>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome to the Cube's coverage of HP Discover 2020 Virtual Experience. I'm Lisa Martin, and I'm pleased to be joined by two guests from HP longtime partner Tech Data. We have calling Blair the vice president of sales and marketing of I. O. T. And Data Solutions and David Smith, H P E Pre Sales Field Solutions are common. And David, Welcome to the Cube. Thanks, Lisa. Great to see. So let's start with the calling. HP and Technical have been partners for over 40 years, but tell our audience a little bit about tech data before we get into the specifics of what you're doing and some of the cool I o. T. Stuff with HP. I >>think that the Tech data is a Fortune 100 distributor. We continued to evolved to be a solutions aggregator in these next generation technology businesses. As you've mentioned, we've been serving the I T distribution markets globally for for 40 plus years, and we're now moving into next generation technologies like Wild Analytics, I O. T and Security bubble Lifecycle Management services. But to be able todo position ourselves with our customer base and the needs of their clients have. So I'm excited to be here today to talk a little bit about what we're doing in I, O. T. And Analytics with David on the HPC side >>and in addition to the 40 plus years of partnership calling that you mentioned that Detected and HP have you've got over 200 plus hp. Resource is David, you're one of those guys in the field. Talk to us about some of the things that you're working on with Channel Partners Table David to enable them, especially during such crazy times of living and now >>absolutely, absolutely so. What we can do is we can provide strong sales and technical enablement if your team, for example, wants to better understand how to position HP portfolio if they require assistance and architect ing a secure performance i o t. Solution. We can help ensure that you're technical team is fully capable of having that conversation, and it's one that they're able to have of confidence, weaken validate the proposed HP solutions with the customers, technical requirements and proposed use case. We can even exist on a customer calls, if it would, would benefit our partner to kind of extend out to that. We also have a a a deep technical bench that Colin can speak to in the OT space toe lean on as well. For so solution is that kind of span into the space beyond where HP typically operates, which would be edge, compute computing and network. Sic security. >>Excellent call and tell me a little bit about Tech Data's investments in I o. T. When did this start? What are you guys doing today? >>Sure, we started in the cloud space. First tackle this opportunity in data center modernization and hybrid cloud. That was about seven years ago. Shortly thereafter we started investing very materially in the security cyber security space. And then we follow that with Data Analytics and then the Internet of things. Now we've been in those spaces with our long term partners for some time. But now that we're seeing this movement to the intelligent edge and a real focus on business outcomes and specialization, we've kind of tracked with the market, and we feel like we've invested a little bit ahead of where the channel is in terms of supporting our ecosystem of partners in this space. >>So the intelligent edge has been growing for quite some time. Poland in the very unique times that we're living in in 2020 how are you seeing that intelligent edge expand even more? And what are some of the pressing opportunities that tech data and HPC i O T solutions together can address? >>So a couple. So the first is a Xai mentioned earlier just data center modernization. And so, in the middle of code 19 and perhaps postcode 19 we're going to see a lot of clients that are really focused on monetizing the things that they've got. But doing so to drive business outcomes. We believe that increasingly, the predominance of use cases and compute and analytics is going to move to the edge. And HP has got a great portfolio for not just on premise high performance computing but also hybrid cloud computing. And then when we get into the edge with edge line and networking with Aruba and devices that need to be a digitized and sense arised, it's a really great partnership. And then what we're able to do also, Lisa, is we've been investing in vertical markets since 2000 and seven, and I've been a long the ride with that team, most all of that way. So we've got deep specialization and healthcare and industrial manufacturing, retail and then public sector. And then the last thing we've kind of turned on here recently just last month is a strategic partnership in the smarter cities space. So we're able to leverage a lot of those vertical market capabilities. Couple that with our HP organization and really drive specialized repeatable solutions in these vertical markets, where we believe increasingly, customers are going to be more interested in a repeatable solutions that can drive quick proof of value proof of concepts with minimal viable what kinds of products. And that's that's kind of the apartment today with RHB Organization and the HP Corporation >>David. Let's double click into some of those of vertical markets that Colin mentioned some of the things that pop into minor healthcare manufacturing. As we know, supply