IoT Leaders
IoT Leaders

Episode · 6 months ago

Digital Twins, the Metaverse, and Connected Ecosystems w/ Tony Shakib

ABOUT THIS EPISODE

The first level is to visualize the data. The second is to contextualize the data. Third is to simulate the data to project the best outcome.

The fourth level of IoT maturity is to execute on the data autonomously.

In this episode, I interview Tony Shakib, GM/Partner at Microsoft Azure IoT, about how IoT can bring different technologies together on behalf of customers for a huge increase in productivity across many industries like transportation and healthcare.

Join us as we discuss:

  • Factors contributing to Microsoft leading in the Gartner Magic Quadrant for 3 years in a row
  • The potential for enterprise to leverage IoT Edge
  • Digital twins: what it is and how it’s used
  • A simplified view of the Metaverse and how to benefit from it today
  • How phases of IoT maturity provide a competitive edge

To hear more interviews like this one, subscribe to IoT Leaders on Apple Podcasts, Spotify, or yo ur prefered podcast platform.

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You're listening to Iot leaders, a podcast from Si that shares real IOT stories from the field about digital transformation, swings, the Miss Lessons Learned and innovation strategies that work. In each episode you'll hear our conversations with top digitization leaders on how Iot is changing the world for the better. Let iot leaders be your guide to Iot, digital transformation and innovation. Let's get into the show. Welcome to the IOT leaders podcast with me, your host, nickel, the CEO of Si. Now, in this episode that you're about to hear, I was delighted and died honored to be joined by the head of Iot for azure globally, Tony Shakib. Tony and I have known each other for many years, which affect he refers to in the broadcast. But what he was doing is giving Microsoft's vision for Iot and the business implications and the business opportunities for for a customers. I really think you're going to enjoy it, and for those of you who always wondered about what a digital twin was or the metaverse, well, this is the podcast for you, because he actually very effectively simplifies that and talks about about Microsoft digital twin strategy, but also what the Meta verse is going to be for industry going forward and why it's much more than second life, which is what you might think it is so far. And we can finish the podcast by just giving a vision of how all the different technologies in the industry will come together and eventually or collaborate on behalf of customers, which will produce a huge increase in productivity, particularly between companies, between companies that are collaborating across things like supply chain, etc. So a lot in the episode, a lot of great content and I'm sure you will enjoy it. So with that, let me hand you over to my conversation with Tony Shikib, the GM of Microsoft Azure for Iot. So, Tony, thanks again for joining us. We've done quite a few of these podcasts and one thing that the listeners, I think, always always like is is to actually learn a little bit more about the person before they go into the subject matter. So, just for the people who don't know you, I mean I think a lot of people do, you're the GM of Microsoft as your Iot so it's a you know, a big player in the IOT industry. But delighted to have you on the on the show, but you know you haven't always been that. So what's the quick potted history of Tony from sort of university onwards? So first of all, Nex, thank you so much for having me on this show. I really enjoyed these series that you put together as very informative and really honored to be here today. You know, in terms of my background, you know I spent the first eighteen years after college nortel and Bell Northern Research, which at the time was like the build ups of Canada. A lot of innovation and I got to learn nationwide networks, like how to put together things that connects the continents together, and had a lot of fun. They're then I was CEO's of three different companies, you know, here in that Bay area. One of them still around when we took public and the last one I sold it, of which Cisco was an investor. It was a fascinating company in the area of Home Automation and home control. That kind of got me into Iot. Then I spent eight years at Cisco, four years running emerging markets out of UK or Nick, you and I had the great opportunity to work together, and then the last four years really leading the Iot practice for Cisco and it was a fascinating job because, you know, we really need to learn industries,...

