>> Live, from Washington, D.C., it's theCUBE, covering AWS Public Sector Summit 2018, brought to you by Amazon Web Services and it's ecosystem partners. >> Welcome back to the District, everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm here with my cohost, Stu Miniman. Day two of the AWS Public Sector Summit. We saw Teresa Carlson yesterday, a lot of keynotes, we saw the CIA. Todd Osbourne is here, he's the Vice President of Alliances of New Relic, a company that's been smokin' hot, six billion dollar market cap, and really is takin' the world by storm. He's joined by Scott Drossos, who's the president of Infiniti, who is a public sector consultancy. Gentleman, welcome to theCUBE, good to see you. >> Thanks, good to be here. >> Thank you. >> So Todd, you heard me, I mean really, everybody's talkin' about New Relic, stocks been smoking, I read an article recently, "it's got to cool off, it's too hot." So why so hot, what's goin' on, why the appeal of New Relic? >> Well as our CEO Lew Cirne has been on a couple of times talking to you about, every business is becoming a software business in the public sector, which we're here representing at the Amazon public sector event. It's the same thing with agencies and all the digital experiences that are happening across all the government and whether it's education, higher ed, healthcare, any of the DOD or other agencies, there's always some sort of digital experience that folks are having with the citizens that all the agencies and organizations are tryin' to support, and New Relic's right there, right there at the forefront of every one of those digital experiences. Everyone's running software that's modern software, or shifting to that with modern software running microservices, running containers, shifting to the cloud, and anyone deploying that type of software needs to have New Relic as part of their engagement to monitor what's happening at the citizen or the customer level, what's going on in the back end, on through the infrastructure. And New Relic, whether it's a large enterprise that we're out there, like Dunkin' Donuts or Dominos, monitoring their applications and their eCommerce sites, or it's an agency in the public sector space, you got to have New Relic as part of those engagements. >> So Scott, when AWS services first came out, 2006 timeframe, we looked at it, we said okay, this is the future, but as much as it potentially simplifies lives, it brings a lot of new complexities. So you know, Stu and I used to talk about, look, the AWS is awesome, we're big fans, but the ecosystem has to grow. Consultancies have to come out of the woodworks, and help customers really, adopt. So that's really exactly what's happened. I presume that's how Infiniti got started, maybe you could tell us a little bit about the company, and what your value is. >> Sure, thanks Dave, so Infiniti is a 15 year old company. We're originally founded in public sector IT consulting, and we realized several years ago that the world was changing and that we needed to make the shift from IT consulting to cloud services. And so we dove in headfirst with AWS, and we really tried to move to the top of the curve very quickly, and so we were a little bit ahead of our market in public sector, being a public sector focused organization, but we felt it was important to get ahead of the market because now the market really is smokin' hot. But we thought it was important that if we're going to move into the cloud, we wanted to move to the top of the curve, and deal with things like DevOps, migrations, even machine learning, predictive analytics, so we kind of pride ourselves on having some of the largest public sector contracts in the US, even though we're, right now, predominantly California based, California focused. >> And what's your head count? >> We're about a hundred people. >> I mean this is the thing, we're seeing this trend toward a lot of, you know, smaller specialists, are really doing super. Why is that, or how are you able to differentiate from these big global SIs that have tens of thousands, hundreds of thousands of employees, vertical expertise, why are you guys winning? >> Well, first of all, I think we're able to be nimble and shift our focus pretty quickly to serve our market, to serve our customers, I think more successfully. But one of the thing's that's changed when the cloud arrived, is the cloud really let smaller organizations like us, act like big organizations, so we didn't need to go deploy millions of dollars of capital to go set up a massive data center, we can build an environment on the fly, as you know, in the cloud, and we can have access to world-class platform tools like New Relic, and we can help a customer, a large customer, perform just as well as if we were a large multi-billion dollar services organization. >> Todd, one of the interesting things to talk to customers about is their journey, and where are they, and the cloud migration and how do they do this, reinvent? A year ago or two I heard there were like seven or nine ARS to get there, anything from the full refactoring and building cool new stuff with server lists and things like that, to just the re-platforming. Lift and shift, is that a good thing, isn't that? Walk us through how New Relic with Infiniti, how are you involved in some of those migrations? There's no typical customer, but give us some examples. >> Yeah absolutely, so Infiniti, just like many of the integrators that we work with are all delivering services generally in a couple different areas. One is typically a cloud adoption, or cloud migration practice. So working with Amazon, how do we get more and more of customer's workloads shifted to the cloud? Usually those projects are also going on with something in the refactoring world or application space. Usually they're also developing or shifting to some sort of DevOps