>> Announcer: TheCUBE presents Ignite '22, brought to you by Palo Alto Networks. >> Welcome back to Las Vegas. It's theCUBE covering Palo Alto Networks '22, from the MGM Grand, Lisa Martin with Dave Vellante. Dave, we are going to unpack in the next few minutes what we heard and saw at day one of Palo Alto Networks, Ignite. A lot of great conversations, some great guests on the program today. >> Yeah last event, CUBE event of the year. Probably last major tech event of the year. It's kind of an interesting choice of timing, two weeks after reInvent. But you know, this crowd is it's a lot of like network engineers, SecOps pros. There's not a lot of suits here. I think they were here yesterday, all the partners. >> Yeah. >> We talked to Carl Sunderland about, Hey, these, these guys want to know how do I grow my business? You know, so it was a lot of C level executives talking about their business, and how they partner with Palo Alto to grow. The crowd today is really, you know hardcore security professionals. >> Yeah. >> So we're hearing a story of consolidation. >> Yes. >> No surprise. We've talked about that and reported on it, you know, quite extensively. The one big takeaway, and I want, I came in, as you know, wanting to understand, okay, can you through m and a maintain, you know, build a suite of great, big portfolio and at the same time maintain best of breed? And the answer was consistent. We heard it from Nikesh, we heard it from Nir Zuk. The answer was you can't be best of breed without having that large portfolio, single data lake, you know? Single version of the truth, of there is such a thing. That was interesting, that in security, you have to have that visibility. I would imagine, that's true for a lot of things. Data, see what Snowflake and Databricks are both trying to do, now AWS. So to join, we heard that last week, so that was one of the big takeaways. What were your, some of your thoughts? >> Just impressed with the level of threat intelligence that Unit 42 has done. I mean, we had Wendy Whitmer on, and she was one of the alumni, great guest. The landscape has changed so dramatically. Every business, in any industry, nobody's safe. They have such great intelligence on what's going on with malware, with ransomware, with Smishing, that they're able to get, help organizations on their way to becoming cyber resilient. You know, we've been talking a lot about cyber resiliency lately. I always want to understand, well what does it mean? How do different organizations and customers define it? Can they actually really get there? And Wendy talked about yes, it is a journey, but organizations can achieve cyber resiliency. But they need to partner with Palo Alto Networks to be able to understand the landscape and ensure that they've got security established across their organization, as it's now growingly Multicloud. >> Yeah, she's a blonde-haired Wonder Woman, superhero. I always ask security pros that question. But you know, when you talk to people like Wendy Whitmore, Kevin Mandy is somebody else. And the people at AWS, or the big cloud companies, who are on the inside, looking at the threat intelligence. They have so much data, and they have so much knowledge. They can, they analyze, they could identify the fingerprints of nation states, different, you know, criminal organizations. And the the one thing, I think it was Wendy who said, maybe it was somebody else, I think it was Wendy, that they're they're tearing down and reforming, right? >> Yes. >> After they're discovered. Okay, they pack up and leave. They're like, you know, Oceans 11. >> Yep. >> Okay. And then they recruit them and bring them back in. So that was really fascinating. Nir Zuk, we'd never had him on theCUBE before. He was tremendous founder and and CTO of Palo Alto Networks, very opinionated. You know, very clear thinker, basically saying, look you're SOC is going to be run by AI >> Yeah. >> within the next five years. And machines are going to do things that humans can't do at scale, is really what he was saying. And then they're going to get better at that, and they're going to do other things that you have done well that they haven't done well, and then they're going to do well. And so, this is an interesting discussion about you know, I remember, you know we had an event with MIT. Eric Brynjolfsson and Andy McAfee, they wrote the book "Second Machine Age." And they made the point, machines have always replaced humans. This is the first time ever that machines are replacing humans in cognitive functions. So what does that mean? That means that humans have to rely on, you know, creativity. There's got to be new training, new thinking. So it's not like you're going to be out of a job, you're just going to be doing a different job. >> Right. I thought Nir Zuk did a great job of explaining that. We often hear people that are concerned with machines taking jobs. He did a great job of, and you did a great recap, of articulating the value that both bring, and the opportunities to the humans that the machines actually deliver as well. >> Yeah so, you know, we didn't, we didn't get deep into the products today. Tomorrow we're going to have a little bit more deep dive on products. We did, we had some partners on, AWS came on, talked about their ecosystem. BJ Jenkins so, you know, BJ Jenkins again I mean super senior executive. And if I were Nikesh, he's doing exactly what I would do. Putting him on a plane and saying, go meet with customers, go make rain, right? And that's what he's doing is, he's an individual who really knows how