(upbeat music) >> Welcome back to theCUBE's continuous coverage of AWS re:invent 2021. I'm here with my co-host John Furrier and we're running one of the largest, most significant technology events in the history of 2021. Two live sets here in Las Vegas, along with our two studios. And we are absolutely delighted. We're incredibly delighted to welcome a returning alumni. It's not enough to just say that you're an alumni because you have been such a fixture of theCUBE for so many years. Annie Weinberger. And Annie is head of product marketing for applications at AWS. Annie, welcome. >> Thank you so much, it's great to be back. >> It's wonderful to have you back. Let's dive right into it. >> Okay. >> Talk to us about Connect. What does that mean when I say Connect? >> Yes, well, I think if we talk about Amazon Connect, we have to go back to the beginning of the origin story. So, over 10 years ago, when Amazon retail was looking for a solution to manage their customer service and their contact center, we went out and we looked at different solutions and nothing really met our needs. Nothing could kind of provide the scale that we needed at Amazon, or could really be as flexible as we needed to ensure that we're our customer obsession could come through in our customer service. So we built our own solution. And over the years, customers were coming to us and asking, you know, what do you use for your customer service technology? And so we launched Amazon Connect, our omni-channel cloud contact center solution just over four years ago. And it is the one of the fastest growing services at AWS. We have tens of thousands of customers using it today, like Capital One into it, Bank of Omaha, Mutual of Omaha, Best Western, you know, I can go on and on. And they're using it to have over 10 million interactions with customers every day. So it's, you know, growing phenomenally and we just couldn't be more proud to help our customers with their customer service. >> So, yeah. Talk about some of the components that go into that. What are the sort of puzzle pieces that make up AWS Connect? Because obviously connecting with a customer can take a whole bunch of different forms with email, text, voice. >> Yeah >> What's included in that? >> So it's an omni-channel cloud contact center. It provides, you know, any way you want to talk to your customers. There's traditional methods of voice. There's automated ways to connect. So IVRs or interactive voice responses where you call with voice prompts, there's chat, you know. We have Lex Bots that use the same technology that powers Alexa for natural language understanding. And I think customers really like it for a few reasons. One is that unlike kind of other contact center solutions, you can set it up in minutes. You know, American Preparatory Academy had to set up a contact center, they did it in two days. And then it's very, very easy to customize and use. So another example is, you know, when Priceline was going through COVID and they realized their call volume went up 300% overnight, and everybody was just sitting near the queue waiting to talk to an agent. So in 20 minutes, we were able to go in and very easily with a drag and drop interface, customize the ad flow so that people who had a reservation in the next 72 hours were prioritized. So very, very easily. >> You just jumped the gun on me. I was going to ask this because we never boarding that Connect during the pandemic was a huge success. >> Annie: Yes. >> It was many, many examples where people were just located, disrupted by the pandemic. And you guys had tons of traction from government public sector to commercial across the board. Adam Solecki told me in person a couple weeks ago that it was on fire, Connect was on fire. So again, a tailwind, one of those examples with the pandemic, but it highlights this idea or purpose built, ready to go. >> Pre-built the applications. >> Pre-built application. This is a phenomenon. >> It's moving up the stack for AWS. It's very exciting. I think, yeah, we had over 5,000 new contact centers stood up in March and April of 2020 alone. >> Dave: Wow. >> Give it some scale, just go back to the scale piece. Cause this is like, like amazing to stand up a call center like hours, days. Like this is like incredible to, give us some stats on some examples of how fast people were standing up Connect. >> Yeah, I mean, you could stand it up overnight. American Preparatory Academy, as I mentioned did it in two days, we had, you know, this county of Los Angeles did theirs I think at a day. You could go and right now you don't need any technical expertise, even though you have some. >> theCUBE call center, we don't need people calling. >> We had everyone from a Mexican restaurant needed to take to go orders. Cause now it's COVID and they don't have a call. They've been able to set that up, grab a phone number and start taking takeout orders all the way to like capital one, you know, with 40,000 agents that need to move remote overnight. And I think that it's because of that ease to set up, but also the scale and the way that we charge. So, you know, it's AWS consumption-based pricing. You only pay for the interactions with customers. So the barrier to entry is really, really low. You don't have to migrate everything over and buy a bunch of new licenses. You can just stand it up and you're only charged for the interactions with customers. And then if you want to scale down like into it, obviously tax season they're bringing on a lot more agents to handle calls, when those agents aren't really needed for that busy time, you're not paying for those seats. >> You're flex. Take me through the, okay, that's a win, I get that. So home run, great success. Now, the machine learning story is interesting too, because you have the purpose-built platform. There's some customizations that can happen on top of it. So it's not just, here's a general purpose piece of software. People are using some customizations. Take us through the other things. >> Well, the exciting thing is they're not even real customizations because we're AWS, we can leverage the AML services and built pre-built purpose-built features. So there it's embedded and you know, Amazon Connect has been cloud native and AI born since the very beginning. So we've taken a lot of the AI services and built them into you don't need any knowledge. You don't have to know anything about AIML. You can just go in and start leveraging it. And it has huge powerful effects for our customers. We launched three new features this year. One was Amazon Wisdom. That's part of Amazon Connect. And what that does is, you know, if you're an agent and you're on the phone and customer's asking questions, today what they have to do is go in and search across all these different knowledge repositories to find the answer or, you know, how do I issue a refund? You know, we're hearing about this feature that's broken on our product. We're listening behind the scenes to that call and then just automatically providing the knowledge articles as they're on the call saying, this is what you should do, giving them recommendations so we can help the customer much more quickly. >> I love them moving up the stack. Again, a huge fan of Connect. We've highlighting in all of our stories. It's a phenomenon that's translating to other areas, but I want to tie back in where it goes next cause on these keynotes, Adam Solecki's and today was Swami, the conversations about a horizontal data plane. And so as customers would say, use Connect, I might want, if I'm a big customer I want to integrate that into my data because it's voice data, it's call centers, customer data, but I have other databases. So how do you guys look at that integration layer snapping it together with say, a time series database, or maybe a CRM system or retail e-commerce because again, it's all data but it's connected call center. Some may think it's silo, but it's not really siloed. So, I'm a customer. How do I integrate call center? >> Yeah and it's, you know, we have a very strong partner with Salesforce. They're actually a reseller of Connect. So we work with them very, very closely. We have out of the box integrations with Salesforce, with your other, you know, analytics databases with Marketo with other services that you need. I think again, it's one of the benefits of being AWS, it's very extensible, very flexible, and really easy to bring in and share the data that we have with other systems. >> John: So it's not an issue then. >> One of the conversation points that's come up is the, this idea that a large majority of IT Spend is still on premises today. In other words, the AWS total addressable market hasn't been tapped yet. And, you imagine going through the pandemic, someone using AWS Connect to create a virtual call center, now as we hopefully come out and people some return to the office, but now they have the tools to be able to stay at home and be more flexible. Those people, maybe they weren't in the cloud that much before. But to John's point, now you start talking about connecting all of those other data sources. Well, where do those data sources belong? They belong in AWS. So, from your perspective, on the surface it looks like, well, wait, you have these products, but really those are gateways to everything else that AWS does. Is that a fair statement? >> I think it's very, yeah. Absolutely. >> Yeah. >> The big thing I want to get into is okay, we're, I mean, we don't have a lot of people calling for theCUBE but I mean, we wouldn't use the call center, but there's audio involved. Are people more going back to the old school phones for support now with the pandemic? Cause you've mentioned that earlier about the price line, having more- >> I think it's, you know, when we talk to our customers too, it's about letting, letting any customer contact you the way they want to. You know, we, you know, I was talking to Delta, spoke with us yesterday in the business application leadership session. And she said, you know, when someone has a flight issue, I'm sure you can attest to this. I did the same thing. They call, you know, if your, if your flight got canceled or it's looking like it's going to keep pushing, you don't necessarily want to go, you know, use a chat bot or send an email or a text, but there's other use cases where you just want a quick answer, you know, if you contact, I haven't received my product yet, you know, it said it was shipped, I didn't get it. I don't necessarily want to talk to someone, but so, it's just about making that available. >> On the voice side, is it other apps are integrating voice? So what's the interface to call center? Is it, can I integrate like an app voice integrated through the app or it's all phone? >> Because for the agents, there's an agent UI. So they'll see kind of calls that they have in their queue coming up, they'll see the tasks that they have to issue or refund. They'll see the kind of analytics that they have. The knowledge works. There's a supervisor view, so they could go see, you know, we with contact lens for Amazon Connect, we had a launch this, you know, this week, every event around contact lens, it lets you see the trends and sentiment of what's going on the call. It gives them like those training moments. If people aren't using the standard sign-off or the standard greeting on the call, it's a training moment and they can kind of see what's happening and get real-time alerts. If two keywords of a customer saying they cancel into the call, that can get a flag and they can go in and help the agent if necessary. So. >> All kinds of metadata extraction going on in real time. >> Yeah. >> How do you, how would AWS to go through the process of determining what should be bespoke solution hearing versus something that can be productized? And we know there are 475 different kinds of instances. However, you can come up with a package solution where people could pick features and get up and running really quickly. How is that decision making process? >> Well, I mean, you know, 90% at least of what we do build, it comes from what our customers ask for. So we don't, it's the onus is not on us. We listen to our customers, they tell us what they want us to build. Contact center solutions are their line of business applications are purchased by business decision makers and they're used to doing more buying than building. So they wanted to be more out of the box, more like pre-built, but we still are AWS. We make it very, very extensible, very easy to customize, like pull in other data sources. But when we look at how we are going to move up the stack and other areas, we just continue to listen to our customers. >> What's the biggest thing you learned in the pandemic from the team? What's the learnings coming out of the pandemic as hybrid world is upon us? >> I mean, I think a few things with, you know, starting, as you mentioned with the cloud, that the kind of idea of a contact center being a massive building, usually in the middle of America where, you know, people go and they sit and they have conversations. If that was really turned on its head and you can have very secure and accessible solutions through the cloud so that you can work from anywhere. So that was really fantastic to see. >> That's going to be interesting to see moving forward. How that paradigm shifts some centralized call centers, but a lot of this aggregated work that can be done. >> I mean, who knows the, you know, gig economy could be in the contact center, you know. >> Yeah, absolutely >> Yeah >> Maybe get some CUBE hosts, give us theCUBE Connect. We get some CUBE hosts remote. >> That's important work, yeah. >> We need, we need to talk. I got to got my phone number in that list. Annie, it's been fantastic to have you. >> Thank you guys so much. I really appreciate it. >> For John Furrier, this is Dave Nicholson telling you, thank you for joining our continuous coverage of AWS reinvent 2021. Stick with theCUBE for the best in hybrid event coverage. (upbeat music)

>> Innovation Day, brought to you by Comcast. >> Hey, welcome back everybody, Jeff Rick, here with theCube. We're at the Comcast Silicon Valley Innovation Center here in Sunnyvale. It's a very cool space, I think it's grown up over a number of years as they've originated with some acquired companies, and now they got a huge setup here, and we had a big day today talking about customer experience, and really, if you look at the Comcast Voice Remote, and there's a lot of stuff going on that's maybe under the covers, you don't really give Comcast credit for, but they're actually doing a lot. And we're excited to, kind of dive into it a little bit deeper with our next guest, she's Annie Weskesser, she's a CMO of Uniphore. Annie, welcome. >> Yeah, thank you for having me here today. >> Absolutely. So what is Uniphore, for people that aren't familiar with the company. >> So Uniphore is a global leader in conversational service automation, and our vision is to bridge the gap between human and machine, through voice AI and automation. >> That's a mouth full. >> Yes. >> Conversational... >> Service. >> Service. >> Yes. >> So, people talk, and so you guys are heavily involved in voice. So what are the applications where people are using your voice? >> Yep, well primarily our focus is call centers. >> Okay. >> So large enterprises who have massive call centers, where we want to go in and help them with AI and automation, to help better listen to their customers, help better listen to the customers voice, and solve the problems in a faster manner. >> So I don't have to repeat my account number six different times to six different agents. >> Exactly, right. >> Or caught an in IVR cycle, or perhaps the chat that you were talking to doesn't-- The person on the phone, you have to repeat your story. This is something where the AI and automation will actually assist the agent to become a superhero. >> So, it's pretty interesting cause you know there's a lot of conversation about AI and ML, but really you know where it's going to have its impact is applied AI. >> Yes. And you said the company started out really more just on a pure voice, but now you're applying more and more kind of AI in the back end. So what kind of opportunities do you have now beyond just simply being able to do voice conversion?. >> To the first part of your question, the company started at IIT Madras back in 2008. And originally the focus of the company was really centered on voice, voice being the lowest common denominator and in Indie where the languages are 260 you know, potential languages to understand and maybe 25 at the top. We set out really to focus on voice and then realize that customer service was a large market and somewhere we can have a big impact. >> Right, right. So you reckon as you said a 100 different languages. >> A 100 different languages through our platform which is pretty incredible when you think about it. All of the different people calling in to customer service potentially or maybe through a chatbot or a voicebot to get their issues solved. >> And then you integrate in whatever the core system is that the customer services agent are using. >> Yes. >> So what are the types of tips and tricks that the call agent gets by using your guys service? >> So think about it as a platform where the customer can help they agents be more affective agents. So one of the things that call centers struggle with is something called after call work, where agents may spend two to three minutes after a call, summarizing the call. One of the things that our technology does and this is primarily for one of our customers who's a health care client. They said "Wouldn't it be great if we can automate that completely". So we've taken the after call work for one customer client, taken that two to three minutes down to 10 seconds, where that work that the agent would have done is completely summarized and the agent validates it, can correct it if needed and its completely done. So that not only saves the agent time to either pick up more calls and help other customers or it can get them of the phone in a quicker manner to save the call center more money. >> So that's doing more than just simply providing a transcript of the call which is something a different track than actually listening into to provide suggestions is actually taking it to the next level in terms of what categorizing, what type of call, the outcome etc. >> it's actually quite interesting because often times less than 1% of calls are listened to somewhere between 1 and 10% of calls are listened to in calls centers. So we can listen to a 100% of those calls in addition we offer something called that's more along the line of like a live agent coach to where the agent can concentrate on the conversation with the customer which is the primary thing listening to the customer. And our technology will serve you up coaching mechanism in terms of getting to faster resolution for the customer and getting them better insights to be almost a superhero of a agent. >> Right, and I would imagine the accuracy in terms of recording what happened in the call to go back and do the analytics and have a text base search you can do all types of analysis on those