>> Live from Washington DC, it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and it's ecosystem partners. >> Hey, welcome back everyone. This is theCUBE's exclusive coverage live in Washington DC at Amazon Web Services AWS Public Sector Summit. I mean, it's so jam-packed you can't even move. This is like the re:Invent for Public Sector even though it's a summit for Amazon Web Services. I'm here with Dave Vellante, my co-host. Our next guest is John Wood, Chairman and CEO of Telos, and Rick Tracy, Chief Security Officer and the co-inventor of Xacta, it's hot technology. John, great to see you, welcome to theCUBE. >> Thanks guys. >> Thanks for having us. >> I love to get the brain trust here, John you're, like, probably one of the most experienced cyber security gurus in the DC area still standing. (laughing) As we said last time on theCUBE. >> Always, always. >> Okay. (laughing) And you've got some patents here, with some core technology, so first of all, I want to, before we get into some of the cool features of the products, talk about the dynamic of public sector, because Amazon has these summits, and they're kind of like a recycled re:Invent. Small scale, still packed. Talk about what Public Sector Summit is, because this is a completely different ballgame in this world. >> Sure, it's a perfect age for the cloud, and what this summit does, is it provides a great venue for people to come, learn about what works, get best practices, find use cases and just see what the ecosystem's all about in terms of how to make it work with the cloud. >> Rick, so what's your take? >> Well, if there's any doubt about it, what, is it double the size of last year? I think there were 7,000 people here last year and Teresa said today 14,500. So, yeah, I mean, it suits us perfectly because this is our sweet spot. >> So, Dave and I are always amazed by Amazon in general, the slew of announcements, Teresa Carlson picking the reins up where Andy Jassy does that Amazon re:Invent which is just tons of content, so many new announcements. What's your guys take on the hot news for you guys, because you guys are a major sponsor and you're in the ecosystem, you've been doing a lot of business with Amazon. >> Sure. >> What's going on in the business? What's happening with Telos? Why is it so booming right now for you guys? >> Well, I think people realize that there is a way to use automation where security can help drive cloud adoption. So, Rick and I co-authored an article back in 2011 that talked about why the cloud was more secure and it went over kind of like a lead ballon. And then back in 2014 the agency made the decision, the CIA made the decision, arguably the most security conscious organization in the world, to go to the cloud. And so that was a big, big, big, deal. But what we do is we help drive the security automation and orchestration stuff so you can reduce the time it takes to get what's called your authority to operate. And so I think that's a big deal now. The use of automation is being used to enhance the mission, so that the mission owners can get to their mission using the cloud, much more quickly. >> And we heard from the most powerful sentence in the keynote this morning was, "The cloud on it's weakest day is more secure than Client Service Solutions." This is a practitioner saying that, a leader of an agency saying that, not Amazon or not Telos. >> Absolutely. >> And it's because of that automation, right? I mean, that's really a key factor. >> It's because of the automation. It's also because the cloud providers are making sure that they lock down their physical infrastructure. Guards, gates, guns. All of the physical infrastructure and the virtual infrastructure, they do a really good job of that. If you think about it, the US government, unfortunately, 80% of their spend is around maintaining old systems. Well, the cloud providers are keeping modern. Those old systems have a lot of weaknesses from a standpoint of cyber security flaws. So, with a modern technology like the cloud, there's a lot more you can do around automation to lock down much more quickly. >> And the standardization that you get with a cloud makes it's easier as well, because there's not so many variations of things that you have to figure out how to protect. So, the standardized services that everything's built on really helps. >> Yeah, and people are adopting cloud in kind of different ways, which makes it harder, too. But you get the benefits of scale and speed, certainly. But I got to just pick up on some big news that's happened just last night and today. Microsoft Azure suffered an 11 hour downtime across Europe. 11 hours Azure's down, Microsoft Azure. This is a huge concern. Downtime, security, these are issues, I mean, this is just like, so, what's going on with this? >> Well, the truth of the matter is, if you think about where Amazon is today, Amazon is light years ahead of the rest of the cloud guys. The reason for that is they made the decision early on to take the risk around cloud. As a result of that, they have so many lessons learned that are beyond all of the other cloud providers, that that wouldn't happen to Amazon today, because they'll be able to back up, replication and duplication if they have, and their environments. >> How big do you think that lead is? You know, there's a lot of debate in the industry that other guys are catching up. The other side of the coin is, no, actually the flywheel effect is a lot like Secretariat in the stretch run of the Belmont, you were talking about racing before. What's your sense of that lead, even subjectively. >> I think it's between 5 and 10 years. There was a, it was crickets in this world, in the public sector world for cloud up until, literally, the agency decided to adopt. So the CIA made that decision, that was, sort of, the shot heard around the world as it relates to cloud adoption. Not just for public sector but for commercial as well, 'cause if you look at Amazon's ramp up, right after that decision was made, their ramp up has been amazing. >> That was a watershed event, for sure. >> It was, and it was very well documented, I mean, I read the judges ruling on that when IBM tried to stop them and