chains have been very challenged during covered. Give us an insight into what you're hearing from channel partners now virtually, but what are some of the things that are pressing importance? >>So from a pressing and important to Collins exact point, and your exact point as well is really it's all about the edge computing space now from a product perspective Azaz Colin had mentioned earlier. HP has their edge line converged systems, which is kind of taking the functionality of OT and edge T Excuse me of OT and I t and combine it into a single edge processing compute solution. You kind of couple that with the ability to configure components such as Tesla GP, use in specific excellent offerings to offer an aid and things like realtime, video processing and analytics. Uh, and a perfect example of this is, ah so for dissing and covert space. If if I need to be able to analyze a group of people to ensure they're staying as far apart as possible or, you know within self distant guidelines, that is where kind of the real time that's like an aspect of things can be taken advantage of same things with with the leveraging cameras where you could actually take temperature detection as as well, so it's really kind of best to think of Edge Lines Solutions is data center computing at the edge kind of transition into the Aruba space. Uh Rubio says offerings aid in the island Security is such a clear pass device inside, which allows for device discovery of network and monitoring of wired and wireless devices. There's also Aruba asset tracking and real time location of solutions, and that's particularly important in the healthcare space as well. If I have a lot of high value assets, things like wheelchairs, things like ventilation devices, where these things low located within my facilities and how can I keep keep track of them? They also, and by that I mean HP. They also kind of leveraging expanse ecosystem of partners. As an example, they leverage thing works allow their i o t solutions as well, when you kind of tying it all together with HP Point. Next to the end, customers provided with comprehensive loyalty solution. >>So, Colin, how ready? Our channel partners and the end user customers to rapidly pivot and start either deploying more technologies at the edge to be able to deliver some of the capabilities that David talked about in terms of analytics and sensors for social distancing. How ready are the channel partners and customers to be able to understand, adopt and execute this technology. >>So I think on the understanding side, I think the partners are there. We've been talking about digital transformation in the channel for a couple of years now, and I think what's happened through the 19 Pandemic is that it's been a real spotlight on the need for those business outcomes to to solve for very specific problems. And that's one of the values that we serve in the channel. So we've got a solution offering that we call our solution factory. And what we do really says is we leverage a process to look outside the industry. At Gartner, Magic Quadrant Solutions forced a Wave G two crowd. You know, top leaders, visionaries and understand What are those solutions that are in demand in these vertical markets that we talked about? And then we do a lot of work with David and his team internally in the HP organization to be able to do that and then build out that reference architectures so that we know that there's a solution that drives a bill of materials and a reference architecture that's going to work that clients are going to need and then we can do it quickly. You know, Tech data. Everything's about being bold, acting now getting scale. And we've got a large ecosystem partners that already have great relationships. So we pride ourselves on being able to identify what are those solutions that we can take to our partners that they can quickly take to their end users where you know we've We've kind of developed out what we think the 70 or 80% of that solution is going to look like. And then we drive point next and other services capabilities to be able to complete that last mile, if you will, of some of the customization. So we're helping them. For those who aren't ready, we're helping them. For those who already have very specific use cases and a practice that they drive with repeatable solutions were coming alongside them and understanding. What can we do? Using a practice builder approach, which is our consultative approach to understand where our partners are going in the market, who their clients are, what skill sets do they have? What supplier affinities do they want to drive? What brand marketing or demand generation support do they need? And that's where we can take some of these solutions, bring them to bear and engage in that consultative engagement to accelerate being ready as, as you rightly say, >>so tech. It has a lot of partners. You in general. You also have a lot of partners in the i o T space calling What? How do you from a marketing hat perspective? How do you describe the differentiation that Tech data and HP ease Iot solutions delivered to the channel to the end user? >>A couple of different things? I think that's that's differentiation. And that's one of the things that we strive for in the channel is to be specialized and to be competitively differentiated. And so the first part, I say to all of