(melodious music) >> Voiceover: From around the globe. It's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Hi and welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We're a virtual this year. But we'll be in real life soon, right around the corner, as we come out of COVID. We got a great guest, a CUBE alumni, Jerry Cuomo, IBM Fellow VP, CTO for IBM automation. Jerry, great to see you. Been on since almost since the early days of theCUBE. Good to see you >> Yeah, John. Thrilled to be back again. Thank you. >> What I love about our conversations, one is you're super technical. You've got patents under your belt. You're on the cutting edge. You've been involved in web services and web technologies for a long, long time. You're constantly riding the wave. And also you're a creator of a great podcast called "The Art of Automation", which is the subject of this discussion. As automation becomes central in cloud operations and Hybrid Cloud, which is the main theme of this event this year and the industry. So great to see you. First give us a little background for the folks that may not know you, about your history with IBM and who you are. >> Yeah. So thanks John. So I'm Jerry Cuomo. I've been with IBM for about three decades and I started my career at IBM research in Yorktown at the dawn of the internet. And I've been incredibly fortunate as you mentioned, to be on the forefront of many technology trends over the last three decades, internet software, middleware, including being one of the founding fathers of WebSphere software. I recently helped launch the IBM blockchain initiative and now all about AI powered automation. Which actually brings me back to my roots of studying AI in graduate school. So it's kind of come full circle for me, really enjoying the topic. >> It's funny you mentioned AI in graduate school. I was really kind of into AI when I was an undergraduate and get a master's degree in Computer Science. I kind of went the MBA route. But if you think about what was going on in the eighties during those systems times, a lot of the concepts of systems programming and cloud operations kind of gel well together. So you got this confluence of computer science and engineering AKA now DevOps, DevSecOps, coming together. This is actually a really unique time to bring back the best of the best concepts. Whether it's AI and systems and computer science and engineering into automation. Could you share your view on this? Because you're in a unique position, you've been there done that, now you're on the cutting edge. What's your thoughts? >> Yeah, absolutely John. And just when you think of automation and time, automation is not new. That literally, if you go into Wikipedia and you look up automation, you see patents and references to like steam engine regulators at the dawn of the industrial era, right? So automation has been around and in its simplest form, automation whether it was back then, whether it was in the eighties or today it's about applying technology that uses technology software to perform tasks that were once exclusively done by us, humans. But now what we're seeing is AI coming into the picture and changing the landscape in an interesting way. But I think at its essence, automation is this two-step dance of both eliminating repetitive mundane tasks that help reduce errors and free up our time. So we get back the gift of time, but also helps. It's not about taking jobs away at that point, it's a sentence of two-step dance. That's step one. But if you stop there, you're not getting the full value. Step two is to augment our skills. And to use automation, to help augment our skills. And we get speed, we get quality, we get lower costs, we get improved user experience. So whether it was back in the steam engine times or today with AI, automation is evolving with technology. >> And it's interesting too, as a student of the history of the computer industry, as you are and now a creator with your podcast, which we'll get to in a second. You're starting to see the intersection of these concerts and not bespoke as much as they used to be. You got transformation, digital transformation and innovation are connected and scale. If you think about those three concepts, they don't stand alone anymore. They can stand alone, but they work better together. Transformation. And it is the innovation, innovation provides cloud scale. So if you think about automation, automation is powering this dynamic of taking all that undifferentiated heavy lifting and moving the creativity and the skillset into higher integrated areas. Can you share your thoughts? >> Yeah, no, right on there. When you talk about transformation, jeez, look around us. The pandemic has made, transformation and specifically digital transformation, the default. So everything is digital. Whether it's ordering a pizza, visiting a doctor through telemedicine, or this zoom WebEx based workplace that we live in. But picture a telemedicine environment, talking about transformation and going digital. With 10 X more users, they can't hire 10 X more support staff. And think about it. I forgot my password, does this work on my version of the Apple iPhone or all of that kind of stuff? So their support desks are lit up, right? So as they scale digitally, automation is the relief that that comes into play, which is just in time. So the digital transformation needs automation. And John, I think about it like this, businesses like cars have become computers. So they're programmable. So automation software just like in the cars, it makes the car self-driving. I think about the Tesla model three, which I recently test drove. So with this digital acceleration, digital opens the door for automation. And now we can muse about self-driving business. We can muse about maybe that's step one, right? That's the remove repetitive work, but maybe we can actually augment business to have an autopilot. So it doesn't need us there all the time to drive. And that's the scale that you talked about. That's the scale we need. So automation is really like the peanut butter and chocolate. Digital is the peanut butter automation is the chocolate. They go well together and they produce amazing tastes. >> Yeah. That's a really interesting insight. And I was just put an exclamation point on that because you mentioned self-driving business you're implying, you said the business is a computer. So if you just think about that mind blowing concept for a second. If it's a computer, what's the operating system and what's the suite of applications that are on top of it? So, okay. Let's go in the old days you had a windows machine and you had office, which was a system software, applications software construct. If you map that to the entire company, you're talking about Red Hat and IBM will kind of come working together. Kind of connects the dots a little bit on what Red Hat could, because they're not breaking system company. So if Hybrid Cloud is the system, edge, hybrid, then you got the application suite is all software for the business. >> That's right. That's right. And if you listen to anything these days about what IBM stands for, it's Hybrid Cloud and think Red Hat as kind of the core element of that with OpenShift and AI. And both of those really matter in terms of automation and maybe I'll come back to the Hybrid Cloud or Red Hat thing in a second, but let's just talk about Watson and AI, which is the application. You mentioned scale, which I'm so glad you did. AI could help scale automation. And the trick is, is that automation sometimes gets stuck. It gets stuck when it's working with data that is noisy or unstructured. So there's a lot of structured data in your organization. With that, we can breeze through automation. But if there is more ambiguous data, unstructured, noisy, you need a human in the loop. And when you get a human in the loop, it slows things down. So what AI can start to do, AI and its subordinates, machine learning, natural language processing, computer vision. We can start to make sense of both unstructured and structured data together and we can make a big deal going forward. So that's the AI part. You mentioned Red Hat and, and Hybrid Cloud Park. Well, think about it this way, when you shop, how many stores do you... You don't just shop in one store, right? You go to specialty stores to pick up that special catsup, I don't know or mustard. (audio cuts) In one store and maybe do shopping in another store. Customers using clouds John, aren't very different. They have their specialty places to go. Maybe they're going to be running workloads in Google, involving search and AI related to search. And they're going to be using other clouds for more specialty things. From that perspective, that's a view of hybrid. Customers today, take that shopping analogy. They're going