>> 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.

>> Narrator: Live from San Francisco, it's theCUBE, covering RSA Conference 2020 San Francisco. Brought to you by SiliconANGLE Media. >> Welcome back everyone. This is theCUBE's coverage from RSA Conference on Moscone South. I'm John Furrier, host of theCUBE. You know, cybersecurity is changing, and the next technology is right around the corner, and it's got to be invented somewhere, and of course Accenture Labs is part of it. Our next guest is Lisa O'Connor, Global Security R&D Lead for Accenture Labs. Lisa's working on some of those hard problems all around the world. Thank you for joining me today. Thanks for coming on. >> Thank you for having me. >> So, we always get the good scoop from Accenture, because you have a lot of smart people in that company. You know, they know their stuff. I know you got a huge analytics team. I've talked to Jean-Luc Chatelain before, and I know you got a massive amount of, deep bench of talent. But as you have to go do the applied R&D, and maybe some of the crazy ideas, you got to start thinking about where the puck is going to be. >> Absolutely. >> You got to understand that. Well, it's pretty clear to us that Cloud is certainly there. Palo Alto Networks had a disappointing earnings yesterday, because their on-premises business is shifting to the Cloud. You're seeing hybrid operating model and multicloud for the enterprise, but now you got global challenges. >> We absolutely do. >> Huge, so what are you guys working on that's coming? Tell us. >> So we're working on lots of exciting things, and Cloud is one of them. But, some of the things I'm so passionate about in labs, and I have the best job at Accenture. Don't tell anyone. (laughs) I do. So, we are working on, like Jean-Luc is working on applied intelligence, we are working on robust AI. So, when we think about AI in the future, how do we feel that, and know that it's okay? How do we put it out there and know it's safe in production, we've done the right training, we've made our model resilient to what's out there? One of the things we see happening, and I love AI, love it. It has great potential, and we get great insights out of it, but a lot of times we stop, we get the insights, and we say, "Okay, it's in the box, we got a couple hits there, "we're good, it's good." No, maybe not. And so really, it's learning and creating the actually applied attacks on AI, and then figuring out what the right defenses are. And, depending on what type of machine learning you're using, those defenses change. And so, we're having a great time in our lab in Washington D.C., working on basically defending AI and building those techniques, so that what we put out as Accenture is robust. >> You know, it's interesting, AI, you watch some of the hardcore, you know, social justice warriors out there going after Amazon, Google, you know, because they're doing some pretty progressive things. Oh, facial recognition, you got AI, you got Alexa. You know, a lot of people are like, "Oh, I'm scared." But, at the end of the day, they also have some challenges like network security, so you have all this AI up and down the stack. And, one thing I like about what's being talked about in the industry is the shared responsibility model. So, I got to ask you, as AI becomes exciting, but also, balancing, frightening to people, how do you get that shared responsibility model, so we get it right, do the experimentation, without people freaking out? (laughs) So, it's kind of like this weird mode we're in now, where I want to do more AI, because I think it benefits society, but everyone's freaking out. >> Yeah, so, in our tech vision that we just launched, The Tech Vision 2020, there's a lot of talk about value and values, which is really important when we think about AI because we can get great value out of it, but there's a values piece of it and it's how we're using it, how we're getting those insights. Because, the one thing, we have this circle, and it's between customer experience, because the companies that do customer experience well are going to excel, they're going to keep their clients, they're going to do amazing things, they're going to become sticky. But, to do that well, you have to be a good custodian of their data and their information, and curated experiences that they want, and not the creepy ones, not the ones they don't want. And so, we really look at that trust is necessary in that ecosystem, in building that, and keeping that with clients. So, that's something that came out of our technology vision. And, in fact, we're going to be talking at the Executive Women's Forum, this is tomorrow, and we're going to be having a panel on AI, and defending it, which will be very interesting. >> Make sure your people film that conference. We'd like to get a view of it on YouTube after. We love those conferences, really insightful. But, I want to get back to what you were talking about, the fun side. >> Yeah. >> You got a lot of new things on, your guys are kicking the tires on, scratching the surface on. You have two operating labs, one in Washington D.C., and one in Israel. What city in Israel? Is it in Tel Aviv or-- >> Herzliya. >> Okay, did not know. >> Yeah, the tech district, just north of Tel Aviv. It's the hotspot. >> So, Silicon Valley, D.C., and Israel, hotbeds of technology now. >> Yes. >> What's coming out of those labs, what's hot? >> Oh, there's so much exciting stuff coming out of our lab in Herzliya. One of the things that we have, and it's something that's been long and coming, it's been brewing for a while, but it's really looking at creating a model of the enterprise security posture. And, when I say a model of it, I'm talking about a cyber digital twin. Because, so much we can't do in our production networks, we don't have the capabilities. We can look around the room, but we don't have the capabilities on the SOCs team side, to ingest all this stuff. We need a playground where we can ask the what-ifs, where we can run high performance analytics, and we do that through a temporal knowledge graph. And, that's a hard thing to achieve, and it's a hard thing to do analytics at scale. So, that's one of the big projects that we're doing out of our Israel lab. >> Are you saying digital twins is a framework for that? >> Yeah. >> Does it really work well with that? >> So the knowledge graph, we can create digital twins around many things, because a digital twin is a model of processes, people, technologies, the statefulness of things, and configurations, whatever you want to pull in there. So, when we start thinking about, what would we take in to create the perfect enterprise security posture? What would give us all the insights? And, then we can ask the questions about, okay, how would an adversary do lateral movement through this? I can't fix everything that's a 10, but I could fix the right ones to reduce the risk impactfully. And, those are the kind of what-ifs that you can do. >> That's real sci-fi stuff, that's right around the corner. >> Yeah, it is. >> That simulation environment. >> It is. >> What-ifs. Oh my god, the company just got hacked, we're out of business. That's your simulation. You could get to, that's the goal, right? >> It absolutely is, to ask those good business questions about the data, and then to report on the risk of it. And, the other thing, as we move to 5G, this problem's getting bigger and bigger, and we're now bringing in very disparate kinds of compute platforms, computing-at-the-edge. And, what does that do to our nice little network model that we had, that our traditional systems are used to defending against? >> I mean, just the segmentation of the network, and the edge opens up so much more aperture-- >> Yes, it does (laughs). >> to the digital twin, or a knowledge graph. You brought up knowledge graph, I want to get your thoughts on this. I was just having dinner last night with an amazing woman out of New York. She's a Ph.D. in computer science. So, we're talking about graphs, and I love riffing on graph databases. But, the topic came up about databases in general, because with the cloud, it's horizontally scalable, you've got all kinds of simulation, a lot of elasticity going on, there's a lot of software being written on this. You got time series database, you got relational database, you got unstructured, and you got graphs. You got to make them all work together. This is kind of the unique challenge. And, with security, leveraging the right database, and the right construct is a super important thing. How do you guys look at that in the labs? Because, is it something that you guys think about, or is it going to be invisible someday? >> Oh, we think about it a lot. In fact, we've had a number of research projects over the last five years now, actually six years, where we've really pivoted hard in cyber security to graph databases. And, the reason for that is, the many-to-many relationships, and what we can do in terms of navigating, asking the questions, pulling on a thread, because in cyber hunting, that's what we're doing. In many of these use cases that we're trying to defend an enterprise, we're following the next new path based on the newest information of now what the challenge is, or what the current configuration is. So, that's really important. So, graph databases enable that so well. Now, there's still the architecture challenge of, okay, when I ask a query, what am I doing? Am I disrupting the whole apple cart? Do I have to process everything over, or is there a way to do that elegantly, where I can ask my query, and because of how I've structured it in storage, I can do it much better, and I can do it much more efficiently. And that, I think, is where the opportunities are. >> I got to tell you, I'm getting exited now on this whole database discussion, because you think about the logic around what you just said. A graph database with that kind of complexity, when you factor in contextually different things happening at any given time, the database needs to be parsed and managed differently. >> Yes. >> That's a huge challenge. >> It is a great research challenge, which is why we're doing it. >> What is that, how far along are we going to be able to have this dynamic, self-evolving, self-governing, self-healing data modeling? Is that coming soon, or... >> Yeah, I hope so. We wrote about it a couple of years ago. >> You did? >> The self-healing enterprise, aspirational. But I think, I mean, we try to get to real time, right? And, we try to get to real time, and again, refactoring. As we talk about what an adversary is going to do, or lateral movement through a business process, we're talking about a lot of computational horsepower to recalculate all that, process it again, update it, and then again present that back. So the number of things we're asking, how we're asking it becomes also very important to the structure. >> Just, it goes zooming up a little bit, high level, what we're really talking about here is value >> of the data. >> Absolutely. >> And, when you get into the valuation of the nodes, and the arcs, and all that graphs, and other databases, you got to know what to pay attention to. It's kind of like going into the hospital and hearing all these alarms going off. At some point you don't know what's, until they hear a flat line, or whatever. >> Right. That's a bad one. >> I mean, well that's obvious. But, now sometimes there's so many alerts, there's so many alarms. How do you understand at any given time what to pay attention to, because obviously when someone's having a problem you want to pay attention to it. If it's a security alert, that's prioritized. >> And the devil is in the analytics, right? What's the question we're asking, and the analytics that give us that prioritization? And that's non-trivial, because there are a lot of other folks that are doing prioritization in a different manner. To do it at scale, and to do it, not just one hop out, but I want to go all the way to the crown jewels, I want that whole path navigated, and I want to know where to cut along that path. That's a hard thing to do. And so, we've actually developed, and we've submitted patents for them, but we've developed new analytics that'll support that. >> Awesome. Well Lisa, I want to ask you kind of a, I'll give you a plug here, just going to get it out, because I think it's important. Skills gap's a big thing, so I want to give you a minute to explain, or share what you're looking for in your hiring. Who are you looking for? What kind of, the make-up of individual, obviously? Maybe, do you use straight, more academic paper kind of people, or practitioners? I mean, when you look to hire, what are some of the priorities that you look for, and who would thrive in an Accenture Lab's environment? >> Oh, my goodness. >> Take a minute to share what you're looking for. >> Yeah, so we love people that think out of the box, and those kinds of people come from very different backgrounds. And so, part of that is, some of them we look for Ph.D.'s, that have wonderful applied skills, and applied is a key word there. White papers are great, I need to be able to prove something, I need to be able to demo something that has value. So, having