>> From the Salesforce tower in downtown San Francisco, it's theCUBE, covering Accenture Tech Vision 2019 brought to you by Silicon Angle Media. (upbeat music) >> Hey welcome back, everybody. Jeff Frick here with theCUBE. We are in an exciting new location. Last year we covered the Accenture technology vision release 2018. It was at Minna Gallery, cool event. But this year the venue is off the hook and 33 stories high and we're really excited to be in the brand-new Accenture Innovation Hub and joining me here our first guest, John Del Santo, he is the senior managing director for the West region for Accenture and he is responsible for this beautiful five-story. So John, first off congratulations to you and the team. >> Thanks, it's been a big project opening up this place over the last year, but it's come together great. >> Yeah and this morning they had a nice ribbon cutting, all kinds of dignitaries so, you know, what does this mean in terms of kind of, you've been with the center a long time. Your presence in the Bay Area specifically, but also as part of more of this global innovation effort. >> Well I think it's this, this is bringing together all the best of Accenture that we already had in the Bay Area. We're putting it all under one roof. We're relocating everybody and we're expanding the team. So we announced 500 new technology jobs here in this location over the next year and expanding our apprentice program. But basically, it's all about bringing more talent to this location in San Francisco to do more projects with clients in this space. >> Right. So we'll get into it with some of the other folks that we have scheduled, but it's both a coworking space for the Accenture people in town and three solid floors of all kinds of labs and innovation, kind of hands-on spaces, if you will, to do this work with your clients. >> Absolutely, that co-creation, we think, is what is really differentiating us from our competitors and it's really allowing our clients to work with us and our experts, our technology experts, and the ecosystem partners that we do a ton of work with, real time to solve a problem. Brainstorm a problem, prototype it, solve it over a very short period of time. >> Yeah, I think it's a pretty unique approach that you guys have, which is imagine the future and then create the future. >> Yeah >> As opposed to just reacting to the future. And you made an interesting comment this morning about, you know, be the disrupter, not the disruptee. And my question is really, as you see the leadership at these traditional companies that are afraid of being disrupted, how are they kind of changing the way that they do things, knowing that the digital natives and the threats that they don't even see coming from a completely different direction are now bearing down, and they have to get with the program. >> Well they do have to. And then it's really our job, our purpose, you know, the talent that we have in this company's purpose is to make our clients succeed and be disrupters. Because if they're not, they will be disrupted. And so it's in our best interest to make sure we're bringin' in the best talent, pushing their thinking on ideas, and actually getting to a solution that can actually allow them to differentiate and serve their customers better. >> Right. >> So that's what we're all about, is making sure our clients are successful. >> And draggin' 'em kicking and screaming? Or are they, are they seeing-- >> Absolutely not. >> Are they seeing it in their competition? I mean, in terms of kind of that board-level discussion, where, you know, it's passe that everybody's a technology company, and everybody's doing digital disruption, but you're down in the weeds helping these people actually execute the detail. >> Yeah, well it's funny, you say everyone's a digital company, that was our big theme a few years ago at this exact event. >> Right, right. >> Absolutely, not kicking and screaming. Most executive teams, most business teams that we work with understand that they need to change. The pace of change at their business is rapid, it's faster and faster, and every year it gets faster, and so they need to actually be a lot more agile in that >> Right. >> And move quickly. >> So one of the big things in like the singularity and accelerating pace of change. And some of these big kind of macro trends that we're experiencing is that there's no single person that sees all the innovation change across this broad front, by industry, by role, etc. You guys are in a pretty unique position 'cause you actually get to see the technology innovation and the disruption and the digitization across a number of industries as well as a number of roles. So you can kind of see this big huge glacier that's moving down the valley. >> That's one of the really cool things about this particular geography and location is that literally steps from our door here on Mission Street in San Francisco, we've got clients from ten, fifteen different industries that we serve, and we can bring talent from ten or fifteen plus different industries plus the technology skills to make sure they're looking at the problem from all angles. So if it's a retailer, are they really thinking about financial services, 'cause we've got both skills here. If it's a retailer, are they thinking about platform-based selling? Do they have an omnichannel strategy? We've got the skills in this location cross-industry to help serve banks, retailers, products companies, software platform companies, etc. And I don't think you can find that anywhere else, at least in the Continental United States, given kind of where we are in our geography. >> Right. So you had a couple of special guests this morning at the ribbon cutting. You had a customer, which is great, but you also had a representative from City of San Francisco and I just want to shift gears and talk about, you know, what it is to be kind of an active member of the community. You know, the responsibility of companies we're seeing, with kind of this backlash, if you will, against some of the mega-companies out there. It's more than just taking care of your customers. It's more than just taking care of your employees and even your stockholders. But now companies are being asked to be more kind of responsible and active participants in their local community. That's always been sort of part of our ethos. It's always been part of our vision to help our clients succeed, but also to change the way the world works and lives. And therefore, we have to be really active in our communities. We're being a