>>From around the globe. It's the cube with digital coverage of IBM. Think 20, 21 brought to you by IBM, >>Welcome back to the cubes coverage of IBM, think 20, 21. We're gonna talk about the edge. Like what is the edge, how it's going to evolve. And we're gonna take a look at an autonomous vessel use case, which is quite interesting with me as Rob high. He was an IBM fellow VP and CTO. IBM edge computing. Rob. Welcome. Great to see you again. Thanks Dave. Appreciate that. Yeah. So let's start with the basic question here. You know, people's like, Oh, what is the edge? Like, it's one big thing and it's not, it's it's many things, but how should we think about the edge and why should enterprises, you know, feel like it's necessary to begin to lean in? >>Well, so let's just start with the use cases. Uh, you know, what edge means is the ability to put a camera on a manufacturing floor, you know, perhaps juxtaposed with a robot monitoring the work that the robot is doing using AI visual recognition to detect whether what that robot is doing is producing high quality parts or not. And to be able to do that in real time, to be able to use that analytic thin to, you know, quickly remediate any kind of quality issues, uh, helps lower costs, it helps increase your yield and it helps increase the overall efficiency of your production processes. Or if not that then putting it in something a little bit. It's perhaps a little bit more familiar to us, the idea of an autonomous vehicle, you know, being able to, you know, drive and, and, uh, do driver assistance to drivers safety kinds of features, you know, all of that requires compute and having that compute where people are actually performing these tasks based on the data that they're receiving at the moment that they receive it, they are able to process that real time, be able to give them the feedback that allows them to make better decisions, to be able to do that. >>Not only with lower latency, but actually with better protection of their data, uh, better protection of their personal information or private information. If you're thinking about, you know, the business in which they operate, you know, be able to do that, even when the network fails, be able to do that without necessarily having to transmit tons and tons of data back to the cloud, especially if you end up not actually using that anywhere. That's what as computing really means. >>Yeah. So it sounds like the edge isn't that maybe we shouldn't think of it as a place, but the most logical place to process the data, um, depending on latency and other factors, it's a, that's a good way to look at it. So >>It's just where we do our work. >>Yeah. Well, you do the work, right? That's that makes a lot of sense. Thank you for that. So, you know, we always were talking about the pandemic changing the way we think about things. And I wonder if you can comment on, on the, the edge context as come back from, you know, work from home or remote work, um, you know, think 20, 22, we hope it's going to be face-to-face could edge play a part in that has the pandemic, uh, made you think differently about the opportunities at edge? >>Yeah. And in fact, what we've seen is the pandemic is actually beginning to accelerate digital transformation. If you think about it, you know, any store that wanted to survive the same Deming could only do so by basically introducing a digital presence, you know, the ability to buy online. And even if you're picking up at the store, picking up the curbside, you know, you can't go into a restaurant without getting that QR code that gives you, you know, your digital menu, um, trying to get workers back into both the factories, as well as the warehouses and offices, and to do so safely, be able to ensure that they're wearing the face mask and socially distancing properly. All of these things I think have driven digital transformation. And if you think about the task of, you know, buying online and picking up the store while store is better, have a pretty good idea of where their inventory is. >>Um, they need to know exactly where that product is so they can quickly pick it and get it available to the client before they arrive at the store. Um, and so that's edge computing. We need edge computing to be able to automate the processes of inventory tracking down to individual items and where they're located throughout the store to be able to do the recognition for whether people are or are not being changing their social distancing or wearing their PPE, um, to be able to ensure that our processes are as automated as possible to limit the amount of human interaction that's required in order to perform these processes. All of that I think has accelerated both digital transformation, as well as particularly the use of edge computing, uh, in, in all of our businesses. >>I think about, you know, the forced March to digital in 2020. And if you weren't a digital business, you were out of business, but to your, my big takeaway from what you just said is that digital transformation is just starting and now people really have some time to think about that, that digital strategy. And as we think about doing things more safely, maybe with less human intervention, we love autonomous vehicles. Examples just cause because there's a technically they're challenging, but, but I wonder if you could tell us the story of the Mayflower autonomous ship it's it's upcoming journey, it's going to be cruelest across the Atlantic, unbelievable collecting data, you know, talk about how edge relates to that story. What can you tell us? >>Well, first of all, this is simply talk about the task of navigating a ship from one port on one side of the world to another port across the ocean, across the Atlantic. Um, you know, the ocean is a dangerous place. Uh, yes, it's wide open it's, you know, lots of water, but the reality is it's full of barriers. Of course, you've got land