>> the CUBE presents Dell Technologies World brought to you by Dell. >> Hey everyone, welcome back to the CUBE'S coverage day one, Dell Technologies World 2022 live from The Venetian in Las Vegas. Lisa Martin, with Dave Vellante. We've been here the last couple of hours. You can hear probably the buzz behind me. Lots of folks here, we're think around seven to eight thousand folks in this solution expo, the vibe is awesome. We've got two guests helping to round out our day one coverage. Ryan Fournier joins us, senior director of product management Edge Solutions at Dell Technologies. And MuneyB Minttazuddin vice president of Edge Computing at VMware. Guys, welcome to the program. >> Oh, glad to be here. >> Yeah. >> Isn't it great to be here in person? >> Oh man, yes. >> The vibe, the vibe of day one is awesome. >> Yes. >> Oh yeah. >> I think it's fantastic. >> Like people give energy off to each other, right? >> Absolutely. So lots of some good news coming out today so far on day one. Let's talk about, Ryan let's start with you. With Edge, it's not new. We've been talking about it for a while, but what are some of the things that are new? What are some of the key trends that you are seeing that are driving changes at the Edge? >> Great, good question. We've been talking to a lot of customers. Okay, a lot of the customers you know, the different verticals really find that is a common theme happening around a massive digital transformation and really based on the pandemic, okay. Which caused some acceleration in some, but also not, but many are kind of laggers left behind. And one primary reason is the culture of the OT, IT, you know, lack of barriers or something like that. The OT is obviously the business outcomes, okay. Focused where the IT is more enabling the function and it'll take retail. For example, that's accelerated a significant usage of an in-store frictionless experience, okay. As well as supply chain automation, warehousing logistics, connected inventory, a lot of the new use cases in this new normal post that pandemic. It's really that new retail operating landscape. >> Consumers we are so demanding, we want the same experience that we have online and we want that in the store and that's really driving a lot of this out of consumer demand. >> Oh yeah, no. I think, you know, retail you know, the way you shop for milk and bread change during the pandemic, right? There was pre-pandemic. The online shopping in the United States was only 5%, but during the pandemic and afterwards that's going to caught up to 25, 30%. That's huge. How do you bring new processes in? How do you create omnichannel consumer experiences where online well as physical are blended together? Becomes a massive challenge for the retailers. So yes, Edge has been there for a long time. Innovation hasn't happened, but a simple credit card swipe When you used to pre-pandemic, just to go do your checkout now has become into a curbside pickup. Integration with like, it's just simple payment card processing is not complicated like, you know, crazy. So people are forced to go in a way and that's happening in manufacturing because they're supply chain issues, could be not. So a lot of that has accelerated this investment and what's kind of driving Edge Computing is if everything ran out of the cloud, then you almost need infinite bandwidth. So suddenly people are realizing that everything runs out of cloud. I can't process my video analytics in a store. That's a lot of video, right? >> So we often ask ourselves, okay, who's going to win the edge? You know, we have that conversation. The cloud guys? VMware? You know, Dell? How are they going to go at it? And so to your point, you're not going to do a round trip to the cloud too expensive, too slow. Now cloud guys will try to bring their cloud basically on prem or out to the edge. You're kind of bringing it from the data center. So how do you see that evolution? >> No, great question. As the edge market happens, right? So there's market data now which says enterprise edge workloads in the next five years are going to be the fastest growing workloads. But then you have different communities coming to solve that problem. Like you just said, John is, you know, hyperscalers are going, Hey, all of the new workloads were built on us, let's bring them to the edge. Data center workloads move to the edge. >> Now important community here are, you know, Telcos and Service Providers because they have assets that are highly distributed at the edge. However, they're networking assets like cell towers and stuff like that. There's opportunity to convert them into computer and storage assets. So you can provide edge computing POPs. So you're seeing a convergence of lot of industry segments, traditional IT, hyperscalers, telcos, and then OT like Ryan pointed out is naturally transforming itself. There's almost this confluence of this pot where all these different technologies need to come together. From VMware and Dell perspective, our mission is a multi-cloud edge. We want to be able to