to interact with the C-suite, has driven value, you know, over the years. So they've got that angle goin', they're driving go to market. They've got the technology piece and they've, they got to build out the ecosystem. That I think is the big opportunity for them. You know, if they're going to double as a company, this ecosystem has to quadruple. >> Yeah, yeah. >> In my opinion. And I, we saw the same thing at CrowdStrike. We said the same thing about Service Now in 2013. And so, what's happened is the GSIs, the global system integrators start to get involved. They start to partner with them and then they get to get that flywheel effect. And then there's a supercloud, I think that, you know I think Nir Zuk said, Hey, we are basically building out that, he didn't use the term supercloud. But, we're building out that cross cloud capability. You don't need another stove pipe for the edge. You know, so they got on-prem, they got AWS, Azure, you said you have to, absolutely have to run on Microsoft. 'Cause I don't believe today, right? Today they run on, I heard somebody say they run on AWS and Google. >> Yeah. >> I haven't heard much about Microsoft. >> Right. >> Both AWS and Google are here. Microsoft, the bigger competitor in security, but Nir Zuk was unequivocal. Yes, of course you have to run, you got to run it on an Alibaba cloud. He didn't say that, but if you want to secure the China cloud, you got to run on Alibaba. >> Absolutely. >> And Oracle he said. Didn't mention IBM, but no reason they can't run on IBM's cloud. But unless IBM doesn't want 'em to. >> Well they're very customer focused and customer first. So it'll be interesting to see if customers take them in that direction. >> Well it's a good point, right? If customers say, Hey we want you running in this cloud, they will. And, but he did call out Oracle, which I thought was interesting. And so, Oracle's all about mission critical data, mission critical apps. So, you know, that's a good sign. You know, I mean there's so much opportunity in cyber, but so much confusion. You know, sneak had a raise today. It was a down round, no surprise there. But you know, these companies are going to start getting tight on cash, and you've seen layoffs, right? And so, I dunno who said it, I think it was Carl at the end said in a downturn, the strongest companies come out stronger. And that's generally, generally been the case. That kind of rich get richer. We see that in the last downturn? Yes and no, to a certain extent. It's still all about execution. I mean I think about EMC coming out of the last downturn. They did come out stronger and then they started to rocket, but then look what happened. They couldn't remain independent. They were just using m and a as a technique to hide the warts. You know so, what Nir Zuk said that was most interesting to me is when we acquire, we acquire with the intent of integrating. ServiceNow has a similar philosophy. I think that's why they've been somewhat successful. And Oracle, for sure, has had a similar philosophy. So, and that idea of shifting labor into vendor R and D has always been a winning formula. >> I think we heard that today. Excited for day two tomorrow. We've got some great conversations. We're going to be able to talk with some customers, the chief product officer is on. So we have more great content coming from our last live show over the year. Dave, it's been great co-hosting day one with you. Look forward to doing it tomorrow. >> Yeah, thanks for doing this. >> All right. >> All right. For Dave Vellante, I'm Lisa Martin. You've been watching theCUBE, the leader in live enterprise and emerging tech coverage. See you tomorrow. (gentle music fades)

>>we'll go back to the cubes. Coverage of the age of US Executive Summit at Davis. Reinvent made possible by Accenture My name is Dave Volunteer. We're gonna talk about the arm nation advantage, embraced the future of productivity, improve speed quality and customer experience through artificial intelligence. And we herewith Bhaskar goes, Who's the chief strategy Officer X censure in Rajendra RP Prasad is the senior managing director in Global Automation. The Accenture guys walk into the Cube. Get to seal. >>Thank you. >>Hey, congratulations on the new book. I know it's like giving birth, but it's a mini version. If the well, the automation advantage embraced a future of productivity, improve speed, quality and customer experience to artificial intelligence. What inspired you to write this book? Can you tell us a little bit more about it and how businesses are going to be able to take advantage of the information that's in there? Maybe you could start, >>so I think you know, if we say that what inspired as primarily the two things really style, you know, over inspired have to start this project in first of all is the technology change step change in the technology. Second is the mile maturity of the buyer maturity of the market when it's a little more, you know, when I talk about the technology change, automation is nothing new in the industry. In the starting from the Industrial Revolution, always, industry adopted the automation. But last few years would happen. That there is a significant change in the technology in terms of not of new technologies are coming together like cloud data, artificial intelligence, machine learning and they are gearing match you, and that created a huge opportunity in the industry. So that is number one second if fighting the maturity of the buyer. So buyers are always buying automation, adopting the automation. So when I talked