calls which was data that was probably just lost before right into (mumbles) >> You're exactly right. I think the accuracy is clearly a lot lower than if you were to have the AI and automation and Machine learning technology there. >> So the other conversation in the sit down that we had earlier today was really about driving a customer centric culture in your own company, not only just enabling it but really building it inside. I wonder if you could share some of the things that you guys have done to help make sure that everybody stays focused on the objective, which is the customer. >> Yip, I think it really starts at the top it starts with the leader of the organization. So we have a CEO whose extremely focused on customer centricity and in fact its our number one core value within the organization. So you see everyone from the CEO down to the rest of the organization completely focused on the customer and their needs. >> What about when the customer doesn't know what they need? What about you know, you bringing a new technology and your inviting a slightly different process or a slightly different change and your saying "Hey, this is actually a better way to keep text and transactions and we actually have a really coach that can help", you know, kind of guy to people. How do you help move customers to a place they don't necessarily know they want to go? >> Yeah, I mean you find that a lot, right. Its not necessarily the technology that we're providing for today but its having the innovation and having the foresight to create a platform that will be future proof. So that's critical, you know, I think that there are a lot of customers who might not know what they need today but that's our job to help them innovate and push the envelope on all things AI and automation. >> Right, I'm just curious to in terms of the impact of your technology on kind of the tracking software for those call center agents, right. So this is a group of people that have to process a lot of calls, you know everything is track to the minute and you know its funny I had a demo with Westworld and you know when Westworld's funny cause we started treating machines like machines and they wanted to be treated like people sometimes I wonder on some of these technologies You know is it enabling them to have more time to be more thoughtful, is it enabling them to have more time to get the better outcomes or is it sometimes perceived as 'oh my gosh you just trying to jam' you know, 'four more calls on in my hour by taking care of my two more minutes that I used to spend wrapping up the call". Do you think about those things and the end customer? >> The time is really the premium, right. So the number one focus is giving people time back and whether that's the customer who's calling in and you want to solve an issue and get them faster resolution or whether that's the agent that wants to free up more time in having the conversation with the customer, solving their problem and then getting of the phone I think that's the most effective way of doing it. >> Final question in terms of voice and the evolution of voice. `Cause I don't think people are really completely tuned in certainly not people old like we are. What are some of the conversations when people finally get, you know, kind of the enabler that voice communications opens up that's not necessarily available with texts or not necessarily available with other types of channels? >> Yeah, I mean I see it most easily in my children they expect everything to be voice enabled and so everything from the Comcast remote that they pick up in our living room everywhere they go when they see a remote they expect everything to be voice enabled. So that's really the future and I think a lot of customer service will be listening to your customers voice however, they want to communicate with you, whatever channel they want to communicate on. >> Great, really cool story Annie and thanks for taking the few minutes and sharing it with us. >> Yeah, thanks for inviting me. >> All right, she's Annie, I'm Jeff your watching theCube with the Comcast CX Experience Innovation day here at the Sillicon Valley Innovation Center. Thanks for watching see you next time.

>>Well, hello everybody. John Walls here and continuing our coverage here at AWS Reinvent 22 on the queue. We continue our segments here in the Global Startup program, which of course is sponsored by AWS Startup Showcase, and with us to talk about any scale as the co-founder and CEO of the company, Robert and n, you are Robert. Good to see you. Thanks for joining us. >>Yeah, great. And thank you. >>You bet. Yeah. Glad to have you aboard here. So let's talk about Annie Scale, first off, for those at home and might not be familiar with what you do. Yeah. Because you've only been around for a short period of time, you're telling me >>Company's about >>Three years now. Three >>Years old, >>Yeah. Yeah. So tell us all about it. Yeah, >>Absolutely. So one of the biggest things happening in computing right now is the proliferation of ai. AI is just spreading throughout every industry has the potential to transform every industry. But the thing about doing AI is that it's incredibly computationally intensive. So if you wanna do do ai, you're not, you're probably not just doing it on your laptop, you're doing it across many machines, many gpu, many compute resources, and that's incredibly hard to do. It requires a lot of software engineering expertise, a lot of infrastructure expertise, a lot of cloud computing expertise to build the software infrastructure and distributed systems to really scale AI across all of the, across the cloud. And to do it in a way where you're really getting value out of ai. And so that is the, the problem statement that AI has tremendous potential. It's incredibly hard to do because of the, the scale required. >>And what we are building at any scale is really trying to make that easy. So trying to get to the point where, as a developer, if you know how to program on your laptop, then if you know how to program saying Python on your laptop, then that's enough, right? Then you can do ai, you can get value out of it, you can scale it, you can build the kinds of, you know, incredibly powerful applica AI applications that companies like Google and, and Facebook and others can build. But you don't have to learn about all of the distributed systems and infrastructure. It just, you know, we'll handle that for you. So that's, if we're successful, you know, that's what we're trying to achieve here. >>Yeah. What, what makes AI so hard to work with? I mean, you talk about the complexity. Yeah. A lot of moving parts. I mean, literally moving parts, but, but what is it in, in your mind that, that gets people's eyes spinning a little bit when they, they look at great potential. Yeah. But also they look at the downside of maybe having to work your way through Pike mere of sorts. >>So, so the potential is definitely there, but it's important to remember that a lot of AI initiatives fail. Like a lot of initiative AI initiatives, something like 80 or 90% don't make it out of, you know, the research or prototyping phase and inter production. Hmm. So, some of the things that are hard about AI and the reasons that AI initiatives can fail, one is the scale required, you know, moving. It's one thing to develop something on your laptop, it's another thing to run it across thousands of machines. So that's scale, right? Another is the transition from development and prototyping to production. Those are very different, have very different requirements. Absolutely. A lot of times it's different teams within a company. They have different tech stacks, different software they're using. You know, we hear companies say that when they move from develop, you know, once they prototype and develop a model, it could take six to 12 weeks to get that model in production. >>And that often involves rewriting a lot of code and handing it off to another team. So the transition from development to production is, is a big challenge. So the scale, the development to production handoff. And then lastly, a big challenge is around flexibility. So AI's a fast moving field, you see new developments, new algorithms, new models coming out all the time. And a lot of teams we work with, you know, they've, they've built infrastructure. They're using products out there to do ai, but they've found that it's sort of locking them into rigid workflows or specific tools, and they don't have the flexibility to adopt new algorithms or new strategies or approaches as they're being developed as they come out. And so they, but their developers want the flexibility to use the latest tools, the latest strategies. And so those are some of the main problems we see. It's really like, how do you scale scalability? How do you move easily from development and production and back? And how do you remain flexible? How do you adapt and, and use the best tools that are coming out? And so those are, yeah, just those are and often reasons that people start to use Ray, which is our open source project in any scale, which is our, our product. So tell >>Me about Ray, right? Yeah. Opensource project. I think you said you worked on it >>At Berkeley. That's right. Yeah. So before this company, I did a PhD in machine learning at Berkeley. And one of the challenges that we were running into ourselves, we were trying to do machine learning. We actually weren't infrastructure or distributed systems people, but we found ourselves in order to do machine learning, we found ourselves building all sorts of tools, ad hoc tools and systems to scale the machine learning, to be able to run it in a reasonable amount of time and to be able to leverage the compute that we needed. And it wasn't just us people all across, you know, machine learning researchers, machine learning practitioners were building their own tooling and infrastructure. And that was one of the things that we felt was really holding back progress. And so that's how we slowly and kind of gradually got into saying, Hey, we could build better tools here. >>We could build, we could try to make this easier to do so that all of these people don't have to build their own infrastructure. They can focus on the actual machine learning applications that they're trying to build. And so we started, Ray started this open source project for basically scaling Python applications and scaling machine learning applications. And, well, initially we were running around Berkeley trying to get all of our friends to try it out and, and adopt it and, you know, and give us feedback. And if it didn't work, we would debug it right away. And that slow, you know, that gradually turned into more companies starting to adopt it, bigger teams starting to adopt it, external contributors starting to, to contribute back to the open source project and make it better. And, you know, before you know it, we were hosting meetups, giving to talks, running tutorials, and the project was just taking off. And so that's a big part of what we continue to develop today at any scale, is like really fostering this open source community, growing the open source user base, making sure Ray is just the best way to scale Python applications and, and machine learning applications. >>So, so this was a graduate school project That's right. You say on, on your way to getting your doctorate and now you commercializing now, right? Yeah. I mean, so you're being able to offer it, first off, what a journey that was, right? I mean, who would've thought Absolutely. I guess you probably did think that at some point, but >>No, you know, when we started, when we were working on Ray, we actually didn't anticipate becoming a company, or we at least just weren't looking that far ahead. We were really excited about solving this problem of making distributed computing easy, you know, getting to the point where developers just don't have to learn about infrastructure and distributed systems, but get all the benefits. And of course, it wasn't until, you know, later on as we were graduating from Berkeley and we wanted to continue really taking this project further and, and really solving this problem that it, we realized it made sense to start a company. >>So help me out, like, like what, what, and I might have missed this, so I apologize if I did, but in terms of, of Ray's that building block and essential for your, your ML or AI work down the road, you know, what, what is it doing for me or what, what will it allow me to do in either one of those realms that I, I can't do now? >>Yeah. And so, so like why use Ray versus not using Ray? Yeah, I think the, the answer is that you, you know, if you're doing ai, you need to scale. It's becoming, if you don't find that to be the case today, you probably will tomorrow, you know, or the day after that. And so it's really increasingly, it's a requirement. It's not an option. And so if you're scaling, if you're trying to build these scalable applications you are building, you're either going to use Ray or, or something like Ray or you're going to build the infrastructure yourself and building the infrastructure yourself, that's a long journey. >>So why take that on, right? >>And many of the companies we work with don't want to be in the business of building and managing infrastructure. No. Because, you know, if they, they want their their best engineers to build their product, right? To, to get their product to market faster. >>I want, I want you to do that for me. >>Right? Exactly. And so, you know, we can really accelerate what these teams can do and, you know, and if we can make the infrastructure something they just don't have to think about, that's, that's why you would choose to use Ray. >>Okay. You know, between a and I and ml are, are they different animals in terms of what you're trying to get done or what Ray can do? >>Yeah, and actually I should say like, it's not just, you know, teams that are new teams that are starting out, that are using Ray, many companies that have built, already built their own infrastructure will then switch to using Ray. And to give you a few examples, like Uber runs all their deep learning on Ray, okay. And, you know, open ai, which is really at the frontier of training large models and, and you know, pushing the boundaries of, of ai, they train their largest models using Ray. You know, companies like Shopify rebuilt their entire machine learning platform using Ray, >>But they started somewhere else. >>They had, this is all, you know, like, it's not like the v1, you know, of their, of their machine learning infrastructure. This is like, they did it a different way before, this is like the second version or the third iteration of of, of how they're doing it. And they realize often it's because, you know, I mean in the case of, of Uber, just to give you one example, they built a system called hova for scaling deep learning on a bunch of GPUs. Right Now, as you scale deep learning on GPUs for them, the bottleneck shifted away from, you know, as you scale GPU's training, the bottleneck shifted away from training and to the data ingest and pre-processing. And they wanted to scale data ingest and pre-processing on CPUs. So now Hova, it's a deep learning framework. It doesn't do the data ingest and pre-processing on CPUs, but you can, if you run Hova on top of Ray, you can scale training on GPUs. >>And then Ray has another library called Ray Data you can, that lets you scale the ingest and pre-processing on CPUs. You can pipeline them together. And that allowed them to train larger models on more data before, just to take one example, ETA prediction, if you get in an Uber, it tells you what time you're supposed to arrive. Sure. That uses a deep learning model called d eta. And before they were able to train on about two weeks worth of data. Now, you know, using Ray and for scaling the data, ingestive pre-processing and training, they can train on much more data. You know, you can get more accurate ETA predictions. So that's just one example of the kind of benefit they were able to get. Right. Also, because it's running on top of, of Ray and Ray has this ecosystem of libraries, you know, they can also use Ray's hyper parameter tuning library to do hyper parameter tuning for their deep learning models. >>They can also use it for inference and you know, because these are all built on top of Ray, they inherit the like, elasticity and fault tolerance of running on top of Ray. So really it simplifies things on the infrastructure side cuz there's just, if you have Ray as common infrastructure for your machine learning workloads, there's just one system to, to kind of manage and operate. And if you are, it simplifies things for the end users like the developers because from their perspective, they're just writing a Python application. They don't have to learn how to use three different distributed systems and stitch them together and all of this. >>So aws, before I let you go, how do they come into play here for you? I mean, are you part of the showcase, a startup showcase? So obviously a major partner and major figure in the offering that you're presenting >>People? Yeah, well you can run. So any scale is a managed ray service. Like any scale is just the best way to run Ray and deploy Ray. And we run on top of aws. So many of our customers are, you know, using Ray through any scale on aws. And so we work very closely together and, and you know, we have, we have joint customers and basically, and you know, a lot of the value that any scale is adding on top of Ray is around the production story. So basically, you know, things like high availability, things like failure handling, retry alerting, persistence, reproducibility, these are a lot of the value, the values of, you know, the value that our platform adds on top of the open source project. A lot of stuff as well around collaboration, you know, imagine you are, you, something goes wrong with your application, your production job, you want to debug it, you can just share the URL with your, your coworker. They can click a button, reproduce the exact same thing, look at the same logs, you know, and, and, and figure out what's going on. And also a lot around, one thing that's, that's important for a lot of our customers is efficiency around cost. And so we >>Support every customer. >>Exactly. A lot of people are spending a lot of money on, on aws. Yeah. Right? And so any scale supports running out of the box on cheaper like spot instances, these preempt instances, which, you know, just reduce costs by quite a bit. And so things like that. >>Well, the company is any scale and you're on the show floor, right? So if you're having a chance to watch this during reinvent, go down and check 'em out. Robert Ashihara joining us here, the co-founder and ceo and Robert, thanks for being with us. Yeah. Here on the cube. Really enjoyed it. Me too. Thanks so much. Boy, three years graduate program and boom, here you are, you know, with off to the enterprise you go. Very nicely done. All right, we're gonna continue our coverage here on the Cube with more here from Las Vegas. We're the Venetian, we're AWS Reinvent 22 and you're watching the Cube, the leader in high tech coverage.

