>> From Mountainview, California, it's The Cube, covering the 15th annual Grow! Awards. Brought to you by ACG SV. >> Hi, Lisa Martin on the ground with The Cube at the 15th annual ACG SV Grow! Awards. At the Computer History Museum in Mountainview, can you hear the buzz of 230 plus attendees behind me? I'm very pleased to welcome one of the ACG SV board members Dr. Shampa Banerjee, technology executive, and chief product officer at Eros Digital. Shampa, thank you so much for giving us some of your time this evening. >> Thank you, it's a pleasure. >> So lots of great, innovative, and inspiring conversations, no doubt, going on behind us. >> I'm trying to listen to it. >> Yeah, so talk to us a little bit about Eros Digital, who you are, what you do. >> So Eros International is the largest studio in India. It produces or distributes around 60 to 70 percent of the films made in India, Bollywood films. So I run the streaming platform, the Netflix for Bollywood, that's what I call it. >> The Netflix for Bollywood, I love it. Now, tell us more about that. >> So, you know, it's a streaming platform, a lot of the titles are from what we produce. A lot of the titles we lease from other production houses, and that is the entire technology platform, and then how do you get to the, we connect the consumers, rather, to the entertainment, right? So we like to help them discover, we help them indulge in the whole experience, and then as they keep coming to us more and more, we personalize the experience for them, so that's really what we give them. >> You know, personalization is so key. We expect it right in our lives, and whatever it is that we're doing, we're engaging with an Amazon or a Netflix or at Eros for example, we kind of now expect that. We're sort of demanding consumers, right? We expect them to know what I want, just what I want, don't give me any things that I don't want, so is that one of the things that you've seen, maybe surprising in your career, is this increasing demand for personalization? >> Absolutely, because, you know, there's so much content out there, so much information, and unless there's a filtering mechanism that makes sense for you, people don't want to, you know, it's very hard for them, so they want you to do the work for them. It's entertainment, right? So absolutely. Everyone kind of expects it. It's not said. It's not explicit, but that's the expectation. >> And obviously, with the goal of delighting and retaining those customers, you as the chief product officer have to listen and react to that. >> I spent, I'll tell you a short story. I spent once a month going through all the customers' comments in different platforms, right? And one of the stories I read was this 17-year-old French gal in Paris, she loves watching Bollywood because she was suffering from leukemia and after she gets a treatment, she comes home, she wants to watch something that makes her happy, and we had some issues with that subtitles, and she was having a problem watching our movies and she begged "Please bring them back". And I ran out of my office, went to my team, and I said, "Guys, this is who we wake up for every day. We give her joy, we give her pleasure." So to me, that's how listening to the customers to me is primary, to me they are my biggest stakeholder, and I've told the CEO and founder that, look at the end of the day, I leave and argue with you if it doesn't serve my customers. That's what I believe, listening to the customers, listening to them, understanding, of course, we do a lot of data collection and we look at what we are doing and the patterns, and based on that we make modifications, we test different things to see what makes sense, what's working, and what's not working, because people don't always tell you, and even if you ask them, they're shy to tell you. But then you can see what they're doing, and that's an indicator. >> Well that makes you feel really good, seeing and hearing and feeling the impact that you're making, and speaking of impact, you have been, in the last minute or so that we have, you've been on the board of ACG SV for about the last five years. We're here tonight to honor Arista as the Outstanding Growth Award winner and (mumbles) Technology as the Emerging Growth winner, but really quickly, what makes ACG SV worth your time? >> So ACG honestly is a fantastic organization and you know, living in the Bay Area, there are many organizations, there are many events that are always going on, you know. ACG has been a place where I've seen it's a very, very, very, very diverse organization, of course I still wish there were more females, you know, but it's a very diverse organization, people of all ages, people from different walks of life, from different kinds of companies, you know, and people are very, very collaborative and help each other to do business. I've become personal friends with many of them, but the main thing is, you know, you come here, if you're new to the Valley especially, whether as a company or as an individual, this is one of the best places to come to because it's not too large, it's not too small, it has the right number of people, and it helps you quickly on board. They'll introduce you to people, introduce you