...we really needed to understand, you know, what are the business problems that these industries are trying to solve and then apply technology towards solving it. So that kind of like got me into this industry learning mode and Iot. And then, you know, now been with Microsoft for five years. It's been an incredible journey and, you know, trying to do the same thing, really a flying cloud technologies to solve business problems and accelerate, you know, value delivery. So that's kind of like my background and so again, thanks for having me here today. You know, in terms of full disclosure, we did work together at Cisco and and actually, looking at your linkedin profile, I I think we graduated around about the same time. So for of course, a lot of our views or be thinking all these guys look far too young too about this much experience. But seriously, you, I mean, based on what you just said, you had a tremendous experience. That it and it is interesting the synergies between networking and Iot. That because, of course IOT represents an extension of the network, you know, to the edge. And when I started off, part of my career. About middle of it was we were extending from, you know, mainframed client server to PCs, to cloud, and then it was phones and now, of course, the big extension is the Itot Edge. And on that point I was looking at the gardener and the famous magic quadrant and you know, there's a lot of hyperscale cloud plays out there. But Microsoft, I think I've got this right. You've been the leader in the magic quadrant now, in this for three years and in the run. So, first of all, congratulations back to you. What is it that you're doing? Those guys are tough. I mean they push you hard. We get interviewed by Gardner. What are you doing that has kept you in that leadership position? And you know what? You explain the value proposition. Why you winning that award each year. Yeah, good question. Next, so, first of all, we're very honored and humble to be in the number ones. Fought for Industrial Iot, you know, the number one hyperscale cloud provider. And yes, they are tough. You know, this is not an easy position to gain. You know, they really come look at your technology, look at your ecosystem, look at your customers, talk to them and they make that determination and honestly, I think is a combination of all those three factors. You know, we have heavily invested in Iot, you know, and because we believe it's the biggest source of data that will come into the cloud. Most of the estimations that we've looked at, you know, only about thirty percent of the data is the crm and the digital data. Seventy percent of it will be the non you know, what we call observational data, that comes from sensors and high capacity sensors like cameras. So it's an area that we really believe in and we've heavily invested in three major areas. One is or technology stack or or textact that the whole IOT portfolio is one of the most comprehensive in the worlds, right both on the cloud side through Iot hub, which is our gateway into the cloud, and also we really believe in the edge, with Iot Edge were a lot of the magic happens, and the edge and a lot of the things will act we run at the edge and then the orchestration between the edge of the cloud. We also have heavily invested in digital twins, which is how do you create these ontologies and this knowledge, data, graph, semantics, graph that can, you know, help you build these highly complex itot solutions, simulated and drive it. So you know the technology is pretty complete. We also are strategy to go to market is through partners. We've heavily invested in our ecosystem and that's really another area that...

...we're doing very well. You know, having over Fivezero Iot partners in different technologies geographies. It really helps. And then, lastly, we have a super focus on different industries. Even though we have all this technology, it's just not going to come together by itself. So we put a lot of care into understanding, you know, the industrial iot manufacturing, both discrete and process, the energy sector, you know, healthcare, transportation, and then trying to really provide a guidance on how our technology should be applied and built through our partners or collection of partners to go to market. So it's a lot of work, it's a lot of heavy lifting, but it's yielding results and that's kind of like how it manifests that itself through the Gartner report, and you know we're very happy about it. Yeah, yeah, and maybe I just pick. You mentioned four areas. Maybe I just picked two to sort of unpack because I'm sure it's peak the interest of listeners and viewers on social media. We got the video feed. But but the first one is the Itot Edge. It is expanding rapidly to the edge, but it in some cases it's brand new devices. It's brand new, there's nothing they're already okay. That's it's feeling about you. But in other cases, in fact in the majority of cases, it's bumping into something which is legacy equipment which isn't smart. In fact it's the opposite of smart. I mean in the in the factory environment, it can be twenty, thirty years old. I mean these things are going back to the old scarred days and it's assets that are very expensive. They probably be completely depreciated, but they're not really work they're not part of this information model. So you mentioned the phrase the Itot Edge. What's your view on what the potential is for enterprise customers to bring the operations technology side of this into their Iot and the whole issue of it's, like you said, it's all about the data. If at the data is actually more valuable than the asset. But at the edge you've got a tremendous amount of legacy asset. So that must be a big area that you took to a customers about. It absolutely is. And and to record on us with you, nick. Originally, when we started at this whole Iot Journey, and was actually good for me, Sam George has been the leader of this group driving at I mean a lot of our focus was on the green field right then. How we create standardization? I mean we were one of the founders of all pcoa of how do we kind of like do that in a much more effective way? And even though we're having really good traction and success, the fact that the matter is that eighty ninety percent of the opportunity and the data is coming from the Legacy Brown field devices that have been there for a long time. The refresh cycle in a lot of these factories or like thirty, forty years, you know, once they install, like you said, the skater system, they lived there for a long time. So you can ignore that and you know. So that's why we kind of like shifted or strategy or augmented or strategy what three to four years ago to also go after the legacy devices, which meant and we had to heavily think about, you know, their characteristics, the way they generate the data. What's the most cost effective way to do the conversion? Where do you do it? And then all the protocol conversions that's involved and the and some of them are on very constrained battery operated devices, some of them are not. So that's what we built a lot of technology to effectively be able to handle both green field and brown field. And you know, some of the examples are like you go to a big you know teller, you know, where they have hundreds of security cameras already there for certain functions. They're not going to go yank them out. So instead of doing that, then we're putting...