the applied skills to a business challenge is really important. So, that sort of ground, understanding the business, very important too. But, our talent comes from many different areas. I mean, I kind of joke, my lab looks like the UN, it's wonderful. I have people from across the globe that are in our cyber security lab. I have, in our Washington D.C. lab, we're 50% women, which is also exciting, because we want different experiences, and we shoot for cognitive diversity, right? So, we're looking for people that think differently about solving problems, and are not encumbered by what they've seen in the past, because we're trying to be tip of spear. And, I'm sure you know that from Paul Daugherty. >> Yeah. >> We are trying to be three to five years over the horizon. >> You guys got a good narrative. I always love talking to Accenture, they have a good vision. So, I got to ask you, the next logical question is, obviously, in the news, you see everyone talking about breaches, and ya know, it's not a breach if the door's open, you just walk in. They're really walking in, nothing was really breached, you're just giving it to them. >> Yeah. It's a passive invitation. >> (laughs) Hey come on in. Human error is a big part of it, but then, breach is obviously targeted, phishing, and all that good stuff. But, as those stories get told, there's a whole nother set of stories that aren't being told that are super important. So, I'd love to get your thoughts on, what are the most important stories that we should be talking about that aren't being talked about? >> Yeah, so I have two that are front-of-mind for me. One theme we come back to, and it's not sexy, it's hygiene. It is IT hygiene, and so many of the large companies, and even medium, small companies, we have legacy technology, and keeping that adds complexity, it adds to the whole breadth and depth of what we have to manage and defend. Keeping that attack surface simple and small, cloud-enabled, all those good things, is a real asset and it makes it much easier to defend. So, that's kind of the first non-sexy one, hygiene. The other one I'll say that I think is a challenge that we are not dealing with yet, quantum computing, right? And so, we're on the way to getting our post quantum cryptography in place, but there's another dimension to it, and it's our histories. So, all of the things that have passed on the wire, all the communications with the key exchanges, all that brilliant stuff, is sitting somewhere. Once we get to that point where this becomes very routine, and it's coming fast, we predicted eight years, two years ago. >> So, all that exhaust is somewhere, pent up. >> It's somewhere that, we have to think about how much data we're keeping as custodians, how we're managing it, and then we have to think about the exposure from our past, and say, "Okay, what does that mean that, that was out there?" "Is it aged enough that it doesn't have value?" And, I think there's a real triage that needs to be done, and certainly data management. >> I think, you know, the hygiene brings up a good point. It reminds me of the story Andy Jassy was telling about the mainframe customer that they couldn't find who had the password. They had to find their person, who was retired 10 years earlier to get the password. You don't forget things, but also, there's a human component in all this. Humans and machines are working together. >> Absolutely. >> And. that's a huge part of it. It's not just machines dominating it all, there's going to be a human component, there's a societal impact that we're seeing with information. And, whether that's out in the open, or behind closed doors, there's all kinds of things looming. >> There are, and I think one of the things in the companies that we're seeing who are embracing innovation well, are doing a lot of retraining. Because, the things that people are excellent at, AI is not good at, and the things that AI is good at, are not at all what people are good at. So, the good news is there is a beautiful teaming there, if we retool the skills, or if we re-envision those roles, so that people can get into those roles, and I think that's really important, because I'd rather see AI do all the heavy lifting well, and be trustworthy, and robust and all those great things, and the people be doing the much smarter things that require a human. >> Does the process serve the purpose? Does the purpose serve the process? Same kind of question, right? >> Exactly. >> AI, you can't have great AI that does nothing. >> That's right. >> (laughs) So, it has to be relevant. >> It absolutely does. >> Relevance is kind of a big thing. >> And we own that context, right? Humans own that context. >> Yeah. Yeah. Yeah. Well, thanks for coming in, and sharing the insight. Really appreciate it. Final question, it's always tough to pick your favorite child, but what is your most coolest thing you're working on right now? >> I'll tell you, the cyber digital twin stuff is so cool. >> The what? >> The cyber digital twin stuff is so cool. When you see the power of what that picture, and the analytics can do, we'll show ya. >> Do you have a demo of that now? >> We absolutely do. >> You do. Is it online, or is it more in person you got to see it? >> More in person. >> Okay. >> Folks can reach out, yeah. >> We'll have to get the exclusive on that. >> We do. >> I love those simulations. I think it's very beneficial. >> It is. >> A lot of learning. I mean, who doesn't want practice? >> Well, and a picture, you know that is worth a million dollars. It's just incredible to look at it, and it clicks. It clicks of all the potential things you could ask or do. And, that's the exciting part now, as we show this with customers' and we co-innovate with customers', they're coming up with a laundry list of questions. >> And, this is the beautiful thing about cloud, is that new capabilities are emerging every day, and you could use the good ones. Lisa O'Connor is here. Thank you very much for sharing your insights. Global Security R&D Lead for Accenture Labs. TheCUBE coverage, getting all the signal here on the show floor, extracting that from all the noise. I'm John Furrier, thanks for watching. (upbeat music)

>> Announcer: From San Francisco, it's theCUBE, covering Accenture Tech Vision 2020, brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Rick here with theCUBE. We're high atop San Francisco on a beautiful day at the Accenture San Francisco Innovation Hub, 33rd floor of the Salesforce Tower, for the Accenture Tech Vision 2020 reveal. It's where they come up with four or five themes to really look forward to, a little bit innovative, a little bit different than cloud will be big or mobile will be big. And we're excited to have, really, one of the biggest brains here on the 33rd floor. She's Teresa Tung, the managing director of Accenture Labs. Teresa, great to see you. >> Nice to see you again. >> So I have to tease you because the last time we were here, everyone was bragging on all the patents that you've filed over the years, so congratulations on that. It's almost kind of like a who's who roadmap of what's happening in tech. I looked at a couple of them. You've got a ton of stuff around cloud, a ton of stuff around Edge, but now, you're getting excited about robots and AI. >> That's right. >> That's the new passion. >> That's the new passion. >> All right, so robots, one of the five trends was robots in the wild, so what does that mean, robots in the wild, and why is this something that people should be paying attention to? >> Well, robots have been around for decades, right? So if you think about manufacturing, you think about robots. But as your kid probably knows, robots are now programmable, kids can do it, so why not enterprise? And so, now that robots are programmable, you can buy them and apply them. We're going to unlock a whole bunch of new use cases beyond just those really hardcore manufacturing ones that are very strictly designed in a very structured environment, to things in an unstructured and semi-structured environment. >> So does the definition of robot begin to change? We were just talking before we turned on the cameras about, say, Tesla. Is a Tesla a robot in your definition or does that not quite make the grade? >> I think it is, but we're thinking about robots as physical robots. So sometimes people think about robotics process automation, AI, those are robots, but here, I'm really excited about the physical robots; the mobile units, the gantry units, the arms. This is going to allow us to close that sense-analyze-actuate loop. Now the robot can actually do something based off of the analytics. >> Right, so where will we see robots kind of operating in the wild versus, as we said, the classic manufacturing instance, where they're bolted down, they do a step along the process? Where do you see some of the early adoption is going to, I guess, see them on the streets, right, or wherever we will see them? >> Well, you probably do see them on the streets already. You see them for security use cases, maybe mopping up a store after, where the employees can actually focus on the customers, and the robot's maybe restocking. We see them in the airports, so if you pay attention to modern airports, you see robots bringing out the baggage and doing some of the baggage handling. So really, the opportunities for robots are jobs that are dull, dirty, or dangerous. These are things that humans don't want to or shouldn't be doing. >> Right, so what's the breakthrough tech that's enabling the robots to take this next step? >> Well, a lot of it is AI, right? So the fact that you don't have to be a data scientist and you can apply these algorithms that do facial recognition, that can actually help you to find your way around, it's actually the automation that's programmable. As I was saying, kids can program these robots, so they're not hard to do. So if a kid can do it, maybe somebody who knows oil and gas, insurance, security, can actually do the same thing. >> Right, so a lot of the AI stuff that people are familiar with is things like photo recognition and Google Photos, so I can search for my kids, I can search for a beach, I can search for things like that, and it'll come back. What are some of the types of AI and algorithms that you're applying with kind of this robot revolution? >> It's definitely things like the image analytics. It's for the routing. So let me give you an example of how easy it is to apply. So anybody who can play a video game, you have a video game type controller, so when your kid's, again, playing games, they're actually training for on the skilled jobs. Right, so you map a scene by using that controller to drive the robot around a factory, around the airport, and then, the AI algorithm is smart enough to create the map. And then, from that, we can actually use the robot just out of the box to be able to navigate and you have a place to, say, going from Teresa, here, and then, I might be able to go into the go get us a beer, right? >> Right, right. >> Maybe we should have that happen. (laughs) >> They're setting up right over there. >> They are setting up right there. >> That's right. So it's kind of like when you think of kind of the revolution of drones, which some people might be more familiar with 'cause they're very visible. >> Yes. >> Where when you operate a DJI drone now, you don't actually fly the drone. You're not controlling pitch and yaw and those things. You're just kind of telling it where you want it to go and it's the actual AI under the covers that's making those adjustments to thrust and power and angle. Is that a good analogy? >> That is a great analogy. >> And so, the work that we would do now is much more about how you string it together for the use case. If a robot were to come up to us now, what should it do, right? So if we're here, do we want the robot to even interact with us to get us that beer? So robots don't usually speak. Should speaking be an option for it? Should maybe it's just gesturing and it has a menu? We would know how to interact with it. So a lot of that human-robot interface is some of the work that we're doing. So that was kind of a silly example, but now, imagine that we were surveying an oil pipeline or we were actually as part of a manufacturing line, so in this case it's not getting us a beer, but it might need to do the same sort of thing. What sort of tool does Theresa need to actually finish her job? >> Yeah, and then, the other one is AI and me. And you just said that AI is getting less complicated to program, these machines are getting less complicated to program, but I think most people still are kind of stuck in the realm of we need a data scientist and there are not a lot of data scientists and they got to be super, super smart. You've got to have tons and tons of data and these types of factors, so how is it becoming AI and me, Jeff who's not necessarily a data scientist. I don't have a PhD in molecular physics, how's that going to happen? >> I think we need more of that democratization for the people who are not data scientists. So data scientists, they need the data, and so, a lot of the hard part is getting the data as to how it should interact, right? So in that example, we