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AI has the potential to profoundly change our lives with Dell Technologies. AI is easy to adopt, easy to manage and easy to scale. And there's nothing artificial about that. Yeah, yeah, from >>the Cube Studios in Palo Alto and Boston >>connecting with >>thought leaders all around the world. This is a cube conversation. Hi, I'm Stew Minimum. And welcome to this special launch with our friends at Dell Technologies. We're gonna be talking about AI and the reality of making artificial intelligence real happy to welcome to the program. Two of our Cube alumni Rob, depending 90. He's the senior vice president of server product management and very Pellegrino vice president, data centric workloads and solutions in high performance computing, both with Dell Technologies. Thank you both for joining thanks to you. So you know, is the industry we watch? You know, the AI has been this huge buzz word, but one of things I've actually liked about one of the differences about what I see when I listen to the vendor community talking about AI versus what I saw too much in the big data world is you know, it used to be, you know Oh, there was the opportunity. And data is so important. Yes, that's really But it was. It was a very wonky conversation. And the promise and the translation of what has been to the real world didn't necessarily always connect and We saw many of the big data solutions, you know, failed over time with AI on. And I've seen this in meetings from Dell talking about, you know, the business outcomes in general overall in i t. But you know how ai is helping make things real. So maybe we can start there for another product announcements and things we're gonna get into. But Robbie Interior talk to us a little bit about you know, the customers that you've been seeing in the impact that AI is having on their business. >>Sure, Teoh, I'll take us a job in it. A couple of things. For example, if you start looking at, uh, you know, the autonomous vehicles industry of the manufacturing industry where people are building better tools for anything they need to do on their manufacturing both. For example, uh, this is a good example of where that honors makers and stuff you've got Xeon ut It's actually a world war balcony. Now it is using our whole product suite right from the hardware and software to do multiple iterations off, ensuring that the software and the hardware come together pretty seamlessly and more importantly, ingesting, you know, probably tens of petabytes of data to ensure that we've got the right. They're training and gardens in place. So that's a great example of how we are helping some of our customers today in ensuring that we can really meet is really in terms of moving away from just a morning scenario in something that customers are able to use like today. >>Well, if I can have one more, Ah Yanai, one of our core and more partners than just customers in Italy in the energy sector have been been really, really driving innovation with us. We just deployed a pretty large 8000 accelerator cluster with them, which is the largest commercial cluster in the world. And where they're focusing on is the digital transformation and the development of energy sources. And it's really important not be an age. You know, the plan. It's not getting younger, and we have to be really careful about the type of energies that we utilize to do what we do every day on they put a lot of innovation. We've helped set up the right solution for them, and we'll talk some more about what they've done with that cluster. Later, during our chat, but it is one of the example that is tangible with the appointment that is being used to help there. >>Great. Well, we love starting with some of the customer stories. Really glad we're gonna be able to share some of those, you know, actual here from some of the customers a little bit later in this launch. But, Robbie, you know, maybe give us a little bit as to what you're hearing from customers. You know, the overall climate in AI. You know, obviously you know, so many challenges facing, you know, people today. But you know, specifically around ai, what are some of the hurdles that they might need to overcome Be able to make ai. Really? >>I think the two important pieces I can choose to number one as much as we talk about AI machine learning. One of the biggest challenges that customers have today is ensuring that they have the right amount and the right quality of data to go out and do the analytics percent. Because if you don't do it, it's giggle garbage in garbage out. So the one of the biggest challenges our customers have today is ensuring that they have the most pristine data to go back on, and that takes quite a bit of an effort. Number two. A lot of times, I think one of the challenges they also have is having the right skill set to go out and have the execution phase of the AI pod. You know, work done. And I think those are the two big challenges we hear off. And that doesn't seem to be changing in the very near term, given the very fact that nothing Forbes recently had an article that said that less than 15% off, our customers probably are using AI machine learning today so that talks to the challenges and the opportunities ahead for me. All right, >>So, Ravi, give us the news. Tell us the updates from Dell Technologies how you're helping customers with AI today, >>going back to one of the challenges, as I mentioned, which is not having the right skin set. One of the things we are doing at Dell Technologies is making sure that we provide them not just the product but also the ready solutions that we're working with. For example, Tier and his team. We're also working on validated and things are called reference architectures. The whole idea behind this is