't need an accounting firm to clear out contracts. Blockchain is very disruptive. What are you guys doing on Blockchain? >> You're absolutely right, John. And you know, the first thing. So, we have seven labs in Accenture Labs. And we have one lab didn't get it on Blockchain, and it's Sophia Antipolis inside of France, where I'm from, by the way. We're doing a lot of things with Blockchain. A lot of people are thinking about Blockchain as a system that's going to regulate, basically, transfer a transaction, financial transaction. We want to take Blockchain to the next level. And one thing we're doing, for example, We're using Blockchain for Angels. How we're track, basically, donation you're going to do. We going to use Blockchain for-- >> Well that's because people want to know their money's actually going to good. >> That's right! That's right! >> Not to scams that have been out there. >> You got it. >> We going to use Blockchain as a DRM system, Digital Rights Management system. We're going to use that in manufacturing industry, in many industry, and it goes on and on and on. >> What is the big buzz right now with Cryptocurrency? You're seeing a lot of these ICOs out there. Are those legit? In your mind, is it just a bubble? Is it just a normalization's going to come, what's your take on Initial Coin Offerings? >> I think, to be honest with you, I think this is a progress with thing. I mean, we discuss about Blockchain and everything. We see some trains going there. I think it's accelerating as well, because it's got a lot of take up and everything. We see, also, the world changing, and I think we need to look at the geo-political context of the world and what could happen. So I think those kind of new regulation, the way it's going to work. I mean, it's coming on time, people's going to leverage it, so I think it's not some fad stuff. This is something that's going to stay. >> It's just a Wild West. >> But it was, exactly. Right now, we need to work on the right standard, we need to figure out how it's going to work and everything. >> What is the exciting things that you see out there right now? I mean, Blockchain just kind of gets us excited 'cause you can imagine different new things happening. But the clients that I talk to, customers, your clients, or CIOs, they have to reimagine the future. >> That's right. >> With preexisting conditions called legacy infrastructure. >> Exactly >> Legacy software. How do they get the best of the magic and manage the preexisting conditions? >> So, there's a lot of innovation in term of software development. You take energy in everything that we have, basically, to connect to your legacy, and leverage it as much as you can. You know, there's a big progress in artificial intelligence today. I mean, I've live a lot of winters of artificial intelligence. I think finally, maybe there's going to be some spring. Why? Because of what we talk about. The iPad from one's computing the data available, and then also, some new type of algorithm like deep learning and everything. That data that is somewhere into this company called the Dark Data, people is going to be able to leverage it, and then make those artificial intelligence systems even more intelligence, smarter, and everything. So, legacy's here, but we're going to leverage it, and we're going to give a second life to those legacy environment. So those technology like artificial intelligence, new analytics and all those different things. >> So I got to ask you a kind of politically hot question, which is the digital transformation. >> Yes. >> So there's doubt we're in a digital transformation. No brainer. Yet, I go to conferences over and over again, and I see Gartner Magic Quadrant. I'm number one on the Magic Quadrant, and everybody's number one in the Magic Quadrant. So, the question is, what's the scoreboard of the new environment? Because, if you use the old scoreboard, and the world's horizontally scalable, you're going to have a blending of Magic Quadrants. So there's going to be a disruption, and that's causing confusion to the CIOs and CXOs because you got Chief Data Officer, Chief Security Officer, you got no perimeter for security, you have quantum computing, you have Cloud. So, people are trying to squint through all the nonsense and saying, how do you measure success? >> Yeah. >> Certainly customers is a good one. >> I think this is the typical question. I mean, this whole digital transformation, I understand that is important, and we need to understand. I mean, Accenture, and especially the lab, it's all about result. And you know what? The mission of the lab is new, it's applied, is now. New technology applied for real challenges, and I want to deliver it now, and I want to work for six months. So my word is that our research is outcome driven, and that's exactly what we're seeing. So, I told you about the quantum computing, and I have other example where we are really laser-focused on making an outcome. I think that's where-- >> So, to your point, people shouldn't buy promises. >> No. >> They should buy results. >> That's right. >> So, Peter Barris, who runs our research, said to me, and I asked him the question, he goes, ah, that's just a bunch of BS. The ultimate metric is how many customers you have. So, someone should be touting their customers. >> Sorry? >> They should be touting their customers, not some survey. >> No, absolutely. And I'm really for that. >> I want to tell you something, that I'm a very pragmatic person. I'm coming from the field, where I was serving 400 clients doing, every day, project delivery, you know? >> John: God bless you. >> And I've always been doing innovation at the same time, but my view was that innovation needs to be scalable, it needs to be tangible, it needs to be outcome driven. So again, this is really the matter of the lab, and if you look at how the lab works with the rest of the organization of Accenture, this is exactly what we're doing. We connect with our studio, where we can do prototyping front of the eyes of our client. We connect with Open Innovation, where we connect with the best start ups in the world. I think, you remember when I told you combinatorial effect. There's a combinatorial effect with technology that is a combinatorial effect with people. If you put the people from start up, the best guys from the lab, the best guys from the studios and everything, that's where the magic happens. >> So this is a new configuration? >> We collect the innovation architecture. >> So this is a scalable model for being agile, and the results are what? Faster performance? >> Faster performance, innovative performance, and tangible outcome. >> Okay Marc, you're an excitable guy, I like talkin' with you, what are you most excited about right now in this world that you're living in? So, I told you about the technology, and there's one thing that the lab is doing, and we'll be launching that this year, and we'll continue expanding. It's what we call Tech For Good. Tech For Good is how we're going to apply technology to change society. What we're going to do for fighting hunger in India. How we're going to give situational awareness to blind people using augmented reality immersion learning. That keeps me awake at night, because this is technology for best usage, it allows for our people to sleep well at night. My kids are proud of me, and I think we can-- >> Change the world! >> That's right! We can attract great people. >> Alright, final question. Here at the celebration, at the Computer History Museum in Silicon Valley, what's the big scene here? Share with the folks who are watching, who aren't here, what's happening. >> I think, first of all, the venue is amazing. Computer Historic Museum is probably one of my favorite museum here in Silicon Valley. I mean, you need to understand that, 15 years old I started to work on a IBM 360 of my uncle, so the machine over there, I know it. I worked on it. And when I see the completed progress where we are today, when we see the Cray, when we see the quantum and everything, I feel so lucky that we're celebrating 30 years. Now I'd to go for the next 30 years of the lab. That's what I want to do. >> Let's get that on our next interview. Marc, thanks for sharing, here's to the next 30 years. This is the Cube coverage of Accenture Lab's 30 year celebration. The Computer History Museum, I'm John Ferry. Thanks for watching.