little bit more explicit about it lately. But it's our view that we need to be able to improve where we're working and living, 'cause our people are active and it's important that we help serve 'em. We have a very strong public service business. We serve the State of California, we serve the City and County of San Francisco as well as well as other entities in California. And it's critical for us to help improve California as we improve the businesses in California. And so it's clearly part of our mission. >> Right. The other thing I think it's interesting is kind of companies' roles with higher education. We've seen a lot of work that Accenture's doing with community colleges and, you know, it's more than just helping so that you get good talent to feed your own system, >> Right. >> But it's really, as the pace of change just continues to accelerate, you know, historical institutions aren't necessarily best-equipped to move that fast. So again, you guys are taking a much more active, you probably done it before, but more active vocal role in the local academic institutions as well. >> Absolutely, I mean, our university relationships are really, really strong, always have been. But it's always been a little selfish on our end. We're always trying to get the best talent out of the universities locally here and there's obviously great schools in the Bay Area. We want to be more engaged with those universities on projects together as well. We want more of a 360-degree relationship. We've got great examples of where we've done research with some of the universities here locally, where we've co-innovated with some of them and we want to do more of that so that there's more of a solid relationship. It's not just about us, you know, helping them find the best students to work here, >> Right. >> Which we want, (laughs) and we do every year, but making sure that we're actually involvin' them from a research perspective and any other kind of, you know, philanthropic idea that we might have together. >> Right. So big event tonight, big event this morning, >> Yeah. >> So before I let you go, it's a brand-new space, I wonder if you could share a couple fun facts for the people who haven't come to visit yet, but hopefully will come as part of a project and a co-creation about some of the cool unique features that you guys have-- >> Well some >> Built in this thing. >> Unique features in the building. First of all, there's unique features with the talent. So we have researchers here, labbers, we call 'em, from our labs, that have, you know, Accenture has thousands of patents. More than 10% of them have been actually invented here. So our inventors are a secret that we've had in Northern California for a long time and they're all based here now. We've got some really cool spaces. We've got an augmented reality room, which is basically a 360-degree room where you can, rather than having to wear virtual-reality goggles, you can actually go inside of a computer, go inside of a lab, go inside of a hospital, and get an experience that's much more hands-on and a lot more immersive, if you will, than you could any other way. We've got a maker lab where we actually are makin' stuff. So we've got a design business here where we've helped physically make not only software, we make a lot of software, everyone knows that, but we've actually made products that have embedded software in them and so there's that fabrication capability we actually have in this building as well, which is pretty unique for a high-rise. (laughs) so >> Right. No, we saw all the machines back there, >> Yup. >> Had a good tour earlier today so-- >> Oh lots of robots and toys and all that good stuff, too. >> Yeah, that's right, it's all the robot room. All right, well, John, thanks for taking a few minutes of your time. Really exciting day for you and the team, >> Yeah. >> And nothing but congratulations. >> Thank you so much. >> All right. >> Thank you, thanks for coming. >> He's John, I'm Jeff, you're watching theCUBE. We're at the brand-new Accenture Innovation Hub in downtown San Francisco in the Salesforce tower. Thanks for watching. (upbeat 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 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. (upbeat techno music) >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are live in downtown San Francisco, the Salesforce office in the brand new Accenture Innovation Hub. It's the grand opening, like I say the soft opening, but we had the ribbon cutting, we're presenting the Accenture Technology Vision 2019 and we're excited to have somebody who's not a technologist who's very important to technology, she's Doctor Rumman Chowdhury, she's the Global Lead For Responsible AI at Accenture. >> I am. >> Great to see you. >> Thank you for having me on your program. >> Absolutely. So I was doing some background research on you and I love you introduce a lot of your talks about the fact that you're not a technologist, you come at this from a very, very different point of view. >> I do. So I am a social scientist by background. I've been working as a data scientist in artificial intelligence for some years but I'm not a computer scientist by trade. I come more from a stats background, which gives me a different perspective. So when I think of AI or data science, I literally think of it as information about people meant to understand trends in human behavior. >> So there's so many issues around responsible AI. We can talk, probably, to all these people, go on above, you know. >> Yeah. >> We don't have too much... And the first one is really a lot in the news right now, about AI is simply a codification of existing biases often, unless you really take a very proactive stance to make sure you're not just codifying biases in software. What are you seeing? >> Absolutely. So we really have to think about two kinds of bias. There's one that comes from our data, from our models. This can mean incomplete data, poorly trained models. But the second one to think about is you can have great data and a perfect model but we come from an imperfect world. We know that the world is not a fair place, some people just get a poor lot in life. We don't want to codify that into our systems and processes, so as we think about ethics and AI it's not just about improving the technology, it's about improving the society behind the technology. >> Right. >> Yeah. Another big topic I think that's really important is if you're doing a project and you want to think through some of the ethical issues, should we be collecting this data, why