to this different by a different industrial wire, suddenly we realise they're not asking about workings automation, how that will help. But primarily they're talking about how they can scaling. They have all have done the pilot, the prototype, how they can take the full advantage in their enterprise through scheme and talking to few client few of our clients, and he realised that it's best to write this boat and film all our clients to take advantage of this new technologies to skill up their business. If I give a little more than inside that one, exactly we are trying to do in this boat primarily, we dealt with three things. One is the individual automation which deals with the human efficiency. Second is the industrial automation who visited a group efficiency. And third is the intelligent automation. We deal city business, official efficiency while business value. So we believe that this is what will really change their business and help our client help the automation. It users to really make clear an impact in their business. >>Yeah, And so you talked about that? The maturity of the customer. And and I like the way you should describe that spectrum ending with intelligent automation. So the point is you not just paving the cow path, if you will, automating processes that maybe were invented decades ago. You're really trying to rethink the best approach. And that's where you going to get the most business value, our peace In thinking about the maturity, I think the a pre pandemic people were maybe a little reluctant s Bhaskar was saying maybe needed some education. But But how? If things change me, obviously the penned Emmick has had a huge impact. It's accelerated things, but but what's changed in the business environment? In terms of the need to implement automation? R. P >>thank you Well, that is an excellent question. As even through the pandemic, most of the enterprises accelerated what I call as the digital transformation, technology transformation and the war all time that it takes to do. The transformation is compressed in our most land prices. Now do compress transformation. The core of it is innovation and innovation, led technology and technology based solutions. To drive this transformation automation. Artificial intelligence becomes hot of what we do while we are implementing this accelerators. Innovation enablers within the enterprises, most of the enterprises prior to the pandemic we're looking automation and I as a solution for cost efficiency. Saving cost in DePina deriving capacity efficiency does if they do the transformation when we press the fast forward but draw the transformation journey liberating automation. What happens is most of the enterprises which the focus from cost efficiency to speed to market application availability and system resiliency at the core. When I speaking to most of the sea woes Corrine Wall in the tech transformation they have now embrace automation and air as a Conan able to bribe this journeys towards, you know, growth, innovation, lead application, availability and transformation and sustainability of the applications through the are A book addresses all of these aspects, including the most important element of which is compute storeys and the enablement that it can accomplish through cloud transformation, cloud computing services and how I I and Michelle learning take log technologies can in a benefit from transformation to the block. In addition, we also heard person talk about automation in the cloud zero automation taking journey towards the cloud on automation Once you're in the clouds, water the philosophy and principles he should be following to drive the motivation. We also provide holy holistic approach to dry automation by focusing process technology that includes talent and change management and also addressing automation culture for the organisations in the way they work as they go forward. >>You mentioned a couple things computing, storage and when we look at our surveys, guys is it is interesting to see em, especially since the pandemic, four items have popped up where all the spending momentum is cloud province reasons scale and in resource and, you know, be able the report to remotely containers because a lot of people have work loads on Prem that they just can automatically move in the company, want to do development in the cloud and maybe connect to some of those on from work clothes. R P A. Which is underscores automation in, of course, and R. P. You mentioned a computing storage and, of course, the other pieces. Data's We have always data, but so my question is, how has the cloud and eight of us specifically influenced changes in automation? In a >>brilliant question and brilliant point, I say no winner. I talked to my clients. One of the things that I always says, Yeah, I I is nothing but y for the data that is the of the data. So that date of place underlying a very critical part of applying intelligence, artificial intelligence and I in the organization's right as the organisation move along their automation journey. Like you said, promoting process automation to contain a realisation to establishing data, building the data cubes and managing the massive data leveraging cloud and how Yebda please can help in a significant way to help the data stratification Dana Enablement data analysis and not data clustering classification All aspects of the what we need to do within the between the data space that helps for the Lord scale automation effort, the cloud and and ablest place a significant role to help accelerate and enable the