(lively peaceful music) >> Live, from New York, it's The Cube. Covering "The Cube New York City 2018." Brought to you by SiliconANGLE Media and its ecosystem partners. >> Well, everyone, welcome back to The Cube special conversation here in New York City. We're live for Cube NYC. This is our ninth year covering the big data ecosystem, now evolved into AI, machine learning, cloud. All things data in conjunction with Strata Conference, which is going on right around the corner. This is the Cube studio. I'm John Furrier. Dave Vellante. Our next guest is Mick Hollison, who is the CMO, Chief Marketing Officer, of Cloudera. Welcome to The Cube, thanks for joining us. >> Thanks for having me. >> So Cloudera, obviously we love Cloudera. Cube started in Cloudera's office, (laughing) everyone in our community knows that. I keep, keep saying it all the time. But we're so proud to have the honor of working with Cloudera over the years. And, uh, the thing that's interesting though is that the new building in Palo Alto is right in front of the old building where the first Palo Alto office was. So, a lot of success. You have a billboard in the airport. Amr Awadallah is saying, hey, it's a milestone. You're in the airport. But your business is changing. You're reaching new audiences. You have, you're public. You guys are growing up fast. All the data is out there. Tom's doing a great job. But, the business side is changing. Data is everywhere, it's a big, hardcore enterprise conversation. Give us the update, what's new with Cloudera. >> Yeah. Thanks very much for having me again. It's, it's a delight. I've been with the company for about two years now, so I'm officially part of the problem now. (chuckling) It's been a, it's been a great journey thus far. And really the first order of business when I arrived at the company was, like, welcome aboard. We're going public. Time to dig into the S-1 and reimagine who Cloudera is going to be five, ten years out from now. And we spent a good deal of time, about three or four months, actually crafting what turned out to be just 38 total words and kind of a vision and mission statement. But the, the most central to those was what we were trying to build. And it was a modern platform for machine learning analytics in the cloud. And, each of those words, when you unpack them a little bit, are very, very important. And this week, at Strata, we're really happy on the modern platform side. We just released Cloudera Enterprise Six. It's the biggest release in the history of the company. There are now over 30 open-source projects embedded into this, something that Amr and Mike could have never imagined back in the day when it was just a couple of projects. So, a very very large and meaningful update to the platform. The next piece is machine learning, and Hilary Mason will be giving the kickoff tomorrow, and she's probably forgotten more about ML and AI than somebody like me will ever know. But she's going to give the audience an update on what we're doing in that space. But, the foundation of having that data management platform, is absolutely fundamental and necessary to do good machine learning. Without good data, without good data management, you can't do good ML or AI. Sounds sort of simple but very true. And then the last thing that we'll be announcing this week, is around the analytics space. So, on the analytic side, we announced Cloudera Data Warehouse and Altus Data Warehouse, which is a PaaS flavor of our new data warehouse offering. And last, but certainly not least, is just the "optimize for the cloud" bit. So, everything that we're doing is optimized not just around a single cloud but around multi-cloud, hybrid-cloud, and really trying to bridge that gap for enterprises and what they're doing today. So, it's a new Cloudera to say the very least, but it's all still based on that core foundation and platform that, you got to know it, with very early on. >> And you guys have operating history too, so it's not like it's a pivot for Cloudera. I know for a fact that you guys had very large-scale customers, both with three letter, letters in them, the government, as well as just commercial. So, that's cool. Question I want to ask you is, as the conversation changes from, how many clusters do I have, how am I storing the data, to what problems am I solving because of the enterprises. There's a lot of hard things that enterprises want. They want compliance, all these, you know things that have either legacy. You guys work on those technical products. But, at the end of the day, they want the outcomes, they want to solve some problems. And data is clearly an opportunity and a challenge for large enterprises. What problems are you guys going after, these large enterprises in this modern platform? What are the core problems that you guys knock down? >> Yeah, absolutely. It's a great question. And we sort of categorize the way we think about addressing business problems into three broad categories. We use the terms grow, connect, and protect. So, in the "grow" sense, we help companies build or find new revenue streams. And, this is an amazing part of our business. You see it in everything from doing analytics on