my team, Lisa, is you know, whether it's our solution consultants or our technical consultants, our solutions to the developers or the software development team that works my organization. Our goal is to be specialized in such a way that we're having relevant value added conversations not only our channel partners, but also end users of our partners want to bring us into those conversations, and many do. The next is really education and enablement as you would expect. And so there's a lot of things that are specialized in our technical. We drive education certification programs, roadshows, seminars, one of the things that we're seeing a lot of interest now. Lisa is for a digital marketing, and we're driving. Some really need offerings around digital marketing platforms that not only educate our partners but also allow our partners to bring their end users and tour some of this some of these technologies. So whether it's at our Clearwater office, where we've got an I. O T. Solution center, that we we take our partners and their clients through or we're using our facilities Teoh to do executive briefings and ideation as a service that, you know, kind of understanding the art of the possible. With both our resellers and their clients work, we're using our solution. Our solution catalogs that we've built an interactive pdf that allows our partners to understand over 50 solutions that we've got and then be able to identify. Where would they like to bring in David and his team and then my consultants to do that, that deep planning on business development, uh, that we talked about a little bit earlier. >>So the engagement right now is maybe even more important than it has been in a while because it's all hands off and virtual David. Talk to me about some of the engagement and the enablement piece that call and talked about. How are you able to really keep a channel partner and their end user customers engaged and interested in what you're able to deliver through this from New Virtual World? >>That's a great, great question. And we work in conjunction with our marketing teams to make sure that as new technologies and quite in I O. T space as well as within the HP East base as well that that our channel partners are educated and aware that these solutions exist. I know for a fact that for the majority of them you kind of get this consistent bombardment of new technology. But being able to actually have someone go out and explain it and then being able to correspondingly position it's use case and it's functionality and why it would provide value for your end customer is one of the benefits of tech data ads to kind of build upon that previous statement. The fact that We have such a huge portfolio of partners, so you kind of have HP and the edge compute space. But we have so many different partners in the OT space where it's really just a phone call, an email, a Skype message, a way to have that conversation around interoperability and then provide those responses back to our partners. >>Excellent. One more question before we go. Colin for you, A lot of partners. Why HP fry Mt. >>So a couple of reasons? One of the one of the biggest reasons as HP is just a great partner. And so when you look at evaluating I. O. T solutions that tend to be pretty comprehensive in many cases, Lisa it takes 10 or 12 partners to complete a really i o t solution and address that use case that that's in the field. And so when you have a partner like HP who's investing in these programs, investing in demand generation, investing in the spectrum of technology, whether it's hybrid Cloud Data Center, compute storage or your edge devices and Iot gateways, then to be able to contextualize those into what we call market ready solutions in each one of these vertical markets where there's references and there's use cases. And there were coupling education that specific rest of solutions. You know HP can do all of those things, and that's very important. Because in this new world, no one can go it alone anymore. It takes it takes partnerships, and we're all better together. And HP really does embrace that philosophy. And they've been a great partner for us in the Iot space. >>Excellent. Well, Colin and David, thank you so much for joining me today on the Cube Tech data. H p e i o t better together. Thank you so much. It's been a pleasure talking with you. >>Thank you. >>Thank you. Lisa. >>And four Collet and David. I am Lisa Martin. You're watching the Cube's virtual coverage of HP Discover 2020. Thanks for watching. Yeah, yeah, yeah, yeah.

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Good afternoon everyone and welcome back to the cubes live coverage of Microsoft ignite 26,000 people here at this conference at the orange County convention center. I'm your host, Rebecca Knight, alongside my cohost Stu Miniman. We are joined by Seth Juarez. He is the cloud developer advocate at Microsoft. Thank you so much for coming on the show. >>Glad to be here. You have such a lovely sad and you're lovely people. We just met up. You don't know any better? No. Well maybe after after the end of the 15 minutes we'll have another discussion. >>You're starting off on the right foot, so tell us a little bit about what you do. You're also a host on channel nine tell us about your role as a, as a cloud developer. >>So a cloud advocate's job is primarily to