Jon Hyde: Hello, and welcome back to The Next Horizon. A Dell Technologies podcast. I’m John Hyde, the show’s new host, and I look forward to exploring several major emerging technologies with you. Together, we’ll learn about their implications for business, society, and most importantly for you
Jon Hyde: I’m joined today by John Roese, who’s the chief technology officer for Dell Technologies. John, welcome to the show. Thank you so much for taking time to join us.
John Roese: Yeah, thanks John. Great being here, always good to have a conversation about technology.
Jon Hyde: Dell Technologies has a lot of strategic themes, and we think of that, but we actually have settled on six big strategic themes to focus on over the next year or so. Would you mind walking me through what these are, and more importantly, how they fit together into a cohesive strategy, that’s helping our customers?
John Roese: We have an ongoing process to evaluate future technologies. We call that the tech radar, that looks at everything. And there’s thousands of new technologies materializing. But in order to develop our strategy about where we go next, we have to determine where are the big inflections coming? Where are the next areas in which technology activity will occur, that will require new product services or a disruption.
John Roese: And as part of that process, I don’t know, probably about a year and a half, two years ago, we updated our thinking and we defined six big areas that are likely to shape the future of IT. At least in the next, let’s say three to five year time horizon. In no particular order. And there is a relationship between them, but in no particular order. They include the evolution of cloud. Our cloud journey is not done. We are just at the beginning of cloudifying the world. And now cloud is an operating model. It’s about autonomous, elastic automated infrastructure, and that’s great. We’ve applied it to public and private. We haven’t really applied it to the edge yet. We’ve come up with new ways to deliver software like containerization, but that’s not the end. There’s things like functions and serverless and unikernels coming. So cloud is still a journey, but the one thing that we have settled on, that’s core to our strategy is that it’s going to be a multicloud.
John Roese: A collection of clouds working together is the answer. And now we have to evolve that forward. And so we have a fairly large activity around building the Dell Technologies cloud. And as a technology area, there will be waves of next generation cloud architectures and technologies that influence it. So that’s part one.
John Roese: Part two is the data ecosystem. There’s a new data pipeline forming. There are two worlds of data. There’s the old world of data at rest. And then there is this new world of data in motion, data pipelines. Telemetry information flowing in from the real world through the IT infrastructure, into AI engines, providing insights, training models, providing feedback systems, automating the world. The tools to do that are totally different. The infrastructure underneath it is totally different. And by and large, the industry hasn’t quite figured out how to do it yet.
John Roese: Every customer on a digital transformation journey, has to develop a modern data pipeline. And so we looked at it and said, “Well, we don’t know exactly all the things we’re going to do there.” But that is definitely a place that we believe is adjacent to our core businesses, like compute, storage virtualization, and data protection. But it’s also an area that has unsolved problems, that Dell is very well positioned to go help solve. Like how do we extract metadata and make it easier? How do we make these things more automated? How do we build a control plane to make these data pipelines work together? So that looks like a very promising area for us to solve problems in, but it’s also one that there’s huge customer demand. Number three on the list is edge. Years ago, we started talking about this concept that cloud topologies would distributed.
John Roese: I remember when I said that the first time people like “You’re wrong, it’s going to be a central thing. One cloud will rule them all.” And I’m thinking, is this Lord of the Rings, or are we having a conversation? The bottom line is, anybody with a brain would have realized it is impossible to think that all IT capacity in the world will be centralized in one giant data center and everybody will use it. That just doesn’t work. And so about three years ago, as IOT and certain new advances started to happen and people realized that, huh, most of the data and most of the things that use data, aren’t in data centers. And most of the processing that needs to happen, happens in the real time world if you want to make systems smart. And all of that is a counter trend to centralization in the large data centers. We’re still going to have large clouds and large data centers.
John Roese: But we realized we have to redistribute some parts of IT back out into the real world. And that became the new modern edge. Now you didn’t do it randomly. It was basically to provide real time processing to be part of the data management data pipeline, to be the IT OT boundary. To be the security envelope, to protect the real world, because you don’t want to do that all the way across the internet. And the reality is those things are now coming to fruition. It’s inevitable. There will be edges. It’s a question of how will we build them, who should build them? Well, what we know for sure is that we definitely don’t want to have edge sprawl. What we want to do is extend the cloud model, the multicloud model, to have edge platforms. And if on that edge platform you have to solve a industrial automation problem, and a video surveillance problem. Wouldn’t it be nice if you could do that on the platform, as opposed to having to build an edge for every one of those?