clickstreams and helping people understand what's happening with their web visitors and the like, all the way through to people standing up entirely new businesses based simply on their data. One large insurance provider that is a customer of ours, as an example, has taken on the challenge and asked us to engage with them on building really, effectively, insurance as a service. So, think of it as data-driven insurance rates that are gauged based on your driving behaviors in real time. So no longer simply just using demographics as the way that you determine, you know, all 18-year old young men are poor drivers. As it turns out, with actual data you can find out there's some excellent 18 year olds. >> Telematic, not demographics! >> Yeah, yeah, yeah, exactly! >> That Tesla don't connect to the >> Exactly! And Parents will love this, love this as well, I think. So they can find out exactly how their kids are really behaving by the way. >> They're going to know I rolled through the stop signs in Palo Alto. (laughing) My rates just went up. >> Exactly, exactly. So, so helping people grow new businesses based on their data. The second piece is "Connect". This is not just simply connecting devices, but that's a big part of it, so the IOT world is a big engine for us there. One of our favorite customer stories is a company called Komatsu. It's a mining manufacturer. Think of it as the ones that make those, just massive mines that are, that are all over the world. They're particularly big in Australia. And, this is equipment that, when you leave it sit somewhere, because it doesn't work, it actually starts to sink into the earth. So, being able to do predictive maintenance on that level and type and expense of equipment is very valuable to a company like Komatsu. We're helping them do that. So that's the "Connect" piece. And last is "Protect". Since data is in fact the new oil, the most valuable resource on earth, you really need to be able to protect it. Whether that's from a cyber security threat or it's just meeting compliance and regulations that are put in place by governments. Certainly GDPR is got a lot of people thinking very differently about their data management strategies. So we're helping a number of companies in that space as well. So that's how we kind of categorize what we're doing. >> So Mick, I wonder if you could address how that's all affected the ecosystem. I mean, one of the misconceptions early on was that Hadoop, Big Data, is going to kill the enterprise data warehouse. NoSQL is going to knock out Oracle. And, Mike has always said, "No, we are incremental". And people are like, "Yeah, right". But that's really, what's happened here. >> Yes. >> EDW was a fundamental component of your big data strategies. As Amr used to say, you know, SQL is the killer app for, for big data. (chuckling) So all those data sources that have been integrated. So you kind of fast forward to today, you talked about IOT and The Edge. You guys have announced, you know, your own data warehouse and platform as a service. So you see this embracing in this hybrid world emerging. How has that affected the evolution of your ecosystem? >> Yeah, it's definitely evolved considerably. So, I think I'd give you a couple of specific areas. So, clearly we've been quite successful in large enterprises, so the big SI type of vendors want a, want a piece of that action these days. And they're, they're much more engaged than they were early days, when they weren't so sure all of this was real. >> I always say, they like to eat at the trough and then the trough is full, so they dive right in. (all laughing) They're definitely very engaged, and they built big data practices and distinctive analytics practices as well. Beyond that, sort of the developer community has also begun to shift. And it's shifted from simply people that could spell, you know, Hive or could spell Kafka and all of the various projects that are involved. And it is elevated, in particular into a data science community. So one of additional communities that we sort of brought on board with what we're doing, not just with the engine and SPARK, but also with tools for data scientists like Cloudera Data Science Workbench, has added that element to the community that really wasn't a part of it, historically. So that's been a nice add on. And then last, but certainly not least, are the cloud providers. And like everybody, they're, those are complicated relationships because on the one hand, they're incredibly valuable partners to it, certainly both Microsoft and Amazon are critical partners for Cloudera, at the same time, they've got competitive offerings. So, like most successful software companies there's a lot of coopetition to contend with that also wasn't there just a few years ago when we didn't have cloud offerings, and they didn't have, you know, data warehouse in the cloud offerings. But, those are things that have sort of impacted the ecosystem. >> So, I've got to ask you a marketing question, since you're the CMO. By the way, great message UL. I like the, the "grow, connect, protect." I think that's really easy to understand. >> Thank you. >> And the other one was modern. The phrase, say the phrase