support multi-cloud services because you've heard this multiple times, is at the edge consumers and customers will require services from all the hyperscalers. They don't want buy a one hyperscaler suit to suit solution. They want to mix and match. So not bound. We want be multi-cloud south bound to support IT and OT environments. So that becomes our value proposition in the middle. >> Yep. >> So Ryan, you were talking about that IT, OT schism. And we talk about that a lot. I wonder if you could help us parse that a little bit, because you were using, for instance retail, as an example. Sometimes I think about in the industrial. >> And I think the OT people are kind of like having an engineering mindset. Don't touch my stuff. Kind of like the IT guys too, but different, you know. So there's so much opportunity at the edge. I wonder how you guys think about that? How you segment it? How you prioritize it? Obviously retail telco are big enough. >> Yep. >> That you can get your hands around them, but then there's to your point about all this data that's going to going to compute. It's going to come in pockets. And I wonder how you guys think about that schism and the other opportunity. >> Yeah, out there. It's also a great question, you know, in manufacturing. There's the true OT persona. >> Yeah. >> Okay, and that really is focused on the business outcomes. Things like predictive maintenance use cases, operational equipment effectiveness, like that's really around bottleneck analysis, and the process that go through that. If the plant goes down, they're fine, okay. They can still work on their own systems, but they're not needing that high availability solution. But they're also the decision makers and where to buy the Edge Computing, okay. So we need to talk more to the OT persona from a Dell perspective, okay. And to add on to Ryan, right. So industrial is an interesting challenge, right? So one of the things we did, and this is VMware and Dell working together at vMware it was virtual. We announced something called edge compute stack. And for the first time in 23 years of vMware history, we made the hypervisor layer real-time. >> Yep. >> What that means is in order to capture some of these OT workloads, you need to get in and operate it between the industrial PC and the program of logical controllers at a sub millisecond performance level, because now you're controlling robotic arms that you cannot miss a beat. So we actually created this real time functionality. With that functionality in the last six months, we've been able to virtualize PLCs, IPCs. So what I'm getting at is we're opening up an entire wide space of operational technology workloads, which we was not accessible to our market for the last 20 plus years. >> Now we're talking. >> Yeah. And that allows us that control plane infrastructure to edge compute. There's purpose built for edge allows us to pivot and do other solutions like analytics with the adoption of AI Analytics with our recent announcement of Deep North, okay. That provides that in store video analytics functionality. And then we also partner with PTC based on a manufacturing solution, working with that same edge compute stack. Think of that as that control plane, where again, like I said, you can pivot off a different solutions. Okay, so we leverage PTCs thing works. >> So, okay, great. So I wanted to go to that. So real-time's really interesting. >> 'Cause most of much of AI today is modeling done in the cloud. >> Yes. >> The real opportunity is real time inferencing at the edge. >> You got it. >> Okay, now this is why this gets so interesting. And I wonder if Project Monterey fits into this at all. because I feel like so why did Intel win? Intel won, it crushed all the Unix systems out there because it had PC volumes. And the edge volume's going to dwarf anything we've ever seen before. >> Yeah. >> So I feel like there's this new cocktail, you guys describe this convergence and this mixture and it's unknown. What's going to happen? That's why Project Monterey is so interesting. >> Of course. >> Yeah. >> Right? Because you're bringing together kind of hedging a lot of bets and serving a lot of different use cases. Maybe you could talk about where that might fit here. >> Oh absolutely. So the edge compute stack is made up of vSphere, Tanzu, which is vSphere's you know, VM container and Tanzu's our container technology and vSphere contains Monterey in it, right. And we've added vSAN a for storage at the edge. And connectivity is SD-WAN because a lot of the times it's far location. So you're not having a large footprint, you have one or two hoses, it's more wide area, narrow area. So the edge compute stack supports real-time, non-real-time time workloads. VMs and containers, CPU GPU, right. >> NPU, accelerators, >> NPU, DPU all of them, right. Because what you're dealing with here is that inferencing real time, because to Ryan's point, when you're doing predictive maintenance, you got to pick these signals up in like milliseconds. >> Yes. >> So we've gone our stack