to events, they give you what you need to kind of get started. So to me it's like, when I joined, I joined before I was on the board, almost, I don't know, seven or eight years ago, and I've seen this whole thing transform and it's just an excellent, supportive, the people are very open-minded, great ideas, and it's just an excellent organization, love it. So it's worth my time, you know, to take the extra hours, and I would love to see it get even bigger and more diverse and more interesting. >> Well it sounds like, I love how you kind of described ACG SV as being that Goldilocks type of organization, not too big, not too small, just right, but we thank you so much. I wish we had more time to talk, as a female in technology, but we'll have to have you back at the studio on The Cube! >> Thank you so much. >> Thank you so much for your time. For The Cube, I am Lisa Martin. Thanks for watching. (music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, welcome back to the cubes. Live coverage here for eight of us. Reinvent 2020. Virtual normally were on the show floor getting all of the interviews and talking about the top newsmakers and we have one of them here on the Cube were remote. I'm John for your host of the Cube. George Ellis Eros, GM and director of product manager for AWS. Talking about Wavelength George. Welcome to the remote Cube Cube. Virtual. Thanks for coming on. >>Good to be here. Thanks for having a John >>Eso Andy's Kino. One of the highlights last year, I pointed out that the five g thing is gonna be huge with the L A Wavelength Metro thing going on this year. Same thing. Mawr Proofpoint S'more expansion. Take us through what was announced this year. What's the big update on wavelength? >>Yes, so John Wavelength essentially brings a W services at the edge of the five G network, allowing our AWS customers and developers to reach their own end users and devices. Five devices with very low latency enabling a number off emerging applications ranging from industrial automation and I O. T. All the way to weigh AR VR smart cities, connected vehicles and much more this year we announced earlier in the year the general availability of wavelength in two locations one in the Bay Area and one in the Boston area. And since then we've seen we've been growing with Verizon or five D partner in the U. S. And and increasing that coverage in multiple off the larger U. S cities, including Miami and D. C in New York. And we launched Las Vegas yesterday at Andy's keynote with Verizon. We also announced that we are going toe to have a global footprint with K d D I in Japan launching a wavelength in Tokyo with SK detail SK Telecom in in South Korea or launching indigestion and with Vodafone in London >>so significant its expansion. Um, we used to call these points of presence back in the old days. I don't know what you call them now. I guess they're just zones like you calling them zones, but this really is gonna be a critical edge network, part of the edge, whether it's stadiums, metro area things and the density and the group is awesome. And everyone loves at about five gs. More of a business at less consumer. When you think about it, what has been some of the response as you guys had deployed mawr, What's the feedback? Um, can you take us through what the response has been? What's it been like? What have been some of the observations? >>Yeah, customers air really excited with the promise of five G and really excited to get their hands on these new capabilities that we're offering. Um, And they're telling us, you know, some consistent feedback that we're getting is that they're telling us that they love that they can use the same A W s, a P I S and tools and services that they used today in the region to get their hands on this new capabilities. So that's being pretty pretty consistent. Feedback these off use and the you know, Sometimes customers tell us that within a day they are able to deploy their applications in web. So that's a that's pretty consistent there. We've seen customers across a number of areas arranging, you know, from from manufacturing to healthcare to a ar and VR and broadcasting and live streaming all the way to smart cities and and connected vehicles. So a number of customers in these areas are using wavelength. Some of my favorite you know, examples are in in actually connected vehicles where you really can see that future materialized. You get, you know, customers like LG that are building the completely secularized vehicle, tow everything platform, and customers like safari that allow multiple devices to do, you know, talkto the Waveland, the closest Waveland Zone process. All of those device data streams at the edge. And then, um, it back. You know messages to the drivers, like for emergency situations, or even construct full dynamic maps for consumption off the off the vehicle themselves. >>I mean, it's absolutely awesome. And, you know, one of things that someone Dave Brown yesterday around the C two and the trend with smaller compute. You have the compute relationship at the edge to moving back and forth so I can see those dots connecting and looking forward to see how that plays out. Sure, and it will enable more capabilities. I do want to