were saying how does Teresa and Jeff interact with the robot? The data scientist needs tons, right, thousands, tens of thousands of instances of those data types to actually make an insight. So what if, instead, when we think about AI and me, what about we think about, again, the human, not the, well, data scientists are people too. >> Right, right. >> But let's think about democratizing the rest of the humans to saying, how should I interact with the robot? So a lot of the research that we do is around how do you capture this expert knowledge. So we don't actually need to have tens of thousands of that. We can actually pretty much prescribe we don't want the robot to talk to us. We want him to give us the beer. So why don't we just use things like that? We don't have to start with all the data. >> Right, right, so I'm curious because there's a lot of conversation about machines plus people is better than one or the other, but it seems like it's much more complicated to program a robot to do something with a person as opposed to just giving it a simple task, which is probably historically what we've done more. Here, you go do that task. Now, people are not involved in that task. They don't have to worry about the nuance. They don't have to worry about reacting, reading what I'm trying to communicate. So is it a lot harder to get these things to work with people as opposed to kind of independently and carve off a special job? >> It may be harder, but that's where the value is. So if we think about the AI of, let's say, yesterday, there's a lot of dashboards. So it's with the pure data-driven, the pure AI operating on its own, it's going to look at the data. It's going to give us the insight. At the end of the day, the human's going to need to read, let's say, a static report and make a decision. Sometimes, I look at these reports and I have a hard time even understanding what I'm seeing, right? When they show me all these graphs, I'm supposed to be impressed. >> Right, right. >> I don't know what to do versus if you do. I use TurboTax as an example. When you're filing TurboTax, there's a lot of AI behind the scenes, but it's already looked at my data. As I'm filling in my return, it's telling me maybe you should claim this deduction. It's asking me yes or no questions. That's how I imagine AI at scale being in the future, right? It's not just for TurboTax, but everything we do. So in the robot, in the moment that we were describing, maybe it would see that you and I were talking, and it's not going to interrupt our conversation. But in a different context, if Teresa's by herself, maybe it would come up and say, hey, would you like a beer? >> Right, right. >> I think that's the sort of context that, like a TurboTax, but more sexy of course. >> Right, right, so I'm just curious from your perspective as a technologist, again, looking at your patent history, a lot of stuff on cloud, a lot of stuff on edge, but we've always kind of operated in this kind of new world, which is, if you had infinite compute, infinite storage, and infinite bandwidth, which was taking another. >> Yes. >> Big giant step with 5G, kind of what would you build and how could you build it? You got to just be thrilled as all three of those vectors are just accelerating and giving you, basically, infinite power in terms of tooling to work with. >> It is, I mean, it feels like magic. If you think about, I watch things like "Harry Potter", and you think about they know these spells and they can get things to happen. I think that's exactly where we are now. I get to do all these things that are magic. >> And are people ready for it? What's the biggest challenge on the people side in terms of getting them to think about what they could do, as opposed to what they know today? 'Cause the future could be so different. >> That is the challenge, right, because I think people, even with processes, they think about the process that existed today, where you're going to take AI and even robotics, and just make that process step faster. >> Right. >> But with AI and automation, what if we jumped that whole step, right? If as humans, if I can see everything 'cause I had all the data and then, I had AI telling me these are the important pieces, wouldn't you jump towards the answer? A lot of the processes that we have today are meant so that we actually explore all the conditions that need to be explored, that we do look at all the data that needs to be looked at. So you're still going to look at those things, right? Regulations, rules, that still happens, but what if AI and automation check those for you and all you're doing is actually checking the exceptions? So it's going to really change the way we do work. >> Very cool, well, Teresa, great to catch up and you're sitting right in the catbird seat, so exciting to see what your next patents will be, probably all about robotics as you continue to move this train forward. So thanks for the time. >> Thank you. >> All right, she's Teresa, I'm Jeff. You're watching theCUBE. We're at the Accenture Tech Vision 2020 Release Party on the 33rd floor of the Salesforce Tower. Thanks for watching. We'll see you next time. (upbeat music)

>> Announcer: From San Francisco, It's theCUBE Covering Accenture Tech Vision 2020. Brought to you by Accenture. >> Hey welcome back, everybody. Jeff Frick here with theCUBE. We are high atop San Francisco, the 33rd floor of the Salesforce building. This is the San Francisco Accenture innovation hub, and we're really excited to have our next guest. She runs all the innovation hubs in all the Americas. It's Mary Hamilton, the managing director of Accenture Labs for Accenture. Mary, great to see you. We saw you last year. >> Great to see you, yes. >> Great to be back. >> But now you've had this place open for a year. Last year was the grand opening I think. >> It was, it was, and now we're doing all kinds of crazy new things here in our labs and in the hub. >> Yeah, that's great. So we've talked before that, you know, Paul and Mike and the team, they've put together this great vision document. It's very provocative and forward-looking and I think it is actually really thought-provoking. That's great, and we're going to have a nice party here and they're going to present, but how do we get this from this pretty piece of paper into my company or into your clients' companies? How do you and the innovation hub help them execute? >> Yeah, it is my job to bring this to life, all right? So it's all about, how do I do applied research, and how do I do that for our clients in a real way with new and emerging technologies? >> Jeff: Right. >> And so we take all of this vision and say, you know, what are the next round of technologies, and how do we think about it in new and different ways, and how do we do that in kind of a sustained, ongoing innovation direction? >> Right, right. So, you guys work with giant companies. They have millions, if not billions of R&D budgets. Where do you fit and how do you augment that? What's kind of the value add that your special asset brings to this huge investment that they're already making? >> Absolutely, so I think what we bring is the combination of everything that's here in this hub. So we've got business research. You know, what are the paradigms and the trends that we're seeing that are shifting society, politics, economics, and technology? We've got the technologists that are partnering with universities, partnering with startups. You know, think about how we view open innovation. And then, how do we actually build that for real, and how do we do it with that industry lens. We're so fortunate that, you know, out of the 500 thousand people we have here, we have deep, deep, industry expertise. So it's really about bringing all those pieces together and then working with those clients to say, how do we augment? How do we shape your future? How do we figure out what direction to go in, create that roadmap, and then together start to turn the crank on innovation from ideation all the way up through scale, and I think that's something pretty unique that we do really well. >> Right, and is it driven kind of top down from the CEO who says I have innovation kind of prerogative, go forth and innovate? Or do you see it more kind of with product groups that are trying to potentially go a slightly different direction, or incorporate some new technology? How does that actually work, or what are some of the models that you see that are successful, I guess? >> Yeah, and I would say yes, uh, all of those. >> Of course. >> You know, we do some big strategic things that are, you know, our CEO, you know, our client CEO coming together and say, you know, we're rethinking mobility. We're rethinking, you know, how we're going to shape our future, what are extended businesses that we've never thought of before? How do we go from a products to a services company? So there's, you know, the big CEO visions that trickle down, you know. We help them through strategy, through innovation, through the technology pieces to deliver that, and then there's also sort of that grassroots. You know, lab to lab pairing up and saying, okay. Let's create a partnership that, you know, you bring kind of the industry lab piece and we'll bring, you know, our technology labs and the work that we do, and come together to create that relationship. >> Right. >> So we've done both. (laughs) >> They're getting ready to start the program as you can tell. >> Mary: I know. (laughs) >> But I got to get a couple more questions. So there's a lot of different types of technology labs that you guys have in here. You've got a really cool quantum computing thing upstairs. You've got VR and AR and all these different things, but I know your passion, you talk about it every time I see you, is material science, >> Mary: It is. and, you know, I don't think if people, cause it's kind of under the covers, if you will, really appreciate the science advancements that are happening with materials, so when you think of kind of material science, how it's moving, and the opportunities that that's opening up just in the technology of the materials themselves, what gets you excited? What are some of the things that people should know about that maybe they're not paying attention to? >> Yeah, well, so first of all, I'm excited about it because that was my degree in college, and I never thought I would use it here at Accenture. (laughs) >> Jeff: Good lesson for those watching at home. >> Yeah, so I used to you know, work in a wet lab and build hydro gels and all kinds of cool, um... So this has been a journey for me, but what I'm really excited is this is a space that you wouldn't think of Accenture playing in normally, right? You wouldn't think of us having this expertise, but when you think about the proliferation of sensors that we think about today, material science allows you to start to do some of the same things that we see with sensors, and even actuators, but at the molecular level, and we can start to do it at a different scale than what's available today, whether it's at a really small scale, or really big scale with coatings, right, or even paint, that start to create really, truly interactive, connected spaces. You know, we all talk about IOT and connected spaces and connected buildings, and that's great, but imagine if everything's connective, like the walls, the floor, your clothing, and you can start to almost in a way have a conversation with the space, right? >> Jeff: Right, right. >> Have an interaction that's super personalized based on everything that's happening. You know, the environment understands everything that's going on, and ideally if we start to apply our research with AI, can start to understand well, what's your intent? What's the context? And then, how do you actually shape and create a super, super personalized experience? >> So just so people understand what you just said, well, let me make sure I understand. Now, you're talking about like in a coating, so instead of a sensor or many sensors, the actual coating, say inside of a pipe that you're trying to keep track of, the whole coating becomes one big sensor? >> Mary: That's right, exactly. >> Yeah, that's a pretty big game changer. (laughs) >> Yeah, yeah. >> And are you seeing the implementation? I mean, what are some of the ones that are actually out in the field today that people probably, you know, are rolling over, walking by, touching, and have no clue that they're really interacting with material science as opposed to electronics, for instance? >> It's still pretty early days, so this is why it's in our incubation stage, and we're playing with things like skin tattoos, right? You've probably, I dunno if you've seen Beyonce's. You know, have those gold leaf tattoos? Well we can do those same cool tattoos but make them controllers for your space, or you know the Levi's jacket that has the jacquard, we actually now have in house one of the teams that worked on that, and so, you know, we're starting to see, you know, in actual clothing, the ability to use that material science, conductive thread to create a whole new way of interacting. (laughs) >> Wow. >> Which is really, really cool, and then, you know, we're thinking about, you know, how do you create those advances? If you can use a stretchy polymer that understands when it's being stretched, you can start to apply that to, you know, maybe an armband or an elbow brace that for physical therapy understands how much you're bending your arm, and are you doing your physical therapy in the right way, so instead of, you know, once or twice going in your doctor and checking, you know, how are things going? >> Jeff: Right, right. >> They can have real time constant updates in a pretty lo-fi way, but it's through these new smart materials. >> Right, such cool stuff. >> Yeah. >> It's like, look at the smile. You love this stuff. >> (laughs) I do. >> All right, well we got to let you go, cause they're getting ready to kick off the big thing. >> I'm getting left behind! (laughs) >> And I don't want to get you the kick, so thank you for taking a few minutes, and thanks for having us back, and congrats to you and the team. >> Thank you, super fun and thanks for having me. >> All right, she's Mary, I'm Jeff. You're watching theCUBE with the Accenture Tech Innovation 2020 launch. Check it out online. They'll have all the stuff. It'll make you think, and thanks for watching. We'll see you next time. (energetic theme music)