the judge eviscerated IBM. And of course IBM had no cloud at the time, they had to go out and spend two billion dollars on software. John has lots of opinions on that, but okay, so that leaves-- >> I'm on the right side of history on that call. >> I think you are, it was a pretty good call. What about, what should be practitioners be thinking about? You talked about the standardization. Where should they be focused? Is it on response, is it on analytics, is it on training? What should it be? >> Well, from our perspective it is, a lot of the focus is on analytics, right? So, a lot of data that we've helped our customers collect over time for this ATO process that John previously mentioned, our goal with IO, Xacta IO, is to help organizations leverage that data to do more through analytics, so there's this dashboard with ad hoc reporting and analytic capability that's going to allow them to blend asset data with risk-to-threat data, with other sorts of data that they're collecting for ATO, specifically for the ATO process, that they can use now for more robust cyber risk management. So, for me, analytics is huge moving forward. >> And that's a prioritization tool so they can focus on the things that matter, or maybe double-click on that? >> It could be, it could be a prioritization tool, but it could also be a tool that you use to anticipate what might happen, right? So, some analytics will help you determine this asset is vulnerable for these variety of reasons, therefore it has to go to the top of the sack for remediation. But also, using that data over time might help you understand that this plus this plus this is an indication that this bad thing is going to happen. And so, analytics, I think, falls into both categories. Probably it's more the forecasting and predictive is something that's going to come later but as you unmask more data and understand how to apply rules to that data, it will naturally come. So, Rick and I have worked together for many, many years and, over a quarter of a century, so the way I would say it is like this. Xacta 360 helps you to accelerate your authority to operate, but that's a point in time. The holy grail for us as security practitioners is all around continuous monitoring of your underlying risk. So, the data analytics that he's talking about, is where we come about and looking at Xacta IO. So, Xacta IO helps fulfill that mission of continuous compliance, which means that the ATO is no longer just relevant at that moment in time because we can do continuous monitoring now at scale, in hybrid environments, in the cloud, on prem. 'Cause our clients are huge, so they're going to be a combination of environments that they're sitting in, and they need to understand their underlying risk posture. They need to have, they're going to have all kinds of scanners, so we don't really care, we can ingest any kind of scanner that you have with Exact IO. As a result of that, the security professional can spend their time on the analysis and not the pedestrian stuff that's just kind of wasting time, like documentation and all that stuff. >> Yeah, for us, data's a means to an end, right? It's either to get an ATO or to help you understand where you need to be focusing your resources to remediate issues. So, for us, leveraging the data that's produced by many companies that are at this show. Their data is a means to help us get our job done. >> Were you able to have, one follow up, if I may, were you able to have an impact, to me, even, again, subjectively, on that number, whatever that number is, that we get infiltrated, the customer gets infiltrated, it's 300 days before they even realize it. Are you seeing an impact on that as a result of analytics, or is it too early days? >> I would say it's still early. But it's reasonable to expect that there will be benefits in terms of faster detection. And maybe it's not even detection at some point, hopefully, it's anticipating so that you're not detecting something bad already happened, it's avoiding it before it happens. >> Yeah, and let me say it this way, too. You know, if you listen to John Edwards, the CIO from the CIA, he talks about how the reason he loves the cloud is because it used to take the agency about a year to provision a server, now it's a few minutes, right? Well that's great, but if you can't get your authority to operate, 'cause that can take another 18 months, you're not going to get the benefit of the cloud, right? So what we do, is we help accelerate how fast you can get to that ATO so that guys like the agency and anybody else that wants to use the cloud can use it much more quickly, right? >> Yeah, and the continuous integration and all that monitoring is great for security but I've got to ask you a question. Analytics are super important, we all know data analysis now is in the center of the value proposition across the board, horizontally. Not just data warehousing, analytics that are used as instrumentation and variables into critical things like security. So, with that being said, if you believe that, the question is, how does that shape the architecture, if I'm in an agency or I'm a customer, I want to build a cloud architecture that's going to scale and do all those things, be up, not go down, and have security. How does the architecture change with the cloud formula for the decision maker? Because right now they're like, "Oh, should I do multi-cloud, should I just Amazon" So, the data is a critical architectural decision point. How do you guys see that shaping, what's your advice to practitioners around designing the cloud architecture for data in mind. Just use Amazon? (laughs) >> Well, yes. (laughs) Just use Amazon. I mean, all the tools that you need exist here, right, and so-- >> If all the tools you need in the cloud exist here. >> Alright, so rephrase another way. >> But John, the issue is you're not going to have all your stuff in the cloud if you're the air force or if you're the army, because you have 75 years of data that you got to push in. So over the next 10 years there's going to be this "hybrid" environment where you'll have some stuff in the cloud, some stuff in a hybrid world, some stuff on prem, right? >> How I secured that, so