data part. Once you do that, building mission learning models on the top of it liberating containers clusters develops techniques to drive, you know the principles on the top of it is very makes it easier to drive that on foster enablement advancement through cloud technologists. Alternatively, using automation itself to come enable the cloud transformation data transformation data migration aspects to manage the complexity, speed and scale is very important. The book stresses the very importance of fuelling the motion of the entire organisation to agility, embracing new development methods like automation in the cloud develops Davis a cop's and the importance of oral cloud adoptions that bills the foundational elements of, you know, making sure you're automation and air capabilities are established in a way that it is scalable and sustainable within the organisations as they move forward, >>Right? Thank you for that r p vast crime want to come back to this notion of maturity and and just quite automation. So Andy Jossy made the phrase undifferentiated, heavy lifting popular. But that was largely last decade. Apply to it. And now we're talking about deeper business integration. And so you know, automation certainly is solves the problem of Okay, I can take Monday and cast like provisioning storage in compute and automate that great. But what is some of the business problems, that deeper business integration that we're solving through things? And I want to use the phrase they used earlier intelligent automation? What is that? Can you give an example? >>Let's a very good question as we said, that the automation is a journey, you know, if we talk to any blind, so everybody wants to use data and artificial intelligence to transform their business, so that is very simple. But the point is that you cannot reach their anti unless you follow the steps. So in our book, we have explained that the process that means you know, we defined in a five steps. We said that everybody has to follow the foundation, which is primarily tools driven optimise, which is process drivel. An official see improvement, which is primarily are driven. Then comes predictive capability, the organisation, which is data driven, and then intelligence, which is primarily artificial intelligence driven. Now, when I talked about the use of artificial intelligence and this new intelligent in the business, what the what I mean is basically improved decision making in every level in the organisation and give the example. We have given multiple example in this, both in a very simple example, if I take suppose, a financial secretary organisation, they're selling wealth management product to the client, so they have a number of management product, and they have number of their number of clients a different profile. But now what is happening? This artificial intelligence is helping their agents to target the night product for the night customers. So then, at the success rate is very high. So that is a change that is a change in the way they do business. Now some of the platform companies like Amazon on Netflix. He will see that this this killed is a very native skill for them. They used the artificial intelligence try to use everywhere, but there a lot of other companies who are trying to adopt this killed today. Their fundamental problem is they do not have the right data. They do not have the capability. They do not have all the processes so that they can inject the decision making artificial intelligence capability in every decision making to empower their workforce. And that is what we have written in this book. To provide the guidance to this in this book. How they can use the better business decision improved the create, the more business value using artificial intelligence and intelligent automation. >>Interesting. Bhaskar are gonna stay with you, you know, in their book in the middle of last decade, Erik Brynjolfsson and Andy McAfee wrote the second Machine Age, and they made a point in the book that machines have always replaced humans in instead of various tasks. But for the first time ever, we're seeing machines replacing human in cognitive task that scares a lot of people so hardy you inspire employees to embrace the change that automation can bring. What what are you seeing is the best ways to do that? >>This is a very good question. The intelligent automation implementation is not, Iet Project is primarily change management. It's primarily change in the culture, the people in the organisation into embrace this change and how they will get empowered with the machine. It is not about the replacing people by machine, which has happened historically into the earlier stages of automation, which I explained. But in this intelligent automation, it is basically empowering people to do the better. Dwelled the example. That is the thing we have written in the book about about a newspaper, 100 years old newspaper in Italy. And you know, this industry has gone through multiple automation and changes black and white printing, printing to digital. Everything happened. And now what is happening? They're using artificial intelligence, so they're writers are using those technologies to write faster. So when they are writing immediately, they're getting supported with the later they're supporting with the related article they are supporting with this script, even they're supported to the heading of this article. So the question is that it is not replacing the news, you know, the content writer, but is basically empowering them so that they can produce the