down to microseconds and we pick up and inform because if I can save this predictive maintenance in two seconds, I save millions of dollars in you know, wastage of product, right? >> And you may not even persist that data, right? You might just let it go, I mean, how much data does Tesla save? Right? I mean. >> You're absolutely right. A lot of the times, all you're doing is this volume of data coming at you. You're matching it to an inferencing pattern. If it doesn't match, you just drop, right. It's not persistent, but the moment you hit a trigger, immediately everything lights go off, you're login, you're applying outcome. So like super interesting at the edge. >> And the compute is going to go through the roof. So yeah, my premise is that, you know, general purpose x86 running SAP is not going to be the architecture for the edge. >> You're absolutely right. >> Going to be low cost, low power, super performance. 'Cause when you combine the CPU, GPU, NPU, you're going to blow away the performance that we've ever seen on the curves. >> There's also a new application pattern. I've called out something called edge-native applications. We went through this client-server architecture era. We built all this, you know, a very clear in architecture. We went through cloud native where everything was hyperscaled in the cloud. Both of the times we optimize our own compute. >> Yeah. >> At the edge, we got to optimize our owns data because it's not ephemeral compute that you have in hyperscale compute space, you have ephemeral data you got to deal with. So a new nature of application workloads are emerging. We call it edge-native apps. >> Yep. >> And those have very different characteristics, you know, to client server apps or you know, cloud native apps, which is amazing. It's driven by data analysts like developers, not like dot net Java developers. It's actually data analysts who are trying to mine this with fast patents and come out with outcomes, right? >> Yeah, I love that edge-native apps Lisa, that's a new term for me. >> Right, just trademark it on me. I made made it up. (panel laughing) >> Can you guys talk about a joint customer that you've really helped to dramatically transform in the last six months? >> You want to shout or I can go-- >> I think my industry is fine. >> Yeah, yeah. So, you know, at VMworld we talked about Oshkosh, which is again, like in the manufacturing space, we have retailers and manufacturers and we also brought in, you know, Proctor and Gamble and et cetera, et cetera, right? So the customers look at us jointly because you know edge doesn't happen in its own silo. It's a continuum from the data center to the cloud, to the edge, right. There's the continuum exists. So if only edge was in its own silo, you would do things. But the key thing about all of this, there's no right place, it's about that workload placement. Where do I place the workload for the most optimal business outcome? Now for real-time applications, it's at the edge. For non-real-time stuff it could be in the data center, it could be in a cloud. It doesn't really matter, where VMware and Dell strengths comes in with Oshkosh or all of those folks. We have the end-to-end. From you want place it in the data center, You want to place it in your charge to public cloud, You want to derive some of these applications. You want to place it at the far edge, which is a customer prem or a near edge, which is a telco. We've done joint announcements with telcos, like South Dakota Telecom, where we've taken their cell towers and converted them into compute and storage. So they can actually store it at the near edge, right. So this is 5G solutions. I also own the 5G part of the vMware business, but doesn't matter. Compute network storage, we got to find the right mix for placing the workload at the right place. >> You call that the near edge. I think of it as the far edge, but that's what you mean, right? >> Yeah, yeah. >> Way out there in the (mumbles), okay. >> It's all about just optimizing operations, reducing cost, increasing profitability for the customer. >> So you said edge, not its own silo. And I agree. >> it's not a silo. Is mobile a valid sort of example or a little test case because when we developed mobile apps, it drove a lot of things in the data center and in the cloud. Is that a way to think of about it as opposed to like PCs work under their own silo? Yeah, we connect to the internet, but is mobile a reasonable proxy or no? >> Mobile is an interesting proxy. When you think about the application again, you know, you got a platform by the way, you'll get excited by this. We've got mobile developers, mobile device manufacturers. You can count them in your fingers. They want to now have these devices sitting in factory floors because now these devices are so smart. They have sensors, temperature controls. They can act like these multisensory device at the edge, but the app landscape is quite interesting. I think John, where you were going was they have a very thin shim app layer that can be pushed