that's a great point. So, data's everywhere, so that means you're going to need to collect it and then measure certain things. What's the best way to secure it and then is that where Xacta fits in? I'm trying to put that together if I'm going to design my architecture and then go to procurement, whether it's on premise or multi-cloud. >> Well, there are lots of security products that people use to secure, whether you're on prem or whether you're in the cloud and our platform leverages that information to determine whether things are secure enough. So there's a distinction between cyber risk management and actually securing a database, right? So, there's so many granular point products that exist for different points along the security chain, lifecycle chain, if you will, that our objective is to ingest as much of that information and purpose it in a way that allows someone to understand whether they're actually secure or not. And so it's understanding your security posture, transforming that security information to risk so that you can prioritize, as you were talking about before. >> You're taking a platform mentality as opposed to a point product. >> We're taking an enterprise view of risk. So, the enterprise is, remember, it's on prem, and hybrid and cloud. If all your stuff is in the cloud, Amazon has the answer for you. None of our customers are in that situation. If you're a start up, Amazon's the way to go, period. But all of our customers have legacy. As a result of that it's an enterprise view of risk. That's why companies like Telos partner so well with Amazon because they're all about being close to the customer, they're all about using automation. We are as well. >> Alright, talk about the news you guys have, Xacta IO, you're the co-inventor of it, Jack. Talk about this product. What's the keys, what does it do, where's it applied to, you mentioned a little bit of getting past the authority time point there. What's the product about? The product is about ingesting massive amounts of information to facilitate the ATO process, one, but managing cyber risk more generically because not everybody has an ATO requirement. So, you asked a few seconds ago about, so you're taking a platform approach. Yes, we're blending three separate products that we currently have, taking that functionality and putting it on a very, very, robust platform that can exist on prem, it can exist in the cloud. To enable organizations to manage their cyber risk and if they choose, or they have a requirement, to deal with things like FedRAMP and risk management framework and cyber security framework and iso certification and things of that nature. The point is, not everyone has an ATO requirement but everyone has a need to manage their risk posture. So we're using our ability to ingest lots and lots of data from lots and lots of different sources. We're organizing that data in ways that allow an organization to understand compliance and/or risk and/or security, and visualize all that through some dashboard with ad hoc reporting that let's them blend that data across each other to get better insights about risk posture. >> And to visualize it in a way that makes sense to the user. >> Yes, so, if you're the CEO, you're going to want to see it a certain way. If you're the IT manager, you're going to want to see it a certain way. If you're a risk assessor, you're going to want to see it a different way. So that's kind of what we're talking about. >> I got to ask you one question, I know we got to go, but, a hardcore security practitioner once said to me that hardcore security practitioners, like you guys, when they were kids they used to dream about saving the world. So, I want to know, who's your favorite superhero? >> Superman. >> Superman? >> Spiderman. >> Alright, awesome. (laughing) >> That was a basic question for you guys. >> Thank you very much >> Yeah, that's the hardest question, see they're fast, they know. Star Trek or Star Wars? (laughing) >> Depends on the generation. >> We won't go there. theCUBE have 15 more minutes today. Okay, final question, what's this going to do for your business now you have new, opened up new windows with the new product integration. How's that going to change Telos, what does it do for you guys from a capabilities standpoint? >> Well, the big thing I'd suggest your listeners and your watchers to consider is, there's a new case study that just came out, it's published jointly by the CIA, Amazon and Telos, talking about why working together is really, really, really groundbreaking in terms of this movement to the cloud. 'Cause your public sector listeners and viewers are going to want to know about that because this ATO thing is really a problem. So this addresses a massive issue inside of the public sector. >> And final question, while you're here, just to get your thoughts, obviously there's a big change of the guard, if you will, from old guard to new guard, that's an Amazon term Andy Jassy uses. Also, we all saw the DOD deal, JEDI's right there on the table, a lot of people jockeying, kind of old school policy, lobbying, sales is changing. How is the landscape, from a vendor-supplies to the agencies changed and/or changing with this notion of how things were done in the past and the new school? So, three points, legislatively there's top cover, they understand the need to modernize, which is great. The executive branch understands the need to modernize through the IT modernization act as well as the cyber security executive order. And then lastly, there are use cases now that can show the way forward. Here's the problem. The IT infrastructure out there, the IT guys out there that do business in the government, many of them are not paid to be efficient, they're paid cost plus, they're paid time and material, that's no way to modernize. So, fundamentally, I think our customers understand that and they're going to revolutionize the move forward. >> And the rules are changing big time. Sole source, multi-source, I mean, Amazon's on record, I've got Teresa on record saying, "Look, if we don't want a sole source requirement, let everyone bid fairly." Let's see who wins. Who can bring a secret cloud to the table? No one else has that. >> In terms of past performance and customer use cases they're pretty much in the head, for sure. >> Great, Amazon kicking butt here, Telos, congratulations for a great event, thanks for coming on. >> Thanks a lot guys. >> I appreciate it. >> Alright, CUBE coverage here in DC, this is theCUBE, I'm John Furrier with Dave Vellante. Stay with us, we have more great interviews stacked up all day and all day tomorrow. Actually you have half day tomorrow until two 'o clock Eastern. Stay with us for more, we'll be right back. (upbeat music)