barriers, you've got other ships, you've got Marine life, you've got debris that gets stuck dropped in the ocean. And so the task of navigating is actually quite difficult. And again, to the same point that we've made earlier, you have to have local compute in order to really be able to make those decisions fast enough with enough acuity, with enough clarity, to be able to, um, to be able to safely safely navigate around those kinds of obstacles. So we have to put compute in the ship. >>So the Mayflower ship is as I sort of implied, uh, a, a ship that will be autonomous. There are no human beings involved in the, in operating the ship. It has to be able to on its own, both recognize these obstacles, recognize on the ship, recognize about recognized, um, you know, that cargo container that happened to fallen off, uh, some other ship and floating through the ocean, uh, recognize, you know, uh, rain life, uh, whales and other, other, uh, fish and birds that might be, uh, uh, on, in the way. Um, and, and, and to be able to, um, do all that, you know, entirely without any human intervention. So that compute power is really a prime example of an edge computer. It is compute in the, in the business of navigation, uh, making decisions about, um, the things that it sees and, and making decisions about how best to circumvent those issues. >>Um, now along the way, I should also say part of what the med flagship is going to do is not only exercise the task of navigation and prove that, um, these algorithms can efficiently and effectively, uh, bring that shift from one side of the world to be upside safe, but along the way, it's going to conduct science is going to, um, collect water samples for the, um, chemical makeup of, of the oceans at various points along the way, it's going to be sampling for microplastics or, uh, examining phytoplankton for its health and life. Uh, it's going to be the detecting wave motions and the wave energy that might be indicative of how the world is transforming in the presence of global climate change. Um, these science packages that are going to be formed are also being performed autonomously without human intervention. And that actually opens up a very exciting potential future, which is the idea of these autonomous ships navigating the oceans, collecting data that can then be brought back for the scientists to examine so that they, the scientists are not having to go out and spend weeks and months at a time in perilous conditions. >>These potentially the only conditions, um, collected that data, but rather they can remain safely at land. The ship will collect the data and they can analyze that data from their home labs. So this is actually a really exciting project, but one that I think would demonstrate not only the idea of edge computing, but also the advances in navigation and Marine science. >>Yeah, because I mean, the ship has to navigate itself. Not only is it bringing back data, but there's a great, great example. I met a lot of the work in machine intelligence today is done in the modeling side. This is, this, this is inference going on in near real time. Uh, which we think is where, where the, the, the action is. That's why we love the autonomous, because there's a lot of IBM tech involved in here as well. Is there not, I mean, you've got to have software and you've got your edge devices. You've got, you know, automation capabilities. I mean, it's not right. That this is like serious technical challenge. >>Yeah. Well, we were approached by the primary team on this project and it didn't take us long to realize the utility that some of our technology would have to advancing their project. And so you're right. I mean, we have things like operational decision manager, ODM, which typically is used in the financial services industry, but now it's being applied to the rules of navigation. We've called the Culver over cold rags. Um, we've got, uh, our AI services that do visual recognition because obviously we've got to be able to detect and identify, um, the things that, that the ship is seeing along the way and be able to distinguish what those things are. Uh, we have our IBM edge application manager, which is being used to manage deployment of these kinds of workloads, and frankly, all of the workloads that are hosted in the ship, getting that managed and deployed onto the ship. Uh, and, and of course, you know, all these things have to be integrated. And so that's just a small sampling of the kinds of technologies, but it's a good example of where I think the edge kind of represents the combination of what we have all been working with in this industry, which is how do we bring technologies together, the solver problem as an integrated solution, >>You mentioned financial services. So I wonder if we could, you know, think beyond shipping maybe, uh, what, what are you seeing in other industries? Are there any patterns that are developing where clients are saying, Hey, we need this sort of this capability. What can you tell us? >>So edge computing is it's probably greatest demand right now in manufacturing, uh, in industrial four dash zero, uh, kinds of, uh, environments where, you know, most of the industry, the industrial industry, the markets have grown up largely dependent upon operations, technology, OT, but one of the things that people need in these kinds of environments is the additional benefits that come from AI. And we've talked about, you know, using AI to do visual recognition on manufacturing processes, looking at quality inspection, for example, but you know, there's other aspects of production optimization of worker safety. We talked a little bit about that, um, around, uh, you know, predictive maintenance and asset management, uh, you know, these kinds of additional things that are necessary to really run your factory efficiently, or you're, you know, you're a drilling rig or your energy production