from anywhere. The, the notion of these edge-native applications could be virtual machines, could be containers, could be, you know, this new thing called Web Assembly Wasm, which is a new type of technology, very thin shim layer which is mobile like app layer. But you know, all of these are combination of how these applications may get expressed. The target platforms could be anywhere from mobile devices to IOT gateways, to IOT devices, to servers, to, you know, massive data centers. So what's amazing is this thing can just go everywhere. And our goal is consistent infrastructure, consistent operations across the board. That's where VMware and Dell win together. >> Yeah. >> Yeah, excellent. And I was just talking to a customer today, a major airline manufacturer, okay. About their airport and the future with the mobile device just being frictionless, okay, no one wants to touch anything anymore. You can use your mobile device to do your check-in and you've got to you avoid kiosks, okay. So they're trying to figure out how to get rid of the kiosk. Now you need a kiosk for like checking baggage, okay. You can't get in the way of that, but at least that frictionless experience, for that airport in the future, but it brings in some other issues. >> It does, but I like the sound of that. Last question guys, where can customers go to learn more information about the joint solutions? >> So you can go to like our public websites obviously search on edge. And if you hear at the show, there's a lot of hands on labs, okay. There's a booth over there. A lot of Edge Solutions that we offer. >> Yeah, no, this is I guess as Ryan pointed our websites have these. We've had a lot of partnership in announcements together because you know, one of the things as we've expressed, manufacturing, retail, you know, when you get in the use cases, they involve ISPs, right? So they you know, they bring the value of you know, not just having a horizontal AI platform. We like opinionated models of fraud detection. So we're actually working with ecosystem of partners to make this real. >> So we may even hear more. >> The rich vertical solution, I call it the ISVs. They enrich our vertical solutions. >> Right. >> Oh, WeMo is going to be revolutionary. >> All right, can't wait. Guys thank you so much for joining David and me today and talking about what Dell and vMware are doing together and helping retailers manufacturers really convert the edge to incredible success. We appreciate your time. >> Thank you very much. Thanks Lisa, thanks John for having us. >> For Dave Vellante, I'm Lisa Martin. You're watching the CUBE. We are wrapping up day one of our coverage of Dell Technologies World 2022. We'll be back tomorrow, John Farrer and Dave Nicholson will join us. We'll see you then. (soft music)

>> From Boston, Massachusetts, it's The Cube, covering LiveWorx '18. Brought to you by PTC. >> Welcome back to Boston, everybody. This is the LiveWorx show, hosted by PTC, and you're watching The Cube, the leader in live tech coverage. I'm Dave Vellante with my co-host, Stu Miniman, covering IoT, Blockchain, AI, the Edge, the Cloud, all kinds of crazy stuff going on. Kevin Ashton is here. He's the inventor of the term, IoT, and the creator of the Wemo Home Automation platform. You may be familiar with that, the Smart Plugs. He's also the co-founder and CEO of Zensi, which is a clean tech startup. Kevin, thank you for coming on The Cube. >> Thank you for having me. >> You're very welcome. So, impressions of LiveWorx so far? >> Oh wow! I've been to a few of these and this is the biggest one so far, I think. I mean, it's day one and the place is hopping. It's like, it's really good energy here. It's hard to believe it's a Monday. >> Well, it's interesting right? You mean, you bring a ton of stayed manufacturing world together with this, sort of, technology world and gives us this interesting cocktail. >> I think the manufacturing world was stayed in the 1900s but in the 21st century, it's kind of the thing to be doing. Yeah, and this... I guess this is, you're right. This is not what people think of when they think of manufacturing, but this is really what it looks like now. It's a digital, energetic, young, exciting, innovative space. >> Very hip. And a lot of virtual reality, augmented reality. Okay, so this term IoT, you're accredited, you're the Wikipedia. Look up Kevin, you'll see that you're accredited with inventing, creating that term. Where did it come from? >> Oh! So, IoT is the Internet of Things. And back in 1990s, I was a Junior Manager at Proctor & Gamble, consumer goods company. And we were having trouble keeping some products on the shelves, in the store, and I had this idea of putting this new technology called RFID tags. Little microchips, into all Proctor products. Gamble makes like two billion products a year or something and putting it into all of them and connecting it to this other new thing called the internet, so we'd know where our stuff was. And, yeah the challenge I faced as a young executive with a crazy idea