>> From the Salesforce Tower in downtown San Francisco, it's theCUBE covering Accenture TechVision 2019. Brought to you by SiliconANGLE Media. (electronic music) >> Welcome back everybody, Jeff Frick here with theCUBE. We're in downtown San Francisco at the Salesforce Tower, the 33rd floor, brand new Accenture Innovation Hub, five stories here in the building, the ribbon cutting this morning, and we're really excited to have our next guest. He's been on many times, I think the first time in 2013. Fresh off the plane from Davos, Paul Daugherty, great to see you. >> It's great to be here Jeff and thanks for joining us at this event. It's a really big day for us here. >> Absolutely, now I didn't get your title in, I give you Chief Technology and Innovation Officer. You're really at kind of the forefront, so let's jump into the TechVision. This is something you guys do every year. You pick five kind of big trends that we should be taking a look at. There's a lot of detail. People can (laughs) take their time to read through it. But, I just want to touch on some of the highlights. What are some of the big changes from when we sat down a year ago? >> We have five trends this year. The number of trends varies a little bit, but the, you know, I think the one key takeaway and highlight from the Vision this year is this idea, the big idea, that we're entering the post-digital era, and I think many people will be surprised by that. They'll go what do ya mean post-digital? >> When you said that earlier today, I'm like post? We're just right in the meat of it aren't we? >> Right, but just to contextualize that a little bit, last year companies spent 1.1 trillion dollars on digital transformation. 94% of companies are doing some stage of digital transformation. 68% of them said they're pretty well set with their digital transformation. >> They said they're set? >> They're in good shape. Now you can question it. >> Does that surprise you? >> I question it, yes, it surprises me, and we're not sure that that's entirely-- >> Accurate? >> Representative, >> That's okay. >> But nonetheless, what is true is that every organization is adopting digital, and the question we're asking in the Vision is if everybody's doing digital, what's going to differentiate you? And, we believe that that's the characteristics of the post-digital environment where what you did leading up to now isn't going to be enough to differentiate you and lead to success in the future. In the post-digital era, it's about some new business concepts about how you shape your business and new technologies and some new corporate obligations that are going to be instrumental in your success as an organization. >> I want to dig into that a little bit 'cause I think it's a really interesting conversation. At the ribbon cutting this morning, we had representatives from the city and county of San Francisco, a representative from, I think, San Francisco State academic institution, and you said in some earlier remarks today that the responsibility for the company has moved beyond kind of stewardship for their customers, stewardship for their employees and their shareholders, but really they've got to be kind of active contributors to the community. And, that's been kind of called out over the last couple years especially in the tech industry that hey, you can't just do this stuff willy-nilly. You got to kind of take responsibility for what you can do. >> Yeah, well put, and that's one of the key things that we've been talking about in prior Visions, if you'll recall. This year, it's a big theme. The importance of this is, it's not just because it feels good. It's not just because you want to create good headlines. It's instrumental to your business success to be responsible, to create trust with your workers, employees, consumers and citizens and people in the communities you live in, and I'll explain why. What's happening is, we're creating increasingly intimate technology-enabled experiences for consumers. Think about implantable medical devices to prevent epileptic seizures. Think about the monitoring devices we use. Think about the information that's collected on us. People swipe on Tinder 1.1 million times per second, 3.7 million Google searches per second, 178 million emails per second, 266,000 hours of Netflix tracking every pause, play, fast forward, yeah per second, 266,000 hours. There's so much information collected on us out there. Our information is being used in so many different ways, and the technology is enabling companies to create individualized services for you that are great for consumers, but they're only going to be great if companies build the trust with their customers to get that data from them and if they honor the boundaries of responsibility to make sure they can sustain those products and services. >> But Paul, you scare me to death because every day we hear this breach, that breach, this breach, that breach. It's almost now-- >> Three billion identities in 2018 alone stolen. >> That's half the world, right, or almost. So, it's almost like okay, that's going to happen. And now that you're getting all this additional information, now you can tie the information from my phone that I'm takin' eight trips to 7-Eleven a day and spending way too much time on my couch not movin' around and how those things are going to tie together. One, for kind of the ethics of how the information is used when they have it, and two, it is probably going to get breached. An amazing concept you talked about earlier today, a digital twin. We hear about it from GE all the time for a jet engine, but to have a digital twin of me in some data base, that's, uh, you know, it's with everything, right? There's a good side and a scary side. >> There is, but I think this is where the idea of trust becomes very important. We need to think about, companies need to think about these services and their consumers in different ways. A lot of people, including myself, in the past have used phrases like data is the new oil. Data's the gold of artificial intelligence in this digital age we're living. I think that's dead wrong, and we got to change the mindset. Data isn't fuel or gold. Each piece of data is a fragment of a person and represents a part of a person's activity and identity, and I think if you change your thinking that way, and if you take a view that it's not all about optimizing the use of data, but it's about carefully using data in the right way that builds trust and provides value for the consumer, and you get that equitable exchange of value, that's what the future's all about. >> Right, so one of the topics, and again, we don't have time to go through all of 'em here, and you're going to give a presentation later, it's kind of just the whole machine and human interaction and how that's evolving. Specifically, I want to ask in terms of the work world. We hear about RPA, and everybody should have their own bots, and you can have bionic legs, so that you don't hurt your back if you're doing lifting. So, as you guys kind of look at how these things are melding, it's going to be an interesting combination of people with machines that are going to enable this kind of next gen of work. >> Yeah, no it'll be interesting. I think the important thing that we need to really think about is that like anything else, all these technologies are being designed by us, and we're deciding how to use them. We're deciding the principals around it, so this is about how do we design the world we want which gets back to the theme around responsibility and such. If you look at it, we find that workers are actually optimistic about the technology. Two thirds of workers are positive and optimistic about how all this technology's going to improve their job to even increase career prospects, but only half of those workers believe that their companies are going to provide them with the right training and learning. When we're talking about the human plus trend in here, the human plus worker trend is that it's not a nice to have for companies to provide learning platforms and train their employees. It's critical to their success because the jobs are changing so fast, roles are changing so fast, that if you as a company don't invest in a learning platform to continuously advance your people to fill the new jobs as they're being redefined every day, you as a company are going to get left behind, and that's what we're talking about in the human plus trend of the Vision. >> Right, another thing we hear all the time in terms of how technology's advancing on accelerating curves and people aren't so good at accelerating curves, but very specifically how no one person in one particular industry really has visibility as to what's happening in all these tangential. What's happening in health care? What's happening in drugs? What's happening in logistics? I'm in the media business, so I don't know. You guys are really sitting in an interesting catbird seat because you can see the transformation and the impacts of technology across this huge front, and it's that movement across that front which is really accelerating this thing way faster than people realize I think. >> Yeah it is, and it's a great position to be in to be able to look across like that. The thing I would say though is that unlike other eras of technology earlier, we're seeing remarkably broad industry adoption of these concepts. It's a little different in each industry as you just said, but every industry is looking at this. The interesting thing to me is one of the most common requests that I get from CEOs and from the C-Suite is they want to pull together a workshop, and they want to talk about their strategy and where they're going, and very often, more often than not now, they're saying, and I want to hear from people outside my industry. I want to hear what's happening over there. If I'm in insurance, I might want to hear what's happening in retail, or you know, they want to hear about different industries because they understand that the change is happening differently. They want to make sure they're not missing a pattern that they could apply in their own industry. >> Right, so last question before I let you go. You're speaking all the time. You're talkin' to customers. You go to cool shows like Davos and get to hang out with other big-brained people, but you get to participate in all these things, and now you have this facility. What does the Innovation Hub and these resources enable you to do with the clients that you couldn't do as we sit here in this beautiful new facility? >> Yeah, that's a great question. It's something we've worked on really hard over the last four or five years. It's creating what we call our Innovation Architecture, and it's, what we think, a unique way of putting together capability from research and thought leadership to our Accenture Ventures which is our venture capital investing arm to Accenture Labs which is our R and D and inventors to our studios where we co-create with clients to our industry professionals, the 2,000 people here in Northern California that are working with our clients everyday, and we can put all that together to turn the idea, the research, into results very quickly for our clients, and I don't think anybody can do it in the same way we can by co-like-heading all this and by the sheer investment we put into this. We invest over 800 million dollars a year in research and development, over a billion dollars a year in training for our people, and that results in things like 6,500, 6,500 patents that we generate, more than anybody else in our sector, and 1,400 of those come from our people right here in the San Francisco Innovation Hub, so it's an amazing place for innovation right here. >> All right, well Paul, thanks again for taking a few minutes. I know it's a busy day. You're gettin' ready to go present the findings for people. Where should they go to learn more about the TechVision? >> Go to accenture.com dot, uh, accenture.com/techvision. I think at midnight tonight Pacific Time it'll be out there, but by the time they see this, they'll probably have access to it, thanks. >> Paul, thanks for takin' a minute and good luck tonight. >> Always fun, thanks Jeff. >> He's Paul, I'm Jeff, you're watchin' theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco in the Salesforce Tower. Thanks for watchin'. (electronic 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)