better quality of product they can, better writing in a faster time. So is very different approach and that is why is, um, needs a change management and it's a cultural change. >>Garden R P What's it for me? Why should we read the automation advantage? Maybe you can talk about some of the key takeaways and, you know, maybe the best places to start on an automation journey. >>Very will cut the fastest MP, Newer automation journey and Claude Adoption Journey is to start simple and start right if you know what's have free one of the process, Guru says, If you don't know where you are on a map, a map won't help you, so to start right, a company needs to know where they are on a map today, identify the right focus areas, create a clear roadmap and then move forward with the structured approach for successful our option. The other important element is if you automate an inefficient process, we are going to make your inefficiency run more efficiently. So it is very important to baseline, and then I established the baseline and know very or on the journey map. This is one of the key teams we discuss in the Automation Advantis book, with principles and tips and real world examples on how to approach each of these stages. We also stress the importance of building the right architecture is for intelligent automation, cloud enablement, security at the core of automation and the platform centric approach. Leading enterprises can fade out adopters and Iraq, whether they are in the early stages of the automation, journey or surrender advanced stage the formation journey. They can look at the automation advantage book and build and take the best practises and and what is provided as a practical tips within the book to drive there. Automation journey. This also includes importance of having right partners in the cloud space, like a loveliest who can accelerate automation, journey and making sure accompanies cloud migration. Strategy includes automation, automation, lead, yea and data as part of their journey. Management. >>That's great. Good advice there. Bring us home. Maybe you can wrap it up with the final final world. >>So, lefty, keep it very simple. This book will help you to create difference in your business with the power of automation and artificial intelligence. >>That's a simple message and will governor what industry you're in? There is a disruptions scenario for your industry and that disruption scenarios going to involve automation, so you better get ahead of editor game. They're The book is available, of course, at amazon dot com. You can get more information. X censure dot com slash automation advantage. Gosh, thanks so much for coming in the Cube. Really appreciate your time. >>Thank you. Thank >>you. >>Eh? Thank you for watching this episode of the eight of US Executive Summit of reinvent made possible by Accenture. Keep it right there for more discussions that educating spy inspire You're watching the queue.

(upbeat music) >> Welcome back to the Cube's coverage of the AWS Executive Summit at AWS re:Invent made possible by Accenture. My name is Dave Vellante. We going to talk about The Automation Advantage, embrace the future of productivity, and improve speed quality and customer experience through artificial intelligence. And we're here with Bhaskar Ghosh who is the Chief Strategy Officer at Accenture and Rajendra 'RP' Prasad who is a Senior Managing Director and Global Automation Lead at Accenture. Guys, welcome to the cube, good to see you. >> Good to see you. >> Hello, David, thank you. >> Hey, congratulations on the new book. I know it's not like giving birth, but it's a mini version if you will. The automation advantage embraced a future of productivity, improved speed, quality, and customer experience through artificial intelligence. What inspired you to write this book? Can you tell us a little bit more about it, and how businesses are going to be able to take advantage of the information that's in there? That's great. Maybe you could start. >> Okay. So I think, you know, if we say that what inspired us, primarily the two things really inspired us to start this project. First of all, is the technology change, step change in the technology. Second is the maturity of the buyer, maturity of the market. So let me explain a little more. When I talk about the technology change, automation is nothing new in the industry, starting from the industrial revolution, always industry adopted the automation. But last few years, what happened, that there is a significant change in the technology in terms of lot of new technologies are coming together like Cloud, Data, Artificial Intelligence, machine learning, and they are getting matured. I think that created a huge opportunity in the industry. So that is number one. Second thing I think the maturity of the buyer. So buyers are always buying the automation, adopting the automation. So when I talk to this different buyer, different industrial buyer, suddenly we realize, they are not asking about what is automation. How that will help. But primarily they're talking about how they can scale it. They have all have done the pilot, the prototype, how they can take the full advantage in that enterprise to scale. And after talking to a few clients, few of our clients, they don't realize that it would be best to write this book and help all our clients to take advantage of this new technologies to scale up their business. If I give them a little more insight that what exactly we are trying to do in this book, primarily we dealt with three things. One is the individual