systems. All these kinds of industrial processes can benefit from the advances that are occurring in analytics in, um, in, and then of course, having localized compute to do that with, to both do those kinds of decisions in real time, but also to offload the amount of transmission, the data that we have the transmitting back to the cloud. >>So industry four O or manufacturing is one big area retail. We talked a little bit about that, but you think about, you know, point of sale terminals, and the idea of being able to brute two offers at point of sale, to be able to do price checking to help you navigate the store is digital signage. Um, you know, all the user experiences, spillage and spoilage and loss prevention, these are all kinds of use cases that will benefit retail retailers, um, lot of demand. And of course, again, the need to be able to do that locally within the store, we talked to touch a little bit on automotive. The whole automotive industry right now is going through a really fundamental transformation where virtually every automobile now is being imbued with more and more compute capacity and localized processing for doing driver's safety and, and car maintenance and, and, and even short of, you know, full autonomy, which is of course is another topic in its own, right? Uh, lots of experiences that can be brought there as well. So lots of opportunity in distribution, manufacturing, retail banking, uh, uh, virtually every industry that we've looked at has some opportunity for, um, leveraging the benefit that does computing. >>It's hard to get cars right now because the chip short is. But, um, I wonder real quick, if you could talk about 5g, you hear a lot about 5g, there's a ton tons of hype there. Uh, how should we be thinking about 5g? How real is it? What's your take in terms of its impact on the edge? >>So a couple of thoughts here. One is 5g obviously is accelerating, and it has the effect of accelerating edge computing, because one of the benefits of 5g of course, is lower latency and higher bandwidth. And that kind of opens people's minds, the potential to leverage the network connectivity of equipment that otherwise, you know, is hard to connect. If you think about the factory floor for a moment in all the kinds of equipment you have on the factory floor, if you had to hard wire, all that equipment to get access to the compute power on that, that could be a very expensive proposition. You'd like to kind of wirelessly connect that equipment. And that's one of the things that 5g brings to the table, because some of the spectrum that five peak uses has less potential to interfere with that equipment then than you would otherwise. So I think that what we're going to see is 5g will sort of disproportionately benefit I'll call them industrial or commercial unit use cases as compared to 4g and LTE, which were very much centered on consumer use cases. 5g is accelerating as competing in a many ways. 5g actually depends on edge computing. It doesn't mean that we can't do educated beginning without 5g. We can, we can certainly do it for DLP than wireline. Uh, but I think 5g is going to have a very symbiotic effect on, on edge computing, >>Just like wifi was enabler on mobile, but this is a, you know, much, much, much larger potential. Rob. We got to go, thanks so much for coming on and sharing your insights. Love to have you back. Awesome. All right. Appreciate it. Thank you for watching everybody. This is Dave Volante for the cubes coverage of IBM. Think 2020, 21, 2021. We'll be right back.

>>from >>around the >>globe, it's the >>Cube with digital coverage of IBM, think 2020 >>one brought to you by IBM. >>Welcome back to the cubes coverage of IBM think 2021 we're gonna talk about the Edge like what is the Edge, how it's going to evolve? And we're gonna take a look at an autonomous vessel use case, which is quite interesting with me is rob high and IBM fellow VP and Cto, IBM edge computing rob. Welcome. It's great to see you again. >>Thanks. Dave appreciate that. Good seeing you too. >>Yeah, So let's start with the basic question here, you know, people are like, well what is the Edge? Like it's one big thing and it's not, it's, it's many things, but how should we think about the edge and why should enterprises, you know, feel like it's necessary to begin to lean in? >>Well, let's just start with the use cases. Uh, you know, what edge means is the ability to put a camera on the manufacturing floor, you know, perhaps juxtaposed with a robot monitoring the work that the robot is doing using ai visual recognition to detect whether what that robot is doing is producing high quality parts or not. And to be able to do that in real time to be able to use that analytic then too, you know, quickly remediate any kind of quality issues, helps lower cost, it helps increase your yield and it helps increase the overall efficiency of your production processes. Or if not that, then putting it in something that's perhaps a bit more familiar to us. The idea of an autonomous vehicle, you know, be able to, you know, dr and do driver assistance to driver safety kinds of features, you know, all of that requires compute and having that compute where people are actually performing these tasks based on the data that they're receiving at the moment they receive it be able to process that real time, give them the feedback that allows them to make better decisions to be able to do that not only with lower latency, but actually with better protection of their data, better protection of their personal information or private information. If you're thinking about the business in which they operate, you know, be able to do that even when the network fails to be able to do that without necessarily have to transmit tons and tons of data back to the cloud, especially if you end up not actually using that anywhere. That's what as computing really means. >>Yeah. So it sounds like