John Roese: Now, the reason that’s so important is there a good estimates that say the majority of data processing of MIPS and bits, are going to either begin or end their journey on an edge. And in many cases, their entire life will be spent out at that edge. So it is a giant part of the IT industry. We happen to be quite good at putting technology out into the real world. And we happen to have built most of the private infrastructure of the world. And edge is by and large, are a private infrastructure done in a more difficult place. Which is something Dell was optimized to do.
John Roese: Continuing on AIML, the AIML space is a little different than the first three. Those first three are actually markets. AIML is not a market. It is not actually even a product. It is a concept that said, within the entire IT ecosystem, we have to divide up not just between mechanical and repeatable tasks, and thinking tasks. Which used to be machines do the mechanical repeatable tests, and people do the thinking tasks. In the AIML world, we can now divide up the thinking tasks. We can shift a lot of decision making into machines that are running new algorithms on new processing architectures, using new data, to actually make some decisions for us. And the result of that, is it will augment the human experience and allow us to scale. We’ll be able to run bigger infrastructure. We’ll be able to run factories more intelligently. It will be able to do healthcare more intelligently, our radiologists will actually now be abundant and scalable because there’ll be augmented by AI, which will do radiology and healthcare.
John Roese: There’s a million examples, but the purpose of the AI ecosystem is to basically allow human beings to focus on the decisions that need to be happening by a human being, but to augment them with technology that can make other decisions for them, to basically make them more efficient and get to faster outcomes. Bottom line is this will impact everything. It will impact how you build products because a smart product is one that uses. Machine learning to exceed the potential of its hardware and software. It will change the way we build infrastructure because here’s a prediction for you, within four to five years, there’s a reasonably good estimate that said the majority of MIPS and bits in enterprise infrastructure, will be consumed by tasks that are driven by a machine learning or an AI algorithm. I keep telling people think of AIs, not as technology, but as users.
John Roese: In fact, they’re the most demanding user you will ever experience. And if you now have thousands or millions of them on your infrastructure, they are the dominant user profile, which means we have to change the way we build infrastructure to basically build for AIs first. And then we’ll adapt for the humans afterwards. If you don’t have an AI strategy, forget about digitally transforming because you’re leaving the most valuable tool you have, which is the ability to scale the performance of your thinking and decision making as a business, on the table. Which is a pretty bad decision.
John Roese: Continuing on, two more. Again, no particular order 5G. 5G is a very specific area. The reason we’re so excited about 5G is not because we think mobile broadband by itself is interesting. It’s because 5G isn’t like 4G or the previous ones. It’s a technology that is the first time mobile infrastructure has been built kind of in the cloud era.
John Roese: It is more software defined. It is more programmable. It has the ability to deploy an edge within it. A thing called a mobile edge compute layer. It has an understanding that it’s not just providing bits over the air. Those bits may be very specialized. There are network slices that can be tied all the way to an application. There are things like ultra reliable low-latency communication, which has a function in 5G, that’s designed for things like drones, and AR, and VR, to guarantee those things can work. And then there’s this massive machine type communication, which is, well, imagine an environment which there’s a million sensors in a kilometer. You can’t do that on traditional cellular, in 5G you can. The reason you need to do that is because the digital transformations have happened. And now we have millions of sensors in a kilometer, which we didn’t have before.
John Roese: So for us, when we look at 5G we don’t view it as just another cellular network. We look at it as the connectivity fabric for the digital transformation that is starting to happen. It’s not the only network and it’s not the only way to do networking, but if we get it right, we have an ability to connect people and things and AIs and systems in a way that is a first class citizen of the overall cloud orchestrated experience. We’ve never been able to do that before, and if we can get it right, we actually have the fabric for the digital transformation, not just the compute, and the storage, and the virtualization, and the applications, which is a pretty important piece to have.
John Roese: And then lastly, on the list is security. You can’t have any technology about security that’s pragmatic, or about technology that’s pragmatic. If you don’t talk about security. Here, we have a bit of a problem as an industry. Our philosophy is look, the security industry is broken. It’s not that any particular companies are good or bad. It’s just that our approach to security has been, for every problem, there is a product. You have this problem, go buy this product, that will take care of the problem. The problem is there’s a lot of security problems and they keep changing. And so what we have now in our data centers or on our devices is layers of agents, and piles of appliances and networks that are incredibly complex, because you have to stick all this stuff in the critical path. We’re never going to get ahead of that. What if we just rethink security? What if we make it intrinsic? What if we decide that, security functions should exist, but they should be software functions.