automation, which deals with the human efficiency. Second is the industrial automation, which deals with the group efficiency . And third is the intelligent automation, which deals with the business efficiency or business value. So we believe that, this is what will really change their business and help our client help the automation IT users to really make an impact in their business. >> Yeah, and so you talked about that, the maturity of the customer and I liked the way you sort of described that spectrum ending with intelligent automation. So the point is you're not just paving the cow path if you will, automating processes that maybe were invented decades ago, you're really trying to rethink the best approach. And that's where you going to get the most business value and RP in thinking about the maturity, I think in pre-pandemic, people were maybe a little reluctant or as Bhaskar was saying, maybe needed some education. But how have things changed? Obviously the pandemic has had a huge impact. It's accelerated things. But what's changed in the business environment in terms of the need to implement automation, RP? >> Thank you for that is an excellent question. As we went through the pandemic, most of the enterprises accelerated what I call as the digital transformation. Technology transformation. And the overall time that it takes to do the transformation has compressed. Most of the enterprises now do compress transformation. The core of it is innovation and innovation led technology and technology based solutions. To drive this transformation, automation, artificial intelligence becomes part of what we do, while we are implementing these accelerators, innovation enablers within the enterprises. Most of the enterprises prior to the pandemic, we're looking, automation and AI as a solution for cost efficiency, saving costs and not deriving capacity efficiency as if they do the transformation (indistinct). Let me press the fast forward button through the transformation journey, leveraging automation. What happens is most of the enterprises switch the focus from cost efficiency to speed, to market, application availability and system resiliency are the core. When I speak to most of the CIO's, who are involved in the tech transformation, they now embrace automation and AI as a core enabler to drive this journeys towards, growth, innovation led, application availability and transformation and sustainability of the applications through their journey. Our book addresses, all of these aspects, including the most important element of AI, which is compute, storage and the enablement that it can accomplish through cloud transformation, cloud computing services and how AI and machine learning technologies can benefit from transformation to the cloud. In addition, we also address and talk about automation in the cloud. Automation, taking journey towards the cloud and automation, once you are in the cloud, what are the philosophy and principles you should be following to drive that automation? We also provide holistic approach to drive automation by focusing process technology that includes talent and change management, and also addressing automation culture for the organizations in the way they work as they move forward. >> So you mentioned a couple of things, compute and storage and when we look at our surveys, guys, it's interesting to see, especially since the pandemic, four items have popped up, where all the spending momentum is cloud, but for obvious reasons, scale and resource, and be able to work remotely, contain us because a lot of people have workloads on prem that they just can't automatically move into cloud, but they want to do development in the cloud and maybe connect to some of those on-prem workloads, RPA, which is _automation, and of course, AI. And, RP, you mentioned compute and storage, and of course the other pieces' data. So we have all this data. But so my question is, how has the cloud and AWS specifically influenced changes in automation in AI? >> Brilliant question and brilliant point. I say, whenever I talk to my clients, one of the things that I always say is, AI is nothing but an UI for the data. Let me repeat that, AI is the UI of the data. So that data plays a underlying and very critical part of applied intelligence, artificial intelligence and AI in the organizations, right? As the organization move along their automation journey, like you said, robotic process automation to containerization, to establishing data, building the data cubes and managing the massive data leveraging cloud and how AWS can help in a significant way to help the data stratification, data enablement, data analysis, and data clustering, classification, all aspects of that what we need to do within the data space. That helps for the large scale automation effort. The cloud and AWS plays a significant role to help accelerate and enable the data part. Once you do that, building machine learning models on the top of it, leveraging containers, clusters, DevOps techniques to drive, the AI principles on the top of it is very, it's kind of makes it easier to drive that and foster enablement advancement through cloud technologies. Alternatively, using automation itself to kind of enable the cloud transformation, data transformation, data migration aspects to manage the complexity speed and scale is very important. The book stresses the very importance of fueling the motion of the entire organization through agility, embracing new development, whether it's like automation in the cloud, DevOps, DevSecOps and the