>> Announcer: Live from Las Vegas, it's The Cube. Covering IBM Think 2018, brought to you by IBM. >> Welcome back to IBM Think 2018. My name is Dave Vellante and you're watching The Cube, the leader in live tech coverage. This is IBM's inaugural Think event. Companies consolidated about six major events into one We're trying to figure it out, 30-40,000 people there's too many people to count, it's just unbelievable. Mary O'Brien is here, she is the vice president of research and development at IBM in from Cork, Ireland. Mary, great to see you, thanks for coming on The Cube. >> Thank you, Dave. >> So tell us a little bit more about your role at IBM as head of research and development. >> Okay so I'm head of research and development for IBM Security explicitly so in that capacity I manage a worldwide team of researchers and developers and we take products from, you know, incubation, initial ideas all the way through to products in the field. Products that help defend businesses against cyber crime. >> So, Jenny was talking today about, you know, security is one of the tenants of your offerings at the core. >> Mary: Yes. >> So, everybody talks about security. >> You can't bolt it on, you know, there's a lot of sort of conversations around that. What does that mean, security at the core from a design and R & D perspective? >> That actually means that the developers of applications are actually aware of security best practices as they design, as they architect and design their applications. So that they don't deliver applications to the field that have vulnerabilities that can be exploited. So, instead of trying to secure a perimeter of an application or a product or, you know, a perimeter full stop they actually design security into the application. It makes it a much more efficient, much cheaper way to deliver security and also, you know, much stronger security base there. >> So, I wonder if you could relate, sort of, what you guys are doing in security with what's happened in the market over the last 10 or 15 years. So, it used to be security was, you know, hacktivists and you know throw some malware in and maybe do some disruption has become cyber criminals, you know, big business now and then of course you've got nation states. >> Mm-hmm How have you had to respond specifically within the R & D organization to deal with those threats? >> So, you know, you have described the evolution of cyber crime over the last years and for sure it's no longer kids in a basement you know, hacking to, for the fun of it. Cyber crime is big business and, you know, there's money to be made for cyber criminals. So, as a result they are looking to hack in and get high value assets out of enterprises, and of course, we as an organization and as a security business unit have had to respond to that. By really understanding, you know, what constitutes a very mature set of security competencies and practices and you know how we break down this massive problem into you know, bite sized consumable pieces that any business can consume and work into their enterprise in order to protect them. So, we have developed a portfolio of products that look at protecting all parts of your enterprise. You know, by infusing security everywhere, you know, on your devices, on the, you know, the perimeter of your business. Protecting your data, protecting all sorts, and we also have developed a huge practice of security professionals who actually will go out and do it for you or will, you know, assess your security posture and tell you where you've got problems and how to fix them. >> I remember a piece that our head of research, >> Peter Burris, wrote years ago and it was entitled something like "Bad User Behavior will Trump Good Security Every Time" and so my understanding is phishing is obviously one of the big problems today. How do you combat that, can you use machine intelligence to help people, you know, users that aren't security conscious sort of avoid the mistakes that they've been making? >> So, before I get into the, the complicated, advanced, you know, machine learning and artificial intelligence practices that we are bringing to bear now, you know, it's important to be clear that you know, a vast number of breaches come from the inside. So, they come from either the sloppy employee who doesn't change their password often or uses the same password for work and play and the same password everywhere. Or, you know, the unfortunate employee who clicks on a malicious link and you know, takes in some malware into their devices and malware that can actually you know, move horizontally through the business. Or it can come from you know, the end user or the insider with malicious intent. Okay, so, it's pretty clear to all of us that basic security hygiene is the fundamental so actually making sure that your laptop, your devices are patched. They have the latest security patches on board. Security practices are understood. Basic password hygiene and et cetera, that's kind of the start. >> Uh oh. >> Okay keep going. >> Okay, so-- >> I'm starting to sweat. >> So, you know, and of course, you know, in this era of cyber crime as we've seen it evolve in the last few years, the security industry has reached a perfect storm because it's well known that by 2020 there will be 1.2 million unfilled security professional roles, okay? Now, couple that with the fact that there are in the region, in the same time frame, in the region of 50 billion connected devices in the internet of things. So what's happening is the attack landscape and you know, the attack surface is increasing. The opportunity for the cyber criminalist to attack is increasing and