>>Mm. Welcome back to the seaports in Boston City is abuzz. Bruins tonight, Celtics Tomorrow night. We're all excited. We're talking open source, which is a very exciting topic. Every company is using open source. I mean, it is the mainspring of innovation. I'm Dave along with my co host, Paul Dillon. And you're watching the cubes. Coverage of Red Hat. Summer 2022. Raj Raj Masinga is here. He's hybrid and emerging Platforms lead at Accenture and Ghetto Greber. Who's red hats? Business group lead eccentric. Gentlemen, welcome to the Cube. Thanks for coming >>on. Thank you. >>Thank you, Raj. We saw in the keynote up there today with Stephanie. She's coming on tomorrow. Rockstar Stephanie. Cheers. Also a Boston sports fan, and I have to work at it, but you can talk about the history with red hat. How long have you guys been at this? And give us a journey update. >>Well, first of all, thanks for having us here. Um, yes, we are big fans of Red Hat and especially Stephanie. I get to I had the pleasure of working with a very closely, um, our relationship with Red Hat goes many, many years, decades I think. And but Paul, come here will tell you that. You know, we've been focused a lot with the formation of our new business unit in Cloud. First around, migrating to the public cloud. But now, as we focus more and more around how our clients begin to operate in the public cloud in the cloud ecosystem hybrid is coming much more into focus. And Red Hat is very much a key client of a key partner of us. So we go way back. But this is all about us doubling down and increasing our partnership and deepening it with them. >>So, uh, you talked today about hybrid Cloud is everything. And it seems like a couple of years ago there was focuses more on moving to the public cloud and getting off of private infrastructure. Has there been a change in the ways in which customers are thinking, are they gonna be hanging onto their private infrastructure longer, perhaps, than was expected a couple of years ago? >>I think the first of all, it's a very different industry by industry. If you look at retail or consumer goods, I think there's a big movement in terms of percentages of workloads that are getting moved onto public cloud. If you look at industries like banking or utilities or government, more regular financial services, more regulated industries. I think we are finding a much larger percentage of their workloads because of regulatory reasons and security reasons, etcetera. Our need to remain either on premise or in private cloud. So I think it very much depends on the industry. But regardless the hype, you know, especially with the movement to edge now hybrid is going to be, you know, permeating everything. So I think by industry depends. But but the edges driving a whole new flywheel. >>You know, we started the Cuban 2010, so the cloud was, you know, modern cloud. Anyway, it was like, say, four years in into it and at the time, to your point Raj Financial Services, there was an evil word. No way we're ever going to the cloud. No, that's changed, obviously. But then, when the financial crisis hit, >>you >>had so initially it was a lot of tyre kicking experimentation. When the financial crisis hit, you had a lot of CFO saying, Okay, let's shift Capex to Apex and so that was sort of a bridge. And then after we came out, it was like this spate of innovation. And then we saw that during the pandemic, where cloud migration was a high priority and or it was the lifeline. And now it sounds like customers are kind of rethinking to your earlier conversation. What is cloud? It's that operating model. So I wonder if you could sort of Can you confirm that's kind of the journey that customers are taking? Where are they today? What does it mean? There? You know the the operating model. What do they consider cloud? >>Um, you actually, you see it? It's like it's really try forward to the cloud. Uh, but where it was in the beginning, If it doesn't hype about Public Cloud, they become more and more aware that it's hybrid because they have to bring the legacy system and process into the cloud as well. And it takes more time that actually they have fought before. So it's like there was a process of learning and also like in the steps moving forward to the operating model because they also understand I cannot operate a cloud like I was operating in the classical way like my old data centre and everything. It needs all the capabilities it needs, all the skills and especially if you go in a hybrid world. And it's a hybrid operation between the classic traditional but also the new ways of how you operate into a cloud. And you really see also the financial services. Now, uh, we had, uh I mean watch presented at keynote. We had a client in Germany. He made a decision, a very traditional financial services clients providing the service to chairman saving banks. And they did this decision and I would say, if you have spoken to them 10 years ago, they will not go into the cloud. But now they went to the cloud via private cloud, and now they got the confidence about how to operate in it. And now they move forward into a public cloud. But from a private cloud into the public cloud. Today, after security, they have up Skilling on skills and people and they understand the process and what's really required and needed in order to have such an environment. >>Generally, what's the strategy with regard to modernisation organisations? More building like an abstraction layer? Uh, with microservices and then connecting to the cloud. Or are they actually rewriting applications to make them cloud native? What are you What are you advising clients from a strategy standpoint, and I know it depends, but, you know, it's >>a It's a great question. I think the genesis to that strategy is how they view infrastructure, Right? So you know, everyone is, has this kind of, I don't know that this is almost mythical opinion out there with cloud. You don't need to worry about your infrastructure. All the providers will worry about it, and you just need to move it there. But the opposite is true. It's really critical what your infrastructure strategy is as you move to the cloud, because depending on what workload you have, you know it can be on any one of the continuum that you described. So the first thing is, where do you want to house your workload? Is the question and that will drive. How what do you want to do with your application? Whether you want to just maintain it the way it is, Do you want to simply modernise it, keeping where it is, or do you want to completely risk in it or even eliminated. So so I think the entire basically the answer to your question around. Do we? What do we do with the application? Is fundamentally driven by what is your infrastructure strategy and what that workload needs to do for you. >>So I know you want to jump in, but I got to follow up. You're saying hardware matters because we heard Paul Corvino today talking about this hardware renaissance. I'm actually I just ran a power panel called. Does hardware still matter? You're saying it matters? >>Yeah. And and it doesn't. And infrastructure doesn't always. I mean, now that you can do infrastructure as code, right? I mean, I was at the Del summit last time and read That is a huge partner of Dell now, right? Which, you know, uh, was much more, uh, partnered with VM ware. But I think the whole ecosystem is opening up, and even the hardware providers are looking at this in a much more nimble way. But yes, it's very much part of the conversation. They haven't gone away. >>During your keynote. You outlined sort of your strategy. Going forward is called cloud first. Yes. What does cloud first mean? >>Well, um, we we want to make sure that when we talk about transformation of business with our clients, So extension always goes with the idea of an industry lens of solving a specific problem for a client. What is the business problem we solve? And increasingly, what we want to message and drive to our clients is if you're thinking about, regardless of what the business is technologies absolutely critical to whatever transformation you're doing and when. When you look at technology, you have to think cloud first because that's where all the innovation is happening. That's where all the, um um, investments are being driven. Whether it's an I mean, it's a software vendor, but it's a hardware vendor with its uh, so you have to think cloud first when you think about transforming your business. >>Uh, what is How does modernisation play into that? You know, a lot of vendors are throwing a lot of resources that the modernisation market VM ware, Tanzania and IBM and such, uh, how interesting our customers really a Modernising legacy applications >>hugely right, because fundamentally, I think everything is now driven by our experiences. What we now are used to in terms of, uh, interfacing with applications are interfacing with function sets or interfacing with technology. So there is a lot of inherent, um, legacy technology that doesn't have that experience. So when you think about transforming, you have to come at it from an experience point of view. And when you think in those terms modernisation or even rebuilding the same, even if it's the same function set, uh, re skinning it and modernisation is critical for the purposes of engagement. >>What's the number one challenge that customers that you're working with face in terms of modernisation? Is it trying to figure out like Rogers sort of laying out the portfolio? What do I do with it? Do I modernise it? Do I retire it? Do I let it just die on the vine? What's their number one challenge? >>Uh, mainly it depends also on the industry, but it's, uh, I would say, for the highly regulated, certainly regulations. They always have an own interpretation of the regulations. Regulation means for them, but normally it's not really what they understand. But I think this is more and more coming to Annie's and more people understand what it really means, but it's also what we see a lot. They think first about technology, but not what kind of business problem they want, Uh, and they want to solve. So it's like, instead of having a technology neutral discussion is really do want to achieve, um, to have really start on this side and then having this discussion away, which, obviously it's one of the key, even because they start to the cloud even without having a strategy without having a vision. If you have a clear vision, if you have a clear strategy, you know where you want to go, and then you can make your business case. You can make you architecture and then you decide on technology. And then, of course, on this journey, all the things about security compliance coming to the plane, Yeah, and I think I think that's the easiest approach. But clients struggle to understand. Of course, I mean, the technology is changing rapidly. Even new products and release cycle new life cycles, the complexity of all the tools hardware we mentioned before network is changing new working coming up. It's really hard to keep pace or keep up with the base of the technology and what's happening even for us. And then you understand the complexity and bring this complexity back to simplicity, but not without losing. We have this also keynote the efficiency and, uh, flexibility for an engineer, because that's what he needs >>to your clients. Have the skill sets to do all that such a self serving question to you guys. But but no, do they? I mean, there's a skills shortage. There's a a battle for talent. So how are they >>dealing? I mean, it's obvious the battle for talent is here. I mean, everybody is looking for the best talent, and if we need, if you need a full stack. Engineer, for example, is very hard to get a full stack engineer on your ground. You call really cloud native. So you have to up skill people to re skilled people. There's also a change coming into it and the changes not to forget. So it's what we say most time. The technology is an easy part, but the change change the organisation, change up skilled organisation. That's the hard part because you need to change from from one mindset to another, and we know from the from the past. What change? People are not open to change in general, so we need to change the mindset. >>I wanna go back to Hybrid Cloud because we have Dani from Red Hat was on earlier and he said, Edges really redefining the definition of hybrid cloud. It's it's more complex architecture, and it's changing the nature of how we think about hybrid Cloud. Are you seeing that with your customers? Are they changing their thinking about what hybrid means in that context? >>Yeah, completely. You know, I was I was We did a bunch of, uh, research recently, and I had I just wanted to make sure I called this. I mean, there's a flexible report that came out that says 80% of all enterprises now are on hybrid 89% multi cloud redheaded. A report that said 80% of our businesses are expected to, um, uh, increase their use of open source. Right, So So, yes, hybrid is everywhere. Edge is driving it, but there's a There's another critical element to that movement. The complexity of our clients. Estates are increasing because whether it's hybrid or whether it's edge or whatever, they are now. You know, given if you're a C i or a C T o. Your estate is really complex now. So one of the things that we now need to do is how do we simplify that? So, you know, we think and we've been talking with red hat about this. We need to come up with a clean, you know, we keep calling it, you know, single pane of glass for a enterprise that allows them to look at their estate in a way that allows them to then simply make some innovative decisions across the entire state. So, yes, edges driving hybrid. But the key thing that we now need to overcome is how do we manage that complexity? >>We have new term. Uh, I call it Super Cloud, but the session is a better word. Medic cloud. That's gonna what I think of that century. I think of deep industry expertise. Of course, we have that, but with the partnership from redhead, it's a very it's horizontal in the sense that it can go anywhere. So how do you guys work in in terms of within Accenture plugging