...an edge device that has enough GPU power that can make those ordinary security cameras smart augment them to do you know, inventory management, theft management, shrink it without having to change anything in the store. You just put this other edge device and that's where you have the brain, that the you know, the AI machine learning functionality, without disrupting what sort of the end the store. Sometimes we do it there, sometimes we do it with the operators through the g edge and sometimes we can process it back in the club. It really depends on the application. So those are the kind of like that hybrid architecture that we've needed to develop and then the way that we could do the conversion of both, you know, Greenfield and Brown field devices to accommodate, you know, whatever is the customer scenario. Yeah, and and and I remember what in our sister days. But but if we were talking to people from Eric's and no tell whoever, we would all, as an industry, talk about the fact that eighty percent of processing is moving to the edge. Percent data is moving to the edges, not getting back hold to the center. And so when you describe that, you know, we used to say, didn't we? It's not that it's a data center. What we've now got is sent as a data so they need the center is actually exploding into seas events and being distributed. But you do still need a common architecture, don't you? I mean, I mean what you described is an architecture problem, because it's a data architecture, it's a process, it's governance, it's a security issue. The consequences are far bro far broader, complex than an aggregation device for that video debt for that video content to the edge. You know, neck that that is an excellent point that I think a lot of people don't understand. Just because you have to process the data at the edge, you know, because they're just too much data being, you know, generated, or you don't have the uplink to absorb the data or various reasons. They need to be error gapped because of certain conditions. It doesn't mean that you don't need a central nerve center to manage these edge devices. Yeah, you know, you still need to make sure that these things are healthy, they're secure, they're having the right from word, they're functioning properly and, you know, doing their job, but centrally managed. And that's what we do, you know, between in our architecture, you know, we can, you know, manage the data ware of it needs to be managed, but centrally keep track of everything in the cloud and provide that, you know, global view of the you know, the most efficient way to run your business. So that's what we call the hybrid, you know, intelligent edge Intel of cloud quartet. Yeah, and it because it's so complex. I think both both companies, yourself too much breader degree than us, but certainly we actually our first engagement is services led, so to speak, giving advice and architecture advice. And whatever, because if you just do the technology but you don't do that piece, the project fails, which kind of brings me on to the second big question, is that that's sort of what you've done so far and you've got the leadership. But but I know, having a visited you guys up there pre covid days. In fact I was up there, I don't really recall, I came to one of your Iot summits and I think February two thousand and nineteen, and then we read in the press after a week after I got back to London, that the first outbreak in the US was not far away from yes, from your office, my last trip to the US. I still haven't been back yet, but but I know from that one and your recent ones, which have been virtual, that you're not standing still. In fact you're working on a lot of new stuff now, because I open above everything that you've talked about, there's a whole bunch of things that you're now talking about. You the company, and sometimes people scratch their heads and and you know one of the purposes of this...