again. >> Yeah. It's the "Cloudera builds the modern platform for machine learning analytics optimized for the cloud." >> Very tight mission statement. Question on the name. Cloudera. >> Mmhmm. >> It's spelled, it's actually cloud with ERA in the letters, so "the cloud era." People use that term all the time. We're living in the cloud era. >> Yes. >> Cloud-native is the hottest market right now in the Linux foundation. The CNCF has over two hundred and forty members and growing. Cloud-native clearly has indicated that the new, modern developers here in the renaissance of software development, in general, enterprises want more developers. (laughs) Not that you want to be against developers, because, clearly, they're going to hire developers. >> Absolutely. >> And you're going to enable that. And then you've got the, obviously, cloud-native on-premise dynamic. Hybrid cloud and multi-cloud. So is there plans to think about that cloud era, is it a cloud positioning? You see cloud certainly important in what you guys do, because the cloud creates more compute, more capabilities to move data around. >> Sure. >> And (laughs) process it. And make it, make machine learning go faster, which gives more data, more AI capabilities, >> It's the flywheel you and I were discussing. >> It's the flywheel of, what's the innovation sandwich, Dave? You know? (laughs) >> A little bit of data, a little bit of machine itelligence, in the cloud. >> So, the innovation's in play. >> Yeah, Absolutely. >> Positioning around Cloud. How are you looking at that? >> Yeah. So, it's a fascinating story. You were with us in the earliest days, so you know that the original architecture of everything that we built was intended to be run in the public cloud. It turns out, in 2008, there were exactly zero customers that wanted all of their data in a public cloud environment. So the company actually pivoted and re-architected the original design of the offerings to work on-prim. And, no sooner did we do that, then it was time to re-architect it yet again. And we are right in the midst of doing that. So, we really have offerings that span the whole gamut. If you want to just pick up you whole current Cloudera environment in an infrastructure as a service model, we offer something called Altus Director that allows you to do that. Just pick up the entire environment, step it up onto AWUS, or Microsoft Azure, and off you go. If you want the convenience and the elasticity and the ease of use of a true platform as a service, just this past week we announced Altus Data Warehouse, which is a platform as a service kind of a model. For data warehousing, we have the data engineering module for Altus as well. Last, but not least, is everybody's not going to sign up for just one cloud vendor. So we're big believers in multi-cloud. And that's why we support the major cloud vendors that are out there. And, in addition to that, it's going to be a hybrid world for as far out as we can see it. People are going to have certain workloads that, either for economics or for security reasons, they're going to continue to want to run in-house. And they're going to have other workloads, certainly more transient workloads, and I think ML and data science will fall into this camp, that the public cloud's going to make a great deal of sense. And, allowing companies to bridge that gap while maintaining one security compliance and management model, something we call a Shared Data Experience, is really our core differentiator as a business. That's at the very core of what we do. >> Classic cloud workload experience that you're bringing, whether it's on-prim or whatever cloud. >> That's right. >> Cloud is an operating environment for you guys. You look at it just as >> The delivery mechanism. In effect. Awesome. All right, future for Cloudera. What can you share with us. I know you're a public company. Can't say any forward-looking statements. Got to do all those disclaimers. But for customers, what's the, what's the North Star for Cloudera? You mentioned going after a much more hardcore enterprise. >> Yes. >> That's clear. What's the North Star for you guys when you talk to customers? What's the big pitch? >> Yeah. I think there's a, there's a couple of really interesting things that we learned about our business over the course of the past six, nine months or so here. One, was that the greatest need for our offerings is in very, very large and complex enterprises. They have the most data, not surprisingly. And they have the most business gain to be had from leveraging that data. So we narrowed our focus. We have now identified approximately five thousand global customers, so think of it as kind of Fortune or Forbes 5000. That is our sole focus. So, we are entirely focused on that end of the market. Within that market, there are certain industries that we play particularly well in. We're incredibly well-positioned in financial services. Very well-positioned in healthcare and telecommunications. Any regulated industry, that really cares about how they govern and maintain their data, is really the great target audience for us. And so, that continues to be the focus for the business. And we're really excited