we want to take the guesswork out for our customers and actually go ahead and destroying things that we have already tested to ensure that the integration is right. There's rightsizing attributes, so they know exactly the kind of a product that would pick up our not worry about me in time and the resources needed you get to that particular location. So those are probably the two of the biggest things we're doing to help our customers make the right decision and execute seamlessly and on time. >>Excellent. So teary, maybe give us a little bit of a broader look as to, you know, Dell's part participation in the overall ecosystem when it comes to what's happening in AI on and you know why is this a unique time for what's happening in the in the industry? >>Yeah, I mean, I think we all live it. I mean, I'm right here in my home, and I'm trying to ensure that the business continues to operate, and it's important to make sure that we're also there for our customers, right? The fight against covered 19 is eyes changing what's happening around the quarantines, etcetera. So Dell, as a participant not only in the AI the world that we live in on enabling AI is also a participant in all of the community's s. So we've recently joined the covered 19 High Performance Computing Consortium on. We also made a lot of resources available to researchers and scientists leveraging AI in order to make progress towards you're and potentially the vaccine against Corbyn. 19 examples are we have our own supercomputers in the lab here in Austin, Texas, and we've given access to some of our partners. T. Gen. Is one example. The beginning of our chat I mentioned and I So not only did they have barely deport the cluster with us earlier this year that could 19 started hitting, so they've done what's the right thing to do for community and humanity is they made the resource available to scientists in Europe on tack just down the road here, which had the largest I can't make supercomputer that we deployed with them to. Ai's doing exactly the same thing. So this is one of the real examples that are very timely, and it's it's it's happening right now we hadn't planned for it. A booth there with our customers, the other pieces. This is probably going to be a trend, but healthcare is going through and version of data you mentioned in the beginning. You're talking about 2.3000 exabytes, about 3000 times the content of the Library of Congress. It's incredible, and that data is useless. I mean, it's great we can We can put that on our great ice on storage, but you can also see it as an opportunity to get business value out of it. That's going to be we're a lot more resource is with AI so a lot happening here. That's that's really if I can get into more of the science of it because it's healthcare, because it's the industry we see now that our family members at the M. Ware, part of the Dell Technologies Portfolio, are getting even more relevance in the discussion. The industry is based on virtualization, and the M ware is the number one virtualization solution for the industry. So now we're trying to weave in the reality in the I T environment with the new nodes of AI and data science and HPC. So you will see the VM Ware just added kubernetes control plane. This fear Andi were leveraging that to have a very flexible environment On one side, we can do some data science on the other side. We can go back to running some enterprise class hardware class software on top of it. So this is is great. And we're capitalizing on it with validates solutions, validated design on. And I think that's going to be adding a lot of ah power in the hands of our customers and always based on their feedback. And they asked back, >>Yeah, I may ask you just to build on that interesting comment that you made on we're actually looking at very shortly will be talking about how we're gonna have the ability to, for example, read or V Sphere and Allah servers begin. That essentially means that we're going to cut down the time our customers need to go ahead and deploy on their sites. >>Yeah, excellent. Definitely been, you know, very strong feedback from the community. We did videos around some of the B sphere seven launch, you know, theory. You know, we actually had done an interview with you. Ah, while back at your big lab, Jeff Frick. Otto, See the supercomputers behind what you were doing. Maybe bring us in a little bit inside as who? You know, some of the new pieces that help enable AI. You know, it often gets lost on the industry. You know, it's like, Oh, yeah, well, we've got the best hardware to accelerate or enable these kind of workloads. So, you know, bring us in its But what, You know, the engineering solution sets that are helping toe make this a reality >>of today. Yeah, and truly still you've been there. You've seen the engineers in the lab, and that's more than AI being real. That that is double real because we spend a lot of time analyzing workloads customer needs. We have a lot of PhD engineers in there, and what we're working on right now is kind of the next wave of HPC enablement Azaz. We all know the consumption model or the way that we want to have access to resources is evolving from something that is directly in front of us. 1 to 1 ratio to when virtualization became more prevalent. We had a one to many ratio on genes historically have been allocated on a per user. Or sometimes it is study modified view to have more than one user GP. But with the addition of big confusion to the VM our portfolio and be treated not being part of these fear. We're building up a GPU as a service solutions through a VM ware validated design that we are launching, and that's gonna give them flexibility. And the key here is flexibility. We have the ability, as you know, with the VM Ware environment, to