get your your thoughts, or you could just for the audience and our perspective just define the difference between wavelength and local zones because we know what regions are. Amazon regions are well understood all around the world. But now you have this new concept called locals owns part of wavelength, not part of wavelengths. Are they different technology? Can you just explain? Take him in to exclaim wavelength versus local zones how they work together? >>Yeah, So let me take a step back at AWS. Basically, what we're trying to do is we're trying to enable our customers to reach their end users with low latency and great performance, wherever those end users are and whatever network they're they're using to get connected, whether that's the five g mobile network with the Internet or in I o t Network. So we have a number of products that help our customers do that. And we expect, like, in months off other areas of the AWS platform, that customers are gonna pick and twos and mix and match and combine some of these products toe master use case. So when you're talking about wavelength and local zones, wavelength is about five g. There is obviously a lot off excitement as you said yourself about five g about the promise off those higher throughput. They're Lowell agencies. You know, the large number of devices supported and with wavelengths were enabling our customers toe to make the most of that. You know, of the five G technology and toe work on these emerging new use cases and applications that we talked about When it comes to local zones, we're talking more about extending AWS out two more locations. So if you think about you mentioned AWS regions, we have 24 regions in another five coming. Those are worldwide and enabled most of our customers to run their workloads. You know all of their workloads with low latency and adequate performance across the world. But we are hearing from customers that they want AWS in more locations. So local zones basically bring a W S extend those regions to more locations by bringing a W s closer to population I t and industrial centers. You know, l A is a great example of that. We launched the lay last year toe to local zones in L. A and toe toe a mainly at the media and entertainment customers that are, you know, in the L. A Metro, and we've seen customers like Netflix, for example, moving their artist workstations to the local zones. If they were to move that somewhere, you know, to the cloud somewhere further out the Laden's, he might have been too much for their ass artists work clothes and having some local AWS in the L. A. Metro allows them to finally move those workstation to the cloud while preserving that user experience. You know, interacting with the workstations that's happened. The cloud. >>So just like in conceptualizing is local zone, like a base station is in the metro point of physical location. Is it outpost on steroids? Been trying to get the feel for what it is >>you can think off regions consisting off availability zones. So these are, you know, data center clusters that deliver AWS services. So a local zone is much like an availability zone. But instead of being co located with the rest of the region, is in another locations that, for example, in L. A. Rather than being, you know, in in Virginia, let's say, um, they are internally. We use the same technology that we use for outpost, I suppose, is another great example of how AWS is getting closer to customers for on premises. Deployments were using much of the same technology that you you probably know as Nitro System and a number of other kind of technology that we've been working on for years, actually, toe make all this possible. >>You know, anyone who's been to a football game or any kind of stadium knows you got a great WiFi signal, but you get terrible bandwidth that is essentially kind of the back hall component for the telecom geeks out there. This is kind of what we're talking about here, right? We're talking about more of an expansionary at that edge on throughput, not just signal. So there's, you know, there's there's a wireless signal, and it's like really conductivity riel functionality for applications. >>Yeah, and many. Many of those use case that we're talking about are about, you know, immersive experiences for for end users. So with five t, you get that increasing throughput, you can get up to 10 GPS. You know, it is much higher with what you get 40. You also get lower latents is, but in order to really get make the most out of five G. You need to have the cloud services closer to the end user. So that's what Wavelength is doing is bringing all of those cloud services closer to the end user and combined with five G delivers on these on these applications. You know, um, a couple of customers are actually doing very, very, very exciting things on immersive application, our own immersive experiences. Um, why be VR is a customer that's working on wavelength today to deliver a full 3 60 video off sports events, and it's like you're there. They basically take all of those video streams. They process them in the waving zone and then put them back down to your to your VR headset. But don't you have seen those? We are headsets there, these bulky, awkward, big