to be using Salesforce or Servicenow, IBM cloud, they have a private cloud. So when you think about automating that world, it's the real world. It's how we shop, whether it's for groceries or for cloud. The Hybrid Cloud is a reality. And how do you make sense of that? Because when an average customer has five clouds, how do you deal with five things? How do you make it easy, normalize? And that's what Red hat really does. >> It's interesting. I'll just share with you though. When I interviewed Arvin, who is now the CEO of IBM when he was at Red Hat summit 2019 in San Francisco. Before he made the acquisition, I was peppering him with questions. Like, you need to get this cloud and he loves cloud, you know, he loves cloud. So he was smiling. He just wanted to say it, he wanted to just say it. And I think Red hat brings that operating kind of mindset where the clouds are just subsystems in the OS of the middleware, which is now software which is software defined business. And this kind of is the talk of your views. Now you have a podcast called "Art of Automation". We want to get that in there, for the folks watching. Search for the podcast, "Art of Automation". This is the stories that you tell. Tell us some stories, from this phenomena. What's the impact of automation for the holistic picture? >> Well, it starts with a lot of, I guess it starts with customers. The stories start with the customer. So we're hearing from customers that AI and automation is where they're investing in 2021. For all the reasons we briefly mentioned, and IBM has a lot to offer there. So we've made AI powered automation a priority. But John, in the pursuit of making it a priority, I've started talking with many of our subject matter experts and was floored by their knowledge, their energy, their passion, and their stories. And I said, we can't keep this to ourselves. We can't keep this locked away. We have to share it. We have to let it out. So basically this is what started the podcast around that. And since then, we've had many industry luminaries from IBM and outside. Starting with customers. We had Klaus Jensen who is the CIO of Memorial Clones Kettering Hospital to talk about automation in healthcare. And he shared great stories. You need to listen to them, about automation is not going to take the place of doctors. But automation will help better read x-rays and look at those shades of gray on the x-ray and interpret it much better than we can. And be able to ingest all of the up-to-date medical research to provide pointers and make connections that the human may not be able to do in that moment. So the two working together are better than any individual. Carol Polson recently joined me to talk, and she's the CIO for Cooperators, to talk about automation and insurance. And she had some great stories too. So John, with that, a bunch of IBM, great IBM fellows like Rama Akkiraju, who is one of Forbes top 20 women in AI research. Talking about AI ops. And also Ruchir Puri talking, and Ruchir has been working on Watson since jeopardy to tell stories about ultimately now how we're teaching AI to code and all the modern programming languages. And really automating application modernization and the like. Four keyed episodes in, we have those under our belt. About 6,000 downloads so far. So it's coming along pretty well. Thanks for asking, John. >> The key is you're a content creator now, as well as a fellow. And this is the democratization, as we say direct to audience, share those stories. Also here, I think you released an ebook. Tell us a little quickly about that. We've got one minute left, give a quick plug for the ebook. >> The book echoes the podcast. Chapters relate to the episodes of the book. We're dropping the first five chapters plus forward for free on the IBM website. Other chapters will become available and drop as they become available. The book makes the content searchable on the internet. We go into more detail with advice on how to get started. You get to hear the topics and the voice of those subject matter experts. And I really suggest you go out and check it out. >> All right, Jerry Cuomo. IBM fellow VP, CTO, IBM automation. Also a content creator, podcast "Art of Automation." Jerry, we're going to list it out on our Silicon angle and our cube sites, gets you some extra love on that. Love the podcast, love the focus on sharing from experts in the field. Thanks for coming on. >> Yeah. Thank you so much for having me again, John. >> Okay, I'm John Furrier with theCUBE. Here for IBM Think 2021. Thanks for watching.

>>from around the globe. It's the >>cube >>With digital coverage of IBM think 2021 brought to you by IBM. Hello and welcome back to the cubes coverage of IBM Think 2021 virtual. I'm john for a year host of the cube. We're virtual this year in real life. Soon, right around the corner as we come out of code, we've got a great guest cube alumni jerry, cuomo IBM fellow V P C T O for IBM automation jerry, Great to see you uh nonsense got almost since the early days of the cube. Good to see you, >>john thrilled to be back again. Thank you >>what I love about our conversations. One is your super technical, you've got patents under your belt during the cutting edge. You've been involved in web services and web technologies for a long, long time. You constantly riding the wave and also your creator of a great podcast called the art of automation, which is the subject of this discussion as automation becomes central in cloud operations and hybrid cloud, which is the main theme of this event this year and the industry so great to see you. Uh First team is a little background for the folks that may not know you about your history with IBM and who you are. >>Yeah, so thanks john, So I'm I'm jerry Carrillo, I've been with IBM for about three decades and I started my career at IBM research in Yorktown at the dawn of the internet and I've been incredibly fortunate, as you mentioned to be on the forefront of many technology trends over the last three decades. Internet software middleware, including being one of the founding fathers of web sphere software, uh I recently helped launch the IBM Blockchain initiative and now all about aI powered automation, which actually brings me back to my roots of studying AI and graduate school. So it's kind of come full circle for me, you know, really you know, enjoying the topic. >>You know, these funny, you mentioned aI in graduate school, I was really kind of into a I when I was an undergraduate and get a masters degree in computer science, I kind of went the NBA route. But if you think about what was going on in the eighties during those systems times, a lot of the concepts of systems programming and cloud operations kind of gel well together. So you've got this confluence of computer science and engineering A. K A. Now devops sec cops coming together. This is actually a really unique time to bring back the best of the best concepts, whether it's A I and systems and computer science and engineering into the automation. Could you share your view on this because you're in a unique position, you've been there, done that now. You're on the cutting edge with your thoughts. >>Yeah, absolutely, john And just when you think of automation and time, automation is not new, literally, if you go into Wikipedia and you look up automation, you see patents and references to like steam engine regulators at the dawn of the industrial era. Right? So automation has been around and and in the simplest form automation, whether it was back then, um whether it was in the 80s or today, it's about applying technology and that that performs, that uses like technology software to perform tasks that were once exclusively done by us humans. Right? So, but now what we're seeing is a I coming into the picture and and changing the landscape in an interesting way. But I think at its essence, you know, automation is this two step dance of both eliminating repetitive, mundane tasks. That helped reduce errors and free up our time. So we get back the gift of time but also helps. It's not about taking jobs away at that point, as I said, it's a two step dance, that's step one. But if you stop there, you're not getting the full value. Step two is to augment our skills right? And and to use automation to help augment our skills and we get speed, we get quality, we get lower costs, we get improved user experience. So whether it was back in the steam engine times or today with a I automation is evolving with technology >>and it's interesting to its you know, as a student of the history of the computer industry as you are and now a creator with your podcast which we'll get to in a second, you're starting to see the intersection of these concepts are not bespoke as much as they used to be. You got transformation. Digital, transformation