 Live from Las Vegas, it's theCUBE, covering NAB 2017, brought to you by HGST. Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at NAB 2017 at the Las Vegas Convention Center. 100,000 people that are here have been coming for decades. It's really quite a convention. It's our first trip here, but we're really excited to be joined by an industry veteran. She's been coming for a while, coming off a pretty impressive keynote. It's Wendy Ailesworth. She's the Chief Executive Officer of Walden Pong and a mini-year veteran at Warner Brothers, right? So welcome. Yes, I am. Thank you. So first impressions of the show? You've been coming for a while. It seems to have kind of a different theme every year. What do you see this year that kind of strikes you? A little less focus on physical devices, and I think there's a growing focus on software and how those applications help streamline production processes, distribution processes. So you're seeing the real more heavy move to IP and software applications. Right, right, which of course is so consistent with what we see in many other industries, right? Between a lot of it's driven by your mobile phone and expected behavior and basically the entire world. I say it's like your remote control for your life now. Exactly. You're thinking this on your phone. But a big piece of it is cloud. And with cloud now, people can dial up at a moment's notice basically infinite amounts of compute and store and leverage that horsepower in ways that you just can't do on a local device. So I'm curious, you've been in the business for a while. How has kind of cloud adoption changed the game and how does it continue to change a game as we look forward? Yeah, exactly. I just came from this keynote by Steven Guggenheimer of Microsoft where he talked about it being all about bandwidth, processing and storage. And as those increase and become more available it kind of democratizes the ability for people to get away from having to purchase their own physical devices. And it has opened up really a wide capability for new methods of doing production that actually couldn't even be done before as well as long distance collaboration and a more rapid distribution and then the ability to track and understand how data is flowing so that you might be able to better understand the consumer. It really allows a content creator to get closer to their audience. And over time I think we will continue to see that ability grow. Which is so interesting because the proliferation of types of content is exploding. Everything from your classic big houses to new houses like Netflix, somebody told me earlier in the week that Netflix is one of the biggest producers now of independent content to YouTubers with not much more than an iPhone and a microphone that can go out and if they've got a compelling piece of content and they relate to a specific audience can see tremendous numbers that a lot of people would do anything for. So that democratization is a huge item but if you don't have an audience and you're not reaching them and you're not measuring them, pretty tough because everybody's once swiped away from something else to watch. Well in fact one of the discussions really now is about that marketing capability because the best marketing capabilities are still in the hands of the people who have been doing it for decades and decades and know where their audiences are and how to reach them. Although those are shifting. And the ability to provide tools that help new content creators find their audience are going to become critical needs in the future. Right, right. And less and less when we see it at other places I'm sure we'll see it here is that marketing intuition going to be the driver of the big spin. Now it's okay you have intuition but what's, do you have some data to back it up? And the intuition can help drive the direction and the data collection but at the end of the day we see it in every other industry I'm sure we'll see it here too where it's data driven decisions using automation, using software to get better results in an increasingly competitive world. Yeah, and getting the right results because as we know there's tons and tons and tons of data but it's understanding the data and putting good intelligence to it that allows you to make the right decisions. Right, right. Now as you're consulting to executives who've been in the industry a while what are they telling you? Are they excited? Are they scared? Are they slightly caught off guard? I mean there's so much new kind of information opportunity I'm struck by this kind of compression it seems like from the outside looking in around your release weekend it's so competitive to have so there's only whatever 52 weekends a year so many films trying to hit that particular window and it seems like there's such pressure to make that number in a really short period of time. At the other hand there's all these on demand opportunities there's all these alternate forms of distribution it seems like a really difficult kind of changing environment for these houses to be in. It is, it's a difficult changing environment I haven't heard anybody be disappointed or pessimistic about it I think they recognize that throughout history things change and you must change with it. The interesting thing there is is that it's traditional windows are shrinking but hopefully over time it'll become more apparent where there can be other monies to be made in later windows or in different augmented settings so I'll use as an example virtual reality. If virtual reality becomes a type of media in its own right then it could be that you take a title type of content and one of its offshoots is a virtual reality piece that's then sold separately and monetized separately. So I think there is pressure on the traditional windows to make them shorter, to get more revenue faster but there are an awful lot of new technologies bubbling up that will create new types of content in the future and the smart players will get into that and monetize it as rapidly as they can. The other thing of course that's changed significantly along with cloud is just the cost of all this technology infrastructure in terms of just compute and store and networking just continue to crash down in terms of the cost and now with these alternative things that you might have down the road that you may or may not even know are going to be opportunities how is that changing looking at the