the edges, maybe we shouldn't think of it as a place, but the most logical place to process the data of, depending on late and see and other factors. It's that's a good way to look at it. So it's >>yeah, just where we do our work. >>Yeah. Well you do the work, right. That that makes a lot of sense. Thank you for that. So you know, we always we're talking about the pandemic, changing the way we think about things. And I wonder if you can comment on the the edge context as we come back From we work from home or remote work. You know, I think 2022, we hope it's going to be face to face. Uh good edge play a part in that. Has the pandemic uh made you think differently about the opportunities that edge? >>Yeah. And in fact what we've seen is the pandemic is actually beginning to accelerate digital transformation. If you think about it, you know any store they wanted to survive. This pandemic could only do so by basically introducing a digital presence, you know, the ability to buy online. And even if you're picking up at the store, picking up the curbside, you know you can't go into a restaurant without getting that Q. R. Code that gives you your digital menu. Um Trying to get workers back into factories as well as the warehouses and offices. And to do so safely be able to ensure that they're wearing their face masks and socially distancing properly. All of these things I think have driven digital transformation. And if you think about the task of buying online and picking up the store well stories better have a pretty good idea of where their inventory is. Um They need to know exactly where that product is. So they can quickly pick it and get it available to the client before they arrive at the store. Um And so that's edge computing. We need edge computing to be able to to automate the processes of inventory tracking down to individual items and where they're located throughout the store. To be able to do the recognition for whether people are or not maintaining social distancing or wearing the PP. E. Um to be able to ensure that our processes or as automated as possible to limit the amount of human interaction that's required in order to perform these processes. All of that I think has accelerated both digital transformation as well as particularly the use of edge computing uh in all of our businesses. >>I think about, you know, the force marched to digital in 2020 and if you weren't a digital business you were out of business. But you're my big takeaway from what you just said is a digital transformation is just starting. And now people really have some time to think about that, that digital strategy and and as we think about doing things you know more safely, maybe with less human intervention, we love autonomous vehicles. Examples, just because they're technically they're challenging. But I wonder if you could tell us the story of the Mayflower autonomous ship, its upcoming journey, it's going to be cruelest across the atlantic, unbelievable collecting data. You know, talk about how edge relates to that story. What can you tell us? >>Well, first of all, this is simply talk about the task of navigating a ship from one port on one side of the world too, another port across the ocean, across the atlantic. Um you know, the ocean is a dangerous place. Yes, it's wide open, it's you know, lots of water, but the reality is it's full of barriers. Of course, you've got land barriers, you've got other ships, you've got marine life, you've got debris that gets dropped in the ocean. And so the task of navigating is actually quite difficult. And again, to the same point that we made earlier, you have to have local compute in order to really be able to make those decisions fast enough with enough acuity with enough clarity to be able to be able to safely safely navigate around those kinds of obstacles. So we have to put compute in the ship. So the may fire ship is as I sort of implied a ship that will be autonomous. There are no human beings involved in in operating the ship. It has to be able to on its own. Both recognize these obstacles, recognizing the ship, recognize about, recognize um, you know, that cargo, uh, container that happened to have fallen off some other ships and floating through the ocean, recognize, you know, rain life, uh, whales and other other fish and birds that might be, uh, in the way. Um, and, and, and to be able to um, do all that, you know, entirely without any human invention. So that compute power is really a prime example of an edge computer. It is compute in the, in the business of navigation, making decisions about the things that it sees and making decisions about how best to circumvent those issues. Um, Now along the way, I should also say part of what the Mayflower ship that's going to do is not only exercise the task of navigation and prove that these algorithms can efficiently and effectively bring that shit from one side of the world to the other side safely. But along the way, it's going to conduct science is going to collect water samples for the chemical makeup of the oceans. At various points along the way it's going to be sampling for microplastics are examining phytoplankton for its health and liveliness. It's going to be the detecting wave motions and the wave energy that might be indicative of how the world is transforming in the presence of global climate change. Um These science packages that are going to be formed are also being performed autonomously without inhuman invention. And that actually opens up a very exciting potential future, which is the idea of these autonomous ships navigating the oceans, collecting data that can then be brought back for the scientists to examine so that they the scientists are not having to go out and spend weeks and months at a time in these perilous conditions, these potentially lonely conditions um collecting that data, but rather they can remain safely on land. The ship will