help developers be successful on Azure. My particular expertise lies in AI and machine learning and so my job is to help developers be successful with AI in the cloud, whether it be developers, data scientists, machine learning engineers or whatever it is that people call it nowadays. Because you know how the titles change a lot, but my job is to help them be successful and sometimes what's interesting is that sometimes our customers can't find success in the cloud. That's actually a win for me too because then I have a deep integration with the product group and my job is to help them understand from a customer perspective what it is they need and why. So I'm like the ombudsman so to speak because the product groups are the product groups. I don't report up to them. So I usually go in there and I'm like, Hey, I don't report to any of you, but this is what the customers are saying. >>We are very keen on being customer centered and that's why I do what I do. >> Seth, I have to imagine when you're dealing with customers, some of that skills gap and learning is something that they need to deal with. You know, we've been hearing for a long time, you know, there's not enough data scientists, you know, we need to learn these environments. Satya Nadella spent a lot of time talking about the citizen developers out there. So you know H bring us inside the customers you're talking to, you know, kind of, where do you usually start and you know, how do they pull the right people in there or are they bringing in outside people a little bit? Great organization, great question. It turns out that for us at Microsoft we have our product groups and then right outside we have our advocates that are very closely aligned to the product groups. >>And so anytime we do have an interaction with a customer, it's for the benefit of all the other customers. And so I meet with a lot of customers and I don't, I'm to get to talk about them too much. But the thing is I go in there, I see what they're doing. For example, one time I went to the touring Institute in the UK. I went in there and because I'm not there to sell, I'm there to figure out like what are you trying to do and does this actually match up? It's a very different kind of conversation and they'd tell me about what they're working on. I tell them about how we can help them and then they tell me where the gaps are or where they're very excited and I take both of those pieces of feedback to the, to the product group and they, they just love being able to have someone on the ground to talk to people because sometimes you know, when work on stuff you get a little siloed and it's good to have an ombudsman so to speak, to make sure that we're doing the right thing for our customers. >>As somebody that works on AI. You must've been geeking out working, working with the Turing Institute though. Oh yeah. Those people are absolutely wonderful and it was like as I was walking in, a little giddy, but the problems that they're facing in AI are very similar. The problems that people at the other people doing and that are in big organizations, other organizations are trying to onboard to AI and try to figure out, everyone says I need to be using this hammer and they're trying to hammer some screws in with the hammer. So it's good to figure out when it's appropriate to use AI and when it isn't. And I also have customers with that >>and I'm sure the answer is it depends in terms of when it's appropriate, but do you have any sort of broad brush advice for helping an organization determine is is this a job for AI? Absolutely. >>That's uh, it's a question I get often and developers, we have this thing called the smell that tells us if a code smell, we have a code smell tells us, maybe we should refactor, maybe we should. For me, there's this AI smell where if you can't precisely figure out the series of steps to execute an algorithm and you're having a hard time writing code, or for example, if every week you need to change your if L statements or if you're changing numbers from 0.5 to 0.7 and now it works, that's the smell that you should think about using AI or machine learning, right? There's also a set of a class of algorithms that, for example, AI, it's not that we've solved, solved them, but they're pretty much solved. Like for example, detecting what's in an image, understanding sentiment and text, right? Those kinds of problems we have solutions for that are just done. >>But if you have a code smell where you have a lot of data and you don't want to write an algorithm to solve that problem, machine learning and AI might be the solution. Alright, a lot of announcements this week. Uh, any of the highlights for from your area. We last year, AI was mentioned specifically many times now with you know, autonomous systems and you know it feels like AI is in there not necessarily just you know, rubbing AI on everything. >> I think it's because we have such a good solution for people building custom machine learning that now it's time to talk about the things you can do with it. So we're talking about autonomous systems. It's because it's based upon the foundation of the AI that we've already built. We released something called Azure machine learning, a set of tools called in a studio where you can do end and machine learning. >>Because what what's happening is most data scientists nowadays, and