bring in also some security, some flexibility through moving the workloads. And let's be honest with some ties into cloud models on, we have our own set of partners. We all know that the big players in the industry to But that's all about flexibility and giving our customers what they need and what they expect in the world. But really, >>Yeah, Ravi, I guess that brings us to ah, you know, one of the key pieces we need to look at here is how do we manage across all of these environments? Uh, and you know, how does AI fit into this whole discussion between what Dell and VM ware doing things like v Sphere, you know, put pulling in new workloads >>stew, actually a couple of things. So there's really nothing artificial about the real intelligence that comes through with all that foolish intelligence we're working out. And so one of the crucial things I think we need to, you know, ensure that we talk about is it's not just about the fact that it's a problem. So here are our stories there, but I think the crucial thing is we're looking at it from an end to end perspective from everything from ensuring that we have direct workstations, right servers, the storage, making sure that is well protected and all the way to working with an ecosystem of software renders. So first and foremost, that's the whole integration piece, making sure they realized people system. But more importantly, it's also ensuring that we help our customers by taking the guess work out again. I can't emphasize the fact that there are customers who are looking at different aliens off entry, for example, somebody will be looking at an F G. A. Everybody looking at GP use. API is probably, as you know, are great because they're price points and normal. Or should I say that our needs our lot lesser than the GP use? But on the flip side, there's a need for them to have a set of folks who can actually program right. It is why it's called the no programming programmable gate arrays of Saas fee programmable. My point being in all this, it's important that we actually provide dried end to end perspective, making sure that we're able to show the integration, show the value and also provide the options, because it's really not a cookie cutter approach of where you can take a particular solution and think that it will put the needs of every single customer. He doesn't even happen in the same industry, for that matter. So the flexibility that we provide all the way to the services is truly our attempt. At Dell Technologies, you get the entire gamut of solutions available for the customer to go out and pick and choose what says their needs the best. >>Alright, well, Ravi interior Thank you so much for the update. So we're gonna turn it over to actually hear from some of your customers. Talk about the power of ai. You're from their viewpoint, how real these solutions are becoming. Love the plan words there about, you know, enabling really artificial intelligence. Thanks so much for joining after the customers looking forward to the VM Ware discussion, we want to >>put robots into the world's dullest, deadliest and dirtiest jobs. We think that if we can have machines doing the work that put people at risk than we can allow people to do better work. Dell Technologies is the foundation for a lot of the >>work that we've done here. Every single piece of software that we developed is simulated dozens >>or hundreds of thousands of times. And having reliable compute infrastructure is critical for this. Yeah, yeah, A lot of technology has >>matured to actually do something really useful that can be used by non >>experts. We try to predict one system fails. We try to predict the >>business impatience things into images. On the end of the day, it's that >>now we have machines that learn how to speak a language from from zero. Yeah, everything >>we do really, at Epsilon centered around data and our ability >>to get the right message to >>the right person at the right >>time. We apply machine learning and artificial intelligence. So in real time you can adjust those campaigns to ensure that you're getting the most optimized message theme. >>It is a joint venture between Well, cars on the Amir are your progress is automated driving on Advanced Driver Assistance Systems Centre is really based on safety on how we can actually make lives better for you. Typically gets warned on distracted in cars. If you can take those kind of situations away, it will bring the accidents down about 70 to 80%. So what I appreciate it with Dell Technologies is the overall solution that they have to live in being able to deliver the full package. That has been a major differentiator compared to your competitors. >>Yeah. Yeah, alright, welcome back to help us dig into this discussion and happy to welcome to the program Chris Facade. He is the senior vice president and general manager of the B sphere business and just Simon, chief technologist for the High performance computing group, both of them with VM ware. Gentlemen, thanks so much for joining. Thank >>you for having us. >>All right, Krish. When vm Ware made the bit fusion acquisition. Everybody was looking the You know what this will do for space Force? GPU is we're talking about things like AI and ML. So bring us up to speed. As to you know, the news today is the what being worth doing with fusion. Yeah. >>Today we have a big announcement. I'm excited to announce that, you know, we're taking the next big step in the AI ML and more than application strategy. With the launch off bit fusion, we're just now being fully integrated with VCF. They're in black home, and we'll be releasing this very shortly to the market. As you said when we acquire institution A year ago, we had a showcase that's capable days as part of the animal event. And at that time we laid out a