collect the data and they can analyze that data from their home labs. So this is actually a really exciting project, but one that I think will demonstrate not only the idea that computing, but also the advances in navigation and marine science. >>Yeah, because I mean the ship has to navigate itself. Not only is it bringing back data, but there's a great, great example. I mean a lot of the work in machine intelligence today is uh in the modeling side. This is this is this is inference going on in near real time, uh which we think is where the action is. That's why we love the autonomous because there's a lot of IBM tech involved in here as well. Is there not? I mean, you've got to have software and you've got your edge devices, you've got, you know, automation capabilities. I mean, it's not all right. This is like serious technical challenge. >>Yeah. Well, we were approached by the primary team on this project and it didn't take us long to realize the utility that some of our technology would have to dancing their project. And so you're right. I mean, we have things like operations, decision and ODM which typically is used in the things of the services industry, but now it's being applied to the rules of navigation would call the cold cold rags. Um We've got our Ai services that do visual recognition because obviously we've got to be able to detect and identify um, the things that the ship is seeing along the way and be able to distinguish what those things are. Uh we have our imagine application manager which is being used to manage deployment of these kinds of workloads and frankly all of the workloads that are hosted in the ship, getting that managed and deployed onto the ship. Uh and and of course, you know, all these things have to be integrated. And so that's just a small sampling of the kinds of technologies. But it's a good example of where I think the edge kind of represents the culmination of what we have all been working within this industry, which is how do we bring technologies together to solve a problem as an integrated solution? >>You mentioned financial services. So I wonder if we could, you know, think beyond shipping, maybe what, what are you seeing in other industries? Are there any patterns that are developing, where clients are saying, hey, we need this sort of this capability? What can you tell us? >>So, I think it is, it's probably greatest demand right now in manufacturing, uh, in industrial 4.0, uh, kinds of environments where, you know, most of the industry, the industrial industries and markets have grown up largely dependent upon operations technology. Ot but one of the things that people need in these kind of environments is the additional benefits that come from A. I and we talked about using ai to do visual recognition on manufacturing processes, looking at quality inspection, for example, but there's other aspects of production optimization of workers safety. We talked a little bit about that around uh, predictive maintenance and asset management. Uh, you know, these kinds of additional things that are necessary to really to run your factory efficiently or you're you're drilling rig or your energy production systems. All these kinds of industrial processes can benefit from the advances that are occurring in analytics. And um, and, and then of course, having localized compute to do that with, to both do these kinds of decisions in real time, but also to offload the amount of transmission that we end up transmitting back to the cloud. So industry 40 or manufacturing is one big area retail. We talked about that, but you think about point of sale terminals and the idea of being able to do offers at point of sale to be able to do price checking to help you navigate the stores, digital signage. Um, you know, all the user experiences, spillage and spoilage and loss prevention. These are all kinds of use cases that will benefit retail retailers. Um, lot demand, of course. Again, the need to be able to do that locally within the store. We talked to touch a little bit on automotive. The whole automotive industry right now is going through a really fundamental transformation where virtually every automobile now is being imbued with more and more compute capacity and localized processing for doing driver safety and car maintenance and, and, and even short of, you know, full autonomy, which is of course is another topic in its own right. Uh lots of experiences that can be brought there as well. So lots of opportunity and distribution, manufacturing, retail banking. Virtually every industry that we've looked at has some opportunity for leveraging the benefits of the computer. Yeah, >>it's hard to get cars right now because the chip shortest. But I wonder real quick if you could talk about five G, you hear a lot about five Gs tons of hype there. How should we be thinking about 5G? How real is it? What's your take in terms of its impact on the edge? >>So a couple of thoughts here, one is 5G obviously is accelerating And it has the effect of accelerating edge computing because one of the benefits of 5G of course is lower latency and higher bandwidth. And that opens people's minds. The potential to leverage the network connectivity of equipment that otherwise is hard to connect. If you think about the factory floor for a moment and all the kinds of equipment you have on the factory floor. If you had to hardwire all that equipment to get access to the compute power on that, that could be a very expensive proposition. You'd like to kind of wirelessly connect that equipment and that's one of things that five day brings to the table because some of the spectrum five take uses has less potential to interfere with that equipment than than you would otherwise. So I think that what we're going to see is 5G will disproportionately benefit. I'll call him industrial or commercial use cases as compared to four G. And L. T. Which were very much centered on consumer use case five Gs accelerating edge computing in many ways Five G actually depends on edge computing doesn't mean that we can't do edge computing without five do we can we can certainly do it for dlt even wire line But I think 5G is going to have a very symbiotic effect on edge computing. >>Yeah just like wifi was enabler mobile but this is much much much larger potential rob. We gotta go. Thanks so much for coming on and sharing your insights. I'd love to have you back, awesome. Thanks. >>Alright appreciate it. Thank >>you for watching everybody's Day Volonte for the cubes coverage of IBM. Think 2020 21 2021 will be right back. >>Yeah. >>Yeah.