into your deep industry expertise? And how does that horizontal redhead >>fit. That's a really good question. So, you know, one of the things, you know. First of all, we came out with a announcement today about our expanded relationship with Red Hat. One of the key elements in that announcement is how we are looking and bringing in red Hat into our industry business motions. So we actually have decided to pick a certain number of industries. You know, financial services is one. Telco is another. We are thinking about utilities in Europe. Public health is a is another one that we are looking at. And as we come up with our offerings, you heard me and Stephanie talk about joint offerings earlier on the keynote. Um, these offerings are industry offerings, but in those offerings we have embedded and we are, they're powered by redhead technology. Um, that allows these industry solutions to drive innovation through their technology. Um, yes. Red hat can be, for the most part, a horizontal cross industry, you know, technology. But you have to really bring them into specific industrial solutions because of the way we go to market. And I think Red hat brings innovation, uh, in a way that these industries haven't seen before. >>So I mean, how do you stay out of their way? Because they have a services operation that they're trying to grow. And that's your business as well. So where the lines of demarcation >>back to your question? I I don't I don't think there is a limiting opportunity. Read? Had, you know Stephanie Me, Paul, we're all talking about How do we collectively increase both our armies? You know, I I Yes, there might be occasional overlaps in the trenches, but when you look at the bigger picture, it is not a problem at all. >>I wouldn't think so. I mean, the way you're describing Rogers exactly the way it should work. You lead with the business, figure out the business problem, how you're gonna solve that. The technology will take care of itself. Technologies come and they go. And you want to use modern technologies, obviously. But if you don't get the business piece right, forget no technology is gonna save you >>exactly, right. And and the complexities of what the businesses today are facing is getting more and more difficult. And I think actually, technologies like red hat, you know, they're the whole concept of open source, I think is very creative around driving innovations from the market. I >>want to ask you that because Paul Kermie is you know, the storey was sort of an homage to open source. How much do customers really care about open source >>customers care about innovation and and anything that drives innovation to their business, whether it's whether it comes from technology, whether it comes from crowdsourcing, whether it comes from, you know, uh, marketing doesn't matter. I think when you look at the key hunger for innovation and how open source drives innovation, it becomes part of the business conversation. And, uh and I think that's been one of the mantras that Paul has had from day one about how this is such a great platform for innovation. And I think that's >>something customers asked for. They say we must develop this using open source platforms and tool sets. >>Um, it depends. I think I think there are some technology CEO s R c T O s that are much more religious about what? Their technologies that needs to be there are others that are that are much more business oriented. Um, so yes, there are. You know, if it's more in telecom field, I think telecom or some of the more, uh, technology driven fields, they will ask for open source. In others, they we bring, bring it through as part of offering. >>Here's the nuance that I see and you mentioned Paul Cormier. Accenture, especially. I mean, you look at your ascendancy as a company, you for years would take known processes and codify them in software. And you made, you know, a lot of great innovations doing that. And people who made a lot of >>money >>today, this new normal, he calls it. I call it the new abnormal. You don't know what's around the corner. You have to build flexibility into your business, and that is something that open source enables. Uh, so that's sort of this, Really Not really. We don't want to speak about it too much. Business resiliency and flexibility is that that is the new normal. I don't see how you can do it without without open sources expertise. >>I completely agree that I and I think, um, it's actually an asset. So you know, in some ways, selfishly, by having open source in a solution stack some of the innovation gets them much more democratised, right? So? So it can come from a much broader sweet. So the load is not only an extension to come up with all the innovation we can, we can actually come up with a more democratised way of bringing that innovation in. So I think that's that's >>great. And it doesn't always go back to the community. I mean, Amazon built a $70 billion business on open source, but not all right, guys. Thanks so much for coming. Thank you very much for having a pleasure. All right, keep it right there. This is Dave Volonte for Paul Dillon. The Cubes. Continuous coverage of Red Hat Summit 2022 from the seaport in Boston. We'll be right back. >>Mm mm.

>>from the cube studios in Palo alto in boston connecting >>with thought leaders all around the world. This is a cute conversation. Hello and welcome to today's session of the 2021 AWS Global public sector Partner awards. I'm your host, Natalie ehrlich. Today we'll discuss the award for the most customer obsessed mission based win for state and local government. I'm pleased to introduce our guests for today's session Todd, Carey, Global Head West Business group Cognizant and David. Sullivan chief executive officer of Elizabeth river crossings. Thank you gentlemen for joining the program. >>Thanks >>Thanks Todd. >>I'd love to start with you. How are companies thinking about cloud today in their businesses? >>Well, there's some, some really exciting developments but at the heart of a cloud is changing the way companies interact with their customers, their suppliers and the way they think about business. And at cognizant it is really a customer first customer centric approach and then we work our way back to a solution. But most of the time, cloud decisions are not really made from a cost optimization or cost take out point of view. They're made from a customer experience or a business driver point of view. And how do we make businesses better? More, more scalable, more agile, more flexible and we've really built some some really great solutions that are industry specific and we've loved working with the R. C. In this capacity. >>How about you? I'd love to get your insight. Um As well. David, what what what do you see is like the main challenges and also how next gen technologies like you know, five G. Can help alleviate in those issues. >>Um Yes. First, it, like Todd said that, you know, the customer has an expectation and that expectation is raised every day by what they experienced in every other channel they work in and shop in and whatever they're doing so, so expectations are always increasing from the customer side, responsiveness personalization. They want to see all of that in everything they do, including paying their told bill. Um, and so I think as technology has changed, you know, tolling has kind of come from technology that is really 2030 years old or older. Uh, two more of a modern influence. And today we use R. F. I. D. Tags that are embedded in things like EZ Pass. But in the future it will be, it'll be your, your mobile device or your automobile itself that that triggers a total transaction and helps us process it and making in a way that is fast, convenient and most importantly accurate. >>Yeah. Well staying with you, David, I'd love to hear how working with AWS helped modernize your systems and as well as if you could give us some insight on your tracking systems. >>Yes. So with AWS, we have been working with Cognizant. Cognizant is our tolling subcontractor. So they are responsible for providing our tolling system. And we had what I would call a typical legacy tolling system. We had to data centers, both of them located pretty close together, a primary and a redundant data center and both of them very close to flood prone areas. And in our location in the southeast corner of Virginia were very vulnerable to tropical storms and tidal flooding. So part of our concern was, you know, we're exposed all our infrastructure, all our tolling infrastructure is exposed. So as we began to pursue a cloud strategy, uh the first idea was just to lift everything out of our environment and move it to a W. S. And Cognizant pull that off in about three months, uh which is really pretty incredible and we never missed a beat. Uh You know, we did it over a three day holiday weekend, but from a business transaction standpoint it all flowed once in the cloud. We began to rethink now that we're out of these legacy hardware environments, How do we get out of the legacy application environment and embrace what the cloud enables and working closely with Cognizant who had a great vision for how this could be achieved. We were able to, you know, systematically move through and migrate to a cloud first cloud oriented uh system. And uh you know, it's given us lower cost, increased availability and most importantly for our customer service agents that deal with customers or customers that deal with the web, it's given them a better experience uh shorter call times, better information and you know, and and frankly better customer satisfaction. >>Terrific. Well, thank you for that Todd. Let's shift to you. What do you see as the next phase of this digital transformation process? >>Well, as David hidden, I think it's an important theme of cloud first. I mean most companies in our clients start with that cloud forest, cloud native mentality. But for cognizant, our cloud approach is really customer first and being able to start with the client in mind and then work our way back into a technology staff or into a scalable solution. But specifically for the coal industry, there's a lot of things that are needed around revenue, predictability and looking at potential leakages. But as we hit on already of making sure that we're really delivering a great customer experience. And so with our solution, as we expect our tolling solution to really grow, we're keeping it cloud native, we're keeping it modular in nature and integration ready. So for example, are total customers can use their own roadside solutions or hand picked some of the small back office modules that they want to use. It's always going to be purpose bill and align to our customer and we see nothing but growth in this segment. It's very exciting. >>Yeah. Terrific. Well, David, you know, now that you've actually implemented this, what do you see as the next phase? What is your vision um for the future for your business in 2021? >>Well, I think, you know, for for us moving forward, um you know, we've been in this uh as Todd said, kind of a modular approach, which is great because you can make the changes and really manage your risk while you're making them. Um so you're you're moving small things. Whereas traditionally new systems meant massive investments, long, long time implementation times and you know, all in cut overs, all of which are packed with risk. So, you know, we want to reduce our risk and the solution that we have being cloud native allows us to really incrementally and quickly, just continually to improve the system. So you know, on our forecast, we would like to have a better insight into our customers and you know, support a direct app, Annie R. C. App that would allow our customers to interact with us and give us a better view of the customer um and a better experience for the customer overall. But you know, we, our goal is to build that total transaction accurately fairly. And then if the customer has an issue to be able to treat them in a way that uh that they feel respected and and valued as a customer because we we do look at it that way. >>Yeah, Terrific. I mean obviously, you know, engagement such an important issue in this area. Now I'd like to shift gears and here a little bit more about, you know, what are some of the other applications that cognizant could provide beyond tolling and let's shift this to Todd? >>Well, David had done a little bit, there's there's a lot of when we start to focus on the customer, there's a lot of opportunity there on the front side. So mobile apps, websites, the synchronization of data, but then also the way that we support that customer interacting with that data. Things like I've er automating, call centers, being able to support that customer through the entire chain of custody. There's some new and exciting applications now that we come out and David touched on a little bit too in terms of vehicles. So the vehicles to everything type motion. That's an exciting development in this segment as well to be able to continually integrate everything that's in the customer ecosystem. So whether that's uh, the, the need to pay a bill or be able to drive a car through a gate and be able to simply not touch anything but be able to have that all the way that payment process all the way through and have clear visibility into usage and insights. And then also be able to turn all that data over to a company like er, C to make good decisions based on what they see in terms of buying patterns, consumption, etcetera. There's a lot of expansion going on in this and the greatest part about this is it's built on the AWS platform. So when we architect something in a cloud native way, we can rapidly expanded and we can really streamline the investment required to jump start any kind of innovation and best of all our customers in keeping with the best model, really only pay for the actual traffic that they use so we can keep those long term costume. >>Yeah. Well, excellent point. Thank you both gentlemen for joining our program. Really loved having you. And uh, you know, that was Todd, Cary and David. Sullivan. Excuse me. And I'm your host, Natalie or like, Thank you for watching. >>Mm hmm. Mm.