>> Narrator: From the Computer History Museum in Mountain View, California, it's theCUBE. On the ground with Accenture Labs 30th anniversary celebration. >> Okay welcome back everyone. We're here for a special on the ground presentation, our Accenture Labs 30th year celebration of being in business at the Computer History Museum in Mountain View, California, the heart of Silicon Valley. I'm John Furrier. Our next guest is Yvonne Wassenaar, who's the CEO of Airwave. Good to see you, Cube alumni, welcome back. >> Thank you so much, I'm happy to be here. >> So your integral executive at this event here. You've worked at VMware, you've worked at New Relic. You're now at Airware. What do you guys do? First explain what Airware is because this is fascinating. >> Yeah, yeah, yeah. Airware is the most fun and impactful company on the planet. I'm a bit biased, but fundamentally I explain it as commercial drone software analytics. And the reason I say that is commercial drone is important because it's not just hobbyists, it's businesses using drones to collect data, but ultimately the important part is what do you do with the data? And we provide cloud based software analytics machine learning AI to derive business insights from what they collect. >> And drones are very practical, other than my kids loving them, put the Go Pro on it, but you can go, instead of saying go drive out and check that meter or you know, go out and take those trash out of the power lines, there's all kind of applications that drones could do with not only technical, but also getting data, visual data. So what is that looking like these days because it sounds very magical and fantasy like? What are some of the applications? >> It's a great question, and I want to start with what are some of the changes that have enabled drones to go from personal use to commercial use? The first thing is the technology, and so if you think about the drones, it's kind of like the cell phones 10 years ago when the iPhone came out. It didn't do that much compared to today, but the advancement has been amazing. So we actually had an innovator, one of our customers, duct tape a cell phone to the bottom of a drone like four or five years ago to get the visual imagery that he needed to drive insights. Now you can just buy from DJI or senseFly, really powerful drones, so you're seeing a huge uptake in what drones can do, and then on the other side, you're seeing the ability with cloud based analytics to get insights in things such as, think about it, insurance, rooftop inspection. You don't have to climb a two story steep on a ladder. You can fly a drone up, less time, more safe, and you get the historical information. Mining and quarrying, we do a lot in that space. Stockpile measurement. It's really fascinating all the things you can do. It's almost what do you not do. >> So I've been fascinated with drones ever since two years ago when Amazon had that big hype announcement where packages will be delivered to your home, and everyone can relate to that because they know Amazon delivers packages, but who's going to deliver, how does that work? I mean is there like a name space for like airspace? That's a hard compute challenge, so how will you guys deal with the spacial imagery aspect of it because this is fascinating because a new set of companies are redefining what was an old, established, boring, static industry. I mean Hoover remaps New York City every five weeks, or some number. >> Well I was going to say, what's important is you have the geo spacial coordinates, and so what we do is to actually align the images we take to geo spatially where they are. We use GCPs to do that, and then we know exactly, to the pinpoint, how to stitch images together, how to relate images over time, so actually that piece is quite easy. The harder part is when you're doing like large quarries or commercial inspections, just the volume of data you're collecting and being thoughtful on how you can upload that, process that, that's the more interesting and challenging part. >> And certainly data ingestion's huge, so given that, I've got to ask you the internet of things questions. Internet of things, the intelligent edge. Drones are moving, so they're real time. They're going to the edge of the network, they are the network, and they're pushing the edge out. How are you looking at the IOT? What's your perspective of the current IOT landscape? Intelligent, dumb, not yet defined, hasn't been to school yet? This is a big topic. Microsoft's talking about it, we've been talking about it on a research side, an intelligent edge. >> Yeah, I think we are just on the cusp of what is possible, and to me, I think about the true power being of marrying that visual data that comes from the drone with the other internet of things data. So for example, if you think about, in the aggregate space, in quarries and mining, where we play a lot. You have a lot of big equipment that has a tremendous number of sensors around, fuel efficiency and what's going on with the machine. You can map that against the hull roads that they're driving and other elements, you know that you can see from the sky. You can start to redesign your roads, you can start to get huge fuel efficiencies and other benefits, so to me the magic is really in marrying the different data sources, which is now becoming more possible as like broader technologies in the cloud and analytics of all. >> So I've got to ask you some technical, kind of high level questions. You don't have to go deep under the hood, but because you worked at VMware, you know the federation which is EMC. You guys are helping the storage guys out big time because there's a lot of data coming in. So two questions. How do you move all that big data, big fat data, through little pipes called the airwaves into the storage? What's the strategy? Is there any kind of emerging trends you see with respect to architecture? >> Yeah, so we actually spent a lot of time thinking about how you pull the huge, vast amounts of data and get it into the cloud. I'm not going to give away all of our secrets there, but what I will fundamentally say is we are big users of the cloud, so we're taking advantage of somebody else building up big data centers and their ongoing reduction in cost. Storage only gets cheaper and cheaper, and so for us, what we're really focused on is the processing power and what you can do in the clouds you put your data into. >> So cloud helps you? >> Totally, yeah, yeah, yeah. >> What would life be like without the cloud? Would you be in business? >> It would be really hard, and it would be hard on two fronts. One because it takes a lot to build and scale up your own data centers as a company today, particularly as a startup, but I think even more importantly, the ability to do, you know, training of these AI algorithms on large datasets. You want to be able to look across datasets, and that's most easily done aggregating the cloud. >> So you guys are cloud native? >> Yes. >> So what's your advice to CIOs as they look at their hybrid or private cloud, or on premise IT that's not even private cloud? What, these guys are trying to transform fast. Accenture Labs and others are helping them. What does a CIO have to do to get to the benefits of being that agile? >> Yeah, I think it's a great question, and when I was at New Relic, I was the CIO, so I have a little bit of experience in it. >> John: Trick question. >> What I would say is it is hard and I feel the pain. You have a lot to do to run the day to day business, but ultimately I think being really strategic and carving out the time and the big initiatives, and fundamentally it comes down to, all your new stuff should be in the cloud. The stuff that's really critical that's on prem that you can convert, you should do it, and the rest you got to get rid of it. You can't be held back by legacy because it will only prevent you from innovating and somebody else will. >> And do you see CIOs ultimately going to an operating model that looks like cloud even though it might be on prem? >> It does, particularly some of the larger companies, and for certain applications where you have to have, for whatever reason, data within the company, but it will be more utility based, it will be more burst capacity. You'll see more sharing as the tools and monitoring gets better. >> So I got to get your take. So as AI comes down the pipe, you're in analytics, it's a big part of your business. >> Yeah, yeah, yeah. >> You understand analytics across your career. As jobs get automated away, we have a survey, and Market Size and Wikimon just did that says that by 2025, 150 billion dollars of non differentiated IT labor is going to go away and shift to other high value activities. So automation is going to replace those non differentiating jobs, labor. Okay, that means some other things are going to happen. So you can almost connect the dots and say software, analytics, some sort of new model. How does a company do analytics? Because what are those new value creation, you started a company on drone trend, real application, analytics is a differentiator. How does a company use analytics to help them figure out a differentiating strategy for their future? >> So I think it's a couple things. One is how to use analytics and automation to do what you currently do better, faster, cheaper. The more interesting thing is what you were talking about is if machines are doing that for you, if software's doing that for you, you have more time to think about well what's that next set of more advanced analytics I might do? Or how might I translate into better customer service? Or what's that new business model? So I think rather than jobs going away, it's really you know kind of like in the banks. The ATMs didn't get rid of the bank employees. It just gave them the ability to be personal advisors and take other. >> And they open up more branches. >> Exactly. >> And it's more people. It's actually helped create jobs. >> Exactly. >> Kind of that fallacy kind of goes away. Okay, we've got a little bit of time left. Do a quick commercial on what you guys are doing. Give a plug for Airware. How many employees do you guys have, what stage you're at, what are you guys looking to do? You're hiring, what do your customers look like, who is your customer? Take a minute to talk about your company. >> Yeah, so like I said, Airware's an amazing company. We're about six years old. We're Series C. We've got great investors and backers with Andreessen, Kleiner, Perkins, John Chambers is on our board. We're about 100 people. We've got global operations, both in EMEA and in the US. The beautiful city of Paris as well as San Francisco, so hard to beat that, and fundamentally what we're focused on is global enterprise commercial drone software analytics. And I call it an enterprise because part of the reason I ended up at Airware is I spent 17 years at Accenture. I understand what it takes to sell into enterprise. I know what they're looking for in terms of security, in terms of scalability, deployment, ease of use, and so bringing that, not just fun innovative experiments and innovation departments, but scaled deployments, and we predominantly focus on insurance and agriculture, mining, and construction right now, but we're building a platform that can be leveraged across industries, and so the real value add is how we reassemble the components to quickly innovate for other industries as well. >> I know we got time to break here, but one final question. We're going to be at the Grace Hopper celebration this year for our fourth year as part of our women in tech celebration. With all the recent Silicon Valley scandals around women in tech, I got to ask you. You've been in the business for a long time. You know, you've seen a lot of stories. I'm not going to ask you to share any specifics. What does the future have to look like to get through this novel of the generational shift that's happening, a new generation's coming on board. What kinds of norms and practices would you like to see, and any comment or color you can share on what is the preferred outcome of the current situation? >> Yeah, so I deeply believe that for companies to be competitive, you have to be diverse in perspective skillset and your employee base, and this war for talent, if you're only going after a certain profile, you're going to lose. So I think the winning companies will diversify. I'm on the board at Harvey Mudd, who's done amazing work increasing the number of women in STEM. They had more than 50% of their computer science majors were female last year, so it's definitely doable. I think we all have a lot of unconscious bias, and fundamentally what's going to shift is having more role models, and quite frankly having more white male sponsors. I mean John Chambers is a huge sponsor of mine and that makes a big difference, and so I think we need. >> And including men in the conversation. >> Totally. >> Is a really important part of it. >> Yeah, yeah, yeah, yeah. I'm 100%. My best sponsors have been men, and that's what we need is that community to make a difference. >> Yvonne, thanks so much for sharing your insight and data here. Accenture Labs celebration. Your role at Accenture, you're working with them, you've worked with them. >> Yeah. >> What's the take here? >> I'm super excited to be here. I was at Accenture for 17 years starting in 1990, so I'm old, and I got to grow up with the labs, and so. >> Were they Arthur Anderson or were they Accenture Consulting at that point? >> It was Anderson Consulting. >> Anderson Consulting. >> I'm that old, it was Anderson Consulting. But I'd say the value of the labs is it's hard when you're a big enterprise company to reimagine the future, and so having places like Accenture Labs where you can see what the possible is and you have somebody experimenting with you is really powerful, so. >> And you've got a good team of people with you. The cloud, really good timing to have a cloud operation too. >> Yeah, yeah I'm excited to be here. >> Yvonne, thanks so much. Cube coverage here at the Computer History Museum. I'm John Furrier with theCUBE, on the ground for Accenture Labs, 30 years. The next 30 years ahead of us. A lot of exciting things, AI, new workforce, great action happening, drones. First of all, the drone racing leak, by the way, is really popular in my household. We're going to have drones in theCUBE >> Yvonne: Maybe we can connect you. >> With Cube coverage with drone cameras, coming soon. Thanks for watching, we'll be right back. (upbeat instrumental music)