the number of professionals available to fight that crime is not increasing because of this huge shortage. So, you know, you heard Jenny this morning talking about the era of man assisted by machine so infusing artificial intelligence and machine learning into security products and practices is another instantiation of man being assisted by machine and that is our, our tool and our new practice in the fight against cyber crime. >> So when I talk to security professionals consistently they tell us that they have more demand for their services than supply to chase down, you know, threats. They have, they struggle to prioritize. They struggle with just too many false positives and they need help. They're not as productive as they'd like to be. Can machine intelligence assist there? >> Absolutely, so computers, let's face it, computers are ideally placed to pour over vast quantities of data looking for trends, anomalies, and really finding the needle in the haystack. They have such a vast capacity to do this that's way out, you know, that really surpasses what a human can do and so you know, with, in this era of machine learning you can actually you know, equip a computer with a set of basic rules and you know, set it loose on vast quantities of data and let it test and iterate those rules with this data and become increasingly knowledgeable you know, about the data. The trends in the data, what the data, what good data looks like, what anomalous data looks like and at speed point out the anomalies and find that needle in the haystack. >> So, there's a stat, depending on which, you know, firm you look at or which organization you believe, but it's scary none the less. That the average penetration is only detected 250 or 350 days after the infiltration, and that is a scary stat, it would take a year to find out that somebody has infiltrated my organization or whatever it is, 200 days. Is that number shrinking, is the industry as a whole, not just IBM, attacking that figure? First of all, is it a valid figure, and are you able to attack that? >> Well, the figure is definitely scary. I don't know whether your figure is exactly >> Yeah, well the latest figure but it's a scary figure >> Yeah. and it's well known that attackers will get in. So, of course, there's, uh there's the various phases of, you know, protecting yourself. So, you're going to try to avoid the attackers getting in in the first place. Using the various hygienic means of you know, keeping your devices, you know, clean and free from vulnerabilities and so on. But you've also got to be aware that the attacker does get in so now you've got to make sure that you limit the damage that they can cause when they're in. So, of course, you know security is a, you know you can take a layered approach to security. So you've got to firstly understand what is your most valuable data, where are your most valuable assets and layer up the levels of security around those first. So you make sure that if the attacker gets in, they don't get there and you limit the damage they can do and then of course you limit their ability to exfiltrate data and get anything out of your organization. Because I mean if they are just in there, of course they can do some damage. But, the real damage happens when they can manage to exfiltrate data and do something with that. >> So again Mary, it make sense that artificial intelligence or machine intelligence could help with this but specifically what do you see as the future role of Watson as it relates to cyber security? >> So, I mentioned the shortage of security professionals and that growing problem, okay so Watson in our cyber security space acts as an assistant to the security analyst. So, we have taught Watson the language of cyber security, and Watson manages to ingest vast troves of unstructured security data, that means blogs and you know, written text of security data from, that's available on the internet and out there all day, everyday. It just ingests this and fills a corpus of knowledge with this, with these jewels of information. And, basically that information and that corpus of knowledge is now available to a security analyst who, you know, a junior security analyst could take years to become very efficient and to really be able to recognize the needle in the haystack themselves. But with the Watson assistant they can embellish their understanding and what they see and all of the, all of the relationships and the data that augments the detail about a cyber incident you know, fairly instantaneous. And it, you know, really augment their own knowledge with the knowledge that would take years to generate, you know. >> So, I wonder if we could talk about collaboration a little bit because this is good versus evil. You guys are like one of the super heroes and your competitors are also sort of super heroes. >> Of course. >> You got Batman, you got Superman, Catwoman, and Spiderman, et cetera. How do you guys collaborate and share in a, highly competitive industry? Well, they're vary as far as you know, appearing for sharing okay, so firstly you absolutely nailed the importance for sharing because you know, the cyber criminals share on the dark web. They actually share, they sell their wares, they trade, you know so very important for us to share as well. So, you know, there are various industry forum for sharing and also organizations like IBM have created collaborative capabilities like we have our X-force Exchange which is basically a sharing portal. So, any of our competitors or other security organizations or interested parties can create you know, a piece of work describing a particular incident that they are investigating or a particular event that's happening and others can add to it and they can share information. Now, historically people have not been keen to share in this space so it is an evolving event. >> So speaking of super heroes I got to ask ya, a lot of security professionals that I talk to say well when I was a kid I read comic books. You know, I envisioned saving the world. So, how did you, how did you get into this, and was that you as a kid? Did you like-- >> No, it wasn't. I'm not a long term security professional. But, I've been in technology and evolving products for, you know, in the telecommunication business and now security over many years. So, I got into this to bring that capability of delivering quality software and hardware products to the field back in 2013 when a part of our IBM security business needed some leadership. So, I had the opportunity to take my family to Atlanta, Georgia to lead a part of the IBM security business then. >> Well, it's a very challenging field. It's one of those, you know, never ending, you know, missions so thank you for your hard work and congratulations on all the success. >> Thank you David. >> Alright, appreciate you coming on The Cube, Mary. >> Thank you. >> Keep it right there everybody, we will be back with our next guest, you're watching The Cube. We're live from IBM Think 2018 in Las Vegas, be right back. (pleasant music)