practice, and that's also part of our sweet spot, what's happening in the application there, whether it's on the cloud yet or not, we're going to provide that visibility to that. And then the third piece is, there's usually something else happening with that, as I was mentioning before, the customer experience or the citizen experience, so what's the browser impact, what's the user experience on that, what's the, if it's on a mobile app, what's the user experience on there? So while Infiniti's delivering all those services for the clients, New Relic's part of all those services, so our whole model that we're tryin' to do with all of our partners is embed ourselves into all of those services, such that we can help Infiniti be more successful, deliver those projects on time, and really resolve any issues that may come up during those migration issues. >> Scott, I'd love to hear especially, I know I hear DevOps talked about a lot in New Relic's customers, is it pervasive around the agencies that you work with and please do add some color there too. >> So in the public sector, it's a range of readiness, but we're seeing a real wave building, we believe. We worked with New Relic on a very large DevOps, SysOps, very complex cloud services engagement, largest higher education cloud services engagement in the US, and in that case, just like Todd was referencing, when we implemented the migration of the legacy platform to the cloud, first of all we had to do, make choices around refactory, host, rearchitect and so forth, but then when we're managing that environment, and there's millions of users hitting that environment, we need to be able to make sure that we can monitor the application to make sure the application's performing well, and if there's an issue, we want to see the line of code that's causing the problem as quickly as possible so we can keep the environment up all the time. Even though public sector may not be driven by the same financials as say, commercial, they still expect to be up all the time. They still want to take advantage of the benefits of the cloud and so New Relic allows us to do that, but then, as we're looking at the users interface with the application environment, New Relic's browser and mobile, they let us monitor how that experience is going, and we can proactively get at the performance issues there that the application may not tell us, if there's an issue there. And then, we can do things like test middleware with synthetics and make sure that the whole environment's working, and then obviously on the infrastructure side, it lets us make sure that we're optimizing the environment for our clients. One of the cool thing is, when you in the past, you'd set up an EC2 instance, you may not see that you don't need as much CPU as you're using, and so you can size that appropriately, and allow your environment to still run at a high performance, 100% up time, but give them the cost efficiencies at the same time. So we use New Relic across board to help support the entire environment. >> I wonder if we could talk about the marketplace a little bit, generally and then specifically, the public sector? So Scott, I presume you're obviously public sector focused, but are you exclusive to AWS, no, you probably do some other stuff, is that right, is that fair? >> Well we are both AWS and Azure Gold, in terms of partner, but we do more of our work in AWS for sure. >> Okay, so we'll come back to that. And New Relic, of course you're a software company, so you want everybody to love your software, so if there's a cloud that a customer wants to use, you want your software to be on that cloud, fair enough? >> Sure, and also on PRIM, I mean a lot of our... >> On PRIM too. >> A lot of our applications we monitor are still on PRIM, and there's a tremendous amount of value there regardless of... >> I would just add, Infiniti is a trusted advisor, we like to see ourselves as a trusted advisor, so we do feel like we have to be multi-cloud and have an objective perspective. >> And New Relic is presumably the same way, I mean let the customers decide, so, and it's a hybrid world, folks, despite what Amazon wants, it's a hybrid world, and they even recognize that. My question is, there's a lot of discussion in the industry about Amazon as an infrastructure service provider and their lead or relative lead on the competition. It's our sense that there's still a lead there, what's your sense? >> Well AWS is still the leading cloud services provider in the marketplace. They lead in innovation, they lead in disruption, they lead in market share, they lead in so many metrics, and because they have that lead, and that's where we started, we've benefited from that, and we've invested heavily, and in the same way, we see New Relic, when we made a choice around who we were going to pick as a platform to support our customers, we wanted something that was cloud-born, didn't come out of on-premise and get sort of bootstrapped into the cloud, and we wanted something that was a complete platform. So New Relic was really a clear choice for us. It was not a, we looked at the entire market when we made that choice. >> So the narrative in the market used to be, oh, security in the cloud, now we hear the CIA say hey, security on the worst day in Amazon's cloud is way better than I ever saw with client server. It was a pretty powerful statement, so let's assume security, people are relatively comfortable with security these days, even though I'm sure there's still some issues with regard to corporate edicts, and flexibility, and audits, let's put that aside. SLAs is another big one. People often criticize the public cloud SLAs, and cost, oh it's so expensive, I can do it cheaper on PRIM. Are those myths, are those realities, is it a it depends? What's your sense? >> I mean they're all, they're all factors that all of our