>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Welcome back, everybody. This is Dave Vellante of the Cube, and you're watching our continuous coverage of the IBM think Digital 2020 experience. And we're really pleased to have Rob High here. He's not only an IBM fellow bodies. He runs the vice president CTO of the IBM Edge Computing Initiative. Rob, thanks so much for coming on the Cube. Good to see you. Which we're face to face, but yeah, that time to be safe and healthy, I guess. And did so edge obviously hot topic. Everybody has this sort of point of view would be interested in how IBM looks at edge. You define it and what your thoughts are on. It's evolution. >>Yeah, well, you know, there's ah really kind of two fairly distinct ways of thinking about the edge of the telcos. Our, ah, you know, they're creating edge capabilities in their own network facilities. We call that the network edge on the other side of the edge they that I think matters a lot to our enterprise businesses is there's remote on premise locations where they actually perform the work that they do, where the majority of people are, where the data that actually gets created is first formed and where the actions that they need to operate on are being taken. That is a lot of interest, because if we can move work workloads, Iot workloads to where that data is being created, where those actions are being taken Uh, not only can we dramatically reduce the late and see to those decisions, uh, but we can also ensure continuous operations and the failed in the presence of perhaps network failures. We can manage the growth of increasing demand for network bandwidth as Maura born data gets created and we can optimize the efficiency of both the business operations as well as the I t operations before that. So for us edge computing at the end of the day is about movie work where the data and the actions are being taken >>well, so this work from home, you know, gives a result of this pandemic is kind of creating a new stresses on networks and people are putting, you know, pouring money actually into beefing up that infrastructure is sort of an extension of what we used to think about edge. But I wonder if you could talk about some of the industries and the use cases that you guys we are seeing and notwithstanding, though assay that >>work from home pivot. Yeah, absolutely. So I mean, look, we have seen ah, the need for placing workloads close to where it is being created and where actions have been picking in virtually every industry, the ones that are probably easier for us to think about and more common in terms of our mindset. Our is manufacturing. If you think about all the things that go on in a factory floor that need to be able to perform analytic in, uh, in the equipment and the processes that are performing in the affection for, If you think, for example, production quality. Uh, you know, if you've got a machine that's putting out parts and maybe it's welding seams on metal boxes, uh, you know, you want to be able to look at the quality of that seem at the moment that is being performed, so that if there are any problems, you can remediate that immediately rather than having that box move on down the line and find that you know the quality issues they were created earlier on now have exacerbated in other ways. Um, you know, so quality, productive quality. Ah, inspection production optimization in our world of Covic Cover 19 and worker safety and getting workers back to work and ensuring that you know people wearing the masks and are exercising social distancing. This is on the factory floor. Worker Insight is another major use case that we're seeing surface of lake with a lot of interest in using whether that's infrared cameras or Bluetooth beacons or infrared cameras. Any variety of devices that could be employed in the work area to help ensure that factories are operating efficiently, that workers are safe. Ah, and whether that's in a factor situation or even in an office situation or e a r in a warehouse or distribution center. And all these scenarios the the utility, the edge computing to bring to those use cases is tremendous. >>And a lot of these devices are unattended or infrequently attended. I always use the windmill example. Um, you know, you don't want to have to do a truck roll to figure out you know what the dynamics are going on, that at the windmill s, so I can instrument that. But what about the management of those devices you know from an autonomous standpoint? And and are you? What are you doing? Or are you doing anything in the autonomous managed space? >>Yeah. In fact, that's really kind of key here, because when you think about the scale, the diversity and the dynamic dynamism of equipment in these environments And as you point out, Dave, you know the lack of I t resource lack of skills on the factory floor, or even in the retail store or hotel or distribution center or any of these environments. The situation is very similar. You can't simply manage getting the right workloads to the right place at the right time. In sort of the traditional approach is, you have to really think about another autonomous approach to management and, you know, let the system the side for you. What software needs