and innovation are connected and scale. If you think about those three concepts they don't stand alone anymore. They can stand alone but they work better together transformation. And is the innovation innovation provides cloud scale. So if you think about automation, automation is powering this dynamic of taking all that undifferentiated heavy lifting and moving the creativity and the skill set into higher integrated areas. Can you share >>your john Yeah no right on there when you talk about transformation, jeez look around us, the pandemic has made transformation and specifically digital transformation the default so everything is digital. You know whether it's ordering a pizza, you know visiting a doctor through telemedicine or or this zoom webex based workplace that we live in. But picture of telemedicine environment right? Talking about transformation and going digital With 10 x more users. They can't hire 10 x more support staff and think about it I forgot my password. Um Does does this work on my version of the Apple iphone or all of that kind of stuff? So their support desks or lit up? Right. So uh as they scale digitally automation is the relief that that comes into play which is which is just in time. Right? So the digital transformation needs automation and john I think about it like this um businesses like cars are have become computers right? So they are programmable. So automation software just like in the cars it makes you know the car self driving? I think about the Tesla model three which I recently test drove. Um so with this digital acceleration digital opens the door for automation And now we can use about a self driving business. We can use about uh maybe that's step one, right? That's the um remove repetitive work, but maybe we can actually augment business to have an autopilot so it doesn't eat us there all the time to drive. And that's the scale that you talked about. That's the scale we need. So automation is really like the peanut butter and chocolate Digital is the peanut butter, automation is the chocolate. They go well together and they produce amazing tastes. >>You know, that's a really, that's a really interesting insight and I will just put an exclamation point on that because you mentioned self driving business, you're implying, you said the computer, the business is a computer. So if you just just think about that mind blowing concept for a second, if it's a computer, what's the operating system and what's the suite of applications that are on top of it? So, Okay, let's go in the old days at a Windows machine and you had office, which is a system software, applications, software construct. Okay, If you map that to the entire company, you're talking about Red hat and IBM kind of come working together. Kind of connects the dots a little bit on what Red Hackett because they're not bring system company. So if hybrid cloud is the system mm hybrid, then you got the applications suite is all software for the That's >>right. That's right. And if you, you know, if you listen to anything these days about what IBM stands words, hybrid cloud and and think red hat as as, you know, kind of the core element of that with open shift in a I right. And both of those really matter in terms of automation and maybe I'll come back to the hybrid cloud and red hat thing in a second. Let's just talk about you know Watson and Ai, you know, which is the application and you mentioned scale, which I'm so glad you did. You know a I could help scale automation. And the trick is is that ai automation sometimes gets stuck right? It gets stuck when it's working with data that is noisy or unstructured. Right? So there's a lot of structured data in your organization and it it with that we can breeze through automation. But if there is more ambiguous data unstructured noisy, you need a human in the loop. And when you get a human in the loop, it slows things down. So what a I can start to do a I. And its subordinates, machine learning, natural language processing, computer vision. We can start to make sense of both unstructured and structured data together and we can make a big deal going forward. Right? So that's that's the way I part you mentioned Red hat and and hybrid cloud part. We'll think about it this way. When you shop, how many stores do you don't just shop in one store? Right. You you go to specialty stores to pick up that special uh ketchup, I don't know or must store and maybe do shopping another store, customers using clouds john aren't very different. You know, they have their specialty places to go. Maybe they're going to be running workloads and google involving search and a I related to search, right? And they're going to be using other clouds for more specialty things. Right? So from that perspective, that's a view of hybrid, you know, customers today, you know, take that shopping analogy, they're going to be using sales force or service Now, IBM cloud, they have a private cloud, right? So, when you think about automating that world, All right. It's the real world. It's how we shop, whether it's for groceries or for cloud, right? So the hybrid cloud is a reality. Um and how do you make sense of a high of that? Right, Because when when an average customer has five clouds, How do you deal with five things? Right. How do you make it easy normalize? And that's what red hat really >>does. It's interesting. I just just share with you the and I interviewed Arvin um who is now the ceo of IBM when he was at Red Hat some in 2019 in SAn Francisco before he made the acquisition here that I was, I was peppered with questions like you know, you need to get this cloud and he loves cloud, you know, he loves clouds. So so he was smiling, he just wanted to say it, I wanted to just say it and I think Red Hat brings that operating kind of mindset where the clouds are just subsystems in the Os >>yes of the middle >>where which is now software which is software to find business. And this kind of is the talk of your, your your views. Now you have a podcast called Art of automation. Want to get that in there for the folks watching uh search for the podcast, Art of automation. This is the stories that you tell. Tell us some stories from this phenomenon. What's the impact of automation for the holistic picture? >>Well, it starts with a lot of, I guess it starts with customers. The stories start with the customers. So we're hearing from customers that Ai and automation is where they're investing in 2021. Um for all the reasons we briefly mentioned and and IBM has a lot to offer there. So we've made a I powered automation of priority but john in the pursuit of making it a priority. I've started talking with many of our subject matter experts and was floored by their knowledge, their energy, their passion and their stories. And I said we can't keep this to ourselves, we can't keep this locked away, we have to share it, we have to let it out. So, so basically this is what started the podcast around that. And since then we've had many industry luminaries from IBM and outside, starting with customers, we had claus Jensen who is the ceo of memorial clones Kettering hospital to talk about automation and health care. And he shared great stories. You need to listen to them about. Automation is not going to take the place of doctors, but automation will help better read um x rays and look at those shades of gray on the X ray and interpret it much better than we can and be able to ingest all of the up to date medical research to provide pointers and make connections that the human may not be able to do in that moment. Right. So the two working together or better than any individual carol Poulsen recently joined me to talk and she's the C. I. O. For cooperators to talk about automation and insurance. And she had some great stories to uh so john with that a bunch of IBM great IBM fellows like Rama Agra jew, who is one of Forbes top 20 women in AI research, talking about Ai ops and also Russia near pori talking and Russia has been working on Watson since jeopardy to tell stories about ultimately now how we're teaching ai to code and all the modern programming languages and really automating application modernization and the like uh, 14 episodes in we have those under our belt, About 6000 downloads so far. So it's it's coming along pretty well. Thanks. >>Thanks for being done. Yeah. The key is your your content creator now as well as a fellow and this is the democratization, as we say, direct to audience, share those stories also here. And thank you released an e book. Tell us a little quickly about that. We've got one minute left, give a quick plug. >>The book echoes the podcast chapters relate to the, to the episodes of the book. We're dropping the first five chapters plus forward for free on the IBM website. Other chapters will become available um, and drop as they become available. The book makes the content searchable on the internet. We go into more detail with advice on how to get started. You get to hear the topics and the voice of those subject matter experts and uh I really, you know, suggest you go out and check it out. >>Alright, jerry, cuomo IBM fellow VPC T IBM automation um also a content creator podcast, art of automation, jerry. We're gonna lift it listed on our silicon angle and our cube sites. Get you some extra love on that. Love the podcast. Love the focus on sharing from experts in the field. Thanks for coming on. >>Thank you so much for having me again, john >>Okay. I'm John Fryer with the Cube here for IBM think 2021. Thanks for watching.