things because we can do a lot of the processing now at the edge rather than on the heads of itself. We are envisioning that these headsets will Will will string down to something that's indistinguishable potential from, you know, your glasses, making that user experience much better. >>Yeah, from anything from first responders toe large gatherings of people having immersive experiences, it's only gonna get better. Jorge. Thanks for coming on. The Cuban explaining wavelength graduates on the news and expansion. A lot more cities. Um, what's your take for reinvent while I got you? What's the big take away for you this year? Obviously. Virtual, but what's the big moment for you? >>Well, I think that the big moment for me is that we're continuing to, you know, to deliver for our customers. Obviously, a very difficult year for everyone and being able to, you know, with our help off our customers and our partners deliver on the reinvent promised this year as well. It is really impressed for >>me. All right. Great to have you on. Congratulations on local news. Great to see Andy pumping up wavelength. Ah, lot more work. We'll check in with you throughout the year. A lot to talk about. A lot of societal issues and certainly a lot of a lot of controversy as well as tech for good, great stuff. Thanks for coming. I appreciate it. >>Thanks for having me. Thanks. >>Okay, That's the cube. Virtual. I'm John for your host. Thanks for watching. We'll be back with more coverage from reinvent 2023 weeks of coverage. Walter Wall here in the Cube. Thanks for watching. Yeah,

>> From our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation. >> Hello and welcome to Cube conversations. I'm James Kabila's lead analyst at Wicked Bond. Today we've got an excellent guest. Who's a Cube alumnus? Par excellence. It's your own Haviv who is the founder and CEO of a guajillo. Hello. You're wrong. Welcome in. I think you're you're coming in from Tel Aviv. If I'm not mistaken, >> right? Really? Close the deal of any thanks from my seeing you again. >> Yeah. Nice to see you again. So I'm here in our Palo Alto studios. And so I'm always excited when I can hear your own and meet with your room because he always has something interesting in new to share. But what they're doing in the areas of cloud and serve earless and really time streaming analytics And now, data science. I wasn't aware of how deeply they're involved in the whole data Science pipelines, so ah, your own. This is great to have you. So my first question really is. Can you sketch out? What are the emerging marketplace requirements that USA gua Si are seeing in the convergence of all these spaces? Especially riel time streaming analytics edge computing server lis and data science and A I can you give us a sort of ah broad perspective and outlook on the convergence and really the new opportunities or possibilities that the convergence of those technologies enable for enterprises that are making deep investments. >> Yeah, so I think we were serving dissipated. What's happening now? We just call them different names will probably get into into this discussion in a minute. I think what you see is the traditional analytics and even data scientist Science was starting at sort of a research labs, people exploring cancer, expressing, you know, impact. Whether on, you know, people's moved its era. And now people are trying to make real or a Y from a guy in their assigned, so they have to plug it within business applications. Okay, so it's not just a veil. A scientist Inning the silo, you know, with a bunch of large that he got from his friends, the data engineer in the scan them and Derrickson Namesake runs to the boss and says, You know what? You know, we could have made some money in a year ago. We've done something so that doesn't make a lot of impact on the business, where the impact on the business is happening is when you actually integrate a I in jackpot in recommendation engines in doing predictive analytics on analyzing failures and saving saving failures on, you know, saving people's life. Those kind of use cases. Doctors are the ones that record a tighter integration between the application and the data and algorithms that come from the day I. And that's where we started to think about our platform. Way worked on a real time data, which is where you know, when you're going into more production environment of not fatal accident. Very good, very fast integration with data. And we have this sort of fast computation layer, which was a one micro services, and now everyone talks about micro services. We sort of started with this area, and that is allowing people to build those intelligent application that are integrated into the business applications. And the biggest challenges they see today for organizations is moving from this process of books on research, on data in a historical data and translating that into a visit supplication or into impact on business application. This is where people can spend the year. You know, I've seen the tweet saying with build a machine learning model in, like, a few weeks. And now we've waited eleven months for the product ization. So that artifact, >> Yes, that's what we're seeing it wicked bomb. Which