customers are looking into. I would say what we're hearing a lot about right now, is how do we help provide more visibility to everything that's happening, so if you've got a developer now that has the ability to write code, put it on any cloud they want, spin up containers, spin down containers, go try out server-less base of architectures, they've got a lot of flexibility to do what they want. Government agencies, as well as customers, one of the things they're looking for is what's actually happening? Who's doing what? The governance piece is a big piece and I think New Relic plays right into that in terms of helping control all that. One of the things that we're, is one of our sweet spots, is as you move to DevOps and a truly microservices architecture, one of the whole values of that is speed, keeping up with how fast the whole market is moving, and customers and agencies, what they want out of that, is to deploy applications where they're releasing multiple times a day. You have to have visibility into everything you're doing across the stack to be successful in that, and that's really New Relic's sweet spot in terms of doing that. So providing that visibility, instrumenting the applications in the infrastructure before, and then helping provide visibility to things like governance, things that other, not necessarily our sweet spot, but other companies in the industry are doing things throughout the DevOps life cycle in the governance realm, things like that. So we're part of that ecosystem that's helping Amazon and the other cloud providers be very successful, helping customers and agencies be very successful deploying modern applications. >> It's all about that visibility. >> Scott, one of the things, when we look at any rollout of new technology or migration, once it's up and running, then what, so wondering how your firm's involved in, you know, is there re-training, is there things go on, once this is in place, now what? >> Well Infiniti, what we found in public sector is that everybody wants to take advantage of the cost efficiencies and the benefits, and most public sector isn't going to reduce cost, they're just going to want to re-use cost more wisely. So some of the confusion around cost savings is that they're getting way more for their dollar in the future state, and the choices you have to make around how fast you want to get to the cloud, and what you want to get out of the cloud when you're there, those all effect the equation in terms of what you're actually outcomes are immediately and in the long term. So we often see that in public sector, some of the legacy applications, they may not naturally or easily move all at once, and so you have to make a choice, are you going to do some refactory and architecting before you get it there, are you going to get in the cloud now, and then do it afterwards. Either way, there's benefits, but you have to make choices about what, how you want to approach it. >> Yeah, when you talk about, after I've rolled this in, I've heard from some customers, they're like, after I've gotten a cloud, I love it, but I had to dedicate an engineer for financial architecting because there's all of these things we need to do. Are we still in that state? And once again, do you help with some of the training as to, okay, or is it plugging them into the Amazon ecosystem and how do they get certified and ready to use all of this. >> So Infiniti works with clients differently, we work with some in a more episodic, lighter capacity, and we work with some in a wholistic capacity where we are that engine for them, where we provide them the complete cloud services team to do everything from migrations, architecture, DevOps, SysOps, SecOps, machine learning and all the way through. And so when we're providing those services, we're doing those kind of things, we're making sure that the next improvement is worked into the architecture. Last year, the customer I was referencing earlier, we did just under a hundred releases, so that's a hundred releases that we're using the New Relic platform and our architectural solution, our solution architects, rather, to make sure that it's faultless, that the process is efficient, it's effective, it's secure, and that we're driving efficiencies wherever possible. So it really depends on what the customer wants. If the customer wants to hone the environment, they may have to go a little slower to account for their learning, their learning curve, and we'll help them, if that's what they want, but if they want to go faster, and they want to take advantage of our expertise, we make that available, and we're happy to do that. >> We had the former CTO of the NSA on yesterday, who now works for Accenture, and we were asking about sort of, federal versus commercial, are we sort of still taking, learning lessons from commercial and bringing it to federal, or is it because federal has so much interesting technology around analytics, does it go the other way, and he said, "it's funny, when you're on the inside, you think all the innovation is goin' on outside, now that I'm on the outside I say wow, there's a lot of interesting stuff going on in federal." We heard Teresa yesterday talk about Aurora, she talked about the VM wear partnership, so things that were announced a while ago and actually being adopted in commercial coming in to federal. So how does it work? Is it more of a two-way than it used to be 20 years ago and I wonder if you could comment? >> Yeah, from Infiniti's perspective, absolutely. We work with clients to understand the problems and where they want to get to, and then we innovate with them. You're pretty dependent on the subject matter expertise of the organization. I think our customers like that, they like that they're part of the solution, but then they need the expertise that we bring to create the next generation solution. We