>>From the cube studios in Palo Alto in Boston. It's the cube covering the IBM thing brought to you by IBM. Everybody we're back. This is Dave Vellante the cube, and this is our wall-to-wall coverage, IBM's digital thing experienced for 2020. We're really excited to have Jerry Cuomo on. He's the, uh, vice president of blockchain technologies and an IBM fellow and longtime cube alum. Jerry, good to see you again. Thanks for coming on and wish we were face to face, but yeah, this'll do. Good to see you too. Yes, thanks for having me. So we've been talking a lot of and talking to, I've been running a CEO series a, of course, a lot of the interviews around, uh, IBM think are focused on, on COBIT 19. But I wonder if you could start off by just talking a little bit about, you know, blockchain, why blockchain, why now, especially in the context of this pandemic. >>David's, it's as if we've been working out in the gym, but not knowing why we needed to be fixed. And I know now why we need to be fit. You know, blockchain is coming just in time. Mmm. You know, with the trust factor and the preserving privacy factor. Okay. The way we move forward the world is now becoming more digital than ever people working from home. Um, the reliance and online services is, that's critical. our ability to work as a community accompanies companies. The shared data is critical. you know, blockchain brings a magical ingredient and that's the ingredient of trust, you know, in sharing data. Okay. When, if that data and the sources that are providing that data arc okay. From verified and trusted, we're more likely to use that data and you the, any friction that's caused for fear of trepidation that the data is going to be misused. >>Mmm. It goes start to go away. And when that happens, you speed up an exchange and we need speed. Time is of the essence. So blockchain brings a platform for trusted data exchange while preserving privacy. And that provides a foundation. I can do some amazing things in this time of crisis, right? Yeah. And it's, it's not only trust, it's also expediency and you know, cutting out a lot of the red tape. And I want to talk about some of the applications. You're heavily involved in that in the distributed ledger, a project, you know, one of the early leads on that. Um, talk about some of the ways in which you're flying that distributed a ledger. And let's go into some of the examples. So we're, we're really fortunate to be an early adopter blockchain and, and provider of blockchain technology and kind of the fruit of that. >>Um, as I said, it couldn't happen any sooner where we have, Mmm, I would say over a thousand, alright. Users using IBM blockchain, which is powered by the opensource Hyperledger fabric, I'd say over a hundred of those users, um, have reached a level of production networks. you know, it's been great to see some of the proprietors of those networks now repurpose the networks towards hastening the relief of, uh, and one, a couple of examples that stand out, Dave. Mmm. You've seen what's happening to our supply chain. And then I think we got some rebound happening as we speak, but companies all of a sudden woke up one morning and their supply chains were, I'm exhausted. So suppliers, we're out of key goods and the buyers needed very rapidly to expand. They're, the supplier is in their, in their supply chain. there are laws and regulations about what it takes to onboard a new supplier. >>You want to make sure you're not onboarding bad actors. So in IBM for example, we have over 20,000 suppliers to our business and it takes 30 to 40 days who, uh, validate and verify one of those suppliers. We don't have 30 to 45 days, you know, think about you're a healthcare company or a food company. So working with a partner called Jane yard, uh, co-created a network called trust yourself buyer. And we've been able to repurpose, trust your supplier now or companies that are looking, you know, around Kobe 19 to rapidly okay, expand, you know, their, their supply chain. So if you imagine that taking us 45 days or 40 days to onboard a new supplier, okay. Pick, pick a company in our supply chain, Lenovo, that supplier may very well want to go to Lenovo to and provide services to them. Well guess what, it's going to take 40 days, the onboard to Lenovo. >>But if they're part of the trust or supplier network and they've already onboarded to IBM, they're well on their way. You're being visible to all of these other buyers that are part of the IBM network, like Lenovo and many others. And instead of taking 40 days, maybe it only takes five days. All right. So radically, radically, you know, improving the time it takes them. You know, with companies like Ford making ventilators and masks, it will kind of be able to onboard Ford into, you know, health care, uh, companies. But you know, we want to be able to do it with speed. So trust your supplier is a great use of blockchain. Two, expand a buyer and suppliers. Mmm. Exposure. Mmm. And they expand their network to quickly onboard. And you know, with the trust that you get an exchanging data from blockchain with the Mmm provenance, that Hey, this company information was truly vetted by one of the trusted members of the network. >>There's no fee or trepidation that somehow these records were tampered with or, or misused. So that's one example they have of using blockchain. That's a huge, uh, example that you gave because you're right, there are thousands and thousands of companies that are pivoting to making, like you said, ventilators and masks and yeah, they're moving so fast and there's gotta be a trust involved. On the one hand, they're moving fast to try to save their businesses or you know, in the case of Ford, you help save the, the country or the world. On the other hand, you know, there's risks there. So that, that helps. I want to understand me. Pasa basically is, if I understand it, you can privately share, uh, information on folks that are asymptomatic but might be carriers of covert 19. Am I getting that right on? Okay. So me Pasa starts as a project, uh, from a company called has Sarah and their CEO Jonathan Levy. >>And among other things, Jonathan Levy is an amazing, uh, software developer and he's helped us and the community at large, bill, the Hyperledger fabric, uh, blockchain technology, that's part of IBM. Mmm. The power is IBM blockchain. So Jonathan, I have this idea because w what was happening is there were many, many data sources, you know, from the very popular and well known, uh, Johns Hopkins source. And we have information coming from the weather company. There are other governments, um, putting out data. Jonathan had this, this idea of a verified Mmm. Data hub, right? So how do we kind of bring that information together in a hub where a developer can now to get access to not just one feed, but many feeds knowing that both the data is an a normalized format. So that's easy to consume. And like if you're consuming 10 different data sources, you don't have to think about 10 different ways to interact it. >>No kind of normalizing it through a fewer, like maybe one, but also that we really authentically know that this is the world health organization. This is indeed John Hopkins. So we have that trust. So, okay. Yeah. With me, Pasa being I'm a data hub four, uh, information verified information related to the Kronos virus, really laying a foundation now for a new class of applications that can mash up information to create new insights, perhaps applying Mmm. Artificial intelligence machine learning to really look not just at any one of those, uh, data sources, but now look across data sources, um, and start to make some informed decisions. No, I have to say operate with the lights on, uh, and with certainty that the information is correct. So me Pasa is that foundation and we have a call for code happening that IBM is hosting for developers to come out and okay. Bring their best ideas forward and X for exposing me Pasa as a service to the, in this hackathon so that developers can bring some of their best ideas and kind of help those best ideas