 Live from Austin, Texas, it's theCUBE. Covering South by Southwest 2017. Brought to you by Intel. Now, here's John Furrier. Okay, welcome back everyone. We are here live inside theCUBE, SiliconANGLE Media's flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier. We're here in the Intel AI lounge for South by Southwest special three days of coverage, interviews all day, some interviews tomorrow, and some super demos and panels with Intel's top AI stuff and thought leaders and experts and management. My next guest is Shuresh Acharya with GDA software. You got it right. Welcome to theCUBE. Thank you. So we were chatting before we were coming on about the IoT in your world, but you had made a comment about, you were walking from the convention center. Yeah. What's it like outside? And what's the other scene looks like out there? Well, I mean, first of all, it's just really fun to be here for South by Southwest, of course. And just walking from the convention center here. There are a lot of places, but you guys have something going on here. Long lines. It's just a very, you know, there's a huge buzz, if you will. Very exciting. People are partying here. They got free beer, free booze. It's great. You're watching and you're here at South by. You definitely want to be at the Intel AI lounge. One, it's cooler. All the cool kids are here. That's right. Called an AI, which is on stage. It's an AI VR show. You're seeing a lot of virtual reality. You're seeing a lot of AI. Okay. It leads to a new interface. New interface from a virtual augmented reality, but also AI from a data-centric world. Yes. Your thoughts, because this is what you're involved in. Sure. So let me tell you a little bit more about what I do, just to set the context. So, JDA, we do work in the supply chain and those are the manufacturing plants into transportation, into warehouse, into stores. Things that are very, yeah. Known business is known processes. Exactly. But what is now changing dramatically is the fact that a lot of this is being digitized. And not only is data being generated, the smarts, that's where the AI comes in, has really helped or will continue to help improve efficiencies. So, in your question around the role of HoloLens or whatever the VR capabilities could be and where the smarts come in, if you will, is what we're trying to do is how do these technologies, how do you use them in the store? How do you use them in the warehouse so that dynamically you can use the smarts for better efficiency. So that's where the machine learning as well as the VR technology comes together. So, Suresh, talk about the dynamics between data science and math and software because what's happening is it's a real intersection, now a confluence of math and science data that's really available and software. This is the power trend, this is the big tailwinds for the marketplace. Sure, so I'm a data scientist by training. I've always done algorithmic work and I've always worked in an industry where my mathematical models make it into the software. And it's just music to my ears that a lot of this is now really, really becoming very, very important. Data science is just the word, there's two pieces. There's a data piece, there's a science piece. We all get trained in school on the science and what we're finding early on was that data sometimes simply wasn't there. But now there's a lot more data, there's a lot more clean data and you can do a lot more with it. So it's a great time to be in AI, machine learning and just a broader space of data science. Well the databases are changing, you're making more unstructured data available, addressable. Okay, let's get back to your example of manufacturing and supply chain because I was going to say boring, but it's never boring, it's in business. I mean, we have a world we live in, an analog world, but you mentioned digitizing. This is not trivial. So I want you to take me through, in your opinion, in working in the labs for JDA software, what are the key things for digitizing businesses? Because you've got to bolt on sensors, you've got to have actuators, you've got to have all kinds of new, potentially hardware, maybe more processors. But now you've got to connect it to the network. That's the internet of things. How hard is it to digitize a business? Sure, so it is hard. And so this is more of a journey than something that's going to happen overnight. Let me walk you through a couple of use cases, both upstream to the end and then the other way around. So just so that you see the value and how complex, but yet how much value one can add. So as you know, there are production plants all over the world. So it's quite possible then that there's a vessel that's carrying your product from China to Long Beach, California. And a lot of times, currently, there's no visibility around when that ship will ever make it to Long Beach. But with sensors, but with real-time tracking of all these vessels, we're now able to say that rather than it arriving in Long Beach on the 22nd because of weather reasons, it's now going to arrive on the 25th instead. And how that then drives a downstream supply chain around when should the product make it to the distribution center? When will it make it to the store? And oh, by the way, I might need to make alternate plans now because I don't have the luxury to wait for the three-day delay that I am incurring, what are my alternate sources? So that's upstream, down to the store. We don't really see it. When we go buy something at the store, the fact that this has had such a long journey upstream is typically shielded from us. So there's a ripple effect. Ripple effect. So the old days was, hey, where's my product? Oh, it's on a boat to China, from China. So you didn't know where it was coming from and the old expression maybe it was China or not. But the point was that you had a delay in the impact of disruption. That's right. Here you can say, okay, contingency policy, software, trigger, hey, it's here. Get some supply from somewhere else. Could be produce or other goods. Exactly. Am I getting it right? You're absolutely right. That's the kind of upstream down to the consumer. But how about the consumer or the store upstream? So sometimes what happens is folks go to the store and then they start to get onto social media to say these are awesome products. Everyone's got to buy them. These things start to sell off the shelf, if you will. Very, very