strategy that part of our institution as the cornerstone off our capabilities in the black home in the Iot space. Since then, we have had many customers take a look at the technology and we have had feedback from them as well as from partners and analysts. And the feedback has been tremendous. >>Excellent. Well, Chris, what does this then mean for customers? You know What's the value proposition that diffusion brings the VC? Yeah, >>if you look at our customers, they are in the midst of a big ah journey in digital transformation. And basically, what that means is customers are building a ton of applications and most of those applications some kind of data analytics or machine learning embedded in it. And what this is doing is that in the harbor and infrastructure industry, this is driving a lot of innovation. So you see the advent off a lot off specialized? Absolutely. There's custom a six FPs. And of course, the views being used to accelerate the special algorithms that these AI ml type applications need. And unfortunately, customer environment. Most of these specialized accelerators uh um bare metal kind of set up, but they're not taking advantage off optimization and everything that it brings to that. Also, with fusion launched today, we are essentially doing the accelerator space. What we need to compute several years ago and that is essentially bringing organization to the accelerators. But we take it one step further, which is, you know, we use the customers the ability to pull these accelerators and essentially going to be couple it from the server so you can have a pool of these accelerators sitting in the network. And customers are able to then target their workloads and share the accelerators get better utilization by a lot of past improvements and, in essence, have a smaller pool that they can use for a whole bunch of different applications across the enterprise. That is a huge angle for our customers. And that's the tremendous positive feedback that we get getting both from customers as well. >>Excellent. Well, I'm glad we've got Josh here to dig into some of the thesis before we get to you. They got Chris. Uh, part of this announcement is the partnership of VM Ware in Dell. So tell us about what the partnership is in the solutions for for this long. Yeah. >>We have been working with the Dell in the in the AI and ML space for a long time. We have ah, good partnership there. This just takes the partnership to the next level and we will have ah, execution solution. Support in some of the key. I am el targeted words like the sea for 1 40 the r 7 40 Those are the centers that would be partnering with them on and providing solutions. >>Excellent. Eso John. You know, we've watched for a long time. You know, various technologies. Oh, it's not a fit for virtualized environment. And then, you know, VM Ware does does what it does. Make sure you know, performance is there. And make sure all the options there bring us inside a little bit. You know what this solution means for leveraging GPS? Yeah. So actually, before I before us, answer that question. Let me say that the the fusion acquisition and the diffusion technology fits into a larger strategy at VM Ware around AI and ML. That I think matches pretty nicely the overall Dell strategy as well, in the sense that we are really focused on delivering AI ml capabilities or the ability for our customers to run their am ai and ml workloads from edge before the cloud. And that means running it on CPU or running it on hardware accelerators like like G fuse. Whatever is really required by the customer in this specific case, we're quite excited about using technology as it really allows us. As Chris was describing to extend our capabilities especially in the deep learning space where GPU accelerators are critically important. And so what this technology really brings to the table is the ability to, as Chris was outlining, to pull those resources those hardware resource together and then allow organizations to drive up the utilization of those GP Resource is through that pooling and also increase the degree of sharing that we support that supported for the customer. Okay, Jeff, take us in a little bit further as how you know the mechanisms of diffusion work. Sure, Yeah, that's a great question. So think of it this way. There there is a client component that we're using a server component. The server component is running on a machine that actually has the physical GPU is installed in it. The client machine, which is running the bit fusion client software, is where the user of the data scientist is actually running their machine machine learning application. But there's no GPU actually in that host. And what is happening with fusion technology is that it is essentially intercepting the cuda calls that are being made by that machine learning app, patience and promoting those protocols over to the bit fusion server and then injecting them into the local GPU on the server. So it's actually, you know, we call it into a position in the ability that remote these protocols, but it's actually much more sophisticated than that. There are a lot of underlying capabilities that are being deployed in terms of optimization who takes maximum advantage of the the networking link that sits between the client machine and the server machine. But given all of that, once we've done it with diffusion, it's now possible for the data scientist. Either consume multiple GP use for single GPU use or even fractional defuse across that Internet using the using technology. Okay, maybe it would help illustrate some of these technologies. If you got a couple of customers, Sure, so one example would be a retail customer. I'm thinking of who is. Actually it's ah, grocery chain. That is the flowing, ah, large number of video