come alive with me. Me has a resource. >>That's great. So we've got two, we got the supply chain, we just need to share the Pasa. There's the other one then I think we can all relate to is the secure key authentication, >>which I love. >>Uh, maybe you can explain that and talk about the role that blockchain >>we're launching fits, right. So you know, there is people working from home and digital identity verification. It is key. You know, think about it. You're working remotely, you're using tools like zoom. Um, there's a huge spike in calls and online requests from tele-health or government benefits programs. Yeah. So this is all happening. Everything behind the scenes is, yeah. Around that is, is this user who they say they are, is this doctor who they say they are, et cetera. And there are scams and frauds out there. So working with speed, it means working with certainty. and with the verified me networks set out to do a couple of years ago and the beautiful part is, you know, it's ready to go now for this, for this particular usage it's been using. Mmm. Basically think about it as my identity is my identity and I get to lease out information too different institutions to use it for my benefit, not necessarily just for their benefit. >>So it's almost like digital rights management. Like if you put out a digital piece of art or music, you can control the rights. Who gets to use it? What's the terms and conditions, um, on, on your terms? So verified me, um, allows through a mobile app users to invite institutions who represent them, verify them. No. And so I'll allow my department of motor vehicle and my employer, Mmm. Two to verify me, right? Because I want to go back to work sooner. I want to make sure my work environment, um, I'm making this up. I want to make sure my work environment, the people have been tested and vaccinated, but I don't want to necessarily, you know, kind of abuse people's privacy. Right? So I'll opt in, I'll share that information. I'll get my, my doctor and my, uh, department of motor vehicle to say, yes, this is Gary. >>He's from this address. Yes, he has been vaccinated and now I can kind of onboard to services as much quicker whether that service is going through TSA. Do you get on an airplane badging back into my office or you know, signing on to a, you know, telemedicine, a service or government, a benefits program, et cetera. So verify me is using the self, uh, at the station through a mobile application to help speed up the process of knowing that that is truly you and you truly want this service. Uh, and you are also calling the shots as to that. What happens with your information that, you know, it's not spread all over the interweb it's under your control at all time. Right. So I think it's the best of all worlds. The national Institute for standards and technology looked at, verified me. They're like, Oh my gosh, this is like the perfect storm of goodness for identity. >>They actually appointed, yeah, it has a term, it's called triple blind data exchange. It sounds like a magical act. A triple blind data exchange means the requester. Mmm. Doesn't know who the provider is and less know the requester. Um, allows the provider to know, Mmm, the provider doesn't know who the requester requested, doesn't know who the prior provider is that is double-blind. And then the network provider doesn't know either. Right. But somehow across disformed and that's the magic of blockchain. I'm allowing that to happen and with that we can move forward knowing we're sharing information where it matters without the risk of it leaking out to places we don't want to do. So great application of secure key and verified me. Yeah, I love that. Then the whole concept of being able to control your own data. You hear so much today about, you know, testing and in contact tracing using mobile technology to do that. >>But big privacy concerns. I've always felt like, you know, blockchain for so many applications in healthcare or just being able to, as you say, control your own data. I want to better understand the technology behind this. When I think about blockchain, Mmm. I obviously you don't think about it. Cryptography, you've mentioned developers a number of times. There's software engineering. Yeah. Distributed ledger. Um, I mean there's, there's game theory in the, in the, in the cryptocurrency world, we're not talking about that, but there's the confluence of these technologies coming to them. What's the technology underneath these, these applications? Talking about it there, there is an open source, an organization called Hyperledger. It's part of the Linux foundation. They're the gold standard and open source, openly governed, Mmm. Technology you know, early on in 2018 yep. 18, 26. I mean, we got involved, started contributing code and developers. >>Two Hyperledger fabric, which is the industry's first permissioned blockchain technology. Permission meaning members are accountable. So the network versus Bitcoin where members are anonymous and to pass industry Reggie regulations, you can't be anonymous. You have to be accountable. Um, that's not to say that you can't, okay. Work privately, you know, so you're accountable. But transactions in the network, Mmm. Only gets shared with those that have a need, need to know. So that the foundation is Hyperledger fabric. And IBM has a commercial offering called the IBM blockchain platform that embodies that. That kind of is a commercial distribution of Hyperledger fabric plus a set of advanced tools to make it really easy to work with. The open source. All the networks that I talked about are operating their network across the worldwide IBM public cloud. And so cloud technology lays a really big part of blockchain because blockchains are networks. >>Mmm. You know, our technology, IBM blockchain platform runs really well in the IBM wow. But it also allows you to run anywhere, right? Or like to say where it matters most. So you may have companies, I'm running blockchain nodes in the IBM cloud. You may have others running it on their own premises behind their firewall. You might have others running an Amazon and Microsoft Azure. Right. So we use, um, you may have heard of red hat open shift, the container technology so that we can run Mmm. Parts of a blockchain network, I guess they said where they matter most and you get strengthened a blockchain network based on the diversity of the operators. Because if it was all operated by one operator, there would be a chance maybe that there can be some collusion happening. But now if you could run it know across different geographies across the IBM cloud. >>So almost three networks all run on use this technology or run on the IBM cloud. And Dave, one more thing. If you look at these applications, they're just modern application, you know, their mobile front ends, their web portals and all of that kind of, okay. Okay. The blockchain part of these applications, usually it's only 20% of the overall endeavor that companies are going through. The other 80% it's business as usual. I'm building a modern cloud application. So what we're doing in IBM with, but you know, red hat with OpenShift with our cloud packs, which brings various enterprise software across different disciplines, blends and domains like integration, application, data, security. All of those things come together to fill the other 80% the above and beyond blockchain. So these three companies, okay. You know, 99 plus others are building applications as modern cloud applications that leverage this blockchain technology. So you don't have to be a cryptographer or you know, a distributed database expert. It's all, it's all embodied in this code. Mmm. Available on the IBM cloud, 29 cents a CPU hour. It was approximately the price. So it's quite affordable. And you know, that's what we've delivered. >>Well, the thing about that, that last point about the cloud is it law, it allows organizations, enterprises to experiment very cheaply, uh, and so they can get, uh, an MVP out or a proof of concept out very quickly, very cheaply, and then iterate, uh, extremely quickly. That to me is the real benefit, the cloud era and the pricing model. >>I just mentioned, David, as I said it when I started, you know, it's like we were working out in a gym, but we weren't quite sure. We knew why we were, we were so keen on getting fit. And what I see now is this, you know, blossoming of users who are looking at, you know, a new agreement. We thought we understood digital transformation. Mmm. But there's a whole new nice to be digitized right now. You know, we're probably not going to be jumping on planes and trains, uh, working as, as, as more intimately as we were face to face. So the need for new digital applications that link people together. Uh, w we're seeing so many use cases from, um, trade