rapidly. And now can you start to detect that social sentiment trend to start to realign your supply chain so that you avoid out of stock? Alternatively, you could have the reverse. Or to game it like they're doing now, create scarcity to make the retail market move. There is that as well. My kids are buying these things, Supreme, these jackets and backpacks. Correct. You can gamify as well. On the other hand, what you can also do is what if you introduce a new product which you're now finding out is not selling as well as you thought it would. You're not going to continue to push inventory there. You're going to be smart about where you now send those and potentially also manage the manufacturing upstream. So it's the classic effectiveness, efficiency, opportunities are everywhere. Exactly. Okay, how about Intel? And what you think Intel is doing right? Because if you think about it, what's powering all this is the chips. And it's not just the processor and the PC. It's software end-to-end solutions. I mean, I was just covering Mobile World Congress two weeks ago and 5G is bringing potentially a gigabit. I mean, not that you need a sensor on a boat or a machine to use a gigabit, but still it does create a more bandwidth because you got to connect to the network. Sure. Exactly. Dave's got to go somewhere. So one of the pieces of work that we're doing with Intel is really at the store level to have sensors detect where an object is. You'd be surprised. People sometimes, not sometimes. A lot of times what happens is retailers will say that they're out of stock when it's still in the store. They just don't know where it is. And to now have sensors to precisely detect whether it's in the back office, whether it's in the fitting room, whether it's somewhere else, and really track that inventory real time to then provide the visibility around inventory is huge. This is the holy grail. You and I may not realize it, but this is the holy grail for a lot of retailers because they simply do not know where their inventory is. And the work that we're doing around sensors, connecting the devices and of course, adding the smarts with AI, that's the value. I love to hear the word holy grail, great stuff. I want to ask you a question on a personal note. Someone who's in the labs and you've been in the industry at data science, at the math background, in retail, on supply chain, you kind of see the big picture. What are the coolest things out there right now for the folks watching, whether it's a young kid or someone in college or an executive or a developer, can you highlight some things that, some of the coolest things that people should pay attention to and what is cool that people aren't paying attention to? Yeah, well, I mean, I think I'm going to be biased when I say just the space of machine learning is actually exploding, but it is. So that's my own heritage as well. To me, it's just fascinating to see how things that were very rudimentary have now really caught on. So the area of AI and machine learning has endless potential in my mind. Around a lot of the devices then that actually generate the data that then feeds into it, that space is exploding as well. One of the pieces of work is the IoT data. IoT data. I'll actually give you a specific example of things that are now possible. We are doing research in the space of cognitive robotics. So these are not robots that will help automate things or make things faster. These are robots in the stores that will actually interact with you. So they will actually talk to you. You can go up to it and say, hey, I'm trying to find these shoes and I can't find them. What it's going to tell you is it's going to bring that immense power of AI to tell you where the products are. It could be in that store and it's going to have someone go fetch it for you. Or it's going to tell you, oh, it's in another store five miles down the road. Would you rather go there to pick it up? Or it can say, I can have it be mailed to your house. So that's in terms of the cognitive robot understanding your emotions that you're angry trying to find something or you're a happy customer and being able to respond that way. But it's also continuously collecting data about you. That it's a male of a certain age group coming into the store at this time, coming out of aisle number 19, looking for this kind of product. This is all pieces of it. So our goal is even when you're 10 feet away from the robot, it's going to know what questions you are likely to ask. So robotics is really hot right now. Right. So this is the interactivity potential. Correct. Not just a static machine. Correct. So more... It's the whole experience. We had Dr. Navina on earlier row. He said, it's like the Jetsons, go clean my room. I mean, we're getting there. We are getting there. Almost there. We're almost getting there. So the notion that users will use software in a two-dimensional screen manner that we're doing now, that's already changing. So to your point earlier around VR, being submersing yourself into your supply chain, which we never have done, is really where this is going. Got it. So... Suresh, okay, final question. Yeah. Shoot the arrow forward five years. What does our future look like? What's going to change? What's it going to look like? Well, there's a lot of the buzz around the autonomous self-driving cars. In my world, it's really the autonomous self-learning supply chain. Think about it. It's going to detect things. It's going to know things. It's going to predict things so much better and also be able to prescribe things dynamically. There is a lot of inefficiencies built into the supply chain that will gradually over time get better and better. You know, to a lot of folks, that could be scary, just like a driverless car to a lot of folks is scary. But if you really grasp the value of it, where we're going is tremendous in terms of operational efficiencies, in terms of smarts, just making our everyday lives so much better. All right, Suresh Charya inside the Cube. We're here in the Intel AI lounge. I'm John Furrier with SiliconANGLE Media. We're breaking it down here. At South by Southwest, we're all the buzzes happening, virtual reality, artificial intelligence. Machine learning is the hottest reality trend right now. Software developers are booming at Suresh. Great. It's the Holy Grail. This is the Cube here at the Intel AI lounge. Back with more coverage after this short break.