I'm guilty of this myself, we put stuff in things called Jupiter notebooks. We release models, we email them to each other, we're emailing Python files and that's kinda like how programming was in 1995 and now we're doing is we're building a set of tools to allow machine learning developers to go end to end, be able to see how data scientists are working and et cetera. For example, let's just say you're a data scientist. Bill. Did an awesome job, but then he goes somewhere else and Sally who was absolutely amazing, comes in and now she's the data scientist. Usually Sally starts from zero and all of the stuff that bill did is lost with Azure machine learning. You're able to see all of your experiments, see what bill tried, see what he learned and Sally can pick right up and go on. And that's just doing the experiments. Now if you want to get machine learning models into production, we also have the ability to take these models, version them, put them into a CIC, D similar process with Azure dev ops and machine learning. So you can go from data all the way to machine learning in production very easily, very quickly and in a team environment, you know? And that's what I'm excited about mostly. >>So at a time when AI and big and technology companies in general are under fire and not, Oh considered to not always have their users best interests at heart. I'd like you to talk about the Microsoft approach to ethical AI and responsible AI. >>Yeah, I was a part of the keynote. Scott Hanselman is a very famous dab and he did a keynote and I got to form part of it and one of the things that we're very careful even on a dumb demo or where he was like doing rock paper, scissors. I said, and Scott, we were watching you with your permission to see like what sequence of throws you were doing. We believe that through and through all the way we will never use our customers' data to enhance any of our models. In fact, there was a time when we were doing like a machine learning model for NLP and I saw the email thread and it's like we don't have language food. I don't remember what it was. We don't have enough language food. Let's pay some people to ethically source this particular language data. We will never use any of our customer's data and I've had this question asked a lot. >>Like for example, our cognitive services which have built in AI, we will never use any of our customer's data to build that neither. For example, if we have, for example, we have a custom vision where you upload your own pictures, those are your pictures. We're never going to use them for anything. And anything that we do, there's always consent and we want to make sure that everyone understands that AI is a powerful tool, but it also needs to be used ethically. And that's just on how we use data for people that are our customers. We also have tools inside of Azure machine learning to get them to use AI. Ethically. We have tools to explain models. So for example, if you very gender does the model changes prediction or if you've very class or race, is your model being a little iffy? We allow, we have those tools and Azure machine learning, so our customers can also be ethical with the AI they build on our platform. So we have ethics built into how we build our models and we have ethics build into how our customers can build their models too, which is to me very. >>And is that a selling point? Are customers gravitating? I mean we've talked a lot about it on the show. About the, the trust that customers have in Microsoft and the image that Microsoft has in the industry right now. But the idea that it is also trying to perpetuate this idea of making everyone else more ethical. Do you think that that is one of the reasons customers are gravitate? >>I hope so. And as far as a selling point, I absolutely think it's a selling point, but we've just released it and so I'm going to go out there and evangelize the fact that not only are we as tickle with what we do in AI, but we want our customers to be ethical as well. Because you know, trust pays, as Satya said in his keynote, tra trust the enhancer in the exponent that allows tech intensity to actually be tech intensity. And we believe that through and through not only do believe it for ourselves, but we want our customers to also believe it and see the benefits of having trust with our customers. One of the things we, we talked to Scott Hanselman a little bit yesterday about that demo is the Microsoft of today isn't just use all the Microsoft products, right? To allow you to use, you know, any tool, any platform, you know, your own environment, uh, to tell us how that, that, that plays into your world. >>It's, you know, like in my opinion, and I don't know if it's the official opinion, but we are in the business of renting computer cycles. We don't care how you use them, just come into our house and use them. You wanna use Java. We've recently announced a tons of things with spraying. We're become an open JDK contributor. You know, one of my colleagues, we're very hard on that. I work primarily in Python because it's machine learning. I have a friend might call a friend and colleague, David Smith who works in our, I have other colleagues that work in a number of different languages. We don't care. What we are doing is we're trying to empower every organization and every person on the planet to achieve