just created something in the higher ed space called, a college called Architecture Builder, and it was after teaming with a specific college, and working in that space for a long time, but we wanted to create a way for colleges to rapidly implement a complete architecture integrated with all the different things, including New Relic, quickly and successfully, and that was done in partnership with them, so we did the work, but we couldn't have done it without them. >> Todd, New Relic obviously, you're a believer, you drink the Koolaid every day. Why New Relic relative to the competition? How do you guys differentiate? Pitch me. >> So it's really all about being successful in that modern software space, again, as I've mentioned, and so New Relic is the only SAS only platform, so we're not going to put anything on PRIM. We've got ourselves one of the biggest and best DevOps team that develops our software, we roll code everyday, and our customers get the benefit of us being a pure SAS platform. Part of that is scalability. What we can do at scale is unbelievable. There was a customer that was just talked about on the news today that I can't mention, but they just went from basically zero to $100 million on an application just in the past 90 days. It's one of our customers and we've scaled, we have no problem scaling with customers that are doing things like that, and again, the full platform value that we have now, looking at everything from the front end on the browser and mobile applications, through the application, which is core to us, it's where we provide that code-level visibility, the ability to trace across all the different microservices that are happening, connected back to that infrastructure. That full platform now provides such tremendous value up and down the stack, but not only to the technology leaders but also to those folks that are business leaders, chief marketing officers, heads of practices at the consultants we work with, all these folks are all getting value out of New Relic. >> What would that customer who should not be named say about the value contribution of New Relic to that scale? >> The value's unbelievable. That's a commercial customer, but their business is taking off like so many of our customer's businesses are at an unbelievable scale. They can't be hamstrung by having to do a server upgrade, or having to go back, working with a release of code from a couple weeks ago, they have to be as fast as possible 'cause their business is moving so fast, their agencies are moving so fast, they need a provider that's going to provide that visibility to that at the speed with which they're moving. >> Awesome so, you got one more? >> No, we've got to run. >> Yeah, we've got to go. So this is the last question, so impressions of AWS Public Sector Summit? I presume you guys, like we did, had to register yesterday. There were some logistic issues, but other than that, maybe you could give us your last word on the summit? >> Well Infiniti is very committed to public sector, so we really enjoy coming to the Public Sector Summit. It's great to connect with our partners, like New Relic and others, and it's great to see the latest innovations coming out from AWS. >> Yeah and I've been to, I don't know, 10 or so summits around the world so far this year. It is unbelievable the excitement and the amount of people that are now excited about what's happening in the clouded option world, and Amazon's piece in that, and what's happening here in D.C. this week is no exception. >> I would second that. It's been a while since I've been at summits. Stu, you go all the time, and they are just exploding and growing, and this is one of the best that's out there. So thanks guys, for comin' on theCUBE, we really appreciate it. >> Thanks very much. >> Thank you for the opportunity. >> You're welcome. Alright, keep it right there everybody, Stu and I will be back with our next guest after this short break. John Furrier's here, you're watchin' theCUBE live, from AWS Public Sector Summit. We'll be right back. (upbeat music)

>> Hello, I'm Kunio Kashino from Biomedical Informatics Research Center of NTT Basic Research Laboratories. I'd like to talk about neural audio captioning and its application to stethoscopic sounds. First, I'd like to think about what captioning is in comparison with classification. When there is a picture of a cat, you will recognize it as a cat. This is a classification or object recognition. Captioning on the other hand is to describe what's going on in a more complex scene. This is an example of a visual case, but the same can be thought of for sound. When you hear a car on the street, you can recognize it as a car. You can also explain the sound when someones hitting a toy tambourine. Of these, the generation of explanatory notes on sounds or audio captioning is a new field of research that has just emerged. (soft music) This is an experimental system that we proposed last year. It listened to sound for two seconds and provides an explanation for the sound of that section. (soft music) Moving the slider to the left produces a short, concise description. Moving it to the right produces a longer, more detailed description. (soft music) The descriptions are not always perfect, but you can see how it works. Here are some early works in this field of study. In 2017, Drossos conducted a study that gave sound a string of words. But there are still a lot of overlap with the classification task at that time. At around the same time, Ikala who was my student at the university of Tokyo proposed a system that could express sounds in onomatopoeic terms as a sequence of phonemes. Recently more works have been reported including those describing more complex scenes in normal sentences and using sentences for sound retrieval. Let's go over the differences between classification and the