>> Announcer: From The Computer History Museum in Mountain View, California, it's theCUBE On The Ground with Accenture Labs' 30th anniversary celebration. >> Welcome to a special CUBE On The Ground presentation of our coverage of Accenture Labs' 30th birthday party. They've been in business for 30 years. Accenture is doing some great things from here, 30 years ago, to the future. Future's all about AI, blockchain, you name it, virtual reality, augmented reality. I'm John Furrier with theCUBE. Our next guest is Joe Mikhail, who's the chief revenue officer of a company called Meta. Welcome to the conversation here at the Accenture Labs party. >> Thank you, John, and congratulations to Accenture. >> They have this theme, Magical, but really, it is a magical time. At my age, I've been in this business long enough, it's like I wish I was 20 again, because the technology is really amazing. Augmented reality, you guys do a lot of new stuff. Tell us what your company does, and you guys are doing some really cool stuff. >> Absolutely. We're really pioneering in augmented reality. For those who don't really understand augmented reality, it basically overlays digital data and virtual optics in the real world. With that comes, really, a change in paradigm of what's possible. Our forte is really in being a spatial interface company. We're not only changing the fidelity of the images you see in augmented reality, but how you interface with them, naturally based on neuroscience. >> Joe, first, take a step back, 'cause a lot of folks here in Silicon Valley, they all know what AR is, or augmented reality, something analyst relations work. But augmented reality is the big future. I always say AI stands for, not artificial intelligence, but augmented intelligence. That's what software's doing. What's your definition of augmented reality? >> Augmented reality is the ability to really change how man/machine interface around information, objects outside of 2D panels, and bringing the digital into our world. >> Let's talk about your company, Meta. You guys are doing some pretty cool stuff. Your CTO's not here, which, we'll get him on theCUBE soon. If you're watching, we'll get you on. But there's some cool stuff going on around visualization. I mean, we've covered big data since the day Hadoop was born 2009, 2010 timeframe. Visualization is key, but now, when you go to the next level, 3D, holograms, this is the future. The user interface is going to be augmented at work or at play. What are you guys doing? >> Absolutely, many things when it comes to data visualization. First of all, the third dimension, obviously adds a new way to see data, so, obviously, everything going from a 2D data analysis, you add a dimension, that gives you, obviously, added productivity. But in addition to that, you know, visualizing concepts. Mind-mapping, being able to correlate ideas, and not just data points. And, again, product design cycles and so on, productivity increases. Thirdly, ideation. Taking all that data, getting a 3D model with all its complexity into a simple form that we can collaborate around and design. >> You know, the next generation of users that are coming through the system, if you will, young kids, they're gamers. They love graphics. We're living in kind of a gaming culture, if you will, not to say gaming, literally, but per se, the interface is very rich in graphics, very rich in data. How is that going to impact CIOs? 'Cause they are looking at a old world of IT, put the servers on the racks, move the packets through the network. Now they have an opportunity with mobile, and now with global internet to put things out there like AR, like blockchain, smart contracts, AI. >> I think it's definitely an area that all CIOs should be looking at today, in many aspects. Number one, just like mobile, bring-your-own-device came into the office space. There will be, obviously, an impact from not just productivity solutions in the office, but as we get to consumer and AR, dealing with that and the implications of that. But, a more important, pressing issue for CIOs would be the fact that this is the future of compute. There is not a need anymore for 2D panels, or in the near future for 2D panels and keyboards and mouse interfaces, and how does that change IT support and, again, data sharing, collaboration, and all these-- >> And we see Siri, voice-activated, that's pretty classic. Throw the old movie Minority Report out there, where you're using your hands out there in the 3D space. This is an interface. >> Yes, it truly is. >> How real is that? I mean, come on, tell us! >> It's real, it's here, it's now. You can get a demo today for the audience. Soon, we can definitely invite you and get a demo. It is here. We're able to interact naturally today. We're on second-generation product. We have the widest field of view, which truly gives you immersion. You can walk around a hologram. You can stretch a hologram. You can surround yourselves with unlimited 3D images and panels and windows. >> So, what's the applications? What does this mean for the typical person out in the real world, whether they work in an enterprise, or a business, or a consumer? >> Absolutely. Early adopters right now are in business, enterprises. High-ROI type of applications and product design, so, rapidly iterating on concepts and ideas, getting all the way to sales and marketing, so once you have that design, then, how can you sell it and demonstrate it. All the way to maintenance, training, et cetera. That's the early adopters. Education is next, very close by. In the near future, and then, of course, we're thinking and trending towards consumers. What does shopping look like in the future? >> Check out Meta. It's a cool company. Now, Accenture Labs are having their party, and Accenture's been around for a while. I'm old enough to remember Arthur Andersen, the Big Six accounting firms, Accenture Consulting. These guys are not Johnny-come-latelies. They're doing some cool stuff. What's your role with Accenture Labs? You're on a panel here at this event, it's kind of a celebration. They're bringing the magic to life, talking about the magic of AI and cool things. What are you guys doing here, and what's Accenture Labs doing? >> Yeah, absolutely. We've been in collaboration with Accenture Labs for a little while, and it's been very, very exciting and productive. Number one, we're aligned on vision and strategy, so, currently, it's productivity. We're supporting productivity, we are going to develop a new platform, and so, for example, we've done a study together where we measured basic instructions around a LEGO, this was for the public, around building a LEGO piece used in our headset, using three-dimensional instructions versus 2D instructions, and Accenture brought that magic of quantifying productivity, and it was proved to be 20% faster with respect to instruction and training. >> So, Accenture has some chops, here, technically. >> Absolutely, absolutely. They do. (both laughing) And in the future, I mean, they're a big part of our ecosystem. This is what we're an enabler. We're a spatial interface-- >> What is the ecosystem for AI? That's a good question, 'cause people want to know, like, it's in a new, emerging area. Young kids are going to love this. New software development's coming in. What does the ecosystem look like in this new AR area, and what's the hiring profile? >> Yeah, that's a good question. Let me focus on ecosystem. I would say 50% of our current customers are developers, so the development community is adopting AR and they're building some really interesting and cool things. But the ecosystem comes from developers' content, so there's a lot of content developers, you know, high-fidelity 3D models. Enterprises are consuming all of this, and then channel partners, system integrators such as Accenture that are seeing the opportunity and bridging that gap for a lot of our corporate customers that are still forming their strategies. >> Joe Mikhail here, the chief revenue officer of Meta. I got to ask you, what percentage of your employees and customers are gamers? High amount, medium, low? Got to be a lot of gamers. >> There are some. Obviously, we integrate with Unity. A lot of our developers have come from that world, but our customers, we're a productivity company, and all of our customers are corporates at this time. Of course, we're interested to see what gamers can do on our platform. >> What's the low-hanging fruit for enterprise with respect to AR, because this is the question. No one debates the future. They see some augmentation coming on, obviously wearables, things of that nature, but software's going to power it all. What is the use case for enterprise? What's the low-hanging fruit? >> The lowest-hanging fruit is 3D CAD visualization in the product design cycle. That's just the lowest-hanging fruit right now. And then, training and education. >> You guys excited? >> We are very, very excited. The market's huge. >> All right, final question for you. For the folks that don't know the AR world, what is the future of AR going to be? What's the impact on society, what's the impact on daily lives of people with augmented reality? >> I think there are many, many impacts. One of our core values is technology serving humanity, so for us, it's very important to remove the barriers of devices coming between you and me, and being able to just look up content directly and interact with that. I think that's going to change how we think, how we collaborate, and then, of course, life sciences is huge, so there's a lot of companies starting to look at the future operating system, and the empathy that could come between a doctor and a patient looking at a case instead of just talking, you know? >> Joe, great, thanks for coming on. I'll give you a quick last word, here. What are you guys looking for as a company? You hiring, what's the strategy, what's the plan? Give a quick soundbite for what you guys are doing. >> Absolutely. We're growing. The market demand is huge, and we are hiring. We're looking for engineering, smart engineers that are interested in the space. We are growing on the sales and marketing side. We are absolutely interested in being part of our family, but I would say the biggest interest is in ecosystem partnerships. >> How long are you around for? >> Five years. >> Five years. Congratulations, Accenture Labs, 30 years celebration, where all the magic's happening, that's the theme. They got a magic show. We couldn't get video of that. They wouldn't let us record it. Joe from Meta, chief revenue officer, thanks for sharing your insight here on theCUBE. Appreciate it. >> Thanks, John. >> There'll be more coverage here at Accenture Labs' next 30 years. This is theCUBE coverage. We'll be right back. Thanks for watching. (upbeat music)