>>from the Keep studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cube conversation. Hi, I'm John Furry with the Cube. We're here for a special Q conversation, housing with remote, where in studio most of the time. But on the weekends, I get an opportunity to talk to friends and experts, and he I wanted to really dig in with an awesome case study around AWS Cloud in a use case that I think is game changing for local community, especially this time of Cove. It you have local community work, local journalism suffering, but also connected this and connected experiences was gonna make. The difference is we come out of this pandemic a societal impact. But there's a real tech story here I want to dig into. We're here with Dan. True is the vice president of engineering for Chemical. Did you? They make a nap coat local be TV, which basically takes over the air television and streams it to an app in your local area, enabling access to many your TV and on demand as well. For local communities, it's a phenomenal project and its unique, somewhat misunderstood right now, but I think it's gonna be something that's going to really put Dan, thank you for coming along and chatting. Thanks >>for having me appreciate it. >>Okay, so I'm a big fan. I've been using the APP in San Francisco. I know New York's on the docket. I might be deployed. You guys have a unique infrastructure capability that's powering this new application, and this is the focus of the conversations. Q. Talk Amazon is a big part of this. Talk about your local be TV that you are protected. This platform for broadcast television has a unique hybrid cloud. Architecture. Can you tell us about that? >>Certainly. I mean, one of our challenges, as you know, is that we are local television eso unlike a lot of products on the markets, you know, like your Hulu's or other VM PV products, which primarily service sort of national feeds and things like that. Ah, we have to be able to receive, um, over the air signals in each market. Um, many channels that serve local content are still over the air, and that is why you don't see a lot of them on those types of services. They tend to get ignored and unavailable to many users. So that's part of our value. Proposition is to not only allow more people to get access to these stations, but, uh, allow the station's themselves to reach more people. So that means that we have to have a local presence in each market in order to receive those signals. Eso that's sort of forces us to have this hybrid model where we have local data centers. But then we also want to be able to effectively manage those in a central way. On. We do that in our cloud platform, which is hosted on Amazon and using Amazon service. >>Let me take take a breath. Here. You have a hybrid architecture on Amazon. So such a using a lot of the plumbing take us through what the architectures ram is on using a variety of their services. Can you unpack that? >>Yeah. So, um, obviously starts with some of the core services, like easy to s three already us, which everybody on planet uses. Um, we're also very focused on using PCs were completely containerized, which allows us to more effectively deploy our services and scale them. Um, and one of the benefits on that front that Amazon provides is that because they're container services wired into all the other services, like cloud, What metrics? Auto scaling policies. I am policies. Things like that. It means it allows us to manage those things in a much more effective way. Um, and use those services too much more effectively make those things reliable and scalable. Um, we also use a lot of their technologies, for example, for collecting metrics. So we use kinesis and red shift to collect real time metrics from all of our markets across the U. S. Uh, that allows us to do that reliably and at scale without having to manage complex each l systems like Kafka and other things. Um, as well a stored in a, uh, large data lake like red shift in Korea for analytics. And you know, things like that. Um, we also use, um, technologies like media Taylor s O, for example, one of the big features that, uh, most stations do not have access to Israel. Time targeted advertising in the broadcast space. Many ads are sold and placed weeks in advance. Um, and not personalized, obviously. You know, for that reason. Where is one of the big features we can bring to the table? Using our system and technologies like Media Taylor is we can provide real time targeted advertising, which is a huge win for these stations. >>What are some of the unique capabilities that you guys are? Offer broadcast station partners because you're basically going in and partnering with broadcast ages as well, but also your enabling new broadcasters to jump. And it's well, what are some of the unique capability that you're delivering? What is that? It's on the table there. What are you doing? This You >>well again. It allows us because we can do things centrally. You know as well as the local reception allows us to do some interesting things. Like if we have channels that, um, are allowed to broadcast even outside their market, Um, then we can easily put them in other markets and get them even more of years. That way we have the ability to even do, like hyper local or community channels, you know that are not necessarily broadcasting over the standard antennas, um, but could get us a feed from, you know, whatever. Zip code in whatever market and we can give them away toe reach viewers in the entire market and other markets, or even just in their local area. So, you know, consider the case where maybe a high school or a college you know, wants to show games or local content. Um, we provide a platform where they can now do that and reach more people, Um, using our app in our platform very, very easily. So that's another area that we want toe help Expand is not just your typical view of local of what's available in Phoenix, Um, but what's available in a particular city in that area or a local community where they want toe, um, reach their community more effectively, or even have content that might be interesting to other communities in Phoenix or one of the other markets? >>No, I think just is not going to side tension here. I talked with your partner. Jim longs to see you guys have an amazing business opportunity again. I think it's kind of misunderstood, but it's very clear to me that follows in. It has huge passion of local journalism. You see awesome efforts out there by Charlie Senate from the ground Truth project report for America. They take a journalism kind of friend few. But if you add like that, did you business model ought to This local journalism you can enable more video locally. I mean, that's really the killer app of video. And now it Koven. More than ever. I really want to know things like this. A mural with downtown Palo Alto Black lives matters. I want to know what's going on. Local summer restaurants, putting people out of sidewalks. Right now I'm limited to, like, next door or very Laghi media, whether it's the website. So again, I think this is an opportunity to that plus education. I mean Amazon educated Prince, that you can get a degree cloud computing by sitting on the couch. So, you know, this is again. This is a paradigm shift from an application standpoint, but you're providing essentially linear TV toe because in the local economy, So I just want to give you a shout out for that because I think it's super important. I think you know, people should get behind this. Eso congratulates. Okay, I'm often my little rant there. Let's get back down to some of that cloud steps. I think what super interesting to me is you guys can stand up infrastructure very quickly and what you've done here, you delivery of the benefits of Amazon of the goodness of cloud you, especially in stand up a metro region pretty quickly try it. And it pretty impressive. So I gotta ask you what? Amazon services are most important for your business. >>Um, well, like I said, I think for us it's matching the central services. So we sort of talked about, uh, managing the software, the AP eyes, um, and those kind of the glue. So, you know, for us standing up a new metro is obviously, you know, getting the data center contracts and all the other you know, >>and >>ask yourself, you have to deal with just have a footprint. But essentially, once we have that in place, we can spin up the software in the data center and have it hooked into our central service within hours. Right? And we could be starting channels >>literate >>literally within half a day. Um, so that's the rial win for us is, um, having all that central blue and the central management system and the scalability where You know, we can just add another 10 20 5100 markets. And the system is set up to scale centrally, um, where we can start collecting metrics their cloudwatch from those data centers. We're collecting logs and diagnostic information. Eso weaken the type health and everything else centrally and monitor and operate all of these things centrally in a way that is saying and not crazy. We don't need a 24 7 knock of 1000 people to do this. Um, you know, and do that in a way that, you know, we, as a relatively small company can still scale and do that in a sensible way, a cost effective way, which is obviously very important for us at our size. But at any size, um, you want to make sure if you're gonna go into 200 plus markets, that you have a really good cost model. Um and that's one of the things that where Amazon has really really helped us is allow us to do some really complex things and an efficient, scalable, reliable and cost effective way. You know, the cost for us to go into the New Metro now is so small, you know, relatively speaking. Um, but that's really allows. What allows us to do is a business of now. We just opened up New York, you know, and we're going to keep expanding on that model. So that's been a huge win for us. Is evaluating what Amazon could bring to the table versus other third parties and or building our own? You know, obviously which >>So Amazon gives you the knock, basically leverage and scale the data center you're referring to. That's pretty much just to get an origination point in the derrick. Exactly. That's right. It's not like it's a super complex data center. You can just go in making sure they got all the normal commute back of recovery in the North stuff. It's not like a heavy duty buildup. Can you explain that? >>Yeah. So one thing we do do in our data centres is because we are local. Um, we have sort of primary data centers. Ah, where we do do trance coating and origination of the video eso we receive the video locally, and then we want to transport and deliver it locally. And that way we're not sending video across the country and back trying to think so that that is sort of the hybrid part of our model. Right? So we stand that up, but then that is all managed by the central service. Right? So we essentially have another container cluster using kubernetes in this case. But that kubernetes cluster is essentially told what to do by everything that's running in Amazon. So we essentially stand up the kubernetes cluster, we wire it up to the Central Service, and then from then on, it just we just go into the Central Service and say, Stand up these channels. Um and it all pops up >>with my final question on the Amazon pieces is really about future capabilities Besides having a cube channel, which I would love to head on there. And I told my guys, We'll get there. But what is this too busy working around the clock is You guys are with Kobe tonight? Yeah, sand. I can almost see a slew of new services coming out just on the Amazon site if I'm on the Amazon. So I'm thinking, OK, outposts. The opportunity from a I got stage maker machine learning coming in any value for user experience and also, you know, enabling in their own stuff. They got a ton of stuff with prime the moving people around and delivering the head room for Amazon. This thing is off the charts. But that being said, that's Amazon could see them winning with this. I'm certainly I know using elemental as well. But for you guys on the consumer side, what features and what new things do you see on the road map or what? You might envision the future looking like, >>Well, I think part of it. I think there's two parts. One is what are we gonna deliver ourselves, you know? So we sort of talked about adding community content and continuing to evolve the local beauty product. Um, but we also see ourselves primarily as a local TV platform. Um, and you know, for example, you mentioned prime. And a lot of people are now realizing, especially with Cove, it and what's going on the importance of local television. Ah, and so we're in discussions on a lot of fronts with people to see how how we can be the provider of that local TV content, you know, um and that's really a lot of stationed are super psyched about that to just, you know, again looking to expand their own footprint and their own reach. You know, we're basically the way that we conjoined those two things together between the station's the other video platforms and distribution mechanisms and the viewers. Obviously, at the end of the day, um, you know, we want to make sure local viewers can get more local content and stuff this interesting to them. You know, like you said with the news, it is not uncommon that you may have your Bay area stations, but the news is still may be very focused on L. A or San Francisco or whatever. Um and so being able to enable, uh, you know, the smaller regional outlets to reach people in that area in a more local fashion, uh, is definitely a big way that we can facilitate that from the platform. And, you know, if you were perspective, so we're hoping to do that in any way we can. You know, our main focus is make local great, you know, uh, get the broadcast world out there, and that's not going anywhere, especially with things like HSC tree. Uh, you know on the front. Um, and you know, we just want to make sure that those people are successful, um, and can reach people and make revenue. And, you know, >>you got a lot of it and search number two. But I think one of the things that's just think about your project that I find is a classic case of people who focus in on that Just, you know, current market value investing versus kind of game changing shifts is that you guys air horizontally, enabling in the sense that there's so many different use cases. I was pointing out from my perspective journalism, you know, I'm like, I look at that and I'm like, OK, that's a huge opportunity. Just they're changing the game on, you know, societal impact on journalism, huge education, opportunity for cord cutters. You're talking about a whole nother thing around TV. I gotta ask you, you know, pretend I'm an idiot for a minute by our pretending that this person from this making I amenity after I don't understand is it Isn't this just TV? What are you doing? Different? Because it's only local. I can't watch San Francisco. I'm in Chicago and I can't watch Chicago in San Francisco. I get that. You know why? Why is this important? Isn't this just TV? Can I just get on YouTube? Mean Tic tac? Well, talk about the yes >>or no. I mean, there's TV, and then there's TV, You know, as you know, um and, you know, if you look at the TV landscape just pretty fracture. But typically, when you're talking about YouTube or who you're talking about, sort of cable TV channels, you know, you're gonna get your Annie, you're going to get some of your local to ABC and what not? Um, but you're not really getting local contact. And So, for example, in our Los Angeles market, um, we there are There are about 100 something over the air channels. If you look at the cross section of which of those channels you can get on your other big name products like you lose your YouTube TV, you're talking about maybe 1/2 a dozen or a dozen, right? So there's like 90 plus channels that are local to L. A. That you can only get through an antenna, right? And those air hitting the type of demographics. You know, quite frankly, some of these other players or just, you know, don't see is important >>under other minorities. Back with immigrants, you know, hit the launch printers of our country. Yes, >>exactly. You know, So, you know, we might see a lot of Korean channels or Spanish channels or other. You know, um, minority channels that you just won't get over your cable channels or your typical online video providers. So that's again Why, you know, we feel like we've got something that is really unique. Um, and that is really underserved, you know, as far as on a television sampling, Um, the other side that we bring to the table is that a lot of these broadcast channels are underserved themselves in terms of technology. Right? If you look at, you know, at insertion, um and you know, a lot of the technical discussions about how to do live TV and how to get live tv out there. It's very focused on the o t T market. So again, going back to who lose and >>the utility well, over the top of >>over the top. Yeah. Um and so this broadcast market basically had no real evolution on that front in a while, you know? And I sort of mentioned, like the way ad buying works. You know, it's still sort of the traditional and buying that happens a couple weeks in front. Not a lot of targeted or anything ability. Um, And even when we get to the HSC three, you're now relying on having an H s street TV and you're still tied to an antenna, etcetera, etcetera, which is again, a good move forward, but still not covering the spectrum of what these guys really want to reach and do. So that's where we kind of fill in the gaps, you know, using technology and filling in the gap of receiving a signal and bringing these technologies. So not only the ad insertion and stuff we can do for the life stream, Um, but providing analytics and other tools to the stations, uh, that they really don't have right now, unless you're willing to shell out a lot of money for Nielsen, which a lot of local small stations don't do s so we can provide a lot of analytics on viewership and targeting and things like that that they're really looking forward to and really excited >>about. I gotta ask you, put you on the spot. He'll because I don't see Andy Jassy. It reinvented might. Hopefully I'll see him this year. They do a person event. He's really dynamic. And you just said it made me think he tends to read his emails a lot. And if your customer and you are. But if you bumped into Andy Jassy on the elevators like, Hey, why should I pay attention to? Did you? What's why is it important for Amazon? And why is it important for the world? How does it raise the bar on society? >>Well, I think part of what Amazon's goal And you know, especially if you get into, you know, their work in the public sector on education. Um, you know, that's really where you know, we see we're focusing with the community on local television and enabling new types of local television eso. I think there's a lot of, uh, advantage, and, um, I hate the word synergy, but I'm going to use the word synergies, you know, um, this for us, You know, our goals in those areas around, you know, really helping, you know, Uh, you know, one of the terms flying around now is the dot double bottom line, where it's not just about revenue. It's about how do we help people and communities be better as well? Um, so there's a bottom line in terms of, uh, people benefit and revenue in that way, not just financial revenue, Right? And you know, that's very important to us as a business as well is, you know, that's why we're focused on local TV. And we're not just doing another food. Go where it's really easy to get a night. The national feed. You know, it's really important to us to enable the local, um, community and the local broadcasters and local channels and the local viewers to get that content, Um, that they're missing out on right now. Um, so I think there's a energy on that front A so >>far, synergy and the new normal to have energy in the near normal. You know, I think I think Kobe did. >>And you know, um, and some of the other, uh, things that have been happening in the news of the black lives matter and, um, you know, a lot of things going around where you know, local and community has been in the spotlight right and getting the word out and having really local things versus 100. Seeing this thing from, you know, three counties away, which I don't really care about, it's not telling me what's happening down the street, like you said, Um, and that's really what we want to help improve and support. >>Yeah, I know it's a great mission is one we care a lot of cute. We've seen the data content drives, community engagement and communities where the truth is so in an era where we need more transparency and more truth, you get more cameras on the street, you're gonna start to see things. That's what we're seeing, a lot of things. And as more data is exposed as you turn the lights on, so this week that kind of data will only help communities grow, heal and thrive. So, to me, big believer in what you guys are doing local be TV is a great mission. Wish you guys well and thanks for explaining the infrastructure on Amazon. I think you guys have a really killer use case. Technically, I mean to me. I think the technical superiority of what you've done. Abilities stand up. These kinds of networks with massive number potential reach out of the gate. It's just pretty impressive. Congratulations, >>Right. Thank you very much. And thanks for taking the time. >>Okay. Dan Drew, vice president of James. Did you start up? That's a lot of potential. Will. See. Let's go check out the comments on YouTube while we're here. Since we got you, let's see what's going on the YouTube front year. Yeah. The one question was from someone asked me, Was stiff from TV Cres that William Dan, Great to see you. Thanks for taking the time on Sunday and testing out this new zoom home recording my home studio, which I got to get cleaned up a little. Thank you for your time problem. Okay, take care.