captioning once again. Classification is the process of classifying or quantizing features in a fixed number of classes. Captioning on the other hand means converting the features. For example, the time series of sound features is translated into the times series of words. Classification requires that classes be determine in advance, but captioning does not. In classification relationships between classes are not usually considered but in captioning relationships between elements are important not just what is there. In the medical context classification corresponds to diagnosis while in captioning we've addressed the explanation and inference rather than diagnosis. Of course, diagnosis is an important act in medical care and neural classification neural captioning is necessarily better than the other. Captioning would be useful to express the comparisons, degree, time course and changes and the relationship between cause and effect. For example, it would be difficult to prepare a class for the situation represented by a sentence of over the past few days pneumonia has gradually spread and worsened. Therefore both of them should be utilized according to the purpose. Now let's consider the challenges of captioning. If you look at this picture everyone will say, it's a picture of a cat. Yes, it is. No one called this a grey and white animal with two round eyes and triangular ears. Similarly, when a characteristic noise is heard from the lungs as the person breathes, you may just say wrong car hire present. And wrong described the noise in detail. That is it's a good idea to use the label, if it's appropriate. As long as the person you are talking to can understand it. Another challenge with captioning is that the exact same description may or may not be appropriate depending on the situation. When you were walking down on each section and a car pops up, it's important to say it's a car and it's inappropriate to discuss the engine sound quality. But when you bring a car to a repair shop and have it checked you have to describe the engine sound in detail. Just saying that the engines running is obviously not enough. It is important to note that appropriate expressions vary and only one best answer cannot be determined. With these issues in mind, we configured a neuro audio captioning model. We call this system CSCG or Conditional Sequence-to-sequence Caption Generator. The system extracts a time series of acoustic features from biological sounds such as hard sounds converts them into a series of words and outputs them with class labels. The green parts are neuro networks. They were so trained that the system outputs both captions and labels simultaneously. The behavior of the sentence decoder is controlled by conditioning it with the auxiliarity input, in order to cope with the fact that the appropriate captions can vary. In the current experimentation we employ your parameter called Specificity. It is the amount of information contained in the words, in the entire caption. In other words the more number of words and the more infrequent or more specific words are used, the higher the variable specificity. And now our experiments the entire network was trained using a set of heart sounds. The sound samples were extracted from sound sources that collected 55 difficult cases. For each case, the signal was about one minute in length. So we extracted sound samples by windowing the signal. In one case four cycles worth of signal were work cut at the timing synchronized with the heartbeats. In another case, signals of six seconds in length were cut out at regular time intervals of three seconds. Class levels and seven kinds of explanations sentences were given manually for each case. This table shows the classification accuracy. We organized categories as general overview description of sound and presence or absence of 12 difficult heart diseases. We then prepared two to six classes for each category. As a result, we found that it is possible to classify with a fairly high accuracy of 94% or more in the case of beats synchronous windowing and 88% or more in the case of regular windowing. This graph shows the effect of the specificity control. The horizontal axis represent the specified specificity of level of detail. In the vertical axis we present the amount of information contained in the rear outfit captions. As you can see, the data is distributed along a straight line with a slope of one indicating that the specificity control is working correctly. Let's take a look at generated captions. This table shows the examples with varying specificity input for three types of sound sources, normal, large split of second sounds and coronary artery disease. If the specified specificity is small then the generator sentence is short. If the specificity value is greater you can see that detailed and long sentences are being generated. In this table, all captions are confirmed to be appropriate for the sound by humor observations. However the system does not always produce the correct output for now. Sometimes it may produce a wrong caption or a statement containing a linguistic error but generally speaking we consider the result promising. In this talk, I first discussed the problem of audio captioning in comparison with classification. It is not just a sound recognition and therefore a new topic in the research field. Then I proposed an automatic audio captioning system based on the conditional sequence-to-sequence model and tested it with heart sounds. The system features a multitasking configuration for classification then the captioning. And allows us to adjust the level of detail in the description according to the purpose. The evaluation results are promising. In the future, we intend to enrich the learning data and improve the system configuration to make it a practical system in the near future. Thank you very much.