John Roese: They should be delivered as microservices. They should be deployed as part of the orchestrated delivery of the application. Through a Kubernetes cluster or as a microservice. They should adopt cloud native principles. They should be connected to the typology, not the physical topology, but the service chain of the SDN. These are all new principles that actually aren’t that hard to do. Because all of those underlying plumbing components that allow you to orchestrate applications, or storage, or data, could be used for security. And so intrinsic security sounds like a revolution, but almost all the plumbing to do it is already there. And it’s, what’s revolutionized all the other dimensions of IT. And so our belief is, let’s get on with that. Let’s start changing security into this new world now it’s non-trivial because we still have the old world. It will always be brownfield.
John Roese: And so we have to be able to bridge between them. If we don’t move to a new approach to security, if we don’t make an intrinsic in the orchestrated experience, we will end up just constantly playing catch up, and reacting to security threats, as opposed to proactively embedding security into the deployment of an application, into the delivery of a service, into a data pipeline. And so, these are the six that we’re focused on.
John Roese: Hopefully they make a lot of sense to you because so far in every conversation I’ve had with the customer in the last probably two years, these are the six that seem to be top of mind. And after our analysis, we picked them as the important ones. And now we’re in full throated, aggressive mode, building out capabilities, developing new business structures. And quite frankly saying, this is where a lot of the future activity of Dell Technologies is going to be about making sure these things happen properly. And there are things that Dell helps customers transition into, solve for, and ultimately get value from.
Jon Hyde: You can visualize how these technologies come together. They’re not abstract things that we think about in silos or isolation. They are, when you apply them to real world examples, like next gen manufacturing, or next gen healthcare, or autonomous vehicles, whatever the industry, whatever the vertical that you’re thinking about. There’s real world applicability to these themes as a whole. And I’m curious your point of view on that, and what you think different industries might be able to capitalize on when they think about these things holistically.
John Roese: Yeah, no, that’s exactly, it’s a great point. Because while those six individually are pretty interesting conversations, they don’t exist independently. They’re overlapping and interdependent. You could argue that a 5G is a very important digital fabric, but one of the things that makes it so interesting is it has an edge capability, but it also happens to be a software defined, cloud oriented architecture.
John Roese: So it’s a future cloud strategy. It also happens to be very dependent on AIML because it’s so scaled and so complex that you can’t possibly manage it without embedding machine intelligence. And then entitle the system. It also happens to be the place where, when things are actually present, what they’re doing is data pipelines, they’re processing data. And by the way, it also has to be secure because you now have this new surface area to attack. So in almost every discussion we have with end customers for an end use case, at least a majority of those six come into play. And so to answer your question if I sit down and talk to… I’ve actually just had some really interesting discussions with some very large and, let’s call it manufacturing companies. And the top of mind topics starts with edge.
John Roese: And the reason it starts with edge is not because of edge in a vacuum it’s because they say, “Ah, I want to make my factory smart.” The problem is all the IT I have isn’t in the factory. But what I need to do in the factory is real time. I can’t afford the time and latency and the cost of moving all my data out of the factory, up into some cloud, and then bringing it back in order to make my factory automated and smart. So immediately they go, “Oh, well I think I need an edge.” Well, good. You should probably build one of those. But what am I building it for? I’m building it because I’m going to have a data pipeline. Because I’m probably, in almost all cases, going to run some machine learning or AI algorithm on that edge, to bring automation and intelligence to the factory.
John Roese: And maybe you’ll deploy it using 5G as connectivity maybe you won’t. But inevitably at least three or four of these things come together anywhere. Same thing is true with education. When you get into an education environment, if you think about the future of education, it’s not Zoom calls by themselves. Zoom calls are good, but what you really are going to end up having to build, is a way to have mixed reality collaborations that you’re going to have people in the classroom, people at home, people virtual people, physical. All of that is going to require a very different IT infrastructure in terms of capacity, which is going to require this next generation of cloud architectures and multicloud, because it’s likely that the tools to actually deliver that outcome come from more than one cloud provider. Some of them will be SAS offering. Some will be hosted locally.