importance of oral cloud adoption that builds the foundational elements of making sure your automation and AI capabilities are established in a way that it is scalable and sustainable within the organizations as they move forward. >> Great. Thank you for that, RP. Bhaskar, I want to come back to this notion of maturity and just apply it to automation. So, Andy Jassy made the phrase, undifferentiated heavy lifting popular, but that was largely last decade applied to IT. And now we're talking about deeper business integration. And so, automation certainly solves the problem of, okay, I got to take mundane tasks like provisioning, storage, and compute and automate that. Great. But what are some of the business problems that deeper business integration that we're solving through things that, and I want to use the phrase that you used earlier, intelligent automation. What is that? And can you give an example? >> That's a very good question. As we said, that the automation is a journey. If we talk to any clients, so everybody wants to use data and artificial intelligence to transform their business. So that is very simple, but the point is that you cannot reach there unless you follow the steps. So in our book we have explained the process. That means, we defined in a five steps. We said that everybody has to follow the foundation which is primarily the tools driven, optimize, which is process-driven then efficiency improvement, which is primarily RPA driven, then comes predictive capability, the organization, which is data driven and then intelligence, which is primarily artificial intelligence driven. Now, when I talk about the use of artificial intelligence and this new intelligent ID in the business, what we mean is basically improved decision-making in every level in the organization. I'll give you an example. We have given multiple example in this book and a very simple example if I take. Suppose a financial sector organization, they're selling wealth management product to the clients. So they have a number of wealth management products and they have number, there are number of clients with different profile, but now what is happening, this artificial intelligence is helping their agents to target the right product for the right customer, so that the success rate is very high. So that is a change. That is a change in the way they do business. Now, some of the platform companies like Amazon and Netflix, you will see that this skill is a very native skill for them. They use the artificial intelligence, try to use everywhere. But there are a lot of other companies who are trying to adopt this skill today. Their fundamental problem is that they do not have the right data. They do not have that capability. They do not have all the processes so that they can inject the decision-making artificial intelligence capability in every decision-making to empower their workforce. And that is what we have written in this book to provide the guidance to this in this book. How they can use the better business decision, improve then create the more business value using artificial intelligence and intelligent automation. >> Interesting, Bhaskar, I want to stay with you, in their book, in the middle of last decade, Erik Brynjolfsson and Andy McAfee wrote. The Second Machine Age and they made the point in the book that machines have always replaced humans in sort of various tasks, but for the first time ever, we're seeing, machines replacing humans in cognitive tasks, and that scares a lot of people. So how do you inspire employees to embrace the change that automation can bring? What are you seeing as the best ways to do that? >> That's a very good question. Intelligent automation implementation is not an IT project. It's primarily change management. It's primarily change in the culture. The people in the organization need to embrace this change and how they will get empowered with the machine. It is not about the replacing people by machine, which has happened historically into the earliest stages of automation, which I explained. But in this intelligent automation, it is basically empowering people to do the better job. I will give you example. That is the thing we have written in the book, about a newspaper, a hundred years old newspaper in Italy. And this industry has gone through multiple automation and changes. So black and white printing to color, printing to digital, everything happened. And now what is happening, they are using artificial intelligence, so their writers are using those technologies to write faster, so when they're writing immediately, they are getting supported with the data, they are supporting with the related article. They are supporting with the script, even they're supported with the heading of this article. So the question is that it is not replacing the news, the content writer, but it's basically empowering them so that they can produce the better quality of product, they can be better at writing in a faster time. So it's a very different approach and that is why this needs a change management than a cultural change. >> Got it. RP, what's in it for me? Why should we read the automation advantage? Maybe you could talk about some of the key takeaways and maybe the best places to start on an automation journey. >> Very good question. The fastest step in your automation journey and cloud adoption journey is to start simple and start right. If you know what's happening, one of the process guru says, "If you don't know where you are on a map, a map won't help you." So to start right, a company needs