finance to food safety, to proxy voting for stock, know all of these applications that we're kind of moving along at a normal speed. I've been hyper accelerated, uh, because of the crisis we're in. So blockchain no. Couldn't come any sooner. >>Yeah. You know, I want to ask you, as a technologist, uh, you know, I've learned over the years, there's a lot of ways to skin a cat. Um, could you do the types of things that you're talking about without blockchain? Um, I'm, I'm sure there are ways, but, but why is blockchain sort of the right path, >>Dave? Mmm. You can, you can certainly do things with databases. Mmm. But if you want the trust, it's as simple as this. A database traditionally has a single administrator that sets the rules up for when a transaction comes in. Mmm. What it takes to commit that transaction. And if the rules are met, the transactions committed, um, the database administrator has access who commands like delete and update. So at some level you can never be a hundred percent sure that that data was the data that was intended in there. With a blockchain, there's multiple administrators to the ledger. So the ledger is distributed and shared across multiple administrators. When a transaction is submitted, it is first proposed for those administrators, a process of consent happens. And then, and only then when the majority of the group agrees that it's a valid transaction, is it committed? And when it's committed, it's committed in a way that's cryptographically linked two other transactions in the ledger, I'm making it. >>Mmm tamper-proof right. Or very difficult to tamper with. And unlike databases, blockchains are append only so they don't have update and delete. Okay. All right. So if you really want that center of trusted data that is a tested, you know, that has checks and balances across different organizations, um, blockchain is the key to do it, you know? So could you do it in data with a database? Yes. But you have to trust that central organization. And for many applications, that's just fine. All right. But if we want to move quickly, we really want to share systems of record. Mmm. I hear you. Sharing a system of record, you have regulatory obligations, you can say, Oh, sorry, the record was wrong, but it was put in there by, by this other company. Well, they'll say, well, >>okay, >>nice for the other company, but sorry, you're the one in trouble. So with a blockchain, we have to bring assurances that we can't get into that kind of situation, right? So that shared Mmm. Distributed database that is kind of provides this tamper resistant audit log becomes the Colonel cross. And then with the privacy preservation that you get from encryption and privacy techniques, um, like we have like these things, both channels, um, you can transact, um Hm. And be accountable, but also, Mmm. Only share of transactions with those that have a need to know, right? So you get that level of privacy in there. And that combination of trust and privacy is the secret sauce that makes blockchain unique and quite timely for this. So yeah, check it out. I mean, on the IBM cloud, it's effortless. So to get up and running, you know, building a cloud native application with blockchain and you know, if you're used to doing things, um, on other clouds or back at the home base, we have the IBM blockchain software, which you can deploy. Yeah. Open shift anywhere. So we have what you need in a time of need. >>And as a technologist, again, you're being really, I think, honest and careful about the word tamper. You call it tamper resistant. And if I understand it right, that, I mean, obviously you can fish for somebody's credentials. Yeah. That's, you know, that's one thing. But if I understand that, that more than 50% of the peers in the community, it must agree to tamper in order for the system. You tampered with it. And, and that is the beauty of, of blockchain and the brilliance. Okay. >>Okay. Yeah. And, and, and for, um, performance reasons we've created optimizations. Like you can set a consensus policy up because maybe one transaction it's okay just to have a couple people agree and say, Oh, well, you know, out of the a hundred nodes, Mmm. Three agree, it's good enough. Okay. Other, other policies may be more stringent depending on the nature of the data and the transaction, right? So you can tone, you can kind of tune that in based on the class of transaction. And so it's kind of good and that's how we can get performance levels in the, you know, thousand plus. In fact, IBM and RBC, um, recently did, um, a series of performance analysis because RBC said, Hey, can I use this for some of my bank to bank exchanges and we need to support over a thousand transactions per second. They were able, in their use case, there's support over 3000. Transact for a second. Okay. Mmm. You know, that we were very encouraged by that. I'm glad you clarified that because, so essentially you're saying you can risk adjust the policies if you will. >>That's great to know. Mmm. I could go on forever on this topic. Well, we're unfortunately, Jerry, we're well over our time, but I want to thank you for coming back, planning this important topic. Thrilled. IBM has taken a leadership position here, and I think, you know, to your point, this pandemic is just going to, can accelerate a lot of things and blockchain is, but in my view anyway, one of them. Thank you, Dave. Oh, great questions and I really appreciate it. So everyone out there, um, stay safe. Stay healthy. All right. Thank you Jerry, and thank you for watching everybody. This is Dave Volante for the cube. Our coverage of the IBM think digital 2020 event. We'll be right back. Perfect. The short break.

>> Announcer: Live from Las Vegas, it's theCUBE, covering Interconnect 2017. Brought to you by IBM. >> Hey, welcome back everyone. We're live here in Las Vegas at the Mandalay Bay for IBM InterConnect 2017 exclusive Cube coverage. I'm John Furrier, my co-host Dave Vellante, our next guest Dr. Angel Diaz who is the vice president of developer technology. Also you know him from the open source world. Great to see you again. >> Nice to see you. Thanks for spending time with us. >> Thank you. >> Boy, Blockchain, open source, booming, cloud-native, booming, hybrid cloud, brute force but rolling strong. Enterprise strong, if you will, as your CEO Ginni Rometty started talking about yesterday. Give us the update on what's going on with the technology and developers because this is something that you guys, you personally, have been spending a lot of time with. Developer traction, what's the update? >> Well you know if you look at history there's been this democratization of technology. Right, everything from object oriented programming to the internet where we realize if we created open communities you can build more skill, more value, create more innovation. And each one of these layers you create abstractions. You reduce the concept count of what developers need to know to get work done and it's all about getting work done faster. So, you know, we've been systematically around cloud, data, and AI, working really hard to make sure that you have open source communities to support those. Whether it's in things like compute, storage, and network, platform as a service like say Cloud Foundry, what we're doing around the open container initiatives and the Cloud Native Computing Foundation to all the things you see in the data space and everywhere else. So it's real exciting and it's real important for developers. >> So two hot trends that we're tracking obviously, one's pretty obvious. That's machine learning in cloud. Really hand and glove together. You see machine learning really powering the AI, hitting IOT all the way up to apps and wearables and what not, autonomous vehicles. Goes on and on. The other one is Kubernetes, and Kubernetes, the rise of Kubernetes has really brought the containers to a whole nother level around multi-cloud. People might not know it, but you are involved in the CNCF formation, which is Kubernetes movement, which was KubeCon, then it became part of the Linux Foundation. So, IBM has had their hand in these two trends pretty heavily. >> Angel: Oh yeah, absolutely. >> Give the perspective, because the Kubernetes one, in particular, we'll come back to the machine learning, but Kubernetes is powering a whole nother abstraction layer around helping containers go to the next level with microservices, where the develop equation has changed. It's not just the person writing code anymore, a person writing code throws off an application that has it's own life in relationship to other services in the community, which also has analytics tied to it. So, you're seeing a changing dynamic on this potential with Kubernetes. How important is Kubernetes, and what is the real impact? >> No, it