are we collecting this data, why are we running these algorithms and you make a decision it's for a particular person, purpose and the value outweighs the cost. But I think where the challenge really comes into is the next people that use that data or the next use that you don't necessarily have in mind and I think we hear that a lot in terms of kind of the complaints about the current state of big tech, where everyone is doing their little piece. >> Right. >> But what happens over time as those get rolled into maybe bigger pieces that weren't necessarily what they were starting with in the first place. >> Right. >> Absolutely, it's something I called moral outsourcing. Because what we build is often, we feel like a cog in a machine, we feel sometimes as technologists people aren't willing to take the responsibility for their actions, even though we should be. If we build something that is fundamentally unethical, we need to stop and ask ourselves, just because we can doesn't mean we should. >> Right. >> And think about the implications on society. Right now there's often not enough accountability because everybody feels like they're contributing to this larger machine, who am I to question it and the system will crush me anyway. So we need to empower people to be able to speak their minds and have an ethical conscience. >> So I'm curious in term of the reception of your message when you're talking to clients because clearly there's a lot of pressure to innovate fast. Everyone is telling everybody that data's the new oil and we've got to leverage these micro-experiences, et cetera, et cetera, et cetera. And they don't necessarily take a minute to step back and reflect >> Right. >> Is this the right thing, is this the right way? Are we collecting more data than we really need to achieve the objective? So how receptive are companies to your message? Do they get it? Do they have >> Yeah. >> To get hit upside the head with some problem before they really understand the value? >> So I'll give you a phrase that everybody understands and then they get the point of ethics in AI. Brakes help a car go faster. If we have the right kinds of guard rails, warning mechanisms, systems, to tell us if something is going to derail or get out of control, we feel more comfortable taking risks. So think about driving on the freeway. Because you know you can stop your car if the car in front of you stops abruptly, you feel comfortable driving 90 miles an hour. If you could not stop your car, nobody would go faster than 15. So I actually think of ethics and AI are an ethical implementation of technology as a way of helping companies be more innovative. It sounds contradictory but it actually works very well. If I know where my safe space is, I'm more capable of making true innovations. >> Right. So I want to get your take on another kind of topic, which is really kind of STEM education versus not STEM, or ethics. >> Right. >> And it's interesting, huge push on STEM, it's very, very important thing that's going on now. But as you look not that far down the road, and this events all about looking down the future, reinventing the future. As more and more of those kind of engineering functions are taken over by the machines >> Right. >> It seems like where the void is is really more talking about what are the implications, what are the deeper questions we should be asking, what are the ethics and the moral questions before just building a better mousetrap. >> Right. So you're raising a very hot button issue in the ethics and AI space. Is it simply enough to say all technologists should take an ethics course? I think it is very important to have an interdisciplinary education but, no, I don't think one ethics course, taken out of context in college will help you. So I think that there's a few things to think about. One is that corporations need to have an ethical culture. It needs to be a good thing to be ethical, number one. Number two, we need interdisciplinary teams. Often technologists will say, and rightfully so, "How was I supposed to know thing X would happen?" It's something very specific to a neighborhood or a country or a socio-economic group. And that's absolutely true. So what you should do is bring in a local community, the ACLU, some sort of a regional expert. So we do also need to move towards creating interdisciplinary teams. >> Right. So you brought up another really cool thing I think in one of your talks, FAITH. Fairness, Accountability, Transparency and Explainability >> Yes. >> Which is a, you know nobody likes black box algorithms. >> Yep. >> But fairness, specifically, is such an interesting concept. We all feel very slighted if we perceive things not to be fair. >> Yes. >> The reality is life is not fair, a lot of things are not fair. So as people try to incorporate some of these things into the way they do business, how can they do a better job, what are some of the things they should be thinking about >> Yeah. >> So they can have the faith? >> Fairness is a very complicated, complex thing and I invite you, or whenever someone asks, "What does it mean to be fair?" I point them towards this really great talk from this conference called Fat Star and it's called, 21 Definitions of Fairness. And it's all these different ways in which we can quantify and measure the concept of fairness. Well at Accenture, we took that talk and some other papers and created something called the Fairness Tool. So it's a tool to help guide discussion and show solutions on algorithmic bias and fairness. Now, the way we think about it is not as a decision maker but a decision enabler. So how can you communicate as a data scientist to a non-technical person to explain the potential flaws and problems and then take collective action? So the algorithm can help you make that decision but it's not automating the decision for you. So what it does is it helps smooth conversation and helps pinpoint where there might be bias or unfairness in your algorithm. >> Right. Well we don't have time tonight but another time we're going to >> Sure. >> Dig deeper into this and all the biomechanics and bioengineering >> Yes. >> And a lot of great topics that you've covered in a number of your talks. So I really enjoy getting to meet you and you do terrific work, really enjoy it. >> Thank you, thank you very much. >> Alright, thank you. She's Rumman, I'm Jeff, you're watching theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco. Thanks for watching, see you next time. (upbeat techno 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)