>> Announcer: 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 are back at NAB 2017 with a hundred thousand of our favorite friends doing everything about broadcast media. It's media, it's entertainment, it's technology, it's the M.E.T. effect, which is all the rage here at the show, because you can't really separate the three, they're all tied together. Really excited to be joined by our next guest, who's in the weeds, keeping an eye on this, trying to keep up with all the crazy trends. He's Avi Swerdlow, he's a Manager, Research and Development at the Walt Disney Company. Avi, welcome. >> Thank you, thank you for having me. >> Absolutely, so first off, we talked a little bit before we went live, your first time at the show, kind of general impressions of NAB? >> Yeah, it's big, a lot of walking, is my first impression. Aside from the tired feet, it's really exciting to see all the new tech out here. From talking to other people who have been in years past, it seems like things move really fast here. So what you were seeing last year is completely different of what you're seeing this year. But loving all the different sections, everything from hardware to some of the more data-driven stuff. Noticing that a lot more things are moving digital, that a lot of demos are now on laptops instead of physical. >> Right. >> Which is exciting to see. I've been impressed by some of the bigger company, like Microsoft's and IBM's machine learning efforts. And equally impressed by some of the hardware plays at DGI and GoPro, so really, really exciting stuff. >> Yeah, it's really interesting, kind of bifurcation of the market. On one hand, you've got all this crazy high end stuff with 4K and 6K and 8K and ultra HD and all these things and 360 and all these crazy cameras. At the other hand, you've got democratization of distribution with YouTube and Vimeo and all these tools being brought down in a price point, Samsung, 360 camera, where you can be a relatively small content creator and have amazing tools at your disposal. So the opportunities from a creative point of view have probably never been richer. >> Absolutely. I think a lot of what we're trying to focus on is moving in that digital direction for some of our content. Trying to implement some of those lower end or more cost efficient tools and those distribution points to get our content to people faster while at the same time trying to keep up on the higher 4K end. Something that's interesting I've chatted with my colleagues is that things move so fast that it's hard year to year to come here and see all the new things that are completely different from what you saw last year. >> Right, right. >> Now you have to start implementing those things. So I think it's a balance between all of that. I think, given that we're a big media company, some of those lower end tools are really interesting to us. In a sense that, take news for example. It's equally exciting to go live on Facebook video as it is sometimes to do it on a traditional broadcast. So I think learning how we integrate those and integrate those well are some of what we're trying to explore. >> Right. One of the topics we talked about before the cameras turned on was this virtual reality and augmented reality, VR and AR. It is pretty interesting because you talked specifically about data infusion on top of tech. And I remember the first time I ever saw a sports broadcast where, I think it was Fox maybe, that put the score bug on the upper left hand corner. You're like what is that, you're taking valuable real estate. Now we're so accustomed to this multi-layers of data on top of the broadcast. Take like a Bloomberg channel, where some of those things, where now they have multiple feeds that are constantly going. It's a very different way to consume data but that's what people really want these days. >> Absolutely. I think that last year was kind of this year of AR, VR. Where people thought there was going to be this massive revolution all of the sudden where everybody would be, would have headsets and VR would become ubiquitous. I think that will happen eventually, it's probably going to be a slower burn, mostly because people don't have devices yet. I think there's not enough content out there, not enough devices out there. Regardless, I think that if you distill down what AR and VR is at its core, it's the augmentation of information over something else. >> Right. >> So I think a lot of people are now starting to explore, what are the baby steps you take to implement some of that technology into your workflow. Assuming that people don't have devices yet, so I think, when I look at some of the virtual sets that we're seeing around this show and the implementation of information over, let's say, news or sports broadcasts, that becomes really interesting. If you use, we were talking about photogrammetry or volume capture, if you can use some of that and do interesting stuff for instance, if you're looking at a sports game and you're able to create in something like Unity or Unreal, an asset that represents the sports game, it becomes a much easier way to understand what's going on in the game then just a set of numbers. Yes, when you saw that score in the top left hand corner that was exciting. Now imagine seeing a live 3D version of the game same information unfolding, just in a different way. I think those are the baby steps towards this AR, VR implementation and eventually you might get to a point where everybody has a headset but baby steps for the average consumer. >> Right, right. In a lot of conversations about machine learning, you said you're excited about some of the machine learning, you've got the metadata and better metadata around the assets themselves, but now actually getting into the assets at the frame level to do more exploration so that people can, it's the age old adage, find, consume and share-- >> Absolutely. >> The stuff that they're most interested in. There's a lot of new opportunities because of the horsepower of these machines here that we're surrounded by, in terms of the massive capacity, and speed of the storage systems, to do things that you really couldn't do inside the assets themselves. >> Absolutely. I think our problem at somewhere like Disney is unique. It's different than at Google or at Facebook. We're not looking at this huge well of content like YouTube. We're looking at a smaller amount of content and what's really important to us is accurate metadata about our content more so than just having metadata. A lot of what we focus on is definitely metadata extraction but to the extent that we're going to use these machine learning tools we want to