is important. And what there actually is, there's a couple of, I think, application or architecture trends that are fundamentally changing how we build applications. So one of them I'll call, let's call it Code First. This is where you don't even think about the Kubernetes layer. All you do is you want to write your code and you want to deploy your code, and you want it to run. That's kind of the platform. Something like Cloud Foundry addresses the Code First approach. Then there's the whole event-drive architecture world. Serverless, right? Where it has a particular use case, event-driven, standing, stuff up and down, dealing with many types of inputs, running rules. Then you have, let's say the more transactional type applications. Microservices, right? These three thing, when combined allows you to kind of break the shackles of the monolith of old application architectures, and build things the way that best suit your application model, and then come together in much more coherent way. Specifically in Kubernetes, and that whole container stuff. You think think about it, initially, when, containers have been around a long time, as we all know, and Docker did a great job in making container accessible and easy, right? And we worked really closely with them to create some multisource activities around the base container definitions, the open container initiative in the Linux Foundation. But of course, that wasn't enough. We need to then start to build the management and the orchestration around that. So we teamed up with others and started to kind of build this Kubernetes-based community. You know, Docker just recently brought ContainerD into the CNCF, as well, as another layer. They are within the equation. But by building this, it's almost just Russian doll of capability, right, you know, you're able to go from one paradigm, whether it's a serverless paradigm running containers, or having your microservices become use in serverless or having Code First kick off something, you can have these things work well together. And I think that's the most exciting part of what we're doing at Kubernetes, what we're doing in serverless, and what we're doing, say, in this Code First world. >> So, development's always been kind of an art form. How is that art form evolving and changing as these trends that you're describing-- >> Oh, that's a great, I love that. 'Cause I always think of ourselves as computer science artists. You and I haven't spoken about that. That's awesome. Yeah, because, you know, it is an art form, right? Your screen is your canvas, right, and colors are the services that you can bring in to build, and the API calls, right? And what's great is that your canvas never ends, because you have, say, a cloud infrastructure, which is infinitely scalable or something, right? So, yeah. But the definition of the developer is changing because we're kind of in this next phase of lowering concept count. Remember I told you this lowering of concept count. You know, I love those O'Reilly books. The little cute animals. You know, as a developer today, you don't have to buy as many of those books, because a lot of it is done in the API calls that you've used. You don't write sorting algorithms anymore. Guess what, you don't need to do speech to text algorithms. You don't need to do some analysis algorithms. So the developer is becoming a cognitive developer and a data science developer, in addition to a application developer. And that is the future. And it's really important that folks skill up. Because the demand has increased dramatically in those areas, and the need has increased as well. So it's very exciting. >> So the thing about that, that point about cognitive developer, is that in the API calls, and the reason why we don't buy all those books is, the codes out there are already in open source and machine learning is a great example, if you look at what machine learning is doing. 'Cause now you have machine learning. It used to be an art and a science. You had to be a great computer scientist and understand algorithms, and almost have that artistic view. But now, as more and more machine learning comes out, you can still write custom machine learning, but still build on libraries that are already out there. >> Exactly. So what does that do? That reduces the time it takes to get something done. And it increases the quality of what you're building, right? Because, you know, this subroutine or this library has been used by thousands and thousands of other people, it's probably going to work pretty well for your use case, right? But I can stress the importance of this moment you brought up. The cognitive data application developer coming together. You know, when the Web happened, the development market blew up in orders of magnitude. Because everybody's is sort of learning HTML, CSS, Javascript, you know, J2E, whatever. All the things they needed to build, you know, Web Uize and transactional applications. Two phase commit apps in the back, right? Here we are again, and it's starting to explode with the microservices, et cetera, all the stuff you mentioned, but when you add cognitive and data to the equation, it's just going to be a bigger explosion than the Web days. >> So we were talking with some of the guys from IBM's GBS, the Global Business Services, and the GTS, Global Technology Services, and interesting things coming out. So if you take what you're saying forward, and you open innovation model, you got business model stacks and technology stacks. So process, stacks, you know, business process, and then technology, and they now have to go hand-in-hand. So if you take what you're saying about, you know, open source, open all of this innovation, and add say, Blockchain to it, you now have another developer type. So the cognitive piece is also contributing to what looks like to be a home run with Blockchain going open source, with the ledger. So now you have the process and the stacks coming together. So now, it's almost the Holy Grail. It used to be this, "Hey, those business processor guys, they did stuff, and then the guys coded it out, built stacks. Now they're interdependent a bit. >> Yeah. Well I mean, what's interesting to me about Blockchain, I always think of, at this point about business processes, you know, business processes have always been hard to change, right? You know, once you have partners in your ecosystem, it's hard to change. Things like APIs and all the technology allows it to be much quicker now. But with Blockchain, you don't need a human involved in the decision of who's in your partner network as long as they're trusted, right? I remember when Jerry Cuomo and Chris Ferris, in my team, he's the chairman of the Blockchain, of the hyperledger group, we're talking initially when we kind of brought it to the Linux Foundation. We were talking a lot about transactions, because you know, that was one of the initial use cases. But we always kind of new that there's a lot of other use cases for this, right, in addition to that. I mean, you know, the government of China is using Blockchain to deal with carbon emissions. And they have, essentially, an economy where folks can trade, essentially, carbon units to make sure that as an industry segment, they don't go over, as an example. So you can have people coming in and out of your business process in a much more fluid way. What fascinates me about Blockchain, and it's a great point, is it takes the whole ecosystem to another level because now that they've made Blockchain successful, ecosystem component's huge. That's a community model, that's just like open source. So now you've got the confluence of open source software, now with people in writing just software, and now microservices that interact with other microservices. Not agile within a company, agile within other developers. >> Angel: Right. >> So you have a data piece that ties that together, but you also have the process and potential business model disruption, a Blockchain. So those two things are interesting to me. But it's a community role. In your expert opinion on the community piece, how do you think the community will evolve to this new dynamic? Do you think it's going to take the same straight line growth of open source, do you think there's going to be a different twist to it? You mentioned this new persona is already developing with cognitive. How do you see that happening? >> Yes, I do. There's two, let's say three points. The first on circling the community, what we've been trying to do, architecturally, is build an open innovation platform. So all these elements that make up cloud, data, AI, are open so that people can innovate, skills can grow, anything, grow faster. So the communities are actually working together. So you see lots of intralocks and subcommittees and subgroups