>> Narrator: Live from Las Veags, it's theCube, Covering NAB 2017. Brought to you by HGST. >> Welcome back everybody, Jeff Frick here with theCube. We're at NAB 2017 with 100,000 of our closest friends. Talking all about media, entertainment and technology. The theme this year is MET, cause the technology is so mixed in with everything else that you can't separate it anymore. And we're really excited to do a deep dive into kind of the customer, or not the customer, excuse me, the consumer side of this whole world with Yves Bergquist. He's the project director, Data and Analytics Entertainment Technology Center at USC. So Yves welcome. >> Thank you, thanks for having me. >> So when I was doing some research on your segment, really interesting to see that you're involved very much in trying to figure out what people like to watch how they like to watch and get a bunch of data because now the choices for the consumers of media and entertainment are giant, like never before. >> Yeah. There's a, very very basic question that I think not a lot of people in media and entertainment can answer. Is that why are people watching your stuff? And they have sort of surface level answers, but there's ways that the content out there, that we watch, resonates cognitively with us, that is really important, is very fundamental in how we consume media and entertainment. And even the decision making of why we decide to go watch a show on Netflix, or play a mobile game, or watch a Youtube video. Why do we make these specific choices? What drives those choices? All these questions don't have a lot of really good answers right now, and that's where I, where we're focus all of our work at ETC. Is to really understand people's drive to entertain themselves or decisions to entertain themselves at a very deep level. And really understand how various narrative structures in film and trailers and brands and advertising resonate with people at a cognitive level. >> So it's pretty intersting, it really goes with the whole big data theme and the AI theme. Because now you can capture, collect, measure data in ways, and consumption in ways you couldn't ever do before. >> Yeah, that's a good point. So, you know, there's three things that are really impacting the media and entertainment industry and every industry, really. It's, number one, the ability to think in systems, right? We used to think about problems in a very sort of siloed manner, right, we think about a problem in isolation with other forces. Like we look at the flu in isolation with the environment that we're in, so like that. There's another way to look at things, in a more holistically, it's a system called systems thinking. And the ability to think of audiences as a system, just like your body's a system inside a system, right, is really revolutionizing the way we're looking at entertainment and media. The second thing thing is the availability of data, just there's an enormous amount of data out there. A lot of it is unstructured, but there's, the good thing about entertainment and media is that it drives passion and drives conversation. And anything that drives passion and conversations get very rich in data. And the third thing that is impacting the industry is machine living and AI. And the ability to really look at all of these data points across the system holistically in a very intelligent more semantic manner. And make sure that you're measuring the right things. For a very very long time the media and entertainment industry has been measuring the wrong things. And it's really now catching up very very fast and making sure that it's measuring the right things. For example, how do we measure how specific narrative structures in film resonate with people cognitively in a way that translates into the box office? Is there a specific character journey that resonates better in an action movie with males versus females. How does that matter for how a story's being told? Where do you innovate in script, right? Interesting point is the entertainment industry is very unique in that it has two major problems. Number one, its clients, its customers are absolute experts in the product. Because if you're 25 or 35, how many movies have you watched? Thousands of movies, right? So you're an expert in movies. >> Jeff: Certainly the ones you like. >> Exactly. If you're 25 you haven't bought hundreds or thousands of cars, right? So, but on the other hand the supplier of the content doesn't know as much of the customer as the customer knows about the product. So you have two problems. You have a really really really highly expert client, and, but you don't know a lot about that client as a studio, right, or a network or a media company. So that's very very unique distinct challenge that they're starting to get very very smart and very advanced in thinking about. >> The other thing is, that I see in the movie industry and I'm no expert by any stretch of the imagination but it seems like the compression pressure is huge. The budgets have grown to be giant. And the number of available weekends for your release are small. And the competition for attention and eyeballs around those weekends, it just seems to really have a really high kind of risk reward profile that's getting more and more extreme. And is that driving people more to kind of the known? Or is it just my perception that