>> Narrator: From the Computer History Museum in Mountain View, California, it's The Cube, on the ground with Accenture Labs' 30th anniversary celebration. >> Hello, everyone, welcome to the special coverage of The Cube, on the ground here at the Computer History Museum in Mountain View, California, the heart of Silicon Valley. It's The Cube's coverage of Accenture Labs' 30th year celebration. I'm here with Paul Dougherty, the chief technology and innovation officer at Accenture Labs. Welcome to The Cube conversation. Thanks for joining me. >> It's great to be here. >> So first I want to toast you guys to 30 years from turning to an accounting firm, Arthur Anderson, to Accenture Labs Consulting. Guys are really changed. Congratulations to all your success. Thanks for having us. >> Yeah, thanks, it's been an incredible journey. If you think back in the 30 years, it's the 30th anniversary of Accenture Labs, and the transformation of our company to now be an innovation-led company, leading in IT services and IT innovation, and with the amazing innovations that are happening in technology, it's a great time to be doing what we're doing. >> So the theme here at the party is magic. There's a magic show going on. We can't get coverage. It's a little private event, probably some G-rated, probably ... >> Lots of magic. >> A lot of magic. But there's magic right now. We were commenting earlier, before you came on, about, you know at my age, I love this innovation cycle, but if I was 20 years old, I'd really be excited. There's so much going on. It's really magical. You've got the convergence of infrastructure, cloud, software. You guys have been on all sides of innovation, from the mini-computer boom, all the way now through now, where AI and software and now data science is coming together. What's the exciting thing for you right now? Because it's beyond software eating the world, it's beyond data eating software. This is real applications. >> Yeah, this is ... We're at an era where technology is the driving force behind every business. There was a survey recently of CEOs, and they asked CEOs how do they view their business, and 81% of CEOs, 81%, said their company's a technology company. And that was a cross-industry survey. And that's why it's an exciting time, because the option we have as Accenture is to work with any company, and every company, and help them transform, change their business, and lead them through the transformation to deliver technology-enabled digital products and services. And that's why it's an exciting time. >> What I find exciting about these global system integrators, as they're now called, is that you guys have always been a consultative organization to customers, helping them through their journey of that generational shift. Now it's interesting, with cloud computing, you guys are not only just advising, you're delivering services. A mindset transformation as well as talent, technology, process, and people. How are you doing it? What's the secret formula? >> Yeah, absolutely. I mean, what we found, the reason we've driven our business model in that direction, is our clients need help throughout the cycle. So we help with Accenture strategy, with advising our clients. We help with Accenture consulting, on helping our clients transform. Accenture digital, bring the digital capabilities in. Accenture technology, building the solutions in. Accenture operations, providing business process, infrastructure, and cloud operations. So, we've found that our clients, they need help with it all. They want to understand where to take their business, they want to understand how to get there, and they want somebody to help them manage their business as they do. And that's why we've taken the business in that direction. >> Not to give you guys a lot of props, but I do want to give you guys kudos, Accenture, Accenture Labs, is that all of folks might not know, or some, you guys probably do know, you've accumulated a lot of data scientists over the years. You've got thousands of data scientists, a lot of talent coming in. Accenture Labs is a booming operation, it's not just a throwaway lip-service kind of operation for customers, to say "Hey, we got some smart people." You guys have actually have a real organization. What are some of the cool things that you guys are doing? Can you give some examples? >> Yeah, let's just step back and talk about Labs a bit, and then I'll give some examples. We've been at Labs now for 30 years, hence the celebration we're talking about, and it's thousands of patents, it's billions of dollars of impact on the revenue of our business. And really, you're driving innovation that sets us ahead in the marketplace. And it's a fabric of a global organizations. We have labs here in Silicon Valley. We have labs in Washington, DC, that focus on security and other things. We have labs in Dublin, Ireland, in Tel Aviv, in Bangalore, India, in Beijing, in Sophia Antipolis in France. And it's that global infrastructure that allows us to tap into the innovation, I think in the key hot spots where it's happening. The kinds of innovation that we've driven are, think back to the early days of the cloud, we were doing R&D in patents and research in the cloud before the term "cloud" existed. And once the cloud phenomena took off, we had assets and architectures that we turned into the Accenture cloud platform, which has made us a leader in the multi-billion dollar ... Built a multi-billion dollar business in the cloud market. So that's an example of research and idea in early patents going to scale business for Accenture. That's the research to results that we talk about and what makes a difference in our business. >> So, talk about AI. AI's a hot trend, it's a great buzzword. I love AI because it gets young people excited about software. IOT is a little bit more boring than AI. But AI is augmented intelligence, also a little bit of artificial intelligence. Look no further than a test load, look no further than some of these cool things. How's AI impacting your world? >> AI's massive. I would say AI is the biggest single innovation and the most disruptive innovation of the information age to date. And probably, the biggest impact on how we work and live since the industrial revolution a couple hundred years ago. That started a couple hundred years ago. So AI is a big impact, and we're just at the start of it. That's kind of a paradox, though, because AI has been around for 60 years. The term was coined 60 years ago in 1956 at Dartmouth. And it just did it kind of slowly, but now we're at the inflection point where we have the computing hardware and the data and the processing power to make it really happen. So for the next five to 10 and 20 years, it's all about applying intelligence to augment the way we as people work and live and really create new opportunities to improve the productivity and creativity of humans. That's why we're excited. >> It's a perfect innovation storm. You've got great compute capability, almost unlimited capacity, software, new developer, open source is booming, and now you have STEM. >> Well, before you get to STEM, let me just make one comment on that. I think the other exciting thing about AI is we've been working with dumb technology up until this point. Think about the way we interact with our thumbs on a mobile phone. Think about the way you use traditional software in an enterprise on your PC or your screen. We're slaves to dumb technology, and the power and potential of AI is to make technology smarter, more human-like, and really enhance our ability as humans to use it. And that's why it's an exciting era. >> That's a great perspective from someone who has been in the process business. The classic example is, does the process work for you? Do you work for the process? >> Dougherty: Yeah. That's what technology ... >> And technology, we don't work for technology. They should work for us. >> And that's what's changing. That's the inflection point. >> So now, 30 years now, a lot's changed, certainly in Silicon Valley lately. Women and the role of women in the industry is certainly important. We're going to be at Grace Hopper for the fourth year this year as part of our women in tech celebration, in California this year covering women in tech. STEM is huge, but also, the gender gap is still there. You guys have a pledge to be 50% by 2025, Accenture as an organization. Labs, in particular, getting STEM in the technical roles is also a challenge. What are you guys doing to address that, and what's your personal philosophy? What's your comment about STEM and women in tech? >> Well, look, the technology industry in general has a gender diversity problem, and we believe at Accenture, we can really set the standard for how to really get to gender equality in the workforce. And that's the commitment we've got with our 50/50 gender diversity pledge by 2025. We're well along the path to getting there, right about 36% or so. Now, with the actions we're taking, the formula we've got, I'm confident that we'll get to the 50/50 pledge that we set out there. And it's an imperative for the technology industry, not just for Accenture, because we won't innovate to the potential of the industry, and we won't create the right opportunity if we don't have the right gender balance in the workforce. That's what will lead to the right innovations. In this new era where the humanity of how we apply technology, as you were saying earlier, flipping the lens on a people-centric view, we need all the perspectives and an equal representation of the population going into the way we develop solutions. That's why it's a priority for us. And we think we can really set a standard for how to apply to the technology industry. >> It's certainly a topic near and dear to my heart and our company's heart. I want to ask one more question on that as a follow-up. Computer science was always kind of narrow, I'm not saying super narrow, but now it's broadened, with analytics, the tech science side is opening up, for all the reasons you were just talking about, the AI stuff. It's a broad landscape now for many diverse roles. Can you share your thoughts on where the entry points could be for women, where it's not a man-led culture or new opportunities or new areas, new opportunities to engage, learn? Certainly digital will help that, in terms of acquiring knowledge. But in terms of getting into the business, what is the surface area of opportunities? >> The surface, it's the whole surface area. I think the wrong approach is to think that there are certain roles that are better for women or better for any group to do. There's equal opportunity in all the roles. One stat that's striking to me is the fact that, when I graduated from college in 1986, 35% of the graduates were women. 35% in 1986. Today that number is about 18%. We've gone backwards in the percentage of women graduates from computer science programs. That's a problem that we need to address. We need to get more women into technology careers. It's about sponsorship, it's about mentorship, it's about having the right role models, and it's about painting the right picture of the opportunity in technology. One of the organizations I'm involved with is Girls Who Code, where I'm on the board of directors because of our Accenture involvement because I believe that we need that kind of early involvement with girls to get them on the right paths and make them aware of the right opportunities that we can get them into the pipeline earlier. >> Congratulations. Thanks for doing that; it's great stuff. Personal question. 30 years, you've been in Accenture for a long time, 30 years of labs now, celebrating. What's the coolest thing you've done? >> You know, the coolest thing, the coolest thing is building the fabric of innovation of the company, so what we've done with the labs, creating Accenture Ventures, which is our tool for investing in companies, formalizing our Accenture research capabilities, that we now have an innovation fabric that goes from research to our ventures into our labs and the rest of Accenture's business. So we can take innovations like quantum computing and scale it and ramp it right into our business like we're doing today. So that's what's exciting to me, is to have created a funnel that we can use to take the early-stage innovations and pump them into real impact on our business. >> Awesome, and quick, what's happening here tonight? We're here at the 30th, labs here in Silicon Valley, Computer History Museum, historic event, magic. What's the show about today? >> Yeah, it's all about the past, the present, and the future. The past is how we got here with tremendous leaders of Accenture Labs, who built the organization to where it is today. The present is what I was just talking about, all the opportunity we have. And the future is more exciting that it's ever been. The next 30 years ... My only regret is that I'm not 20 years old right now. So the next 30 years are going to be even more exciting than the 30 years that I've lived through. And we're in a great place. Computer History Museum isn't just about the past. It's about the future. I'm on the board of trustees here at the Computer History Museum, and I love the mission of the museum in the way it brings the stories of innovation to light and sets us on the course for the future as well. >> Well, since you have so much influence, we're going to have to get our genes edited for sequencing so we can actually live longer because that's coming around the corner, too. >> I think that's the right idea. >> Cheers. Congratulations. >> Paul: Cheers. >> We'll be back with more coverage here live in The Cube. Accenture Labs' 30-year anniversary. I'm John Furrier with Paul Daugherty, chief technology and information officer, great work, innovation officer, great work. Congratulations. More coverage after this short break. Thanks for watching.