within teams, right? Just say this kind of nesting of technology. So I think that's one megatrend that will continue-- >> Integrated communities, basically. >> Integrated communities. They do their own thing. >> Yeah. >> But to your point earlier, they don't reinvent the wheel. If I'm in Cloud Foundry and I need a container model, why am I going to create my own? I'll just use the open compute initiative container model, you know what I'm saying? >> Dave: And the integration point is that collaboration-- >> Is that collaboration, right. And so we've started to see this a lot, and I think that's the next megatrend. The second is, we just look at developers. In all this conversation, we've been talking about the what? All the technology. But the most important thing, even more so than all of this stuff, is the how. How do I actually use the technology? What is the development methodology of how I add scale, build these applications? People call that DevOp, you know, that whole area. We at IBM announced about a year and a half ago, at Gene Kim's summit, he does DevOps, the garage method, and we open sourced it, which is a methodology of how you apply Agile and all the stuff we've learned in open source, to actually using this technology in a productive way at scale. Often times people talk about working in theses little squads and so forth, but once you hire, say you've got 10 people in San Francisco, and you're going to hire one in San Ramon, that person might as well be on Mars. Because if you're not on the team there, you're not in the decision process. Well, that's not reality. Open source is not that way, the world doesn't behave that way. So this is the methodology that we talked about. The how is really important. And then the third thing, is, if you can help developers, interlock communities, teach them about the how to do this effectively, then they want samples to fork and go. Technology journeys, physical code. So what you're start to see a lot of us in open source, and even IBM, is provide starters that show people how to use the technology, add the methodology, and then help them on their journey to get value. >> So at the base level, there's a whole new set of skills that are emerging. You mentioned the O'Reilly books before, it was sort of a sequential learning process, and it seems very nonlinear now, so what do you recommend for people, how do they go about capturing knowledge, where do they start? >> I think there's probably two or three places. The first one is directly in the open source communities. You go to any open source community and there's a plethora of information, but more so, if you hang out in the right places, you know, IRC channels or wherever, people are more than willing to help you. So you can get education for free if you participate and contribute and become a good member of a community. And, in fact, from a career perspective today, that's what developers want. They want that feeling of being part of something. They want the merit badge that you get for being a core committer, the pride that comes with that. And frankly, the marketability of yourself as a developer, so that's probably the first place. The second is, look, at IBM, we spend a huge amount of time trying to help developers be productive, especially in open source, as we started this conversation. So we have a place, developer.ibm.com. You go there and you can get links to all the relevant open source communities in this open innovation platform that I've talked about. You can see the methodologies that I spoke about that is open. And then you could also get these starter code journeys that I spoke about, to help you get started. So that's one place-- >> That's coming out in April, right? >> That's right. >> The journeys. >> Yeah, but you can go now and start looking at that, at developer.ibm.com, and not all of it is IBM content. This is not IBM propaganda here, right? It is-- >> John: Real world examples. >> Real world examples, it's real open source communities that either we've helped, we've shepherded along. And it is a great place, at least, to get your head around the space and then you can subset it, right? >> Yeah. So tell us about, at the last couple of minutes we have, what IBM's doing right now from a technology, and for developers, what are you guys doing to help developers today, give the message from what IBM's doing. What are you guys doing? What's your North Star? What's the vision and some of the things you're doing in the marketplace people can get involved in? You mentioned the garage as one. I'm sure there's others. >> Yeah, I mean look, we are m6anically focused on helping developers get value, get stuff done. That's what they want to do, that's what our clients want to do, and that's what turns us on. You build your art, you talk, you're going back to art, you build your drawing, you want to look at it. You want it to be beautiful. You want others to admire it, right? So if we could help you do that, you'll be better for it, and we will be better for it. >> As long as they don't eat their ear, then they're going to be fine. >> It's subjective, but give value of what they do. So how do they give value? They give value by open technologies and how we've built, essentially, cloud, data, AI, right? So art, arts technology adds value. We get value out of the methodology. We help them do this, it's around DevOps, tooling around it, and then these starters, these on-ramps, right, to getting started. >> I got to ask you my final question, a more personal one, and Dave and I talk about this all the time off camera, being an older guy, computer science guy, you're seeing stuff now that was once a major barrier, whether it's getting access to massive compute, machine learning, libraries, the composability of the building blocks that are out there, to create art, if you will, it's phenomenal. To me, it's just like the most amazing time to be be a computer scientist, or in tech, in general, building stuff. So I'm going to ask you, what are you jazzed up about? Looking back, in today's world, the young guns that are coming onto the scene not knowing that we walked barefoot in the snow to school, back in the old days. This is like, it's a pretty awesome environment right now. Give us personal color on your take on that, the change and the opportunity. >> Yeah, so first of all, when you mentioned older guys, you were referring to yourselves, right? Because this is my first year at IBM. I just graduated, there's nothing old here, guys. >> John: You could still go to, come on (laughs). >> What does that mean? Look you know, there's two things I'm going to say. Two sides of the equation. First of all, the fundamentals of computer science never go away. I still teach, undergrad seminars and so forth, and you have to know the fundamentals of computer science. That does not go away because you can write bad code. No matter what you're doing or how many abstractions you have, there are fundamental principles you need to understand. And that guides you in building better art, okay? Now putting that aside, there is less that you need to know all the time, to get your job done. And what excites me the most, so back when we worked on the Web in the early 90s, and the markup languages, right, and I see some in the audience there, Arno, hey, Arno, who helped author some of the original Web standards with me, and he was with the W3C. The use cases for math, for the Web, was to disseminate physics, that's why Tim did it, right? The use case for XML. I was co-chair of the mathematical markup language. That was a use case for XML. We had no idea that we would be using these same protocols, to power all the apps on your phone. I could not imagine that, okay? If I would have, trust me, I would have done something. We didn't know. So what excites me the most is not being able to imagine what people will be able to create. Because we are so much more advanced than we were there, in terms of levels of abstraction. That's what's, that's the exciting part. >> All right. Dr. Angel Diaz, great to have you on theCUBE. Great inspiration. Great time to be a developer. Great time to be building stuff. IOT, we didn't even get to IOT, I mean, the prospects of what's happening in industrialization, I mean, just pretty amazing. Augmented intelligence, artificial intelligence, machine learning, really the perfect storm for innovation. Obviously, all in the open. >> Angel: Yes. Awesome stuff. Thanks for coming on the theCUBE. Really appreciate it. >> Thank you guys, appreciate it. >> IBM, making it happen with developers. Always have been. Big open source proponents. And now they got the tools, they got the garages for building. I'm John Furrier, stay with us, there's some great interviews. Be right back with more after this short break. (tech music)