they're taking less risks on modifications from the script or modifications of kind of the norm especially around these big budget? I mean just the fact that you've got version 1,2,3,4,5,6, pick your favorite theme seems to be a trend that continues and gets even more, I mean Superman. How many Superman movies are there, or Spiderman? >> So you know, that's really interesting right? So the very natural tendency of the media and entertainment industry is when it doesn't know, as I was mentioning, it doesn't know as much as it could or should know about who its audience is. The tendency is then becomes to just take less and less risk in telling stories exactly the same way that's why you see a lot of really really formative very formulaic movies. What we're trying to do is, and the challenge with that is that, again you have an audience of experts and so if every single movie looks like the same one, look like the other one, you're going to have a problem. People aren't going to go see, going to go gravitate towards another kind of entertainment or some of your competitors. So you have to know where do you meet peoples expectations in a movie and where do you innovate? Deadpool is a really interesting example. Deadpool has the structure of a basic superhero movie but it has a lot of innovation underneath that. And so for the studios knowing where do you stick to the formula and where do you innovate in telling a story when you make a billion dollar movie, is going to become more and more interesting. Because if you innovate too much you're going to turn people off. If you don't innovate enough, you're going to turn people off. So we actually have some research looking at the mathematical definition of why we think certain things are interesting and certain things are not interesting so we can separate. These are the things you need in your movies, this is some aspects, if you go back to Deadpool, there's some aspects of Deadpool as a movie that are very traditional to the superhero genre. And a lot of other aspects that are very very innovative. So you have to innovate in certain areas and you have to no innovate areas. And that's a real challenge, and so that's why we're really applying our work to looking at narrative structure in storytelling at ETC is because that's where a lot of the revenue opportunities and the de-risking opportunities are. >> And it's interesting before we went live you were talking about thinking of storytelling and narrative as a little bit less art and a little bit more science in terms of of thinking at in terms of algorithms and algorithmically. Because there are patterns there, there is data there. So what does some of the data that you measure to get there? You mentioned earlier that in the past people were measuring the wrong thing. What are the right things to measure? What are some of the things you guys are measuring now? >> Yeah, so you know, it is still very much an art, right? It's making it, making art a little bit more optimal, and optimizing art is what we're doing, but it's, it will remain art for a very long time. I think for, and since we're at NAB, sort if in a broadcasting environment, I think a lot of the measurements and systems that have been in place for decades now are looking at demographics. And demographics, whether you're a male or female, Your age, your ethnicity, or your income, used to predict what you would watch. It doesn't do that anymore, and if you have kids, you know like me, you watch the same thing that they're watching, you're playing the same video games that they're playing. I think there's a new way to measure things more cognitively and semantically and neuroscience is starting to get into the issue of why do we think certain stories are more interesting or more appealing than others. Why do certain stories lead us to make actual decisions more than others? And so I think at a very very basic level you have to unpack this notion of why do people go see this movie? And it's a system, you know, that decision happens in a system where some of the system is demographics, demographics aren't going to go away they're still predictive to a certain extent. But it's also, you know, cast, it's also who has recommended this movie. And what are the systems of influence in driving certain people to see a movie? And all these things, and of course, what we're focusing on, which is storytelling and narrative structure and how that, sort of translates to making decisions to see this movie. A lot, you know, we're still in the infancy of measuring all of the system in a very scientific granular way, but we're making very very quick progress. And so even things like understanding the ecosystem of influence around why certain communities are influenced to go see certain movies by other communities and what happens there, right. So I'll give you an example, we did, we pulled months of data on Reddit about where supporters of Hillary Clinton and where supporters of Donald Trump would engage on that topic. Are they talking about that amongst each other or are they really going out there and trying to convince other people to vote for Trump or to vote for Hillary Clinton? And we saw some, two radically different patterns. So pattern number one, the Clinton people would mostly engage with each other on Reddit. So that's cool and that has very little value because you're not being an ambassador. On the other hand, the Trump people were engaging far outside of the Trump subReddit and trying to convince people to join the movement, to donate, to vote for Trump. So we think there's a model there that can be ported to the entertainment industry, where if your fans, if your fan base is mostly engaging with each other it has less value than if your fan base is really going out there and really trying to get other people excited about your movie. And why do certain people get excited and how do your fans, what argument do your fans use out there to convince others to go see your movie. All these things we're looking at, and it's brand new world now for media because of all of these data points. >> The systems conversation is so interesting because it's not only the system, but the individual. But it's