is that A. I is the heart of modern applications in business and the new generation of application developers, in many ways, our data scientists, or have you know, lovers the skills and tools for data science. Now, looking at a glass zeros portfolio, you evolve so rapidly and to address a broader range of use cases I've seen. And you've explained it over the years that in position to go, as well as being a continuous data platform and intelligent edge platform, a surveillance platform. And now I see that you're a bit of a data science workbench or pipeline tooling. Clever. Could you connect these dots here on explain what is a guajillo fully >> role, Earl? Nice mark things for this in technology that we've built, OK, just over the years, you know, people, four years when we started, So we have to call it something else. Well, that I thought that analytic sort of the corporate state of science. And when we said continued analytics, we meant essentially feeding data and running, some of them speaking some results. This is the service opposed to the trend of truth which was dating the lady Throw data in and then you run the batch that analytic and they're like, Do you have some insight? So continue statistics was served a term that we've came up with a B, not the basket. You know, describe that you're essentially thinking, needing from different forces crunching it, Prue algorithms and generating triggers and actions are responsible user requests. Okay on that will serve a pretty unique and serve the fireman here in this industry even before they called it streaming or in a real time, data science or whatever. Now, if you look at our architecture are architecture, as I explained before, is comprised of three components. The first event is a real time, full time model database. You know, you know about it really exceptional in his performance and its other capabilities. The second thing is a pursue miss engine that allows us to essentially inject applications. Various guys, initially we started with application. I sense you do analytics, you know, grouping joining, you know, correlating. And then we start just adding more functions and other things like inference, saying humans recognitions and analysis. It's Arab is we have dysfunction engine. It allows us a lot of flexibility and find the really fast for the engine on a really fast data there endure it, remarkable results and then this return calling this turn this micro assume it's finger serve Ellis who certainly even where have the game of this or service gang. And the third element of our platform is a sense she having a fully manage, passed a platform where a ll those micro services our data and it threw a self service into face surfing over there is a mini cloud. You know, we've recently the last two years we've shifted to working with coronaries versus using our own A proprietary micro spurs does or frustration originally. So we went into all those three major technologies. Now, those pit into different application when they're interesting application. If you think about edge in the engine in serving many clouds, you need variety of data, sources and databases. With you, no problem arose streaming files. Terra. We'LL support all of them when our integrated the platform and then you need to go micro services that developed in the cloud and then just sort of shift into the enforcement point in the edge. And you need for an orchestration there because you want to do suffer upgrades, you need to protect security. So having all the integrated separated an opportunity for us to work with providers of agin, you may have noticed our joint announcement with Google around solution for hedge around retailers and an i O. T. We've made some announcement with Microsoft in the fast. We're going to do some very interesting announcement very soon. We've made some joint that nonsense with Samsung and in video, all around those errands, we continue. It's not that we're limited to EJ just what happens because we have extremely high density data platform, very power of fish and very well integrated. It has a great feat in the India, but it's also the same platform that we sell in. The cloud is a service or we sell two on from customers s so they can run. The same things is in the clouds, which happens to be the fastest, most real time platform on the Advantage service. An essential feature cannot just ignore. >> So you're wrong. Europe. Yeah, Iguazu is a complete cloud, native development and run time platform. Now serve earless in many ways. Seems to be the core of your capability in your platform. New Cleo, which is your technology you've open sourced. It's bill for Prem bays to private clouds. But also it has is extensible to be usable in broader hybrid cloud scenarios. Now, give us a sense for how nuclear and civilised functions become valuable or useful for data science off or for executing services or functions of data of the data science pipeline kick you connect the dots of nuclear and data science and a I from the development standpoint >> church. So So I think you know, the two pillars that we have technology that the most important ones are the data. You know, we have things like twelve batons on our data engine is very