Iot leaders podcast is to try and demistify some of the things that's going on and just you know, break it down and took it make it real. And so the one that that I heard about for the first time in two thousand and nineteen at your event was digital twins, and I know that you're making a big deal. Microsoft makes much more AB in my view of that than any other company. You really believe in it. So maybe for for the listeners, can you just sort of simplify digital twins? What is it and what's it used for? What are the benefits? Yeah, that's a great question. You know, we stumbled into digital twins through our smart buildings practice and what we learned is that you know, for it's like you when you're building a house. The first thing that you need to do you need to bring the architect and you need to kind of look start thinking about where everything's going to go. You know, the floors, the walls and all the way down to the therm of staff, the bises, chairs and things like that, and it's sometimes hard to think about how are you going to digitize your business before knowing you know how this product is built, you know where do you put things? What's the best way to do it? And that's the fascinating job that an architect has. You think about digital twins. It's like the job of that architect right that you have to go and create a semantics, you know graph. It's and it's kind of a knowledge graph, but it's more on the data Schema and data semantics of creating the relationship between, you know, the actual devices, the people and the environment. So it's that context that's super important and when you have that contact, the beauty of it is two things. One is that before you actually go build a product, think of it as an engine. You can do a lot of simulation to figure out what is the best way to build that engine. Rather than building a fifty times and doing trial and error, you can kind of like try to figure out what is the best placement of things to kind of like create that environment right, so you get to the, you know, optimum position faster. And then the second value is that once you've built it and this thing is up and running, it's not like everything static. Things change all the time. So, without disrupting your business, then you can always run active simulations and AI modules to Ai Algorithms to figure out like how do you, how do I keep running this thing better and better to improve the efficiency and the capability right so those are the two things and that's really what you know, what we're doing is that we're providing a service for our customers that they can model their business, you know, and then they can have that ontology, whether it's a mall, whether it's an airport, whether it's a hospital, that they can keep track of how it's functioning, they have real time visibility of its performance and they can keep tweaking it without bringing it down. By the way, you know, the core concept of digital twins started with NASA, with Apollo Eleven. You know, when they sent the first one two outer space, they couldn't tink her with it anymore. So they had a replica of it and they can tribe things on it and to see her. Yeah, Hey, what is the best thing to do? And then they sent the commands to the one that was actually in space. That's where it all started, back in s and now just getting perfective and getting better and better. You know, the Vision I've got in my mind, Turney, when you're describing that is I was thinking about the house. The architect is that, you know, when I got my last house, I mean even as recently, you know, not that many years ago. You've basically got a brochure and a floor plan, but you had no idea what the house was. You have no idea what the house wasn't yet to go and visit the house. And then, just occasionally people it started to be you could go to a website and you could you could get a camera and you could see someone else walking around the house. But what you're de describing is is is where you could actually almost like enter the house...

...or the architect or the builders. I could say, well, would this work if I was to put a door here, with this, with this work, if I was to do this, and so, an ongoing basis, try out your home improvements, try out changes to the house, without actually doing it in the House and making a mistake and having to underdo and it sounds it actually is enabled by all these technologies and it sounds so familiar, or similar rather to, you know, an announcement that we've all seen recently, which is facebook, you know, and facebook talking renaming the company. Met and lots of comments as did they do that for other reasons, but we won't go there. But the idea of the metaverse and it's always seemed a bit futuristic. I remember when second life came out, I, along with many others, sort of went in there and after about ten minutes I got bored and I was thinking, tell me why I would do this, and then it started coming into by the gaming industry and people found ways to make money by digital tokens and whatever. But I know that something else, that the idea of matter and Meta verse is something that Microsoft is also taking very seriously. I mean I mean the additional turns is one example, isn't it? But but you believe that it will enter our lives and and it will change a lot of things. Right. Yeah, absolutely. You know, we we believe in Meta verse in a Big Way and Sutia and Saint George and many of the leaders of Microsoft have been talking about it for a while, you know. I think about nine months ago, you know, we discussed it and we're actively are working on it. So the first of all, you know, the whole concept of matter verse, to make it very simple, it's really to bring you know, we have this we have this previous concept that we call reality as a service, and it's basically bringing compute to every environment. And when you bring compute and intelligence into an environment, it can help create really amazing things. That is the simplest form of what I think about. You know, want to talk about the Meta verse. If you think of but the Meta verse itself, it really is like three different domains that we separate out. There is a consumer matter verse, which I think is where, you know, facebook is mostly focused on. There's the enterprise metal verse and then there's the industrial metaverse. So we're focused on the ladder two, not so much on the first one, and you've seen like recently at ignite, which is a big event, we talked a lot with our teams on the Enterprise Meta verse. You know, the kind of things that we could do to in the collaboration, you know, using avatars and other forms of virtual reality to make engagements a lot more engaging and interesting. And we're obviously in the iota side, or heavily focus on the industrial Iot side of the metaverse. And basically, you know, we have it Meta verse. It's comprised of a lot of different technologies and when we talked about the matter verse, is like how do we compose or stack together in a lot, you know, more seamless fashion that we can bring those reality, you know, virtual ideas to reality. And, as you said, so it's not futuristic. Is something that people can take value, you know, out of it right away. And the way what kind of like thinking about it is that Iot is the foundational layer to bring all the data. Is the ingest layer of the observational data. We have to be in much with the real world. That's what Iot brings forward. The next layer is digital twins that will start making sense of that data. Of How do we put it in the context of the environment that they live in? The next layer is the synapps, which is our analytics engine that says,...