like you said, it's all these systems of influence today. Look at the Yahoo reviews, the Rotten Tomato reviews, you know, what are there, Reddit, you know, as a system of influence, who would have ever thought? >> Yeah and we're getting it, we're going into a world very quickly, we're going to be able to understand entertainment and storytelling and narrative and it's cognitive power almost on a neural network base. In looking at what kind of neural network in our brains get fired when we are exposed to this type of character, or this type of storyline, or this type of narrative mechanics. And so this is a really exciting time. >> The other thing that's interesting, we talked again a little bit before we turned the cameras on, is about the trailers. Because that's kind of the story within the story. And depending on your objectives, and the budget, you know, they can make all kinds of number of trailers, in very different way, to approach or to target very specific audiences. I wonder if you can get into that a little bit. >> Yeah so, you know in the media and entertainment industry decisions have been made, and if you think about it it's amazing that the media and entertainment industry has made so much money, so I think it's a testament of the enormous creative talent that's involved. But, you know, especially for trailers a lot of the decisions about trailers are made sort of looking what's worked in the past in a very sort of haphazard way. There really isn't a lot of data and analytics and science applied to, hey what kind of trailer, what structure of trailer do we need to put out there in each channel for each target audience to get them really excited about the movie? Because there's many different ways you can present a movie, right, and we've seen, we've all seen many different types of trailers for many different types of movies. What we're doing, and nobody's really worried about hey let's analyze, for example, the pace, right, the edit cuts, the structure of the edits for the trailer and how that resonates with people. And now we have the ability to do that because people, you know, we will count views on YouTube for example, or there will be a way to measure how popular a trailer is. So what we're doing is we're just measuring everything that we can measure about a trailer. Is it a complete story? What is the percentage of the trailer is the main character in? What is the percentage of the trailer that the influence character is in? We're looking at cast. Does a trailer with Ben Affleck, you know, work better if Ben Affleck is a lot in the trailer, or not a lot in the trailer? And what kind of trailer types work better for specific genres, specific target audience, specific channels? So we're really unpacking that into a nice little spreadsheet. And measuring all the things that we can measure. And the thing about this is, if you think about the amount of money that's involved in making these decisions, you know if you're a studio and you're spending 3,4,5 billion dollars a year in marketing expense, and my work can make it even 10 percent more efficient, that's like half a billion dollars in savings. >> That's a real number. >> That's enormous right? So it's a really exciting time for media and entertainment because there are all these things on the horizon to help them make better decisions, more data driven decisions. And really free up creators, because if we can tell the people who tell the stories in film every, you can innovate so much more now because we've, we know that we've boiled it down to a science, and we know that in this, if you have these four or five things in your script, everywhere else you can innovate, go nuts. I think it's going to free up a lot of creative talent. We're going to see a lot more interesting movies out there. >> The other piece I think, I mean obviously a trailer for a movie's one thing, but take that little genre of creative that's purely built to drive behavior and that's a commercial. And I always joke with my kids, I watch a lot of sports, and there'll be a car ad and I'm like, just think if you're the poor guy that gets the assignment to make another car ad, I mean, how many car ads have been made, and you've got to think creatively. But the data that you're talking about, in terms of the narrative, what types of shots, the cutting, based on the demographic that you're trying to go after for that specific ad. That must be tremendously valuable information. >> Yeah it is really valuable. So you know, our philosophy is that everything is story. You're tie is a story, your haircut's a story, you're cereal's a story, your cars, everything. We make decisions based on the narratives that other other people tell us and that we tell ourselves about how to represent the world. Simply because the universe out there and the reality out there is too complex for our brains to really represent as it is, so we have to simplify, compress it into a set of a behavioral script that says, okay I'm, it's sort of an executive summary of their reality. And though that executive summary is a story. And so it's especially powerful in driving how what we buy and how we consume things. And so, I've build a platform that looks at, that extracts very very structured data from conversations about what is the narrative structure about a specific brand. You know, is it focused more on, you know,emotions? Is it focused more on ethics? Is it focused more on the, sort of the utility of the product? And trying to correlate that to look at what kind of narrative structure's around your brand? What kind of story around your brand, drives more sales? And so that's really really interesting, in sort of understanding, again, that cognitive relationship between stories and how efficient they are in driving specific behavior. That is exactly what my research is about. >> Yves, we could go on all day, but unfortunately we are out of time. So thank you for spending a few minutes and dropping by. Fascinating conversation. Alright, he's Yves Bergquist from USC, where all the film stuff's happening. I'm Jeff Frick, you're watching theCube. We'll be back NAB 2017 after this short break. Thanks for watching. (uptempo rock music)