high performance and nuclear functions, and also they're very well integrated because usually services stateless. So you know, you you end up. If you want to practice that they have some challenges with service with No, no, you can't. You stay for use cases. You can mount files. You have real time connections to data, so that makes it a lot more interesting than just along the functions. The other thing, with no clothes that is extremely high performance has about two hundred times faster than land. So that means that you can actually go and build things like the stream processing and joins in real time all over practice, their base activities. You can just go and do collectors. We call them those like things. Go fetch information from whether services from routers for the X cybersecurity analysis for all sorts of sensors. So those functions are becoming like, you know, those nanobots technology of off the movies is that you just send them over to go and do things for you, whether it's the daily collection and crunching, whether it's the influencing engines, those things that, for example, get a picture of very put the model, decide what's in the picture, and that this is where we're really comes into play. They nothing important you see now an emergence off a service patterns in data science. So there are many companies that do like mother influencing as a service city what they do, they launch an end point of your eleven point and serve runs the model inside you send the Vector America values and get back in the Americans and their conversion. It's not really different and service it just wait more limited because I don't just want to send a vector off numbers because usually I understand really like a geo location of my cellphone, which are user I D. And I need dysfunction to cross correlated with other information about myself with the location. Then came commendation of which a product they need to buy. So and then those functions also have all sorts of dependency exam on different packages. Different software environment, horribles, build structures, all those. This is really where service technologies are much more suitable now. It's interesting that if you'LL go to Amazon, they have a product called Sage Maker. I'm sure yes, which is dinner, then a science block. Okay, now sage mint for although you would say that's a deal use case for after Onda functions actually don't use Amazon London functions in sage maker, and you ask yourself, Why aren't they using Lambda Stage Maker just telling you, you know you could use Lambda is a blue logic around sage maker. And that's because because London doesn't feed the use case. Okay, because lambda doesn't it is not capable of storing large content and she learning miles could be hundreds of megabytes or Landa is extremely slow. So you cannot do hi concurrency influencing with will land the function so essentially had to create another surveillance and college with a different name. Although if they just would have approved Landa, maybe it was one or a Swiss are So we're looking, We've took it, were taken the other approach We don't have the resources that I have so we created a monster virus Engine one servant attention does batch Frost is saying scream processing, consort, lots of data, even rocketeer services to all the different computation pattern with a single engine. And that's when you started taking all this trend because that's about yeah, we need two version our code. We need to, you know, record all our back into dependencies. And although yes, service doesn't so if we just had to go and tied more into the existing frameworks and you've looked at our frantically product called Tokyo Jupiter, which is essentially a scientist, right, some code in his data's passport book and then in clicks. One command called nuclear Deploy, it automatically compiles, is their science artifact in notebooks, that server and converted into a real hand function that can listen in on your next city. People can listen on streams and keep the scheduled on various timing. It could do magic. So many other things. So, and the interesting point is that if you think about their scientists there, not the farmers, because they should be a scientist on this's means that they actually have a bigger barrier to write in code. So if you serve in this framework that also automates the law daughter scaling the security provisioning of data, the versions of everything in fact fantasies, they just need to focus on writing other them's. It's actually a bigger back for the book. Now, if you just take service into them, Epstein's and they will tell you, Yeah, you know, we know how to explain, Doctor. We know all those things, so they're very their eyes is smaller than the value in the eyes of their scientists. So that's why we're actually seeing this appeal that those those people that essentially focus in life trying math and algorithms and all sorts of those sophisticated things they don't want to deal with. Coding and maintenance are refreshed. And by also doing so by oppression analyzing their cool for service, you can come back to market. You can address calle ability to avoid rewriting of code. All those big challenges the organizations are