...okay, all the data's coming in and I've got it into the rights must but what is that data really telling me, you know, in terms of, you know, the business values that we want to deliver, whether it's inventory reduction or o ee optimization or asset up time. So that's the next layer. And then from there we have another set of technologies like bons eye, that is machine reinforcement learning, and then we have our aarvr capabilities and many other things that, once you can pose the whole stack together, you can see that we can get that physical data, start modeling it, visualizing the data. You know, that's been contextualized and then imagine what are the best outcomes and quickly get up to those, you know, outcomes that people are looking for. So it is like a you know, the two worlds of the actual physical world that we live in the built virtual world that we want to live in, and connecting them together and making it real. That's kind of like what we're trying to do with metaphors. The image I have in my mind, and I'd like to in a minute going and ask you, are the sort of individual technologies like g and others. But, but, but if the image I had in my mind is when everything becomes connected. So let's just take five g inside a factory. Everything millions of senses, everything will be connected private lity networks. But your fo lay, a model that you described, is that if you could do that and if you could do that between companies, not just within a company, then you could actually start modeling, to use a word of as much more than modeling. Its scenario testing, it's it's it's seeing the effects of things, almost like complex weather patterns. Almost is a millions of things, and actually trying to map it. Say if this change is over here, does it change over there? So the idea of supply chain collaboration between companies, the ability to companies to to do that between each other. That then becomes something you physically can't do without this, I mean you can't be the only way you can do it is to is the company's collaborate. You can't model it, but but what you am I right, that what you seem to be painting is a world where, what if we could model collaboration between companies and dynamic collaboration, and that's tremendously powerful. Yeah, in our IOT journey we've always have talked about three phases of maturity. One is the connected products, right, but you see, in fact, that we connect an elevator and you know where there's up or are them? Yeah, the other one is what we call connected environments, which digital twins brings forward. And then the third stage of maturity is what we call connected ecosystems, that not only you running your own operations, you're extending it to the people upstream and downstream. When we introduced Meta verse, you know, we had a great video the encourage all of your viewers to go seats on Youtube and we did it with a B Inbeth and then the best story that I can tell is that Ab Inbev, you know. So the company has been around four hundred fifty years. They make beer, you know, and the person that sits at the center it's the Brewmaster, right, and most of them are actually ladies. Interestingly enough, that kind of like the way it started. And then they have a very big challenge because they have to produce, you know, the same tasting beer in hundred and seventy countries around the world. Right. So they're sitting in the middle, but they're in a middle of a very complex supply chain all the way from the way they get the Boer, league which field it comes from, the rain and all the stuff, to when it comes to the factory, to the whole operations and to the distribution and then the way they deliver it. There's a million variables along this path that always is constantly...