cameras into their to their stores in order to do things like, um, watch for pilfering, uh, identify when storage store shelves could be restocked and even looking for cases where, for example, maybe a customer has fallen down in denial on someone needs to go and help those multiple video streams and then multiple app patients that are being run that part are consuming the data from those video streams and doing analytics and ml on them would be perfectly suited for this type of environment where you would like to be ableto have these multiple independent applications running but having them be able to efficiently share the hardware resources of the GP use. Another example would be retailers who are deploying ml Howard Check out registers who helped reduce fraud customers who are buying, buying things with, uh, fake barcodes, for example. So in that case, you would not necessarily want to employ a single dedicated GPU for every single check out line. Instead, what you would prefer to do is have a full set of resource. Is that each inference operation that's occurring within each one of those check out lines could then consume collectively. That would be two examples of the use of this kind of pull in technology. Okay, great. So, Josh, a lot last question for you is this technology is this only for use and anything else. You can give us a little bit of a look forward to as to what we should be expecting from the big fusion technology. Yeah. So currently, the target is specifically NVIDIA GPU use with Cuda. The team, actually even prior to acquisition, had done some work on enablement of PJs and also had done some work on open CL, which is more open standard for a device that so what you will see over time is an expansion of the diffusion capabilities to embrace devices like PJs. The domain specific a six that first was referring to earlier will roll out over time. But we are starting with the NVIDIA GPU, which totally makes sense, since that is the primary hardware acceleration and for deep learning currently excellent. Well, John and Chris, thank you so much for the updates to the audience. If you're watching this live, please throwing the crowd chat and ask your questions. This faith, If you're watching this on demand, you can also go to crowdchat dot net slash make ai really to be able to see the conversation that we had. Thanks so much for joining. >>Thank you very much. >>Thank you. Managing your data center requires around the clock. Attention Dell, EMC open manage mobile enables I t administrators to monitor data center issues and respond rapidly toe unexpected events anytime, anywhere. Open Manage Mobile provides a wealth of features within a comprehensive user interface, including >>server configuration, push notifications, remote desktop augmented reality and more. The latest release features an updated Our interface Power and Thermal Policy Review. Emergency Power Reduction, an internal storage monitoring download Open Manage Mobile today.

>> Live from Orlando, Florida It's the que covering accelerate nineteen. Brought to you by important >> Welcome back to the Cube. Live from Orlando, Florida at Fortinet Accelerate twenty ninety nine. Lisa Martin Joining and welcoming to the queue for the first time, the CEO and president of Novy Flow. Dominique Jordan. Dominic. Great to have you joining on the Cube at accelerate. So here we are in Orlando, talking about all things cyber security. I just came from the keynote session where Fortinet was talking about how much they're innovating. What? How they're leading from a competitive perspective. What customers air saying why their security fabric is so differentiated? No, the flow is one of their security fabric ready partners. But before we talk about that, why don't you take a minute or two to describe to our audience who know the flow is and what you guys are doing in cybersecurity? >> Yeah, way We came in a little bit by accident. The cyber security. We we've been founded seven years ago, and the idea was to create the very programmable networks. It's very much in line with what we heard today on the keynote, and we became a technology leader in that field as the and software defined networking. And three, four years ago, customers started to use our product, obviously for cybersecurity application. We didn't even know about that. They don't necessarily tell us, and we spend a bit more focus into it. And over time we started to work with fortunate, for example. And now we have a developing. Is Greg relationship great solutions? Also for the for the customers. >> So one of the things that we understand from Fortinet and from all of the conversations that the Cube has globally is is that digital transformation is fundamental to every business to compete right. But as is secure transformation and security transformation, very challenging to do as businesses. And you think of any industry, financial services, retail, consumer packaged goods. As they expand digitally, so does the attack surface. So one of the things that fourteen it talks about is it's not enough anymore to have these point solutions pointed at different, you know, on Prem Cloud edge that the entire infrastructure as it's changing and they attacked services expanding has got to be protected more from an integrated perspective. This notion of the of the security fabric. Talk to us about a fabric ready partnership. What that means to know that though I know that's only in the last six months or so. So walk us through what you did to become a fabric ready partner and what it is that you in forging that are seeing in the market as challenges that you're helping to results. >> Yeah, what we see. Actually, I like to decide the defined that as a battlefield, the attacks are being waged, really, and and the band we feel is