John Roese: More importantly, the education experience isn’t just about in-classroom. There’s hands on. Well, if you can’t do hands on, because you’re not physically there, how do you create a hands on experience, where you do that by, I don’t know, outfitting your labs with robotics and augmented reality systems, and virtual reality environments, and providing those tools back to the end user in the house. Pick an industry, and I guarantee you the answer to solve its problem won’t be just one of these. First I’ll guarantee you that some of them are going to be involved in are critical, and very likely multiples of them will come together and create a composite that really describes that future state to revolutionize healthcare, revolutionize learning and education. Revolutionize transportation. I’ve yet to find an example where that pattern hasn’t held. The combinations are different. The outcomes are different, but this future of technology seems to be universally applicable.
Jon Hyde: I think something key that I took away from that, is there’s a lot of applicable examples. There’s a lot of different flavors by which this can come to fruition for companies or customers, depending on exactly what their market is. But it all starts with their data, and all starts with their information and how they actually are able to act on it. And you mentioned things that hint at things like latency, and near real time, and accessibility.those are powerful things to think about as a customer, because that’s how you differentiate. That’s how you make quantum leaps against your competition.
John Roese: No, you’re absolutely correct. And what we found is most people don’t understand that, where their data lives. There’s a term in the industry, in many industries called a pipe cleaner. If you want to understand something. Let’s say you have a broken business process, you send in a pipe cleaner. And the pipe cleaner is a person who literally manually walks through the process and figures out, ah, hey, that PO went to that person got lost. And then it went over to this inefficient system. And the reason that order entry takes seven weeks is because there’s a bunch of things in the pipes. That was a traditional way to solve business process issues. But when you start thinking about a data pipeline, you need to think about the fact that maybe your pipeline, isn’t very clear.
John Roese: Maybe if you have this aspiration of building a smart factory, and you think that just by putting an edge out there or putting in a new tool like Kafka, you’ll get there. You probably will discover very quickly that that doesn’t really work until you go into the data pipeline and start to walk through how this stuff moves. And here’s a good example. We have some partners that are doing this already in big steel mills and other places, where they went from non smart factories that generated like 10 megabits per day of telemetry. And then they instrumented everything and they generated like five petabytes in a week. And then you start to look at the data pipeline and maybe with at 10 megabits per day, you can just batch oriented, upload it to a cloud, and do remote processing on it, and then generate a report and somebody would take an action.
John Roese: And it would take six weeks for this to happen. Now you have petabytes of data. You’re surely not going to batch all that up and send it to a public cloud to run a report on it. So it leads you to the conclusion that wait a minute, that probably would be better processed in the factory on an edge. That’s part A.
John Roese: Then you keep moving through the pipeline and say, well what am I doing with it? And you realized, hey, I’m not doing it because I’m not processing it because I want a report. I’m processing it because I want an insight. And the insight, if I only tell people, isn’t interesting. But if on the other hand, I send it back into the factory and tune in the way I use power, or change my supply chain, or change the way the factory operates, the factory can now work better.
John Roese: It can save me money. It can be more productive. It can have less loss. And then you start to realize, well, wait a minute, that’s not a data movement problem, or even a processing problem. That’s a timing problem, because if I can do that fast, I save more money. If I do it slow, it doesn’t really have an impact. So then you go, oh, wait a minute. What I need is not just an edge. I need an edge that can do real time processing. And I need an edge that can do that at a very high performance and MIPS per watt, which means I should probably have accelerators out of that edge. And so again, all of these decisions about, do I use the accelerator? Do I have an edge? Which clouds do I use? Understanding your data pipeline of how data is used today, and how you would like it to be used to have the best impact, will lead you to the right conclusion about the typology and the kind of technologies that you’re going to deploy.
John Roese: Data’s not everything, but one thing that is incredibly consistent in the digital world is it’s always present. It’s always a big part of the problem. It’s always a big part of the solution. And if you want to do one thing well, is understand your data flows today and understand what the ideal state is of how you might want to exploit data, to make your business faster, more efficient, more productive, more secure. And once you start understanding that, it informs your decision making about which clouds to use and which places to do work, and whether you need an edge, and whether you need 5G, and what kind of virtualization you use, and what kind of compute architecture. And honestly, that creates a very informed IT organization.