have really good training sets and get back really accurate data. So a lot of what we focus on is being able to have a QA layer on top of the machine learning efforts. Being able to use machine learning efforts that can be honed towards one show for instance. >> Right. >> So only extracting a certain set of characters. We really enjoy using these tools and enjoy finding ways that we can apply them to a unique problem which seems to be different than the problem that some of them are trying to address. >> Right. >> But regardless, they're working really well for us. >> So what are some of the use cases, or can you share any of how you're using machine learning to get and score that kind of metadata. >> Yeah. For instance, we're starting to use metadata in some of the ways other people are. Some of the stuff that I can talk about for instance is facial capture, location capture. Things that other people are doing but again, they're unique to one show. For instance, a Quantico on ABC might be something where we have a set of characters that we're looking for. We're starting to use machine learning to look at things like that. >> Interesting. Now Disney obviously, great company, been around forever, huge legacy. I'm just curious to the conversations in the hallway there's just this crazy wave of technology butting up against, we still have to tell great stories. Disney has a long history of telling great stories whether it's through the original animation studios or all the vast properties in which you guys have grown up. Is there still a creative ying and yang there-- >> Absolutely. >> Is there a thread and a rebalancing about technology versus let's not forget what should be-- >> A hundred percent. >> Job one. >> Absolutely. I think that's why I really enjoy working at Disney. It's always story first. My background is actually in creative development in the film industry so I always come at it from a story first point of view. I enjoy that the rest of the company does as well. But if you look at Disney's history, it's always been technology complimenting story. Think about the multi-plane camera in Snow White. The reason Snow White was able to be made was because Disney democratized animation. He figured out the technology that made animation possible at a feature film scale. Without that machine, that would not have been possible. I think in our core history you have these certain technologies that are put to use in the service of story. I think that's pretty much how we approach everything. We're looking for stuff that's going to augment our storytelling efforts. Not replace it, not degrade it in any way but only to enhance it. That's in our legacy. >> Right, right. That's interesting, I've never heard it explained that way but that is so much the trend that we continue to be on today. It's democratization of the data, democratization of the access to the data, democratization of the analytics of the data. And then operating at scale. Which requires, in today's scale, I'm not talking about a two hour movie scale, actually be able to set animation, but massive amounts of data that are flowing through the system. So how do you-- >> Absolutely. We want to use that data to empower our storytellers. To empower anybody at the company to tell better stories. But data management it's tough. I think a lot of what we had to do is first of all put in place the plumbing to make that data easily accessible. To make it easily searchable. To make it correct. To make it authoritative. To get people out of their spreadsheets that you had stored away somewhere. And unify that data so that it starts to tell a story. We've been very successful in those efforts. But it's a massive undertaking because you have companies that have not necessarily thought from a data first point of view and are now realizing that the actual value of this data. So part of what we're doing is extracting that metadata. Doing it in a way that's extremely accurate and authoritative. But also going as far upstream as possible to try to find are there other people that are already collecting this metadata and can we have them put it into a central database as opposed to everybody having their own little corner of data? >> Right, right. Is there an effort to reassess the value of the data? Where before just raw data in and of itself was a liability. Was expensive to store, expensive to keep and there was always trade off decisions about what you keep what you throw away. Now there really is the opportunity to keep it all and there's significant data outside, maybe beyond the box office gate of the feature film with all the various distribution channels and ancillary things. Obviously Disney is way ahead of the curve in terms of licensing and realizing value beyond just the core asset. But are there new ways now that those models are being worked in so that you can justify the additional expense of all this extra metadata and storage and infrastructure which, at the end of the day, you got to pay the bill-- >> Certainly. >> To the data center. >> Absolutely. I think to the extent that we can use our data to tell our stories to gain new insights it is extremely valuable. I think there are efforts around the company to, not necessarily store as much data as possible but to find what data is valuable and where it is. We're finding more and more data that is valuable. Because when you are able to unify it with other data it starts to tell a story. That's both data about our content, about our content performance, about our consumers, that what types of stories we should and shouldn't be telling. I think it's not just taking everything but it's figuring out what data is actually valuable and then trying to derive as much insight as possible from that. >> Right. Alright so, 2017, what are your top priorities for this year? Can't believe we're a third of the way through 2017- >> I know. >> It used to be like a stereo question, I guess it's not an end of the year question anymore. >> I would say one of our main goals is really to advance our automation efforts. I think also to the extent possible to advance our metadata tagging efforts as much as possible. I'd say that's top of mind at the moment. In addition to some other things but that's some of the stuff we're thinking about. >> Alright, great. Well Avi, thanks for-- >> Thank you for having me. >> For taking a few minutes and enjoy your first ever >> Thank you, yeah I will. >> NAB 2017. Alright Avi Swerdlow from Disney. I'm Jeff Frick from theCUBE, you're watching us like from NAB 2017 at the Las Vegas convention center. We'll be back after this short break. Thanks for watching. (upbeat music)