 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 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 Mark Carell-Billiard, the global lead for Accenture Labs last we saw you at the 38th anniversary. So Mark, 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 it 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 technology only for people and by people, but how technology basically is shaping the society. And what people basically, I mean, you know what I mean, they're like technology is changing basically their life, the way they work and everything. What we say to all these technologies that there's 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. I mean, what we say also is that something which is very important is that there's a transparency that we need to be brought up by this technology. You know, I mean, it's like if you look at companies and everything they will have to build basically a social contract with those people, bringing the technology. It's a two-way street now. Right, right. It's like you build a lot of technology and people adopt this technology and they 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. It is. 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 MarTech, 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. So I love this discussion because I tell you this, I completely agree. But I think people need to recognize that artificial intelligence we made tons of progress there. You remember we had so many winters along the way in everything. I think there will still be winters for artificial intelligence. Machine can do things very, very well. But it still can't do what people can do. You know, for example, common sense learning. It's very difficult to explain a machine what is common sense learning. You know what is common sense. For example, if I would like to build a robot that come in your office and pick, for example, a cup of coffee and decide whatever 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 wouldn't 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 of us, and you guys have twisted kind of common phrases. We did. A little bit of a central branding, of course, right? So one of them is the Internet of Thinking. So rather than the Internet of Things, which is very popular, 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 virtual agents into systems. They all have machine learning. They all learn about what you're doing, you know? So what we need to do is that when we're going to build basically new environment and everything, we need to understand exactly where all the processing power for this intelligence is going to be sitting. Is it going to be, for example, if you have to reinvent the car of the future, okay, where it's going to be driverless, you need to rethink about the cockpit of the future and the experience. There need to be a lot of machine learning, intelligence to understand exactly how they want to interact with you, through the voice, through recognizing your face when you're frowning and stuff like that. I mean, there's going to be so many things. So there's a lot of processing power to put. When you put all this processing power in a chip in the car, do you want to split it between the chip in the car and some other chip in the cloud? Where you put all the data related to what you're going to be doing in this car? You want to look at all this data only on a 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're going to be sitting in a seat. American people spend, in average, 500 hours per year in the car. Can you imagine what we can do there? So 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 on the car or on the cloud? So what we want to say is that 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 architecture. Where are we going to put all that stuff? Which processor 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 to play. Mark, 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 so they can take it a few minutes. They're going to start the program behind us. I'm Jeff Rick, he's Mark. You're watching theCUBE. It's the Accenture Technology Vision 2018. We'll be right back after the presentation. All right, sure. Thanks, Mark. Thank you. All right, welcome back, everybody. We are still the Accenture Tech Vision 2018. Free of it. The autonomous band is playing very loudly, but it's good. So we got Mark back, Mark Correll, Billyard. And again, he is the Accenture Labs global lead and he's also all on top of extended reality. Extended reality. So Mark, we're talking about VR, VR, AR, you guys have introduced... Actics, all stocktive, everything. Now it's ER. That's right. Extended reality. Extended reality. I mean, it's like, because I mean, I think it takes every type of sensors or immersion feeling and everything you can have because you know, it's all about combinatorial 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. How long until you just pass all the sensors and just go right to the wires? That's what I'm waiting for. These things are not built to look at goggles, 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. That's right. You guys are, you're positioning this as really a way to break down distance. Absolutely. How does that work? Yeah, that's what we call it. 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, I mean, it's always the same stuff. 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. So 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 company, 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 knowing. It's pouring. It's raining. You're not going to do it. What are you going to do? Why are you going to use the virtual reality environment? They're all autonomous, though. They all drive themselves around. But not now. They're not there. But eventually, you can use that in your office. You're going to be trained in your office. And when you stop raining, basically, you're going to be there and you're going to be able to drive there 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. You know, 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 the day, it's end of time. I can reduce the time that this stuff is delivered virtually to train the people on board. 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 and equipment by overlaying 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? We're still wearing the punky 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-fourth. The billion dollars today, which is a lot. Yeah, it's a real number. But most of it is on the devices. Most of it is on the gaming devices. You know the stuff that you find on the Xbox, the stuff you find on the PlayStation, very consumer driven. The big business is really enterprise business, which is how you're going to use this device 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 environment. The devices are coming. And then by 2020, the estimate is that that whole business is going to shift from $14 billion to $143 billion. In 2020. Yeah. Two years from now. That's right, two, three years, because the devices are there. And then right now, it's 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. And 2020. Yeah, that's right around the corner. Yeah, it's right around the corner. I mean, I met with capital companies. These companies call real wear. They're doing amazing devices. It's a device you wear. You can put that on the helmet very, very light. You can drop it from 10 meters. It bonds back. It works. And then basically, you have voice recognition in a very noisy environment like this one. You can speak. It recognizes 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 environment. It has older certification. I mean, it's IPv6 and everything. You can run on it. I mean, it doesn't do anything. And that's exactly what we need to develop the new use case that are going to drive this further. Yeah, because we're still a long way from there. But two years is not very long for the devices. I mean, it's acceleration. Right, right. All right, Mark. Well, we're excited. What's your favorite AR, VR, application? So my favorite, I can tell you that. You and I, we go to Venice tomorrow, always virtual reality. And so with the combination of the all-factive, the stuff, the sound and everything, you can be sitting there on the terrace. You can hear the vaporito passing by. You eat a bread and I fake your brain with the all-factive stuff. You believe it's a pizza, and you're doing the water and it's kianti. That's what it's going to be. See, I think the device is going to be when a plug's in your head. Again, avoid all these things that go straight in. And then it begs the question, did you really do it? Or not? I know, I know. We don't go there. That's way deep. We don't have time, Mark. It's good to see you again. Thanks for stopping by. Thank you. He's Mark. I'm Jeff. You're watching theCUBE, a sensor technology vision preview party. Thanks for watching.