asset value because before maybe you couldn't keep dailies or maybe storage of all this stuff was a liability it was expensive and once you got the finished product out the door maybe you're less likely to keep all the derivative works but in today's world you might have some new distribution form that you didn't even think about before oh I wish I had this version or that version or that rough cut. I think asset keeping is always going to be a problem I don't think it's any different than our homes or any closet or drawer you own with when you started in your first department you had limited space and every time you get a bigger house then you fill it up and then all of a sudden you decide you want a down size and you got a problem. Right. And I think that's always going to be a challenge where companies have to figure out what is the best of these assets that I should retain and what should I not bother to retain because it's frankly too expensive to keep everything. Right. That said in the shift from analog to digital content creation we've seen the production staff it's just so easy to take more photos and keep them so there's been a shift in putting the onus on the content directly on the content creator to decide what they think is the best of their work that should be kept. Right. Because it's unmanageable now just like my cell phone pictures are unmanageable. It's funny the pictures because before you know pictures were rare and a special picture was special because it was like open up the Easter egg. Right. You took your film down maybe as a couple of weeks after you got back from vacation you had a couple of roles at 36 and maybe one or two great ones. Right. Where you have that treasured picture of a relative or something. Now it's almost a curse of abundance because you can just put your button down and the hard drives are getting bigger and everything's getting faster. Now I have thousands. I can't even find a good one not because I didn't have a good one because I have to wallow through 2,472 because the 73rd is the one that I really want. That must be amplified tremendously in this space. Maintenance of your storage. Again I don't care whether it's the shoes in your closet or your photographs on your phone or for a movie production all of the footage that they're shooting and all of the special effects and all these different forms of content that are coming in. Management of what you're going to retain is still a problem. Maybe there's machine learning that can help us whittle that down. Right. Certainly AI and machine learning are coming. Yeah. And I wonder if you're hearing much about that but not only for kind of the standard metadata that we would want. We had someone earlier talking about archiving and basic kind of metadata but now we can get into the metadata at the frame level. Yes. And a lot better intelligence. I'm sure in the future it'll be valued judgments as well as whether this is a good shot or not a bad shot. That's right. Or it's applicable to whatever. Yeah. Are you seeing much curiosity, adoption, experimentation, what do you kind of see? A lot of interest, a couple of experiments. Not particularly in the what to save area but a lot of experiments in other areas of production that are monotonous and boring like take the example of pulling great shots from a film in order to cut together a trailer or a teaser that's going to go on the air. Well, a machine can kind of pick out the best shots thereby saving the person time of going through all the shots and pulling the right footage. And then the editor can spend their time doing what they do best which is taking those shots and cutting them into an interesting sequence. So I see a lot of experimentation going on that rudimentary machine learning being applied to quality control. So every time a file gets shipped from one company to another, they check it to make sure that it's correct. Well, applying a machine, that's a really boring job. Right, right. Applying a machine to figure out whether that file came in correctly and didn't get corrupted. Great use of machine learning. So when you're in the field, what do you hear is kind of the top priorities from some of the people that you're working with now and this is super crazy evolving environment. What are they looking to your help and assistance for? Well, in terms of cloud sorts of work, it's they're looking to reduce their capital assets and be able to aggregate and use the resources of the cloud to lower their costs of development. Just kind of a clapstick, a capex versus. Yeah, yeah. Yeah. Versus stop-ex. And in some cases, whether they can help streamline their process and speed up their schedule and do things more in parallel. It seems like a perfect match because movies by the very nature are these transient little projects that form and come together, be produced and then they disappear. And then they disappear. I mean, that's like perfect kind of an application for a cloud world, which is the same thing. It's on demand, you assemble it, use it. When it's done, it goes back, it goes back. So it seems like a pretty good match. And applications in the cloud that are modeling themselves to offer the services based upon the usage as opposed to setting up a long-term contract. Those are the apps that are going to win. Right, and that's very consistent with the way that industry's worked for a long, long time, right? Yeah. Yeah, all right. Well, I'll give you the last word as you're leaving the show here in a couple of days headed back to LA. What are you thinking about for kind of the balance of 2017 that you're taking away that you're excited to share with some of your clients? I think the power of doing little steps and getting involved into using machine learning in various methods, whether that be in the cloud or in a local cloud. And then looking longer range to where artificial intelligence will actually play into that. But there's initial steps that have to be done in terms of applying machine learning first. And then I think we'll get into the more interesting stuff of artificial intelligence, five years down the street. Yeah, early days. Yeah. Exciting times. It is very exciting. All right, well, Wendy, well, thanks for taking a few minutes out of your busy day. I really appreciate the time. All right, Wendy Ellsworth from Walden Pond. I'm Jeff Frick. You're watching theCUBE. We're at NAB 2017 from Las Vegas. We'll be right back.