was how to explain that to senior management. And these were guys who, in those days, they didn't even do email. You send them an email, they'd like have their secretary print it out and then hand write a reply. It would come back to you in the internal mail. I'm really not kidding. And I want to put chips in everything. Well the good news was, about 1998, they'd heard of the internet, and they'd heard that the internet was a thing you were supposed to be doing. They didn't know what it was. So I literally retitled my PowerPoint presentation, which was previously called Smart Packaging, to find a way to get the word Internet in. And the way I did it was I wrote, Internet of Things. And I got my money and I founded a research center with Proctor & Gamble's money at MIT, just up the road here. And basically took the PowerPoint presentation with me, all over the world, to convince other people to get on board. And somehow, the name stuck. So that's the story. >> Yeah, it's fascinating. I remember back. I mean, RFID was a big deal. We've been through, you know-- I studied Mechanical Engineering. So manufacturing, you saw the promise of it, but like the internet, back in the 90s, it was like, "This seems really cool. "What are you going to do with it?" >> Exactly, and it kind of worked. Now it's everywhere. But, yeah, you're exactly right. >> When you think back to those times and where we are in IoT, which I think, most of us still say, we're still relatively early in IoT, industrial internet. What you hear when people talk about it, does it still harken back to some of the things you thought? What's different, what's the same? >> So some of the big picture stuff is very much the same, I think. We had this, the fundamental idea behind the MIT research, behind the Internet of Things was, get computers to gather the relevant information. If we can do that, now we have this whole, powerful new paradigm in computing. Coz it's not about keyboards anymore, and in places like manufacturing, I mean Proctor & Gamble is a manufacturing company, they make things and they sell them. The problem in manufacturing is keyboards just don't scale as an information capture technology. You can't sit in a warehouse and type everything you have. And something goes out the door and type it again. And so, you know, in the 90s, barcodes came and then we realized that we could do much better. And that was the Internet of Things. So that big picture, wouldn't it be great if we knew wherever things was, automatically? That's come true and at times, a million, right? Some of the technologies that are doing it are very unexpected. Like in the 1990s, we were very excited about RFID, partly because vision technology, you know, cameras connected to computers, was not working at all. It looked very unpromising, with people been trying for decades to do machine vision. And it didn't work. And now it does, and so a lot of things, we thought we needed RFID for, we can now do with vision, as an example. Now, the reason vision works, by the way, is an interesting one, and I think is important for the future of Internet of Things, vision works because suddenly we had digital cameras connected to networks, mainly in smartphones, that we're enable to create this vast dataset, that could then be used to train their algorithms, right? So what is was, I've scanned in a 100 images in my lab at MIT and I'm trying to write an algorithm, machine vision was very hard to do. When you've got hundreds of, millions of images available to you easily because phones and digital cameras are uploading all the time, then suddenly you can make the software sing and dance. So, a lot of the analytical stuff we've already seen in machine vision, we'll start to see in manufacturing, supply chain, for example, as the data accumulates. >> If you go back to that time, when you were doing that PowerPoint, which was probably less than a megabyte, when you saved it, did you have any inkling of the data explosion and were you even able to envision how data models would change to accommodate, did you realize at the time that the data model, the data pipeline, the ability to store all this distributed data would have to change? Were you not thinking that way? >> It's interesting because I was the craziest guy in the room. When I came to internet bandwidth and storage ability, I was thinking in, maybe I was thinking in gigabytes, when everyone else was thinking in kilobytes, right? But I was wrong. I wasn't too crazy, I was not crazy enough. I wouldn't, quick to quote, quite go so far as to call it a regret, but my lesson for life, the next generation of innovators coming up, is you actually can't let, kind of, the average opinion in the room limit how extreme your views are. Because if it seems to make sense to you, that's all that matters, right? So, I didn't envision it, is the answer to your question, even though, I was envisioning stuff, that seemed crazy to a lot of other people. I wasn't the only crazy one, but I was one of the few. And so, we underestimated, even