>> 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)

>> 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 the Salesforce Tower. We're in the 33rd floor with the grand opening of the Accenture Innovation hub. It's five stories inside of the Salesforce Tower. It's pretty amazing, couple of work floors and then all kinds of labs and cool things. Tonight they introduce the technology vision. We've been coming for a couple of years. Paul Daugherty and team. Introduce that later, but we're excited to have a couple of the core team from the innovation hub. And we're joined by Mary Hamilton She's a managing director of Accenture Labs. Great to see you Mary. >> Nice to see you too. >> And Teresa Tung also managing director of Accenture Labs. Welcome. >> Thank you. >> So it's been quite a day. Starting with the ribbon cutting and the tours. This is quite a facility. So, what does it mean having this type of an asset at your disposal in your client engagements, training your own people, it's a pretty cool spot. >> Yeah, I think it's actually something that's, these innovation hubs are something that we're growing in the U.S. and around the world, but I think here in San Francisco, we have a really unique space and really unique team and opportunity where we're actually bringing together all of our innovation capabilities. We have all of them centered here and with the staircase that connects everyone, we can now serve clients by bringing the best of the best to put together the best solutions that have open innovation and research and co-creation and innovation all in one. >> Right and you had a soft opening how many months ago? So you've actually been running clients through here for a number of months, right? >> We have. So, we've been working here probably about six months in the workspaces. We've been bringing clients through, kind of breaking in the space, but just over the holidays we opened sort of all of the specialty spaces. So, the Igloo, the Immersive Experience, we've got a Makeshop, and those all started to open up so our employees can take advantage and our clients can come in. >> Right, right. >> Yeah. >> So one of the things that comes up over and over I think in every other interview that we've had today is the rock stars that are available here to help your clients. And Teresa I got to brag on you. >> Got one here. >> You're one of the rock stars, all you hear about is most patents of any services for most patents from this office of all the other offices in Accenture. >> All of Accenture >> You're probably the person. (laughs) So congratulations. Talk about your work. It's funny, doing some research, you have an interview from a long time ago, you didn't even think you wanted to get in tech. >> Yeah. >> Now you're kicking out more patents than anybody in Accenture which has like 600,000 people. Pretty great accomplishment. >> I think it's a great story how a lot about people think about technology as a geek sort of thing and they don't actually picture themselves in that role but really, technology is about imagining the future and then being able to make it happen. You can imagine an idea, and you think Cloud, and AI, VR, it's all so accessible today. You could buy a 3D printer and just print your own idea. >> Right. >> And that's so much different than I think it was even ten, twenty years ago. And so when you think about tech, it's much more about making something happen instead of, just again, coding and math. Those are enablers but that's not the outcome. >> Right, right. So what type is your specialty in terms of the type of patent work that you've done? >> I've done them all. So I start with cloud computing, doing a lot of APIs and AI. Most recently doing a lot of work on robotics and that's the next generation. >> Right. so one of the cool things here is, software is obvious, right? You get to do software development, but there's a lot of stuff. There's a lot of tangible stuff. You talked about robotics, there's a robotics lab. Fancy 3D printing lab. >> There's like this, >> Yep. >> I don't know, the maker lab, I guess you call it? >> That's right. >> So, I don't know that most people would think of Accenture maybe as being so engaged in co-creation of physical things beyond software innovation. So, has that been going on for a long time? Is that relatively new? And how is it playing in the marketplace? >> Yeah, so, there's a few things we've been doing. Some of it is the acquisitions we've made, so Mindtribe, Pillar, Matter, that really have that expertise in industrial design and physical products. So we're getting to that space. And then, I'm also, as a researcher's standpoint, I'm really excited about some of the area that you'd never think Accenture would play in around material science. So if you start to combine material science plus artificial intelligence, you start to have smart materials for smart products and that's where we see the future going is what are all the kinds of products and services that we might provide with new material? And new ways to use those materials And, >> Right. >> My original background, my degree is in material science so I feel like I've kind of come full circle and exactly what Teresa was saying is how can you design things and come up with new things? But now we're bringing it from a technology perspective. >> Right, got to get that graphene water filtration system so we can solve the water problem in California. That's another topic for another day. But I think one of the cool things is really the integration of the physical and the software. I think a really kind of underreported impact of what we're seeing today are