to be placed out there? Which software to put their If it's an analytic algorithm, what models to be associated with that software and getting to the right place at the right place at the right Time is a key Part of what we do in this thing that we call IBM Edge application manager is that product that we're really kind of bringing to market right now in the context of edge computing that facilitates this idea of autonomous management. >>You know, I wonder if you could comment Robb on just sort of the approach that you're taking with regard to providing products and services. I mean, we've seen a lot of, uh, situations where people are just essentially packing, packaging traditional, you know, compute and storage devices and sort of throwing it over the fence at the edge. Uh, and saying, Hey, here's our edge computing solution and another saying there's not a place for that. Maybe that will help flatten the network and, you know, provide Ah, gateway for storing on maybe processing information. But it seems to us that that that a bottoms up approach is going to be more appropriate. In other words, you've got engineers, you know who really understand operations, technology, people, maybe a new breed of developers emerging. How do you see the evolution you know of products and services and architectures at >>the edge? Yeah, so First of all, let me say IBM is taking a really pretty broad approach to edge computing we have. What I just described is IBM Edge Application Manager, which is the if you will the platform or the infrastructure on which we can manage the appointment of workloads out to the edge. But then add to that we do have a whole variety of edge and Nevil enabled applications that are being created are global service of practices and our AI applications business all are creating, um, variations of their product specific to address and exploit edge computing and to bring that advantage to the business. And of course, then we also have global services Consulting, which is a set of skilled resource, is who know we understand the transformations that business need to go through when they went, take advantage of edge computing and how to think about that in the context of both their journey to the cloud as well as now in this case, the edge. But also then how to go about implementing and delivering that, uh and then firmly further managing that now you know, coupled out then with at the end of the day you're also going to need the equipment, the devices, whether that is an intelligent automobile or other vehicle, whether that is an appellate, a robot or a camera, Um, or if those things are not intelligent. But you want to bring intelligence to them that how you augment that with servers and other forms of cluster computing that resides resident with the device. All of those are going to require participation from a very broad ecosystem. So we've been working with partners of whether that is vendors who create hardware and enabling that hardware in certifying that hardware to work with our management infrastructure or whether those are people who bring higher order services to the table that provide support for, let's, say, data cashing and facilitating the creation of applications, or whether those are device manufacturers that are embedding compute in their device equipment. All of that is part of our partnership ecosystem, Um, and then finally, you know, I need to emphasize that, you know, the world that we operate in is so vast and so large. There are so many edge devices in the marketplace, and that's growing so rapidly, and so many participants in that likewise There are a lot of other contributors to this ecosystem that we call edge computing. And so for all of those reasons, we have grounded IBM education manager on open source. We created an open source project called Open Rise, and we've been developing that, actually now, for about 4.5 years just recently, the Linux Foundation has adopted Stage one adoption of Open arising as part of its Lennox Foundation edge LF edge, uh, Reg X Foundry project. And so we think this is key to building out, Um, a ecosystem of partners who want to both contribute as well consumed value and create ecosystems around this common idea of how we manage the edge. >>Yeah, I'm glad you brought up the ecosystem, and it's too big for any one company toe to go it alone. But I want to tap your brain on just sort of architectures. And there's so many diverse use cases, you know, we don't necessarily see one uber architecture emerging, but there are some characteristics that we think are important at the edge you mentioned sort of real time or near real time. In many cases, it has to be real time you think about autonomous vehicles? Um, yeah. A lot of the data today is analog, and maybe it doesn't have to be digitized, but much of it will be, um, it's not all gonna be sent back to the cloud. It may not all have to be persisted. So we've envisioned this sort of purpose built, you know, architecture for certain use cases that can support real time. That maybe have, you know, arm based processors. Ah, or other alternative processors there that can do real time analytics at the edge and maybe sending portions of the data back. How do you see the architectures evolving from a technologist? >>Well, so certainly one of the things that we see at the edge is a tremendous premium being placed on things like energy consumption. So architectures they're able to operate efficiently with less power is ah is certainly an advantage to any of those architectures that are being brought aboard. Um, clearly, you know x 86 is a dominant architecture in any information technology endeavor. More specifically at the edge. We're seeing the emergence of lot of arm based architecture chips out there. In fact, I would guess that the majority of the edge devices today are not being created with, um, arm architectures, but it's the you know, but