>>lie from Copenhagen, Denmark. >>It's the >>Q covering Nutanix dot Next 2019. Brought to you by >>Nutanix. Welcome back, everyone to the cubes. Live coverage of Nutanix. Stop! Next here in Copenhagen, Denmark. I'm your host, Rebecca Knight, coasting along side of stew minimum. Of course. We're joined by Regime Mirani. He is the CTO clad platforms at Nutanix. Thank you so much for coming on the Cubans. You need >>to be here as usual. >>So you were up on the main stage talking about your guiding force. Your mission to make enterprise computing so reliable, so ubiquitous that it's invisible. >>You don't think about >>it. You don't even get a little No, I mean, look, >>if you look at any successful technology, consumer technology doesn't need to be aware of the details around it, right? I mean, take cars, even because the first introduced you probably had to understand Rick operate. There was how it all works. Remember for water in the radiator. But most people don't know how to do that today. I wouldn't know how to do that today, even though my Utah actually had to do some of those things. Um, that isn't the point. of the cars or self driving. Now the same thing should happen to computing. And we spend way too much time today just doing things that keep the light. Don't nights on. Just imagine infrastructure patching things up, grading them. I really should be something that not what idea is doing i d should be focusing on the business, delivering applications that their customers need and not so much on managing infrastructure. >>Rajiv, that one click Simplicity is so important, yet we know things are becoming even more complicated. Bring us inside a little bit that you know, you've got 14,000 customers. Guess and there's been a major, basically rewrite of a less to be able to be ready for all of the new ash cloud Native envy me obtained, you know, you name it all of these things. How do you balance getting all of this new stuff up with making sure that you keep that simplicity and don't make things for all of your customers while all the jet engines, uh, you know, >>it takes constant effort. It takes a conscious effort to make sure that things are in drifting away from our goal of being simple and to be frank. At times it has and you know, we periodically to audits off all our work floors. Make sure that as simple as you think they are and haven't drifted over time. And occasionally we do find some rail clunkers and have to go back and fix those things. What >>makes it >>different is that we start with a fairly opinionated view on how things should be done. The idea is to make it simple for 99% of the people, while still offering the all that washed options of one person power users would need them and making sure that we understand what 90% 99% of people need. And focusing on that is very important to a lot of customer focus study sort of design reviews, but also this constant going back and you're taking work feel like we m creation like provisioning of'em. When he started, it was pretty simple right then, as we started adding more and more options eyes, this thing going to use a PC I passed through isn't going to use this option. That option suddenly realized that now they're 30 things that people are feeling into provisional we have, most of which nobody cares I care about. So you go back, read I tte keep doing that again and again and again. >>So rich Eve It's one thing when you talk about living on different servers, whether it be super micro underneath or Delhi Emcee Lenovo H p e. It's >>gonna be a >>little bit different if you're talking about where you're going with H p E Green Lake with, you know, the X in AWS that you talk about when I talk to people, you know, it's like, Oh, I'm trying to use terror form and you know, But I have to write it. One way to work with Amazon. I have to write it another way. If it's, you know, azure G C P S o. You know, will Nutanix be able to keep that simplicity and bring, you know, homogeneity to thes dispersed invite? >>Absolutely. So the point is, watch a layer of abstraction right the way we are going to public cloud away we go every server winter out the way of doing things and sigh all if it starts with the hyper wiser and the story of stock and networking with three layers of abstraction. And if you have the same three components everywhere, everything we built on top of that remains exactly the same. Prison was the same on a P S. On the same. Everything looks the same. So higher level constructs like calm and so on don't have to be aware of what the actual substrate is creating a calm blueprint, whether it works on ZAY on AWS or whether Trump's on SX or whether runs on Nutanix H way. The blue blueprint remains exactly the same. Now, if you want to consume more, service is if you want to consume. So this is an Amazon, which are not available on premises. You want to use things like auto scaling groups in Ec2. Sure, you could then create blueprints that our customers we're putting in the substrate. >>So, in terms of this, you said, you start with a very opinionated place of where the customer is well, First of all, it's based on customer feedback and customer surveys. And so where were are you right now in terms of where the customer is? Are you meeting the customer now, or is the customer ahead or what? Where would you describe that? I think it >>depends on what you're looking at. If you're looking at the core products, absolutely, the customers are with us. They were ready to consume. They actually drive a lot of the innovation that we're doing. We're feeding, feeding back changes that we could be doing to make things even simpler on the private cloud side that's getting there. I think we get a lot off feedback on files on on present pro on com on on Flow because those have started getting a lot of adoption in the market, and we do get a lot of feedback on them on. So our newer products that you started a war being more recently, it's a more collaborative process. There were actually working with customers directly understanding their problems on dhe, moving a roadmap forward based on that. So while it's early in terms off adoption in production, the whole process is very collaborative in those situations. So we really are very close to the customers there. >>What are some of the biggest customer problems right now that they're facing what's what's keeping them up at night and therefore keeping you up at night? >>Security is always a big one. Complexity, people skills. All those things are big problems. In fact, one of the biggest things like that was just training enough people to handle all the complexity in a data set. Is the Morrigan removed from that? The more they don't have to focus on that, the easier you make their lives. The other thing is just a lot of time to spend on routine activities which, which acquired disruption to service is right. This is something we've talked about before. Why does it Why does it require a legacy three tier system to have maintenance windows and downtime to do an upgrade? Google our has downtime. Google is never down for maintenance. Doesn't mean they're not already there waiting all the time. So how do we bring that same kind of capabilities on premises that's gonna focus our long power? >>So, Rajiv, when I'm talking to users out there, when they talk about all of the items that are out there that they need to deal with and the routine task automation is something keeps, you know, coming up. So tell us where automation fits into some of the new things that you were talking about today in this week with your customer? >>Yeah, automation >>for us. Waking automation in three steps anything that's automatic better be safe. First of all, safety is paramount. Started security. It has to be simple, and we talked about how calm provides for that. And then you can start adding in this new wave off technologies around artificial intelligence and machine learning. And it's not so much about automation right now. It's all gone to me. It's it's autonomous operations, not just scripts. That due to a task on dhe, that's >>an area >>we invested in very heavily early on with our prison pro product way, build our own patented or thumbs for machine learning applied them to operational metrics like capacity planning. And what if modeling and dynamic alerts and what we've been doing with that is extending that more into the application layer so that not only can you apply these algorithms to CP when memory, we can actually get insights into Hey, the Leighton see on this particular application looks somewhat unusual, or the amount of cash available on a sequel server is unusually low and act on those, and the other part is acting on on alert. Something happens. There's a human being need to get in wall to solve for that. And if it does, then well, it's not really automatic. Right? So that's the other part that we introduce, which is a cross for a product which lets you define these action chains that automatically, uh, what about to be triggered when Annie went on alert takes place, they can go ahead and fix the problem. But also, you know, simple things like send your slack notification or an email locked. They went, maybe create a snapshot of your wee am so that you could go back and be back problems later. All that sort of thing made really, really simple. >>Yes, it goes back to the simplicity and the invisibility to this. >>Yes, yes. Uh, autonomous data centers, by definition, have to be invisible, right? If if if If you're to get involved in marriage and autonomous Data center, then what's the plane? It's a point. Exactly. So the whole idea is that, uh, human involvement in day to day operations against solo that everybody's focused on applications on line of business use cases. >>Rajiv, when it when it comes to those applications. You know, you talked about some of the new enhancements like envy me on and obtain, You know, Where are your customers today? You know, Are there any interesting applications that you're seeing them deploying today? Ah, Pattern. I've talked about the last couple of years of the Nutanix show, is modernized the platform and then modernized the absolute top of it. Things like container ization. I'm sure to bell curve in a journey where all the customers But you know, what are some of the patterns that air starting emergen where they finding success? >>Yeah, This >>whole wave off new applications around data pipelines with Kafka spark things like that Apache stack effectively which are putting more more off load on storage in particular. So that's that's one area. We see customers looking for more performance. But >>even, >>you know, some of the traditional ah traditional uh, applications like ASAP Hana and epic and meditate expanse. They also have patterns which can benefit greatly with some of that wants wants that we have been making and gets a technical issue. No, The size of the working said with it all fits and car and on sst was spitting on magnetic drives. But something like we've been doing is moving the overheads. If you do have a miss and you go to slow a media, you still get good performance. And that's really how we're getting good to the new. >>Well, yeah, maybe without getting, you know, we don't need to go drill down into the core of the intel chip everything. But you know, Nutanix doesn't just take off the shelf stuff and, you know, put a box together. It's software, and there's work that happens with your partners in the ecosystem. Give us a little flavor as toe. You know where you're making the investments and where some of those partnerships and integrations or a key? >>Yeah, So on the platform side, Ah, a lot of the investments happen in validation of the platforms, making sure that we're ahead of the curve in adopting technologies but also feeding back from our side things we would like to see in the platform. Right? So how do you adapt things like R d m A. To handle not just the traditional work with the happy converge workload? How do you essentially look for things in this new class? of memories that would benefit from data locality for us. So that's one class off partnership that we have the hardware vendors with GHB, with Intel, with the IBM, a whole bunch of people. But >>then >>we also have partnerships up the stock these days with companies like service. Now, with we for backup for for our mind product. I think you saw a little bit of that today. It's a whole bunch of things happening across all areas. >>One of the things that it really comes across at this conference is just how strong Nutanix culture is. The company culture, the humble, honest, hungry and another word that's creeping in now is resilient. I'm wondering if you could talk a little bit about your division of the company and describe how the company's resilience, the employees and the company itself has really displayed itself. >>So, you know, as it any company you know, Any time you go through the kind of growth we have, there's the forward momentum that everybody sees. They also a lot of setbacks that people don't really see, and they've been a whole bunch of us off these in our history. They've been areas where literally. The product has has a floor which is so fundamental we call it internally a near death experience. What's really great until again, from an engineering point of yours, how the teams come together at that point instead of these war rooms, even working weekends, Everybody's there. Everybody's on it and nobody talks about. Hey, look, where's my work? Life? Balance of things like that, especially when they're the customer in world. If there's if there's a problem that's causing customers outages, our engineers will give up everything. They'll give up everything and not just at work with their lives to make sure that gets fixed. And that has helped us get Basti setbacks get back in stride. Happens last Now. It used to happen a lot earlier, but spill this real culture resilience from the big *** in the early engineers. >>All right, Rajiv, what's exciting? You going forward? You know you don't have to touch on this one. But you know, when I saw at the end, the site clusters and hibernate feature was something that was like, Oh, yeah. I don't think I've seen that as to how I could make sure I save my data be ableto, you know, Shut things down. Maybe start there. But give us You know what a little bit. Look forward as to where the team's playing. >>Now, that's kind of, >>you know, thinking that detail thing that you have to do. What, you want to launch a new product, right? Okay, look, the whole point of doing doings, I clusters on Amazon. One of the biggest use cases. This cloud bursting cloud busting is not just about increasing your workload size, scaling it up at some point, you want to scale it down? How do you do that for state for work? Stateless. It's easy. All I'm registering Web servers over that sort of my way, they're gone. But our database that I scaled out over there well, that data can't go away. So we had to find ways to essentially solve for those from. So that's how the hibernate feature came around in general, The bigger question that you asked about, You know what I'm most excited about? I >>think this >>whole convergence of private and public cloud with same stack on both sides is a new new tank. It really hasn't existed before. Um, the father applications can now move back and forth seamlessly between public cloud and private cloud without rewriting without re factoring without a big lift and shift is very, very interesting. But by itself, it's not enough. Um, the flip that's missing is what about data movement? What about if you have your data and Amazon and I want to move it on premises? That there really are no good solutions of the Amazon doesn't give you a P eyes on dhe the tools to do that. So I think data movement's gonna be a big thing. And then Billy, a common service's tack on board because it's not just networking, storage in and compute anymore, right? If you're an Amazon, you're probably using all kinds off. Networking service is security groups. Ah, Route 53. How do you take those kind of service is and also make them available on premises. >>So, Rajiv, is there anything you've learned as a team when you look at AWS outposts or Oracle clouded customer, we've had a few years of talking about, but not a lot of deployments yet, so, you know, not saying you're late to the market, but you know what would have been able to sit back and learn from what has been done so far. >>So the >>reason we >>a little bit late to the market is that we think of solving a problem which the other windows are not, Which is kind of what I alluded to before that is that how do you support both the legacy applications on the cloud Net Cloud applications? How do you provide for migration both ways? Applications of a born in the cloud and now you want to move them on premises or applications of a born on premises and you want to move them to the Cloud Outpost is great. I think it's a good good product of technologies that AWS are thinks that hybrid is the right strategy, but it's also one problem. It's also the problem off cloud applications running on premises it does not solve for the problem of legacy applications running and cloud right, that is just a cz difficult as ever. That's that's not become any easier without force. Similarly, if you look at what we are very swing with AWS, it's also legacy applications going going to AWS. But in doing so, they don't have access to all the different networking services that AWS offers because you're not running and a sex, and you're kind of running a different networking start tonight. So with well, thought long and hard about this problem. And I said, Hey, look, we're not going to take the easy answer over here. You can take Take our stock, which is known to run both legacy and cloud native applications. If probe in that on Internet natively into Amazon so that you can use Amazon service is you can use our service is you can a legacy. Applications can run more than applications without giving up. Anything on that, I think is why signal this longer? But I think it's a more powerful solution for the long term. >>Thank you so much for coming on the Cube. It's always a pleasure having you on my back and see us again. Thanks. I'm Rebecca Knight for stew. Minutemen stay more of the cubes. Live coverage of dot Next Nutanix here in Copenhagen,