connected devices. Not that they're just connected to do things, but they phone home at the end of the day and really enable the people that developed the products, to actually know how they're being used. And then the other thing I think is so powerful is you can get shared learning. I think that's one of the cool thing about autonomous cars and Waymo, right? If there's an accident, it's not just the people involved in the accident and the insurance adjuster that learn what not to do but you can actually integrate that learning now into the broader system. Everyone learns from one incident and that is so, so-- >> Right. >> different than what it was before. >> Yeah I mean, it really points to type of shared pursuits of larger business outcomes. By yourself, a company might see their customer and impact their business and their product, but if you think about the outcome for the customer, it's around taking an ecosystem approach. It might be your car, your insurance company, you as an individual, and maybe you might be a hobbyist with the car, you're mechanic. Like this ecosystem that I just described here. It's the same across all of the different types of verticals. People need to come together to share data to pursue these bigger outcomes. >> Right, you need to say? >> I was just going to say, and along those lines, if you're sharing data, those insights go across the legal system. But then they can get plugged back in to thinking about the design, and we're looking at something called generative design where if you have that data, you can start to actually give the designer new creative solutions that they may not have thought about. >> Right. >> So you can kind of say, hey based on these parameters of the data we've received back about this product, here are all the permutations of design that you might want to consider, and here's all the levers you can pull and then the designer can go in and then say, okay, this makes sense, this doesn't. But it gives them the set of here are all of the options based on the data. >> Right. >> And I think that's incredibly brilliant. It's kind of the human plus machine coming together to be more intelligent. >> So, human plus machine, great Segway, right? What we just got out of the presentation and one of the guys said there's three shortages coming up. There's food, water and people. And that the whole kind of automation and machines taking jobs is not the right conversation at all, that we desperately need machines and technology to take many of the tasks away because there aren't enough people to do all the tasks that are required. >> I mean think about it as a good thing. As a human, the human plus workers really enabling your job to be easier, more efficient, more effective, safer. So any task that's dull dirty, dangerous, those are things that we don't want to do as humans. We shouldn't be doing those as humans. That's a great place for the robotics and the machines to really pair with us. Or AI, AI can do a lot of those jobs at scale that again, as a human we shouldn't be doing. It's boring. Now you could have human plus machine whether it's robotics or AI to actually make the human a higher level worker. >> Right, I love the three Ds there. You got to add the fourth D, drudgery. Talking about automation, right, it's like drudgery. Nobody wants to do drudgery work. But unfortunately we still do. I mean, I'm ready for some more automation in my daily tasks for sure. Okay, so before we wrap up. What are you looking forward to? We got through the ribbon cutting. Are there some things coming in the short term that people should know about, that you're excited that you're either doing here, or some of your, kind of research directives now that we got the big five from Paul and team. What are you doing in the next little while that you can share? >> Well, I'm excited to have clients coming in, so >> Yeah. >> Al lot of the innovations that we have like Quantum Computing. This is a big bet for Accenture. At the moment, at the time we started Quantum Computing, our clients weren't begging for it yet. We made that market. We went out and took a bet. We saw how the technology was changing. We saw the investments in Quantum. We made the relationships with 1QBit, with IBM and through that, now we're able to find this client opportunity with Biogen and that's the story that we published a drug discovery method that is actually much better than what would happen before. >> Right. >> Yeah. >> Mary? >> For me it's about, it's also the clients and it's thinking about it from a co-research and co-innovation standpoint. So, how do we establish strategic, multiyear, long-term relationships with our clients where we're doing joint research together and we're leveraging everything that's in this amazing center, to bring the best and to kind of have this ongoing cycle of what's the next thing. How are we going to innovate together, and how are we going to transform them, talk about approximately from building physical products to building a set of services. >> Right, right. >> And I think that's just taking advantage of this to make that transformation with our clients is so exciting to me. >> Well, what a great space with great energy and clearly you guys look like you're ready to go. >> Hey, we are. >> So congrats again on the event, and thanks for taking a few minutes and sharing this terrific space with us. >> Thank you. >> Thank you. >> All right. She's Teresa, she's Mary, I'm Jeff. You're watching theCube, from San Francisco the Accenture Innovation Hub. Thanks for watching, we'll see you next time. (upbeat 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.