Jon Hyde: Yeah, having actually been that business pipe cleaner in one of my previous jobs. I can tell you that what you’re describing is a far better solution. I think one of the things that you said that really keyed for me is, and you alluded to it, but didn’t explicitly say it. But I think what you’re getting at is, not only do you need to be able to think about how your data pipelines deal with, and manage, and handle your data, but you need to think about how you embed machine intelligence within the data pipelines to make those decisions in more of a perpetual motion or perpetual engine type of a topology,
John Roese: The most pragmatic way to use machine intelligence in a process. Wherever that process is, is to look at the process, and find places where data driven decisions happen. If you’re inside of Dell Technologies. And you’re in supply chain, and you have a existing process that has lots of steps of which many of them are manual, and there’s human intervention. And that process governs your inventory management. And you can improve that process by careful curation of machine learning at three or four places. And you can improve it by 5%. 5% better outcome of inventory management. That doesn’t sound like a lot, except if your Dell Technologies and your supply chain is the largest supply chain and the technology ecosystem, changing it in one direction by 1%, is hundreds of millions of dollars of savings and productivity.
John Roese: I guarantee you, in every business, maybe you’re not as big as Dell, but you have a big business process somewhere, and ask yourself, which of your processes, if they got better, more precise, more accurate, less error prone by just five or 10% would bend the curve in your competitiveness, or make you more effective, or save you the kind of money that’s interesting? Well, as soon as you identify those processes, that’s where you should go spend your time trying to inject machine intelligence, because it almost certain that if you do that, one it’s possible, and two, you’ll get those kinds of outcomes.
Jon Hyde: Yeah. And a part of that’s an economic conversation, just the availability of that type of technology at scale, to be able to meet that demand, which is, that’s always going to be a challenge. I think those things happen in waves over time, and we just, we have to ride those waves and really capitalize them when they’re available as our customers. Which leads me to a question. And we look at the recent pandemic and it’s really showing us that no one is invincible when it comes to business. Can you talk about how these types of technologies as a group are much more robust and resilient rather than separately in this kind of environment.
John Roese: Taking a step back, one thing we’ve learned, and I think the data… The studies haven’t been completed, and the world hasn’t gathered all the data, but I’ll make a prediction. When all this settles down and we look back, and we ask, who did okay, and who didn’t during this, from a business perspective. The direct correlation is likely to be the companies that had begun and were well into their digital transformation, came out ahead. As a company, almost every company was on a different stage in their digital transformation. And like I said, the correlation is, if you were just beginning or hadn’t even started, and you were really in the old world, you suffered horribly during this period. Because you were dependent on human beings, moving stuff around, or goods and services being delivered, or interaction with your customers being a face to face meeting. And that all just stopped.
John Roese: And yet there were companies, including Dell, interesting enough, we’re brick and mortar and we’re digital. But funny enough, we had invested heavily for 10 years in our digital transformation. We are one of the most digitally transformed businesses in the world. And when we had to move a hundred thousand extra people to work at home, it happened on a weekend. Everything continued. In fact, our productivity got better. We are operating on a higher productivity level today than we were operating before the pandemic. Now we have to do new things in new ways because we have to adapt to customer segments that are changing and there’s lots of activity. But because we had the digital infrastructure because we were software oriented, because we embraced these new typologies and technologies, we managed better. And so from a resiliency perspective, technology is not there just to solve an academic problem. Technology, always if it’s done right, always trends towards greater efficiency effectiveness.
John Roese: And one of the consequences of using technology, is that it’s far less fragile than human beings are. Humans are kind of the weak link, in many cases. They’re very important, but one of the reasons we use machines to build things is because they just do it better. They’re just more efficient at those rudimentary tasks. And now in the digital world, we have machines doing more of our digital tasks, but the fact that they can be replicated, that we can scale them independently, that we can spawn more of them, gives us a lot more tools to survive things that aren’t just about pandemics, but are about demand. A well formed digital business that suddenly has the benefit of having exponential demand for their product, is likely to be able to keep up with that demand. A company that literally has to go build a new factory to build more product, because they don’t have a digital supply chain, or a modern global supply chain, is likely to not be able to react to that.