about that narrowing of focus and what opportunities that's going to build for us. To not just land new customers, but more to expand our existing ones into a broader and broader set of use cases. >> And data is coming down faster. There's more data growth than ever seen before. It's never stopping.. It's only going to get worse. >> We love it. >> Bring it on. >> Any way you look at it, it's getting worse or better. Mick, thanks for spending the time. I know you're super busy with the event going on. Congratulations on the success, and the focus, and the positioning. Appreciate it. Thanks for coming on The Cube. >> Absolutely. Thank you gentlemen. It was a pleasure. >> We are Cube NYC. This is our ninth year doing all action. Everything that's going on in the data world now is horizontally scaling across all aspects of the company, the society, as we know. It's super important, and this is what we're talking about here in New York. This is The Cube, and John Furrier. Dave Vellante. Be back with more after this short break. Stay with us for more coverage from New York City. (upbeat 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)

(clicking) >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in Denver, Colorado. It's our first trip actually to Denver for theCUBE, so we're excited to be here. It's DJI AirWorks show. It's the second show they've ever had, about 500, 600 people here talking about the commercial applications for drone. There's no conversation really about consumer stuff here, the spark is not here. This is really about commercial applications for drones technology, the platform, the software. We're really excited about the keynote speaker today. He's Michael Perry. He's a Director of Strategic Partnerships for DJI. Michael, welcome. >> Thanks for having me, Jeff. Absolutely, and great job on the keynote. Really enthusiastic crowd. I think you pretty much had their wrapped attention the entire time. (laughs) So before we get into today, talk a little bit about why DJI has invested in this conference, and kind of what are your high level objectives in doing AirWorks. >> Yeah, so over the last several years we started seeing more and more maturity in how people are using drones for commercial work. Ultimately what we found though, is that a lot of these conversations were happening one to one, and often they were coming to DJI to have that conversation and then we'd connect them to somebody else in the network. Instead, a year ago, we decided, why don't we just connect everybody together so they can have those conversations directly? And that was a huge success. We had end users, developers, and dealers all coming together to think about how we can push forward the future of enterprise with drones. And this year, it's even bigger. We've now included not just end users and developers, but also training companies and financial service providers, hardware providers. Everyone's coming together to look at what's the future of this industry and how we can push it forward. >> Yeah, it's pretty interesting. So really the high light of verticals if you will, so agriculture, energy, construction, public safety, and infrastructure, and of course media as well, but those are really hardcore industrial sectors where you've already seen a lot of pretty advanced solutions, and you're really pushing the solution messaging as opposed to the point products or even talking about the drones themselves. >> Yeah, that's right. So I think if we had this conversation five years ago, we'd be trying to tell everybody why drones are so useful. That's no longer the issue. The question is, how can we take these drones and operate them at scale? How can we move them from an R&D project where everyone understands the value proposition, but how can we make sure that it's able to use by the guys in the field on a daily basis? And that's what everybody here in this room is here to decide. >> Now you guys take a really interesting approach. You've really broke the drone up into pieces. So you've got the actual platform itself, the thing that flies, and you guys have spent a lot of time and effort in letting it fly itself if you will, really, with instruction. Then there's the sensors, whether that be a camera, the axsensors, infrared, all type. I mean Hasselblad is here, one of the oldest camera companies around. And then there's the software, and you opened up your API both on the mobile device side, the control side, as well as, sounds like this year, even giving the raw access to the most fundamental sensor data. So that's a pretty bold kind of path to choose. How did that go down, and obviously the results are huge. You're building an ecosystem across all of those units. >> Yeah, when we started seeing the applications for drones in the commercial space, we ultimately realized that we can't develop end to end solutions for every application for drones. It's just too big. So what we started seeing is, hey, look, there's a company that already doing fantastic work in GIS mapping. Let's just enable them to use our platform. And ultimately we're starting to look at how we can use the base core of DJI technology as a platform for other people to build