more where they are, how they are, and hopefully bring a little bit of of it to our cloud. >>What are you doing that, that's really exciting to you right now? I know you're doing a new.net library. Any other projects that are sparking your end? >>Yeah, so next week I'm going to France and this is before anyone's going to see this and there is a, there is a company, I think it's called surf, I'll have to look it up and we'll put it in the notes, but they are basically trying to use AI to be more environmentally conscious and they're taking pictures of trash and rivers and they're using AI to figure out where it's coming from so they can clean up environment. I get to go over there and see what they're doing, see how I can help them improvement and promote this kind of ethical way of doing AI. We also do stuff with snow leopards. I was watching some Netflix thing with my kids and we were watching snow leopards and there was like two of them. Like this is impressive because as I'm watching this with my kids, I'm like, Hey we are at Microsoft, we're helping this population, you know, perpetuate with AI. >>And so those are the things it's actually a had had I've seen on TV is, you know, rather than spending thousands of hours of people out there, the AI can identify the shape, um, you know, through the cameras. So they're on a, I love that powerful story to explain some of those pieces as opposed to it. It's tough to get the nuance of what's happening here. Absolutely. With this technology, these models are incredibly easy to build on our platform. And, and I and I st fairly easy to build with what you have. We love people use TensorFlow, use TensorFlow, people use pie torch. That's great cafe on it. Whatever you want to use. We are happy to let you use a rent out our computer cycles because we want you to be successful. Maybe speak a little bit of that when you talk about, you know, the, the cloud, one of the things is to democratize, uh, availability of this. >>There's usually free tiers out there, especially in the emerging areas. Uh, you know, how, how is Microsoft helping to get that, that compute and that world technology to people that might not have had it in the past? I was in, I was in Peru a number of years ago and I and I had a discussion with someone on the channel nine show and it was absolutely imp. Like I under suddenly understood the value of this. He said, Seth, if I wanted to do a startup here in Peru, right, and it was a capital Peru, like a very industrialized city, I would have to buy a server. It would come from California on a boat. It would take a couple of months to get here and then it would be in a warehouse for another month as it goes through customs. And then I would have to put it into a building that has a C and then I could start now sat with a click of a button. >>I can provision an entire cluster of machines on Azure and start right now. That's what, that's what the cloud is doing in places like Peru and places that maybe don't have a lot of infrastructure. Now infrastructure is for everyone and maybe someone even in the United States, you know, in a rural area that doesn't, they can start up their own business right now anywhere. And it's not just because it's Peru, it's not just because it's some other place that's becoming industrialized. It's everywhere. Because any kid with a dream can spin up an app service and have a website done in like five minutes. >>So what does this mean? I mean, as you said, any, any kid, any person or rural area, any developing country, what does this mean in five or 10 years from now in terms of the future of commerce and work and business? >>Honestly, some people feel like computers are art, stealing, you know, human engineering. I think they are really augmenting it. Like for example, I don't have to, if I want to know something for her. Back when, when I was a kid, I had to, if I want to know something, sometimes I had to go without knowing where like I guess we'll never know. Right? And then five years later we're like, okay, we found out it was that a character on that show, you know? And now we just look at our phone. It's like, Oh, you were wrong. And I like not knowing that I'm wrong for a lot longer, you know what I'm saying? But nowadays with our, with our phones and with other devices, we have information readily available so that we can make appropriate response, appropriate answers to questions that we have. AI is going to help us with that by augmenting human ingenuity, by looking at the underlying structure. >>We can't, for example, if you look at, if you look at an Excel spreadsheet, if it's like five rows and maybe five columns, you and I as humans can look at and see a trend. But what if it's 10 million rows and 5,000 columns? Our ingenuity has been stretched too far, but with computers now we can aggregate, we can do some machine learning models, and then we can see the patterns that the computer found aggregated, and now we can make the decisions we could make with five columns, five rows, but it's not taking our jobs. It's augmenting our capacity to do the right thing. >>Excellent. We'll assess that. Thank you so much for coming on the Cuba. Really fun conversation. >>Glad to be here. Thanks for having me. >>Alright, I'm Rebecca Knight for Stu minimun. Stay tuned for more of the cubes live coverage of Microsoft ignite.