facing. >> You're gonna have to ask you, that's great. You have the tools to build, uh, help customers build serve Ellis functions for and so forth inside of Jupiter notebooks. And you mentioned Sage Maker, which is in a WS solution, which is up in coming in terms of supporting a full data science tool chain for pipeline development. You know, among teams you have a high profile partnerships with Microsoft and Google and Silver. Do you incorporate or integrator support either of these cloud providers own data science workbench offerings or third party offerings from? There's dozens of others in this space. What are you doing in terms of partnerships in that area? >> Yeah, obviously we don't want to lock us out from any of those, and, you know, if someone already has his work bench that I don't know my customers say they were locking me into your world back in our work when things are really cool because like our Jupiter is connected for real time connections to the database. And yes, serve other cool features that sentir getting like a huge speed boost we have. But that's on A with an within vigna of round Heads and Integration, which reviews are creating a pool of abuse from each of one of the data scientist running on African essentially launch clubs on this full of civilians whose off owning the abuse, which are extremely expensive, is you? No. But what we've done is because of her. The technology beside the actual debate engine is open source. We can accept it essentially just going any sold packages. And we demonstrate that to Google in danger. The others we can essentially got just go and load a bunch of packages into their work match and make it very proposed to what we provide in our manage platform. You know, not with the same performance levels. Well, functionality wise, the same function. >> So how can you name some reference customers that air using a guajillo inside a high performance data science work flows is ah, are you Are there you just testing the waters in that market for your technology? Your technology's already fairly mature. >> That says, I told you before, although you know, sort of changed messaging along the lines. We always did the same thing. So when we were continuous analytics and we've spoken like a year or two ago both some news cases that we Iran like, you know, tell cooperators and running really time, you know, health, a predictive health, monitoring their networks and or killing birds and those kind of things they all use algorithms. You control those those positions. We worked with Brian nailing customers so we can feed a lot of there there in real time maps and do from detection. And another applications are on all those things that we've noticed that all of the use cases that we're working with involved in a science in some cases, by the way, because of sort of politics that with once we've said, we have analytics for continuous analytics, we were serving send into sent into the analytic schools with the organization, which more focused on survey data warehouse because I know the case is still serve. They were saying, and I do. And after the people that build up can serve those data science applications and serve real time. Aye, aye. OK, Ianto. Business applications or more, the development and business people. This is also why we sort of change are our name, because we wanted to make it very clear that we're aren't the carnage is about building a new applications. It's not about the warehousing or faster queries. On a day of Eros is about generating value to the business, if you ask it a specific amplification. And we just announced two weeks in the investment off Samsung in Iguazu, former that essentially has two pillars beyond getting a few million dollars, It says. One thing is that they're adopted. No cure. Is there a service for the internal clouds on the second one is, we're working with them on a bunch of us, Della sighs. Well, use case is one of them was even quoted in enough would make would be There are no I can not say, but says she knows our real business application is really a history of those that involves, you know, in in intercepting data from your sister's customers, doing real time on analytics and responding really quickly. One thing that we've announced it because of youse off nuclear sub picture. We're done with inferior we actually what were pulled their performance. >> You're onto you see if you see a fair number of customers embedding machine learning inside of Realtor time Streaming stream computing back ones. This is the week of Flink forward here in San San Francisco. I I was at the event earlier this week and I I saw the least. They're presenting a fair amount of uptake of ml in sight of stream computing. Do you see that as being a coming meet Mainstream best practice. >> Streaming is still the analytics bucket. OK, because what we're looking for is a weakness which are more interactive, you know, think about like, uh, like a chatterbox or like doing a predictive analytic. It's all about streaming. Streaming is still, you know, it's faster flow data, but it's still, sir has delay the social. It's not responses, you know. It's not the aspect of legacy. Is that pickle in streaming? Okay, the aspect of throughput