the networks of those carriers. There was a government agencies, large enterprise, etcetera, and those those companies are not really taking advantage of their position because, in fact, with the right network fabric the right tools to be able to react, they could actually be very much more powerful. So this is where we are working with forty nine to equip those customers with solutions that are much more agile, more programmable because the network is also evolving. It's not only that the attacks are broader, they also changing the nature of it is changing, and the fact that we came from a background of working at the edge of the networks mostly. Well, I wouldn't mention that before we deployed. Typically at the large tier one carriers all around the world are mentioned. A few tell Strike group, wait deployed at the Hutchison Group Young law, etcetera. And also a two of these five eyes. So government agencies that are engage in fighting these attacks. So So we come with a background of working in a decentralized approach anyway, So it was a very natural evolution. Work was done with Fortinet so far. So what we built so far together we built some integrated solutions s So far, we have two solutions that we are demonstrating two customers. The first one is to allow the large. It tends to be the larger customer fortunate that are making the transition from a in existing appliance to virtual eyes solutions. That's an area where we are very effective at helping them to scale. And those would be for customers that would have say, hundred gig of traffic or more. So we're fortunate we built a and undermanned solution. It's an integrated solution that enables those carriers to are. Those customers could be other kind of customers to gradually grow the number of the EMS that are used in real time for doing whatever Sabbath security job they have to do. And if they the demand comes down, these v EMS were released in the customer data centers. To do some other jobs like this is one of the products that we built together, and we are demonstrating. The second one is a. A feature of that is that we can process about the way this is Ah is able to scale all the way up to six point five terra bits per second. I'Ll repeat that six point five terror bits per second. This is a unheard of and this is, I think one of the interests of Fortinet is working with no visible. We already have developed not really the metal ring system, but all the O. N m features that you demand as a customer to be deployed in the real world. So so that's that. That's the base on. The second option is that we developed is a carry Great Nat again. Same idea. We can scale the Terra great net analysis up to one point six terabit per second. Former, very powerful. They're powerful solutions to meet this this raising the man which you talked about? They say this literally a wave of attacks coming more and more. >> So you mentioned some customers by name. Telstra, for example. CEO to CEO conversations tells, has been around for a long time as the organization expands digitally. And we talked about a minute ago as this the attack surface. What are some of the conversations that you're having with the scene? The C suite about security? It's not just talking to, you know, network security admits. Right? What are those conversations that you're having with the CEO in the C suite that are where they're saying these are my business problems? Dominic, help us solve these problems. >> Well, it comes to two words, basically its scale and are slow flexibility. It comes to that simple. Is this so they are struggling to see how they can cope with the especially the ones that are virtual izing because you end up. Imagine the model is that you go from a very powerful appliance and once you virtual eyes this appliance, you might end up with thirty different servers, you know, running in parallel, you have to have low balancers in front of it. That makes for a very complex and very expensive solution. So that's that's are they searching for? How can we reduce the complexity, for example, one of the advantages of our product working side by side with fortunate. Since we worked at six point five terabytes per second, we do some of the pre processing of the traffic before it hits the virtualized solution forty gate, for example. We have built some blacklist white list we can do also the load balancing. No need to install some additional law balancing can have. That is a kind of a black box I get that does all the required feature to increase the scaling off those those combined solution and the second, the second party flexibility. You got to be able to evolves your solution in time as these attacks are revolving now or product is built from bottom up, and it's built on and infrastructure typically white boxes that are running chips that are programmable by us. So the software, the NASA's it's Gone, is complemented by some very easy to use porting layers if you like. So the Fortinet solution could be easily adapted to this platform and And that's how we can achieve this kind of throughput. And in fact, I will tell to your viewers that we already have built live demos of those solutions in the Sofia anti police lab in France. The labs of Fortinet, Where were you? We're doing demos for the for customers of those solutions. >> So I'MA tell Stir, though, and you said speed and flexibility scale rather the other sailor disability scale. Inflexibility. What are some? How does my business? What am I looking to achieve? A. My looking to scale to x number of users X number of regions. How does how is that measured from, say, a Telstra's perspective as a big business impact that Novy Flow and Fortinet are helping to them to achieve? >> Yeah, the It's really all dimensions way have some challenge just by