John Roese: So we think that there’s staying ahead of the curve, embracing the new technologies, knowing how to have modern infrastructure, it’s not just about goodwill and better improvements of your existing applications. It’s a foundation of resiliency and flexibility that allows you to deal with the next thing. Hopefully it’s not the next COVID, but maybe the next thing that happens to you, isn’t a bad thing. It’s tripling the demand of your product. Or the demand from your customers to produce more revenue. Ask yourself, are you prepared for that? And it’s the same answer as are you prepared for the next pandemic? And the answer is always, are you a digitally transformed business? Are you using these technologies? Is technology an asset and a capability that allows you to scale and adapt? Or is it something that you view as a liability that you’re quite frankly resisting?
Jon Hyde: Yeah. That’s a powerful statement to make. And I think it creates this nice opportunity for us to speak with our customers and talk about why it’s important. But as I keep looking ahead, you’ve talked about a lot of things that are keeping my mind moving in some pretty interesting ways. This can’t be the end though. Are there any other emerging technologies that you’re looking at on the horizon that we could see added to this list of the big six in the future, that are going to continue to impact and influence our customers in similar ways?
John Roese: Yeah. And the answer is there are literally hundreds of them. Some of the bigger ones that are happening first is, during the COVID crisis, what we started to realize was the way we work, the way we interact is almost as important as the tools that we use. And from that, we started to realize that we did a hard pivot into virtual, but then we started to realize that, well, we don’t want to be a hundred percent virtual, but we also realized we’re not going back to being a hundred percent physical. And so where we’re likely to land a squarely in the mixed reality world. Where, the future of collaboration and enterprise, will now be not everybody in a conference room and a bunch of second class citizens get to video conference in. But more of an optimized experience that says, hey, everybody’s the first class citizen.
John Roese: We want people in a conference room, people in their home, people coming in as an avatar, to all be able to operate in a mixed reality environment. We want them to be able to maybe enter that environment as an augmented reality or virtual reality. There’s this idea of the next generation user experience is incredibly important because it gives us a lot of flexibility about what’s that experience going to be. Which brings us to the second point in this, which is, when we went virtual during the pandemic, we sent everybody home to do whatever job they were doing. And we gave them exactly the same tools. The analogy is, imagine if you went into an enterprise, and the enterprise had a hundred thousand employees. There are manufacturing people, engineers, finance people. And everybody who showed up, you handed them a piece of paper and a pencil and said, “Go do your job.”
John Roese: That’s what we did when everybody went home. And we said, “Here’s your Zoom thing. Congratulations.” Now that works to a point. But now if we’re going to live in this world long term, we’re going to have to get really creative about what are the tools for an engineer working at home, or a finance person working at home, or creative working at home? And we’re going to discover very quickly that they’re going to need different interfaces. They’re going to need different peripherals. Some of them are going to want to be in the augmented and virtual world. Some of them are going to need better video quality. Some of them are going to need a lot more bandwidth and processing available to them in cloud environments because the kind of work they do is different. And so we’re just beginning this idea that the user experience of being in this new reality is not homogenous.
John Roese: We know that augmented reality and virtual reality was kind of considered a toy. But I guarantee you, if you’re a mechanical engineer and you’re trying to collaborate with other mechanical engineers to do design work on a prototype physical layer thing, doing that over a Zoom call is not easy. Doing it in a virtual reality environment would be incredibly better. And so we know that that wave of the next gen of user experiences, as big as these six I just talked about. The good news is we’re working on it. And there are others. We absolutely know that low-level semiconductor technology is changing, and accelerators are changing. Trust me, we’re not going to stick with these six forever. We’re going to add to them because technology is constantly changing, and our job is to make sure we stay ahead of it.
Jon Hyde: I look forward honestly, to having this exact same conversation again, in the future and hearing how things are evolving. Because I think it’s a super powerful conversation to think about. I think it’s inspiring for our customers to hear and to understand that not only are we thinking about it when paying attention to it, but we’re actively investing, and we’re implementing a lot of these things for ourselves. So it’s a powerful story. I really want to thank you for taking time to share it with us. It’s been a great time speaking. So thank you so much for the time, John, and have a great one.
John Roese: Thanks, John. Appreciate it.
Jon Hyde: For those of you who enjoyed this podcast, you can find it at www.delltechnologies.com/nexthorizon. Along with feature podcasts, and other great content focused on emerging technologies. Thank you so much for listening and be sure to subscribe. Until next time, I’m John Hyde, and this is The Next Horizon.