...changing and they have to be in control of it, to manage this thing so the same quality comes out reliably inconsistently day after day in hundred seventy countries. It's not an easy thing to tag no, no, and almost like every process manufacturing company that you go through, you know, they have the same challenge, same challenge. Yeah, consistently no variables that they're in control of, variables that they're not in control of, events that they predict, events that they don't predict. That's I guess that was why I has it the weather analogy, and that's a whether in your case, is a is a really good one. They if you have storms where they hops and the balley are grown, it has a huge effect downstream eight months later exactly. Look at the problems that we have now around the world with the supply chain and supply chain diversification and chip shortages and all that stuff. So to be able to manage all of that, I think first of all, you need to visualize the data to understand what kind of state you're in. Honestly, a lot of people are running their business blind. You know, it's still with excels for a cheats. I don't know what are the issues. Second is contextualizing the data, so it's not the individual pieces of the data, but putting it all together in the context of their business. Third, is simulating the data to see which one is going to give them the best outcome. And fourth is actually executing on that data to the point that is being done autonomously. So it's the computers making those decisions and either augmenting human decision making or they don't get on their roll. Those are kind of like the levels of maturity that we all need to go through, and any business that's at the fort level they're going to be incre incredibly more successful than their competition. That's quite a journey for people. It it and it's an executive. It Raises Iot from the project product, individual product layer in the company to the XO executive, sweet player, and I you know, I think very few companies in our experience I've really grasp that. It's still many cases a project. And one of the reasons it's a it's a project is that people are which brings me to the fourth big question. One of the one of the reasons it's a project is that it's still, frankly, too damn complicated. I mean either reason I got a balloon behind my head is some of our imagery is around, you know, rising above the complexity and giving you the view of what's of what's happening. So so actually, if we can flip from the the overall view and then down into some of the more basic technology components, we are as SI. You know we're we're cellular and we have a bunch of customers for the Fortune Ten, two Thousan customers. But but there's a lot of other technologies out there. When you were telling your story, I was thinking of satellite you know, I was thinking of satellites and I was listening to a podcast by Danny forts and, who's the technology writer for the Sunday Times, and he interviewed coming called planet that photographs of the World Twice Day, quite amazing from shoot oo sized satellites and and so you know that idea of monitoring the crops. You have to use that's all right. And then, obviously cellular. We understand about eight hundred and twenty cellular companies out there. But then you've got other technologies, which are really lpone, low power battery device. Optimize that. I noticed in my research that that you are I think you joined the board of Laura One as a crime nation, if I've got that right. So maybe you can just explain a little bit about what that's all about and how you see these pieces fitting together, because it is complex for people. Yet the vision and you have all these technologies and some of them seem to compete and yet others they have to be complimentary on behalf of the customer. Yeah, now, that's a...

...good question that you're absolutely right. I did very happy to join the board of Laura. It's a great set of companies and you know, the reason that I did it is, you know, first of all, from a Microsoft point of view, were really agnostic to the way that the data comes in. Or goal is to be able to ingest the data and do incredible things with that in the cloud and be the world's computer right, and we work with all technologies. You know, whether it's never been Iot with many of our, you know, cellular operators, whether it's g whether it's just physical layer coming in, you know, it doesn't matter. But Laura is yet another channel to connect. You know, hundreds of millions of will be called highly constrained devices, devices that, as you said, or battery operated, that need a long range to be able to get through them, that are in difficult areas like in a building, you know, in the basement or whatever, and Laura just seems to be a very good technology to be able to get to these things. You know, it has somewhere, you know, reliably ten mile range some of these things can be on a battery operated device for five to seven years and it just solves a big problem. So that's what we really excited about it. And there's just many applications were, you know, there's an enterprise in the middle of nowhere that they don't have any kind of other connectivity and then they can put this gateway in there. They get the range, they have visibility of their devices, they can reliably manage them and that's yet another way that we can add the services that we have on Azure, you know, and our IOT cloud to these devices. That's why we joined really excited about it. And for like utility market, there's a lot of good traction around it. For Logistics Market, you know, like you have a ship out on the sea, it's got a lot of different containers, things need to be monitored. It's a great right way and then they could have a sound like back hall for, you know, a lot of the logistics call chain tracking. It's great, and also in healthcare and agriculture in particular. It's got wide applicability. So we're pretty excited about it. And yet, you know, it's it's another technology to add to or portfolio and I think of Microsoft, we can really help with some of our chippabilities, like plug and play, to make it easy for these law of devices to just connect to the network seamlessly and work. That's why we join. Yeah, and probably that's a good way to try and wrap a bow around this to finish, because I think, as I said at the beginning, unit have been around the technology industry for a few years and one thing that we've always seen. It's always been the cases that the industry tends to talk about itself a lot and doesn't talk about how they solve problems enough. And so, you know, you get debates about world what about law of us? Is Sick folks versus primary Uity, this is public this versus satellite. We got ask specsions about that. But really, from a user point of view, they really they don't want us to compete. What they actually want is the business outcome. In fact, you know, we are re design hardware. We've designed over over two hundred hardware devices for our customers and what we basically say to them is, look, you're a you're a meter company. Europe mentioned the utilities, or you're a cost for selling, selling coffee. You you don't want to have to go back and design hardware and the same way you don't want to have to be an expert on all of the different radio access network technologies. And I still think it's a challenge for all of us to to actually translate it from from inside out to outside in. In other words, let's let's talk about what the business benefits and the road map of how you get there. And we've got people...