>> Hey, welcome back already, Jeffrey. Here with the Cube, we are high top San Francisco in the Salesforce Tower in the newest center offices. It's really beautiful and is part of that. They have their San Francisco innovation hubs, so it's five floors of maker's labs and three D printing and all kinds of test facilities and best practices Innovation theater and in this studio, which is really fun to be at. So we're talking about hybrid cloud in the development of cloud and multi cloud. And, you know, we're, you know, continuing on this path. Not only your customers on this path, but everyone's kind of on this path is the same kind of evolved and transformed. We're excited. Have a couple experts in the field. We got Larry Soccer. He's the global managing director of Intelligent Cloud Infrastructure Service's growth and strategy at a center. Very good to see you again. Great to be here. And the Jay Patel. He's the senior vice president and general manager, cloud provider, software business unit, being where enemies of the people are nice. Well, so, uh so first off, how you like the digs appear >> beautiful place and the fact we're part of the innovation team. Thank you for that. It's so let's just >> dive into it. So a lot of crazy stuff happening in the market place a lot of conversations about hybrid cloud, multi cloud, different cloud, public cloud movement of Back and forth from Cloud. Just wanted. Get your perspective a day. You guys have been in the Middle East for a while. Where are we in this kind of evolution? It still kind of feeling themselves out. Is it? We're kind of past the first inning, so now things are settling down. How do you kind of you. Evolution is a great >> question, and I think that was a really nice job of defining the two definitions. What's hybrid worse is multi and simply put hybrid. We look at hybrid as when you have consistent infrastructure. It's the same infrastructure, regardless of location. Multi is when you have disparate infrastructure. We're using them in a collective. So just from a level setting perspective, the taxonomy starting to get standardized industry starting to recognize hybrid is a reality. It's not a step in the long journey. It is an operating model that's gonna be exists for a long time, so it's no longer about location. It's a lot harder. You operate in a multi cloud and a hybrid cloud world and together, right extension BM would have a unique opportunity. Also, the technology provider Accenture, as a top leader in helping customers figure out where best to land their workload in this hybrid multicolored world, because workloads are driving decisions right and one of the year in this hybrid medical world for many years to come. But >> do I need another layer of abstraction? Cause I probably have some stuff that's in hybrid. I probably have some stuff in multi, right, because those were probably not much in >> the way we talked a lot about this, and Larry and I were >> chatting as well about this. And the reality is, the reason you choose a specific cloud is for those native different share capability. Abstraction should be just enough so you can make were close portable, really use the caper berry natively as possible right, and by fact, that we now with being where have a native VM we're running on every major hyper scaler, right? And on. Prem gives you that flexibility. You want off not having to abstract away the goodness off the cloud while having a common and consistent infrastructure. What tapping into the innovations that the public cloud brings. So it is a evolution of what we've been doing together from a private cloud perspective to extend that beyond the data center to really make it operating model. That's independent location, right? >> Solarium cures your perspective. When you work with customers, how do you help them frame this? I mean, I always feel so sorry for corporate CEOs. I mean, they got >> complexities on the doors are already going on >> like crazy that GDP are now, I think, right, The California regs. That'll probably go national. They have so many things to be worried about. They got to keep up on the latest technology. What's happening in containers away. I thought it was Dr Knight. Tell me it's kubernetes. I mean, it's really tough. So how >> do you help them? Kind of. It's got a shot with the foundation. >> I mean, you look at cloud, you look at infrastructure more broadly. I mean, it's there to serve the applications, and it's the applications that really drive business value. So I think the starting point has to be application lead. So we start off. We have are intelligent. Engineering guys are platform guys. You really come in and look And do you know an application modernisation strategy? So they'll do an assessment. You know, most of our clients, given their scale and complexity, usually have from 520,000 applications, very large estates, and they got to start to freak out. Okay, what's my current application's? You know, you're a lot of times I use the six R's methodology, and they say, OK, what is it that I I'm gonna retire. This I'm no longer needed no longer is business value, or I'm gonna, you know, replace this with sass. Well, you know, Yeah, if I move it to sales force, for example, or service now mattress. Ah, and then they're gonna start to look at their their workloads and say OK, you know, I don't need to re factor reform at this, you know, re hosted. You know, when one and things obviously be Emily has done a fantastic job is allowing you to re hosted using their softer to find a data center in the hyper scale er's environments >> that we called it just, you know, my great and then modernized. But >> the modern eyes can't be missed. I think that's where a lot of times you see clients kind of getting the trap Hammer's gonna migrate and then figure it out. You need to start tohave a modernisation strategy and then because that's ultimately going to dictate your multi and your hybrid cloud approaches, is how they're zaps evolve and, you know, they know the dispositions of those abs to figure out How do they get replaced? What data sets need to be adjacent to each other? So >> right, so a j you know, we were there when when Pat was with Andy and talking about, you know, Veum, Where on AWS. And then, you know, Sanjay has shown up, but everybody else's conferences a Google cloud talking about you know, Veum. Where? On Google Cloud. I'm sure there was a Microsoft show I probably missed. You guys were probably there to know it. It's kind of interesting, right from the outside looking in You guys are not a public cloud per se. And yet you've come up with this great strategy to give customers the options to adopt being We're in a public hot. And then now we're seeing where even the public cloud providers are saying here, stick this box in your data center and Frank, this little it's like a little piece of our cloud of floating around in your data center. So talk about the evolution of the strategy is kind of what you guys are thinking about because you know, you're cleared in a leadership position, making a lot of interesting acquisitions. How are you guys see this evolving? And how are you placing your bets? >> You know, that has been always consistent about this. Annie. Any strategy, whether it's any cloud, was any device, you know, any workload if you will, or application. And as we started to think about it, right, one of the big things be focused on was meeting the customer where he's out on its journey. Depending on the customer, let me simply be trying to figure out looking at the data center all the way to how the drive in digital transformation effort in a partner like Accenture, who has the breadth and depth and something, the vertical expertise and the insight. That's what customers looking for. Help me figure out in my journey. First tell me where, Matt, Where am I going and how I make that happen? And what we've done in a clever way, in many ways is we've created the market. We've demonstrated that VM where's the omen? Consistent infrastructure that you can bet on and leverage the benefits of the private or public cloud. And I You know, I often say hybrids a two way street. Now, which is you're bringing Maur more hybrid Cloud service is on Prem. And where is he? On Premise now the edge. I was talking to the centering folks and they were saying the mitral edge. So you're starting to see the workloads, And I think you said almost 40 plus percent off future workers that are gonna be in the central cloud. >> Yeah, actually, is an interesting stat out there. 20 years 2020 to 70% of data will be produced and processed outside the cloud. So I mean, the the edges about, you know, as we were on the tipping point of, you know, I ot finally taking off beyond, you know, smart meters. You know, we're gonna see a huge amount of data proliferate out there. So, I mean, the lines between public and private income literary output you look at, you know, Anthony, you know, as your staff for ages. So you know, And that's where you know, I think I am where strategy is coming to fruition >> sometime. It's great, >> you know, when you have a point of view and you stick with it >> against a conventional wisdom, suddenly end up together and then all of a sudden everyone's falling to hurt and you're like, This is great, but I >> hit on the point about the vertical ization. Every one of our client wth e different industries have very different has there and to the meeting that you know the customer, you know, where they're on their journey. I mean, if you talk to a pharmaceutical, you know, geekspeak compliance. Big private cloud started to dip their toes into public. You know, you go to minds and they're being very aggressive public. So >> every manufacturing with EJ boat back in >> the back, coming to it really varies by industry. >> And that's, you know, that's a very interesting here. Like if you look at all the ot environment. So the manufacturing we started see a lot of end of life of environment. So what's that? Next generation, you know, of control system's gonna run on >> interesting on the edge >> because and you've brought of networking a couple times where we've been talking it, you know, and as as, ah, potential gate right when I was still in the gates. But we're seeing Maura where we're at a cool event Churchill Club, when they had Xilinx micron and arm talking about, you know, shifting Maur that compute and store on these edge devices ti to accommodate, which you said, you know, how much of that stuff can you do at the adverse is putting in. But what I think is interesting is how are you going to manage that? There is a whole different level of management complexity when now you've got this different level of you're looting and security times many, many thousands of these devices all over the place. >> You might have heard >> recent announcements from being where around the carbon black acquisition right that combined with our work space one and the pulse I ot well, >> I'm now >> giving you a management framework with It's what people for things or devices and that consistency. Security on the client tied with the network security with NSX all the way to the data center, security were signed. A look at what we call intrinsic security. How do we bake and securing the platform and start solving these end to end and have a park. My rec center helped design these next generation application architectures are distributed by design. Where >> do you put a fence? You're you could put a fence around your data center, >> but your APP is using service now. Another SAS service is so hard to talk to an application boundary in the sea security model around that. It's a very interesting time. >> You hear a lot of you hear a >> lot about a partnership around softer to find data center on networking with Bello and NSX. But we're actually been spending a lot of time with the i o. T. Team and really looking at and a lot of our vision, the lines. I mean, you actually looked that they've been work similarly, agent technology with Leo where you know, ultimately the edge computing for io ti is gonna have to be containerized because you can need multiple middleware stacks supporting different vertical applications, right? We're actually you know what we're working with with one mind where we started off doing video analytics for predictive, you know, maintenance on tires for tractors, which are really expensive. The shovels, It's after we started pushing the data stream up it with a video stream up into azure. But the network became a bottleneck looking into fidelity. So we gotta process there. They're not looking autonomous vehicles which need eight megabits low laden C band with, you know, sitting at the the edge. Those two applications will need to co exist. And you know why we may have as your edge running, you know, in a container down, you know, doing the video analytics. If Caterpillar chooses, you know, Green Grass or Jasper that's going to co exist. So you see how the whole container ization that were started seeing the data center push out there on the other side of the pulse of the management of the edge is gonna be very difficult. I >> need a whole new frontier, absolutely >> moving forward. And with five g and telco. And they're trying to provide evaluated service is So what does that mean from an infrastructure perspective. Right? Right, Right. When do you stay on the five g radio network? Worse is jumping on the back line. And when do you move data? Where's his process? On the edge. Those all business decisions that need to be doing to some framework. >> You guys were going, >> we could go on. Go on, go. But I want to Don't fall upon your Segway from containers because containers were such an important part of this story and an enabler to the story. And, you know, you guys been aggressive. Move with hefty Oh, we've had Craig McCloskey, honor. He was still at Google and Dan great guys, but it's kind of funny, right? Cause three years ago, everyone's going to Dr Khan, right? I was like that were about shows that was hot show. Now doctors kind of faded and and kubernetes has really taken off. Why, for people that aren't familiar with kubernetes, they probably here to cocktail parties. If they live in the Bay Area, why's containers such an important enabler? And what's so special about Coburn? 80 specifically. >> Do you wanna go >> on the way? Don't talk about my products. I mean, if you >> look at the world is getting much more dynamics on the, you know, particularly you start to get more digitally to couple applications you started. You know, we've gone from a world where a virtual machine might have been up for months or years. Toe, You know, obviously you have containers that are much more dynamic, allowed to scale quickly, and then they need to be orchestrated. That's essential. Kubernetes does is just really starts to orchestrate that. And as we get more distributed workloads, you need to coordinate them. You need to be able to scale up as you need it for performance, etcetera. So kubernetes an incredible technology that allows you really to optimize, you know, the placement of that. So just like the virtual machine changed, how we compute containers now gives us a much more flexible portable. You know that, you know you can run on anything infrastructure, any location, you know, closer to the data, et cetera. To do that. And I >> think the bold movie >> made is, you know, we finally, after working with customers and partners like century, we have a very comprehensive strategy. We announced Project Enzo, a philosophy in world and Project tansy really focused on three aspects of containers. How do you build applications, which is pivotal in that mansion? People's driven around. How do we run these arm? A robust enterprise class run time. And what if you could take every V sphere SX out there and make it a container platform? Now we have half a million customers. 