>> Narrator: From the Computer History Museum in Mountain View, California, it's The CUBE. On the ground with Accenture Labs 30th Anniversary Celebration. (techy music) >> Hello everyone, welcome to the special CUBE coverage of Accenture Labs 30th years of celebration here at the Computer History Museum in Mountain View, California, the heart of Silicon Valley. I'm John Furrier with The CUBE. Our next guest is John Walsh who is the Northern California Office Managing Director as well as the General Manager of the P&L of Telecom, High Tech, and Media Entertainment. Three big P&Ls, plus running the whole territory. You got a big celebration here, thanks for joining me. >> Thanks for coming, John. It's great to have you. >> So first of all, Northern California, you got The Warriors in the backyard. I'm sure Accenture's got a box, schmoozing customers, you guys working with them at all? >> Well, ya know, it's funny you bring that up, John. We are working, we're pretty close with The Warriors as it turns out. As you know, The Warriors are building out their new stadium, right down at the Dogpatch in San Francisco, and so we've been working with them to really design the fan experience. Before, during, and after the game, what that experience is going to look like. Being here in Northern California, you can imagine that's going to be a very, very tech forward experience. Hopefully it's going to kind of define the state of the industry. We're proud to be a partner of The Warriors, and part of that design. >> What better topic to kind of, as a backdrop to the Labs, Accenture Labs, 30 years here, looking forward to the next 30 years. I mean, The Warriors are the poster child, kind of like The Patriots are in football, with respect to a culture, but they're innovative, tech geeks too. They understand how to use technology for an outcome, not trying to get an outcome out of their technology. They really understand that, and that's really kind of the ethos, of the Labs. >> I think that's exactly right, and obviously, ya know, we can talk about The Warriors as much as you want (John Furrier laughs) I'm a huge fan, but ya know, the way they've thought about actually changing the game through technology, and embedding it in part of the way they actually build that experience out, is one of the reasons why we partner well with them. Obviously, we'll leverage our Labs' capabilities and a lot of our Lab practitioners in order to actually co-innovate with The Warriors. I think all of us here in the Bay Area, are going to be able to appreciate that in the coming years. >> Well, when the NDAs are expired, or maybe even sooner, we'll have to come up to your office and get a deeper dive on The Warriors situation. >> Let's do a double click on that. >> It's worth a bigger feature. But here at the Labs and Computer History Museum, better place to kind of talk about where the industry's come from, where Accenture Labs has come from, and where it's going. So I got to ask you, Arthur Anderson back at a big six accounting firm 30 plus years ago, to Anderson Consulting to Accenture, really kind of was the ways of innovation that everyone talks about. Now, the next 30 years, we're looking down the throat of AI, blockchain, internet of things, using data at scale, cloud computing, quantum computing, really changing how companies are executing their business architecture, not just IT. >> For sure. >> I mean, it's a complete transformation, disruption. >> For sure. >> Well, I mean, Accenture, you went through the history. I actually joined Arthur Anderson, ya know, 30 some years ago. I think we've always prided ourselves on being on that leading edge, and sort of our objective was to actually incorporate those new technologies, apply them to our enterprise client base. Be able to do that, ya know kind of be there, and then be gone before our competitors get there. I think you'll see some of that tonight as we're sort of walking around the showcase here. You've heard this a hundred times, John. There's never been a better time to be in the tech world. To be able to actually look at the breadth of technology opportunity that's here. How to apply that to our global enterprise base to create advantage differentiation and change. Change is what drives our business model. >> Yeah, we were just talking with Mark, one of the Senior Directors of the Labs. Ya know, talking about accounting firms and those kinds of, way back in the day, they would instrument business. Now, as you guys are now in more, 30 years, plus years later, the instrumentation's all in the data. So literally, for the first time in the history of the world of business, you might not need accounting with blockchain, and everything's instrumented. So there's no more questions that can't be answered, some level! So this is going to be like a complete new generation. Next 30 years, pretty significant. Everything's instrumented, and all kind of disruptions around how a company organizes themselves. What is Accenture's vision? How do you guys talk to customers? Not only is it mind blowing, it also is fear. >> Yeah >> If I don't adapt and move on, I can't get there. >> Yeah, well I mean, and again that is, that's the nature of competition. That's always been the nature of technology. Right now, I think it's a combination of, the digital natives have been the ones that have kind of been pushing the envelope and putting pressure on every industry, every business model, and I think that they've been out in front. We're seeing, ya know, sort of our whole global client base adapt and respond and start to incorporate all of these, and re-engineer their processes with benefit of digital at every one of those layers. You mentioned it, analytics, sort of end data, is at the core of, I think, what will define success in the future for every enterprise, in every industry. That's really where we're spending our time with our customers. It's like, how do you take advantage of the data and the insight and the knowledge that you have, to run your business more efficiently and better serve customers? By empowering your employees to serve customers, and to allow customers to better serve themselves, with all these tools? >> We're here at the Computer History Museum, in your backyard, your territory, so you're obviously going to crash the party, but I find that really compelling, and rightfully so, to be in Silicon Valley. But the world's changing, and they're going to come up with the next 30 years, it's going to match your show here. So I got to ask you, someone who leads the business, who have been through the organization, how do you hire the next generation talent? You got to build out, you got to innovate. What's the profile, is there an algorithm? Is there a formula that you have as you build out and continue to scale out your people? Got the innovation DNA and the culture-- >> We do. >> We see that. We got the Labs pumping on all cylinders, we see that. What's the people strategy? Diversity's key, you're seeing more women coming into the workforce. Certainly in Silicon Valley, our territory, has been great news lately for women. >> Right. >> What are you guys doing? >> So, let me start last first, with the diversity comment. I think we've been pretty public in terms of communicating sort of, what the profile of our employee base looks like. All the statistics, top to bottom, from diversity, ethnic diversity and gender diversity. Our CEO has recently made a commitment to be at 50/50 gender diversity by 2025. I don't think there's any other company-- >> That's amazing-- >> of our size and scale, that's made that level of commitment >> That's a moon shot. That's a moon shot level, Mars shot, what do you want to call it. >> It's a moon shot, for sure, but the way we're looking at it, it's 50 percent of the IQ actually, ya know, is there, and we need to be able to be tapping into all of that. For those folks, they're in the marketplace, they're just not at Accenture, and we want to create an environment that actually brings all those folks in. Other than that, it's just, ya know, it's based-- >> More data scientists. >> More data scientists. >> More engineering. >> More engineers, more computer science, and more people that are good at problem solving, and naturally curious. We have a pretty rigorous recruiting process, and we also have a brand that I think, attracts talent. We build deep relationships with universities, which helps, kind of gives us early access. I was talking to a couple of our interns who are here tonight, like wow, this is awesome. That's always been the recipe for Accenture. >> What do you say to the young college grads that are graduating, undergraduate or Masters degree, man, I'm going to land a job at Accenture! It's a dream job at some level. What do you say to them? What do you look for? I'm looking for, fill in the blank. When you say, answer that question. >> For me, I'm looking for people that love problem solving, right. That are naturally curious. Working at Accenture's hard, right. So having that work ethic, that ability to be persistent. >> You got to be skilled, you got to be skilled. >> Well, you got to be skilled. You don't even get the interview if you don't have (John Furrier laughs) at least that much on your resume. But beyond that, ya know, it's how they interact. We're a client focused business as well, so having people that are actually able to to work as part of a team, and work with clients, is pretty critical. >> John, congratulations, and the event's starting. Thanks from all at the CUBE, we really appreciate it. John Walsh, who runs the California, Northern California Managing Director, as well as the P&L responsibility for Telecom, High Tech, and Media Entertainment. Here at the CUBE coverage of Accenture Labs 30 year celebration at the Computer History Museum. I'm John Furrier with the CUBE, thanks for watching. (techy music)