in our wildest dreams, we underestimated the bandwidth and memory innovation, and so we've seen in the last 25 years. >> And, I don't know. Stu, you're a technologist, I'm not, but based on what you see today, do you feel like, the technology infrastructure is there to support these great visions, or do we have to completely add quantum computing or blockchain? Are we at the doorstep, or are we decades away? >> Oh, were at the doorstep. I mean, I think the interesting thing is, a lot of Internet of Things stuff, in particular, is invisible for number of reasons, right? It's invisible because, you know, the sensors and chips are embedded in things and you don't see them, that's one. I mean, there is a billion more RFID tags made in the world, than smartphones every year. But you don't see them. You see the smartphone, someone's always looking at their smartphone. So you don't realize that's there. So that's one reason, but, I mean, the other reason is, the Internet of Things is happening places and in companies that don't have open doors and windows, they're not on the high street, right? They are, it's warehouses, it's factories, it's behind the scenes. These companies, they have no reason to talk about what they are doing because it's a trade secret or it's you know, just not something people want to write about or read about, right? So, I just gave a talk here, and one of the examples I gave was a company who'd, Heidelberger. Heidelberger makes 60% of the offset printing presses in the world. They're one of the first Internet of Things pioneers. Most people haven't heard of them, most people don't see offset printers everyday. So the hundreds of sensors they have in their hundreds of printing presses, completely invisible to most of us, right? So, it's definitely here, now. You know, will the infrastructure continue to improve? Yes. Will we see things that are unimaginable today, 20 years from today? Yes. But I don't see any massive limitations now in what the Internet of Things can become. >> We just have a quick question, your use case for that offset printing, is it predictive maintenance, or is it optimization (crosstalk). >> It is initially like, it was in 1990s, when the customer calls and says, "My printing press isn't working, help", instead of sending the guide and look at the diagnostics, have the diagnostics get sent to the guide, that was the first thing, but then gradually, that evolves to realtime monitoring, predictive maintenance, your machine seems to be less efficient than the average of all the machines. May be we can help you optimize. Now that's the other thing about all Internet of Things applications. You start with one sensor telling you one thing for one reason, and it works, you add two, and you find four things you can do and you add three, and you find nine things you can do, and the next thing you know, you're an Internet of Things company. You never meant to be. But yeah, that's how it goes. It's a little bit like viral or addictive. >> Well, it's interesting to see the reemergence, new ascendancy of PTC. I mean, heres a company in 2003, who was, you know, bouncing along the ocean's floor, and then the confluence of all this trends, some acquisitions and all of a sudden, they're like, the hot new kid on the block. >> Some of that's smart management, by the way. >> Yeah, no doubt. >> And, I don't work for PTC but navigating the change is important and I want to say, all of the other things I just talked about in my talk, but, you know, we think about these tools that companies like PTC make as design tools. But they're very quickly transitioning to mass production tools, right? So it used be, you imagined a thing on your screen and you made a blueprint of it. Somebody made it in the shop. And then it was, you didn't make it in a shop, you had a 3D printer. And you could make a little model of it and show management. Everyone was very excited about that. Well, you know, what's happening now, what will happen more is that design on the screen will be plugged right in to the production line and you push a button and you make a million. Or your customer will go to a website, tweak it a little bit, make it a different color or different shape or something, and you'll make one, on your production line that makes a million. So, there's this seamless transition happening from imagining things using software, to actually manufacturing them using software, which is very much the core of what Internet of Things is about and it's a really exciting part of the current wave of the industrial revolution. >> Yeah, so Kevin, you wrote a book which follows some of those themes, I believe, it's How to Fly A Horse. I've read plenty of books where it talks about people think that innovation is, you know, some guy sitting under a tree, it hits him in the head and he does things. But we know that, first of all, almost everybody is building on you know, the shoulders of those before us. Talk a little bit about creativity, innovation. >> Okay. Sure. >> Your thoughts on that. >> So, I