70 million be EMS, all of sudden that run time. We're continue enabling with the Project Pacific Soviets. Year seven becomes a commonplace for running containers, and I am so that debate of'em czar containers done gone well, one place or just spin up containers and resource is. And then the more important part is How do I manage this? You said, becoming more of a platform not just an orchestration technology, but a platform for how do I manage applications where I deploy them where it makes most sense, right? Have decoupled. My application needs from the resource is, and Coburn is becoming the platform that allows me to port of Lee. I'm the old job Web logic guy, right? >> So this is like distributed Rabb logic job on steroids, running across clouds. Pretty exciting for a middle where guy This is the next generation and the way you just said, >> And two, that's the enabling infrastructure that will allow it to roll into future things like devices. Because now you've got that connection >> with the fabric, and that's working. Becomes a key part of one of the key >> things, and this is gonna be the hard part is optimization. So how do we optimize across particularly performance, but even costs? >> You're rewiring secure, exact unavailability, >> Right? So still, I think my all time favorite business book is Clayton Christians. An innovator's dilemma. And in one of the most important lessons in that book is What are you optimizing four. And by rule, you can't optimize for everything equally you have to you have to rank order. But what I find really interesting in this conversation in where we're going in the complexity of the throughput, the complexity of the size of the data sets the complexity of what am I optimizing for now? Just begs for applied a I or this is not This is not a people problem to solve. This is this >> is gonna be all right. So you look at >> that, you know, kind of opportunity to now apply A I over the top of this thing opens up tremendous opportunity. >> Standardize infrastructural auditory allows you to >> get more metrics that allows you to build models to optimize infrastructure over time. >> And humans >> just can't get their head around me because you do have to optimize across multiple mentions. His performances cost, but then that performances gets compute. It's the network, I mean. In fact, the network's always gonna be the bottlenecks. You look at it even with five G, which is an order of magnitude, more bandwidth from throughput, the network will still lag. I mean, you go back to Moore's Law, right? It's Ah, even though it's extended to 24 months, price performance doubles. The amount of data potentially can kick in and you know exponentially grow on. Networks don't keep pays, so that optimization is constantly going to be tuned. And as we get even with increases in network, we have to keep balancing that right. >> But it's also the business >> optimization beyond the infrastructure optimization. For instance, if you're running a big power generation field of a bunch of turbines, right, you may wanna optimize for maintenance because things were running at some steady state. But maybe there's oil crisis or this or that. Suddenly the price, right? You're like, forget the maintenance. Right now we've got you know, we >> got a radio controlled you start about other >> than a dynamic industry. How do I really time change the behavior, right? Right. And more and more policy driven. Where the infrastructure smart enough to react based on the policy change you made. >> That's the world we >> want to get to. And we're far away from that, right? >> Yeah. I mean, I think so. Ultimately, I think the Cuban honeys controller gets an A I overlay and the operators of the future of tuning the Aye aye engines that optimizing, >> right? Right. And then we run into the whole thing, which we've talked about many times in this building with Dr Room, A child re from a center. Then you got the whole ethics overlay on top of the thing. That's a whole different conversation from their day. So before we wrap kind of just want to give you kind of last thoughts. Um, as you know, customers Aaron, all different stages of their journey. Hopefully, most of them are at least at least off the first square, I would imagine on the monopoly board What does you know, kind of just top level things that you would tell people that they really need just to keep always at the top is they're starting to make these considerations, starting to make these investments starting to move workloads around that they should always have kind of top >> of mind. For me, it's very simple. It's really about focused on the business outcome. Leverage the best resource for the right need and design. Architectures are flexible that give you a choice. You're not locked in and look for strategic partners with this technology partners or service's partners that alive you to guide because the complexities too high the number of choices that too high. You need someone with the breath in depth to give you that platform in which you can operate on. So we want to be the digital kind of the ubiquitous platform. From a software perspective, Neck Centuries wants to be that single partner who can help them guide on the journey. So I think that would be my ask. It's not thinking about who are your strategic partners. What is your architecture and the choices you're making that gave you that flexibility to evolve. Because this is a dynamic market. What should make decisions today? I mean, I'll be the one you need >> six months even. Yeah. And And it's And that that dynamic that dynamics is, um is accelerating if you look at it. I mean, we've all seen change in the industry of decades in the industry, but the rate of change now the pace, you know, things are moving so quickly. >> I mean, little >> respond competitive or business or in our industry regulations, right. You have to be prepared for >> Yeah. Well, gentlemen, thanks for taking a few minutes and ah, great conversation. Clearly, you're in a very good space because it's not getting any less complicated in >> Thank you. Thank you. All right. Thanks, Larry. Ajay, I'm Jeff. You're watching the Cube. >> We are top of San Francisco in the Salesforce Tower at the center Innovation hub. Thanks for watching. We'll see next time. Quick

>> Live from Stanford University. It's the Cube covering global Women in Data Science conference brought to you by Silicon Angle media. >> Welcome back to the key. We air live at Stanford University for the fourth annual Women in Data Science Conference. The Cube has had the pleasure of being here all four years on I'm welcoming Back to the Cube, one of our distinguished alumni Janet George, the fellow chief data officer, scientists, big data and cognitive computing at Western Digital. Janet, it's great to see you. Thank you. Thank you so much. So I mentioned yes. Fourth, Annie will women in data science. And it's been, I think I met you here a couple of years ago, and we look at the impact. It had a chance to speak with Margo Garrett's in a about an hour ago, one of the co founders of Woods saying, We're expecting twenty thousand people to be engaging today with the Livestream. There are wigs events in one hundred and fifty locations this year, fifty plus countries expecting about one hundred thousand people to engage the attention. The focus that they have on data science and the opportunities that it has is really palpable. Tell us a little bit about Western Digital's continued sponsorship and what makes this important to you? >> So Western distal has recently transformed itself as a company, and we are a data driven company, so we are very much data infrastructure company, and I think that this momentum off A is phenomenal. It's just it's a foundational shift in the way we do business, and this foundational shift is just gaining tremendous momentum. Businesses are realizing that they're going to be in two categories the have and have not. And in order to be in the half category, you have started to embrace a You've got to start to embrace data. You've got to start to embrace scale and you've got to be in the transformation process. You have to transform yourself to put yourself in a competitive position. And that's why Vest Initial is here, where the leaders in storage worldwide and we'd like to be at the heart of their data is. >> So how has Western Digital transform? Because if we look at the evolution of a I and I know you're give you're on a panel tan, you're also giving a breakout on deep learning. But some of the importance it's not just the technical expertise. There's other really important skills. Communication, collaboration, empathy. How has Western digital transformed to really, I guess, maybe transform the human capital to be able to really become broad enough to be ableto tow harness. Aye, aye, for good. >> So we're not just a company that focuses on business for a We're doing a number of initiatives One of the initiatives were doing is a I for good, and we're doing data for good. This is related to working with the U. N. We've been focusing on trying to figure out how climate change the data that impacts climate change, collecting data and providing infrastructure to store massive amounts of species data in the environment that we've never actually collected before. So climate change is a huge area for us. Education is a huge area for us. Diversity is a huge area for us. We're using all of these areas as launching pad for data for good and trying to use data to better mankind and use a eye to better mankind. >> One of the things that is going on at this year's with second annual data fun. And when you talk about data for good, I think this year's Predictive Analytics Challenge was to look at satellite imagery to train the model to evaluate which images air likely tohave oil palm plantations. And we know that there's a tremendous social impact that palm oil and oil palm plantations in that can can impact, such as I think in Borneo and eighty percent reduction in the Oregon ten population. So it's interesting that they're also taking this opportunity to look at data for good. And how can they look at predictive Analytics to understand how to reduce deforestation like you talked about climate and the impact in the potential that a I and data for good have is astronomical? >> That's right. We could not build predictive models. We didn't have the data to put predictive boats predictive models. Now we have the data to put put out massively predictive models that can help us understand what change would look like twenty five years from now and then take corrective action. So we know carbon emissions are causing very significant damage to our environment. And there's something we can do about it. Data is helping us do that. We have the infrastructure, economies of scale. We can build massive platforms that can store this data, and then we can. Alan, it's the state at scale. We have enough technology now to adapt to our ecosystem, to look at disappearing grillers, you know, to look at disappearing insects, to look at just equal system that be living, how, how the ecosystem is going to survive and be better in the next ten years. There's a >> tremendous amount of power that data for good has, when often times whether the Cube is that technology conferences or events like this. The word trust issues yes, a lot in some pretty significant ways. And we often hear that data is not just the life blood of an organization, whether it's in just industry or academia. To have that trust is essential without it. That's right. No, go. >> That's right. So the data we have to be able to be discriminated. That's where the trust comes into factor, right? Because you can create a very good eh? I'm odder, or you can create a bad air more so a lot depends on who is creating the modern. The authorship of the model the creator of the modern is pretty significant to what the model actually does. Now we're getting a lot of this new area ofthe eyes coming in, which is the adversarial neural networks. And these areas are really just springing up because it can be creators to stop and block bad that's being done in the world next. So, for example, if you have malicious attacks on your website or hear militias, data collection on that data is being used against you. These adversarial networks and had built the trust in the data and in the so that is a whole new effort that has started in the latest world, which is >> critical because you mentioned everybody. I think, regardless of what generation you're in that's on. The planet today is aware of cybersecurity issues, whether it's H vac systems with DDOS attacks or it's ah baby boomer, who was part of the fifty million Facebook users whose data was used without their knowledge. It's becoming, I won't say accepted, but very much commonplace, Yes, so training the A I to be used for good is one thing. But I'm curious in terms of the potential that individuals have. What are your thoughts on some of these practices or concepts that we're hearing about data scientists taking something like a Hippocratic oath to start owning accountability for the data that they're working with. I'm just curious. What's >> more, I have a strong opinion on this because I think that data scientists are hugely responsible for what they are creating. We need a diversity of data scientists to have multiple models that are completely divorce, and we have to be very responsible when we start to create. Creators are by default, have to be responsible for their creation. Now where we get into tricky areas off, then you are the human auto or the creator ofthe Anay I model. And now the marshal has self created because it a self learned who owns the patent, who owns the copyright to those when I becomes the creator and whether it's malicious or non malicious right. And that's also ownership for the data scientist. So the group of people that are responsible for creating the environment, creating the morals the question comes into how do we protect the authors, the uses, the producers and the new creators off the original piece of art? Because at the end of the day, when you think about algorithms and I, it's just art its creation and you can use the creation for good or bad. And as the creation recreates itself like a learning on its own with massive amounts of data after an original data scientist has created the model well, how we how to be a confident. So that's a very interesting area that we haven't even touched upon because now the laws have to change. Policies have to change, but we can't stop innovation. Innovation has to go, and at the same time we have to be responsible about what we innovate >> and where do you think we are? Is a society in terms of catching As you mentioned, we can't. We have to continue innovation. Where are we A society and society and starting to understand the different principles of practices that have to be implemented in order for proper management of data, too. Enable innovation to continue at the pace that it needs. >> June. I would say that UK and other countries that kind of better than us, US is still catching up. But we're having great conversations. This is very important, right? We're debating the issues. We're coming together as a community. We're having so many discussions with experts. I'm sitting in so many panels contributing as an Aye aye expert in what we're creating. What? We see its scale when we deploy an aye aye, modern in production. What have we seen as the longevity of that? A marker in a business setting in a non business setting. How does the I perform and were now able to see sustained performance of the model? So let's say you deploy and am are in production. You're able inform yourself watching the sustained performance of that a model and how it is behaving, how it is learning how it's growing, what is its track record. And this knowledge is to come back and be part of discussions and part of being informed so we can change the regulations and be prepared for where this is going. Otherwise will be surprised. And I think that we have started a lot of discussions. The community's air coming together. The experts are coming together. So this is very good news. >> Theologian is's there? The moment of Edward is building. These conversations are happening. >> Yes, and policy makers are actively participating. This is very good for us because we don't want innovators to innovate without the participation of policymakers. We want the policymakers hand in hand with the innovators to lead the charter. So we have the checks and balances in place, and we feel safe because safety is so important. We need psychological safety for anything we do even to have a conversation. We need psychological safety. So imagine having a >> I >> systems run our lives without having that psychological safety. That's bad news for all of us, right? And so we really need to focus on the trust. And we need to focus on our ability to trust the data or a right to help us trust the data or surface the issues that are causing the trust. >> Janet, what a pleasure to have you back on the Cube. I wish we had more time to keep talking, but it's I can't wait till we talk to you next year because what you guys are doing and also your pact, true passion for data science for trust and a I for good is palpable. So thank you so much for carving out some time to stop by the program. Thank you. It's my pleasure. We want to thank you for watching the Cuba and Lisa Martin live at Stanford for the fourth annual Women in Data Science conference. We back after a short break.