handling the raw volume of traffics. Sometimes some customers are pumping terra bits of traffic between one country and the other, so that's one. And but it's also geography because your attack and come and any anywhere in your network that the periphery or inside your network so you have to be able to in a centralized away once you detect there's an attack you have to be able to respondent and in some time, and that's how we can do with our programmable infrastructure can actually reprogrammed those air routing tables. You can take some mitigation action, for example, some of some of the bad traffic on the blacklist. If you've looked at it, perhaps you could put it on a white list for serpent of time. Don't don't look at it over and over. Just wait, maybe a little bit those kind of off measures to alleviate the load. So, in fact, it's work more intelligently with the raw volume of traffic that comes to you. So this is one of the real advantage of is the end. So after defined networking applied to a cyber security problem, >> what are some of the other industries that you are seeing that have potential to dramatically benefit from suffer to find networking in cyber security? Knowing that he d threat landscape, it is exponentially growing. Yes, we've got tools like a I and Machine Learning, which we'LL talk about later on the program today with respective forty Gar labs, for example. But of course, so do the attackers have access to utilize artificial intelligence to create even smarter attacks. But from your perspective, what are some of the other industries that are really right to take advantage of SGN and cyber security practices? >> You know, I think all industries are moving to data. There's no exception. I was talking to some guy, an interpreter in Montreuil yesterday's doing farming, but it's high tech farming with several earlier. It's all based on a I. It's all based on data, even those industry that the forming industry thing that may be so every industry will rely on data, and that means it will rely on a network, and it all comes down to the network. You gotta be able to build a cyber security network ready fabric from the bottom up so that your network is one of the key features is actually stop the attacks, and that doesn't matter in which industry you are. I think they you can think about the industry where you have vast volumes of data. They will be most likely the first one to take benefit of these. You know, we talk about countries before, and this is one such an industry, but it certainly where you process the vast amount of traffic. So they taking advantage of our technology, for example. And but I think it will be probably most of the industry will be affected by that shorter later >> and hopefully sooner rather than later, considering how fast all of these opportunities, good and bad, are growing. One of the things sporting that talked a lot about this morning during this section and some of the press releases is this growth that they've experienced growing twenty percent year on year from last year one point eight billion in revenue over three hundred eighty five thousand customers. You're one of the fabric ready partners, of which there are fifty seven. So a lot of growth, a lot of potential. What excites you as the head of no be Flo and your recent and developing partnership with Fortinet for twenty nineteen and beyond were gonna latch onto that growth trajectory. >> Absolute well, you know, when you mentioned high volume of traffic that plays to our cards. So the market is actually coming where we are way have our product runs at six for five terabytes per second, and that's today because we have a *** plans to move to twelve Tara bits and so forth. So for us, it's exciting because we feel we have the right scaling platform and the right program ability. So our customers, fortunate customers together with us can start with the existing. They're powerful platform. But should that evolved, they'LL be able to move to a new level of software new capacity gradually over time. So that's very exciting for us. >> But what about some of the announcements that came out this morning? Over three hundred new features added, for example, that's a tremendous amount of innovation since last year's accelerate. >> Yeah, well, the's features needs also have the right, I would say filtered level of data to be able to do it more efficiently. And that's where we commend we're not inside the subway Security company. We are really complimenting the product of forty nine by playing upstream and doing a pre filtering controlled by the policy management of the Fortunate, the equipment but nevertheless taking up some of the load of it so that the equipment could be more efficient. But just as an example, I read in a magazine a couple days ago that Google is building a A two hundred fifty terabyte cable between North America and Europe. Think about that. It's it's mindboggling is three time Library of Congress per second. And those are the kind of volume of data did you see coming so suddenly? Six point five terabytes per second doesn't sound so big, does it? But in fact, that's the world win today, and we're lucky it may be flow. We invested early on in the software layer that runs on top of these extremely powerful white boxes and were taking advantage of it with Fortinet. >> Gotta deliver that scale, that flexibility and his son's more and more like Speed. Dominic, thank you so much for stopping by the Cuban joining me on the program today, talking about Novy float what you're doing with Fortinet and what excites you about the year ahead >> was a pleasure, Liza. Thank you for >> mine as well. I want to thank you for watching the Cube Lisa Martin live on the Cube from Fortinet Accelerate twenty nineteen in Orlando. Thanks for watching