on top of, to really expand the potential of drones. And that's true for everybody here in this room. >> So now you've got really a wide range of platforms if you will, but the other thing that you announced today that I thought was pretty interesting, and I'm relatively new to this space, but getting beyond kind of the one person, one drone concept, and really enabling an enterprise operation. One of the guys was up talking about their customer, Komatsu, says, we love it, can you put 20,000 of these things in the air for us? >> Yeah, that's right. >> So that's a whole different way to think about your aerial assets if you will. I think back to the early military days, right? We didn't have an air force, right? It was part of the army. But to actually now have the ability to have kind of an aerial branch within your business process that feeds into your other business process, a very different way to think about the world. >> That's exactly right. So FlightHub is the answer to that exact question. If I'm a business and I want to operate drones at scale, how am I going to do that? So FlightHub does multiple things simultaneously. Allows you to see the live feeds from multiple drones. Allows you to assign tasks to individual drone pilots. Allows you to monitor all of the drones in your fleet and see how are they performing, where have they flown, what kind of missions are they optimized for, and use all of that information to be able to operate drones across an enterprise. >> Yeah, and then you talked about the other side of the equation, which is, investors still concerns about safety and privacy and this and that. And you're coming up with another product that's really for law enforcement and airports and those types of people so they have a better view of what's happening around there airspace that they're responsible for managing. Not really for the consumers or even for the operators, but really for more of the control and the trust if you will within this bigger ecosystem. >> That's exactly right. One of the barriers to broader adoption is the perception of drones, if there's drone flying by, whose drone is that? What is it doing? Is it doing the thing that it's supposed to be doing? Is there an accountability mechanism? So with AeroScope we've designed an easy to implement accountability mechanism for law enforcement, for airspace regulators, and between the two of them, they can start saying, hey, look, there's a category of drones that can just fly and we can make sure that they're not flying in anyway that's effecting safety or security, and if they are, then there's a follow up mechanism. >> Right, right. Okay, so I got to ask you a fun question. Of all the crazy applications that the ecosystem has delivered, what are some of your favorites that either just seem, wow, who would have ever thought of that, or just really leveraging the power of the platform in a way that, again, you would of never thought of on your own? >> Honestly, every week there's a new, exciting application. The one that always brings to mind though is the Ocean Alliance had a problem in that they need to collect information about whale pods in order to assess their health and their diet and how they're faring. The best way to do that is collecting whale snot. >> Jeff: Whale snot? >> Whale snot. So previously-- >> Jeff: Who knew whales had snot? >> Exactly, so previously they would row in dinghies next to whale pods as they breach, try to collect the snot as they go up the spout. Now they're using drones to do that. It's much more time efficient, allows them to better assess the health of the whales that they're trying conserve, and it also doesn't put the researchers in harm's way. >> Yeah, it's bad news for what's his name with the dirty job show because-- >> Yup. (laughs) >> Really the drones are taking a lot of these dirty jobs. It's really a safety issue when you're inspecting. I talked to somebody over coffee inspecting oil refineries. You don't have to send somebody up a 200 foot tower anymore. You can send the drone, use software, and you can get a better indication than you could from somebody that maybe missed a spot. >> Yeah, you can decrease the amount of hazardous work hours and increase the efficiency. You can not only do the inspection faster, but I can do it more frequently and get a bigger data set so that you can take that intelligence and make your business operate a lot more effectively. >> Alright, so the goals for 2018. What will be talking about at AirWorks 2018? >> I think next year you'll see a lot more mature applications within the different protocols that you've just mentioned. There're already software providers and hardware providers trying to address them, but I think today you'll start seeing all of those solutions coming together into one platform that can easily be sold and easily scaled in these business. So you'll probably see a lot more players here talking about that. >> Alright, well Michael, again, congratulations on the show. Congratulations on the keynote. Exciting times at DJI. >> Yeah, thank you. >> Alright, Michael Ferry, I'm Jeff Frick. You're watching theCUBE from DJI AirWorks. Thanks for watching. (clicking)