have an undergraduate degree in Scandinavian studies, okay? I studied Ibsen in 19th century Norwegian, at university. And then I went to Proctor & Gamble and I did marketing for color cosmetics. And then the next thing that happened to me was I'm at MIT, right? I'm an Executive Director of this prestigious lab at MIT. And I did this at the same time that the Harry Potter books were becoming popular, right? So I already felt like, oh my God! I've gone to wizard school but nobody realizes that I'm not a wizard. I was scared of getting found out, right? I didn't feel like a wizard because anything I managed to create was like the 1000th thing I did after 999 mistakes. You know, I was like banging my head against the wall. And I didn't know what I was doing. And occasionally, I got lucky, and I was like, oh they're going to figure out, that I'm not like them, right? I don't have the magic. And actually what happened to me at MIT over four years, I figured out nobody had the magic. There is no magic, right? There were those of us who believed this story about geniuses and magic, and there were other people who were just getting on with creating and the people at MIT were the second group. So, that was my revelation that I wasn't an imposter, I was doing things the way everybody I'd ever heard of, did them. And so, I did some startups and then I wanted to write a book, like kind of correcting the record, I guess. Because it's frustrating to me, like now, I'm called the inventor of the Internet of Things. I'm not the inventor of the Internet of Things. I wrote three words on a PowerPoint slide, I'm one of a hundred thousand people that all chipped away at this problem. And probably my chips were not as big as a lot of other people's, right? So, it was really important to me to talk about that, coz I meet so many people who want to create something, but if it doesn't happen instantly, or they don't have the brilliant idea in the shower, you know, they think they must be bad at it. And the reality is all creating is a series of steps. And as I was writing the book, I researched, you know, famous stories like Newton, and then less famous stories like the African slave kid who discovered how to farm vanilla, right? And found that everybody was doing it the same way, and in every discipline. It doesn't matter if it's Kandinsky painting a painting, or some scientist curing cancer. Everybody is struggling. They're struggling to be heard, they're struggling to be understood, they're struggling to figure out what to do next. But the ones who succeed, just keep going. I mean, and the title, How To Fly A Horse is because of the Wright brothers. Coz that's how they characterized the problem they were trying to solve and there are classic example of, I mean, literally, everybody else was jumping off mountains wit wings on their back, and dying, and the Wright brothers took this gradual, step by step approach, and they were the ones who solved the problem, how to fly. >> There was no money, and no resources, and Samuel Pierpont Langley gave up. >> Yeah, exactly. The Wright brothers were bicycle guys and they just figured out how to convert what they knew into something else. So that's how you create. I mean, we're surrounded by people who know how to do that. That's the story of How To Fly A Horse. >> So what do we make of, like a Steve Jobs. Is he an anomaly, or is he just surrounded by people who, was he just surrounded by people who knew how to create? >> I talk about Steve Jobs in the book, actually, and yeah, I think the interesting thing about Jobs is defining characteristic, as I see it. And yeah, I followed the story of Apple since I was a kid, one of the first news I ever saw was an Apple. Jobs was never satisfied. He always believed things could be made better. And he was laser focused on trying to make them better, sometimes to the detriment of the people around him, but that focus on making things better, enabled him, yes, to surround himself with people who were good at doing what they did, but also then driving them to achieve things. I mean, interesting about Apple now is, Apple are sadly becoming, kind of, just another computer company now, without somebody there, who is not-- I mean, he's stand up on stage and say I've made this great thing, but what was going on in his head often was, but I wish that curve was slightly different or I wish, on the next one, I'm going to fix this problem, right? And so the minute you get satisfied with, oh, we're making billions of dollars, everything's great, that's when your innovation starts to plummet, right? So that was, I think to me, Jobs was a classic example of an innovator, because he just kept going. He kept wanting to make things better. >> Persistence. Alright, we got to go. Thank you so much. >> Thank you guys. >> For coming on The Cube. >> Great to see you. >> Great to meet you, Kevin. Alright, keep it right there buddy. Stu and I will be back with our next guest. This is The Cube. We're live from LiveWorx at Boston and we'll be right back.