is is higher on streaming, but not necessarily the response that I think about sparks streaming. You know, it's good at crossing a lot of data. It's definitely not good at three to one on would put spark as a way to respond to user request on the Internet S O. We're doing screaming, and we see that growth. But think where we see the real growth is panic to reel of inches. The ones with the customer logs in and sends a request or working with telcos on scenarios where conditions of LA car, if the on the tracks and they settled all sorts of information are a real time invent train. Then the customer closer says, I need a second box and they could say No, this guy needs to go away to that customer because how many times you've gotten technician coming to your house and said I don't have that more exactly. You know, they have to send a different guy. So they were. How do you impact the business on three pillars of business? Okay, the three pillars are one is essentially improving your china Reducing the risk is essentially reducing your calls. Ask him. The other one is essentially audio, rap or customer from a more successful. So this is around front and application and whether it's box or are doing, you know our thing or those kind of us kisses. And also under you grow your market, which is a together on a recommendation in at this time. So all those fit you if you want, have hey, I incorporated in your business applications. In few years you're probably gonna be dead. I don't see any bits of sustained competition without incorporating so ability to integrate really real data with some customer data and essentially go and react >> changes. Something slightly you mentioned in video as a partner recently, Of course, he announced that few weeks ago. At their event on, they have recently acquired Melon ox, and I believe you used to be with Melon Axe, so I'd like to get your commentary on that acquisition or merger. >> Right? Yes, yes, I was VP Data Center man Ox. Like my last job, I feel good friends off off the Guider, including the CEO and the rest of the team with medicines. And last week I was in Israel's with talk to the media. Kansas. Well, I think it's a great merger if you think about men in Ox Head as sort of the best that breaking and storage technology answer Silicon Side and the video has the best view technologies, man. It's also acquired some compute cheap technologies, and they also very, very nice. Photonics technologies and men are today's being by all the club providers. Remiss Troll was essentially only those technical engagement would like the seizures and you know the rest of the gas. So now VP running with the computation engine in and minerals coming, we serve the rest of the pieces were our storage and make them a very strong player. And I think it's our threatens intel because think about it until they haven't really managed to high speed networking recently. They haven't really managed to come with Jiffy use at your combat and big technology, and so I think that makes a video, sort of Ah, pretty. You know, vendor and suspect. >> And another question is not related to that. But you're in Tel Aviv, Israel. And of course, Israel is famous for the start ups in the areas of machine learning. And so, especially with a focus on cyber security of the Israel, is like near the top of the world in terms of just the amount of brainpower focused on cyber security there. What are the hot ML machine? Learning related developments or innovations you see, coming out of Israel recently related to cybersecurity and distributed cloud environments, anything in terms of just basic are indeed technology that we should all be aware of that will be finding its way into mainstream Cloud and Cooper Netease and civilised environments. Going forward, your thoughts. >> Yes, I think there are different areas, you know, The guys in Israel also look at what happens in sort of the U. S. And their place in all the different things. I think with what's unique about us is a small country is always trying to think outside of the box because we know we cannot compete in a very large market. It would not have innovation. So that's what triggers this ten of innovation part because of all this tippy expects in the country. And also there's a lot of cyber, you know, it's time. I think I've seen one cool startup. There's also backed by our VC selling. Serve, uh, think about like face un recognition, critical technology off sent you a picture and make it such that you machine learning will not be able to recognize Recognize that, you know, sort of out of the cyber attack for image recognition. So that's something pretty unique that I've heard. But there are other starts working on all the aspects on their ops and information in our animal and also cyber automated cyber security and hope. Curious aspect. >> Right, Right. Thank you very much. Your own. This has been an excellent conversation, and we've really enjoyed hearing your comments. And Iguazu. It was a great company. Quite quite an innovator is always a pleasure to have you on the Cube. With that, I'm going to sign off. This is James Kabila's with wicked bond with your own haviv on dh er we bid You all have a good day. >> Thank you.