...who can work out the technology pieces and they'll change over time. But I think we are maturing as an industry. I think we've it's just that you're seeing the maturing in Iot right now, which you know, we were talking about this in the s. We were talking about in the s the first decade, two thousands, and now we're talking about it in Iot. But we will, we will make it all interoperable. I mean technology always starts off as proprietary. User demand causes the introduction of interoperability in some forms of standards and then adoption goes through an inflection point and that's always been the rule for technology and I think our feeling is that that's where we are right now and we are seeing, as you said, we are seeing now some great case studies of people who have sort of punch through all of that and are getting returns or business outcomes it orders of magnitude greater. I mean in the case just of what you just talked about, the idea of it assuring in the ear of massive Iot, so not just Iot, but but getting the sensors down and pricing so it can actually be at hatched to a thing and maybe a printable center of print a print a printable battery, so then you can start putting sensors on food supply chain, vaccines, plow sensors into the soil so they can measure measure the water content so you know where to turn the waters on, things like that. That scene. We seem to be getting to that area where these solutions are nowcoming and so that's a whole nother podcast on its own to talk about some of the case studies that we're both seeing. Absolutely I've got an eye on the clock and I want to be respectful of your time, so I'm going to sort of draw it to a close here. Thanks very much for demistifying it, which is what we're trying to do. I think a lot of people would have learned an awful lot about architectural models, digital twins. Maybe met averse really is a thing and there is something behind what Zukerberg is saying, not just renaming the company, and the idea of virtually modeling an enterprise in a multi company collaborative environment by business process is enough to blow anyone's head. Maybe in a few few years will take that for granted and we'll be talking about the AIML on top of it and all the things we can do. But in the meantime, Tony, thanks again. I really appreciate it. And and for you, the listeners. Thank you for listening or watching and this has been the IOT leaders podcast. And if you want to reach out, well, that's a question for you, Tony. Of If people want to message you at all or ask you questions, is there some the best way of doing it? If they want to US link them is fully the easiest way and a lot of people do reach out and I really welcome down. Please do and and there thank you so much for having me here. Really enjoy the conversation. Right, all right, thanks again, and if you want to ask me a question, need to do Linkedin as well. Nickel R Reli or Iot leaders at SI seyecom. Thank you for listening and I hope you enjoyed this episode as much as I did. Thank you very much. Thanks for tuning in to Iot leaders, a podcast brought to you by Si our team delivers innovative Global Iot cellular connectivity solutions that just work, helping our customers deploy differentiated experiences and disrupt their markets. Learn more at SICOM. You've been listening to Iot leaders, featuring digitization leadership on the front lines of Iot. Our Vision for this podcast is to be your guide to Iot and digital disruption, helping you to plot the right route to success. We hope today's lessons, stories, strategies and insights have changed your vision of Iot. Let us know how we're doing by subscribing, rating, reviewing and re recommending us. Thanks for listening. Until next time,.

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