some of this is about the underlying architecture of the compute. But also then the augmentation of that compute the the compute Thea the CP use with other types of processing units. Whether those GPS, of course, we're seeing, you know, a number of deep use being created that are designed to be low power consuming, um, and have a tremendous amount of utility at the edge. There are alternate processing units, architectures that have been designed specifically for AI model based analytics. Uh, things like TP use and infuse and and, uh, and set around, which are very purpose built for certain kinds of intellect. And we think that those are starting to surface and become increasingly important. And then on the flip side of this is both the memory storage in network architectures which are sort of exotically different. But at least in terms of capacity, um have quite variability. Specifically, five G, though, is emerging and five g. While it's not necessarily the same computing, there is a lot of symbolism between edge and five G and the kinds of use cases that five G envisions are very similar to those that we've been talking about in the edge world as well. >>Rob, I want to ask you about sort of this notion of program ability at the edge. I mean, we've seen the success of infrastructure as code. Um, how do you see program ability occurring at the edge in terms of fostering innovation and maybe new developer bottles or maybe existing developer models at the edge? Yeah, >>we found a lot of utility in sort of leveraging what we now think of as cloud computing or cloud computing models. Uh, you know, the idea of continue ization extends itself very easily into the edge. Whether that is running a container in a docker runtime, let's say on an edge device which is, you know, resource constrained and purpose built and needs to focus on sort of a very small footprint or even edge clusters edge servers where we might be running a cluster of containers using our kubernetes platform called open shift. Um, you know the course of practices of continuous integration, continuous delivery. What we write a Otherwise think of his Dev ops. Ah, and, of course, the benefits they continue. Realization brings to the idea of component architectures. Three. Idea of loose coupling. The separation of concerns, the ability to mix and match different service implementations to be opposed. Your application are all ideas that were matured in the cloud world but have a lot of utility in the edge world. Now we actually call it edge native programming. But you can think of that as being mostly cloud native programming, with a further extension that there are certain things you have to be aware of what you're building for the edge. You have to recognize that resource is air limited. Unlike the cloud where we have this notion of infinite resource, you don't have that at the edge. Find and constrained resources. Be worried about, you know, Layton sees and the fact that there is a network that separates the different services and that network can be and reliable. It can introduce his own forms of Layton sees it, maybe bandwidth constrained and those air issues that you now have to factor into your thinking as you build out the logic of your application components. But I think by building on the cloud native programming about me paradigm. You know, we get to exercise sort of all of the skills that have been developing and maturing in the cloud world. Now, for the edge >>that makes sense. My last question is around security. I mean, I've often sort of tongue in cheek said, you know, building a moat around the castle doesn't work anymore. The queen i e. The data has left the castle. She's everywhere. So what about the security model? I mean, I feel like the edge is moving so fast you feel confident or what gives you confidence >>that we can secure the edge. You know, the edges does introduce some very interesting and challenging concerns with respect to security because, frankly, the compute is out there in the wild. You know, you've got computers in the store you've got, you know, people walking around the kiosks you have in the manufacturing site, you know, workers that are, you know, in the midst of all of this compute capability and so the attack surface is substantially bigger. And that's been a big focus for us, is how to the only way validate in 30 of the software that was But it also takes advantage of one of the key characters with edge computing to bring to the table, which is, if you think about it. You know, when you've got personal and private information being entered into quote system, the more often you move that personal private data around, and certainly the more that you move it to a central location and aggregate that with other data, the more of a target becomes more vulnerable, exposed that data becomes and by using edge computing, which moves the workloads out to the edge where that did has been created in some sense, you can process on it there and then move it back. They need central location, you don't have to aggregate it. And that actually in itself is a counterbalance of all of the other issues that we also describe about security by essentially not moving the personal privacy and in protecting by keeping it exactly where it began. >>You know, Rob, this is an exciting topic. Is a huge opportunity for IBM and Ginny in and talk about the trillion dollar opportunity and hybrid cloud and the Edge is a multi $1,000,000,000 opportunity for IBM and, uh So you just got to go get her done. But I really appreciate you coming on the Cube and sharing your insights. That awesome topic in the best interest of the David. Yeah. Thank you. Thank you for the thank you. Stay safe and thank you for watching everybody. This is Dave Volante for the Cube. This is our coverage of IBM. Think 2020 the digital. Think >>we'll be right back after this short break? >>Yeah, yeah, yeah, yeah.