to know where they are on a map today, identify the right focus areas, create a clear roadmap and then move forward with a structured approach for successful adoption. The other important element is if you automate an inefficient process, you are going to make your inefficiency run more efficiently. So it is very important to baseline and establish the baseline and know where you are on the journey map. This is one of the key themes we discuss in the Automation Advantage book. With principles and tips and real world examples on how to approach each of these stages. We also stress the importance of building the right architectures for intelligent automation, cloud enablement, security at the core of automation and the platform centric approach. Leading enterprises can fit on adopters and whether they are in the earlier stages of the automation journey or they're in the advanced stage of automation journey. They can look at the Automation Advantage book and build and take the best practices and what is provided as a practical tips within the book to drive their automation journey. This also includes importance of having right partners in the cloud space like AWS, who can accelerate automation journey and making sure a company's cloud migration strategy includes automation, automation-led AI and data as part of their journey management. >> That's great. Good advice there. But Bhaskar, bring us home, maybe you could wrap it up with the final word. >> So let me keep it very simple. This book will help you to create difference in your business with the power of automation and artificial intelligence. >> That's a simple message. And no matter what industry you're in, there is a disruption scenario for your industry, and that disruption scenario is going to involve automation. So you better get ahead of the game there. The book is available of course, at Amazon.com and you can get more information at accenture.com/automationadvantage. Guys, thanks so much for coming in the Cube. I really appreciate your time. >> Thank you. >> Thank you. >> And thank you for watching this episode of the AWS Executive Summit at re:Invent made possible by Accenture. Keep it right there for more discussions that educate and inspire, you're watching the Cube. (upbeat music)

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

(upbeat music) >> From the SiliconANGLE Media office, in Boston Massachusetts, it's theCUBE. Now, here's your host, Stu Miniman. >> I'm Stu Miniman, I'm here with Bobby Patrick, the Chief Marketing Officer of UiPath and Bobby, UiPath sponsored a new survey in paper that is from the economists, it's called The Advance of Automation. Tell us a little bit about why that paper was done. >> Yeah. So Robotic Process Automation is fairly new to the market. Automation, obviously has been around a while. It's been mostly in I.T. where we've automated for the last 20 years. With RPA now, you can really begin to talk to the C level executives about, "Hey, I can really drive 10, 15 percent productivity with every employee. I can really being to think about dramatic digital transformation across my entire enterprise". And so, we approached a few outlets, The Wall Street Journal being one, the FT, and The Economist. The Economist was very interested, they obviously have studies about the impacts of the workforce around productivity. And they viewed this as a really exciting effort to engage in. We obviously sponsored it as well. But the results really were from their surveys. They had multiple professionals on it, and we couldn't be more excited about the results of the paper. >> Awesome, a lot of data in there which our audience always love. What were some of the key takeaways from the results? >> High interest in automation. But only about half solved, really broad usage of automation in their company. I think what we realize here is that automation has impacted a number of areas. Certainly hard automation, hard automation is physical robots. But soft automation, or robotic automation, actually had higher awareness in it's potential. So I was surprised about that. But I think what the most important part to me is that over 90% said they thought automation could have massive impacts on their company. Not really surprising data, I would say I some cases. But I think the way they pull it all together and summarize about it's potential. I think that's what was most impactful. >> All right, Bobby, we've been loving digging in on theCUBE for years about the future of work. There is still so much concern or fear out there. "Robots are taking my job" "I throw in this new technology." And we understand in the I.T. industry, it is very rare that a technology directly replaces people. >> Right. >> As a matter of fact, we've done events with MIT and it's people plus machines. >> Right. >> It's usually the best answer. Where does this research fit with that whole second machine age and discussing their jobs? >> Yeah, I think what's great is, two years ago, RPA was not widely known, at all. And I think at the time the narrative was AI's going to replace jobs. There was a lot of fear. But that's not what we're seeing at all. And I think the paper confirms this as well. But, this is about robots doing the work we hate. Nobody misses the work that robots do. We see in terms of the results in data is that the increase in productivity actually drives a more efficient workforce and a more satisfied workforce. Happier employees. Employee engagement. Employment productivity is what we talk about often now. And so I think that narrative has shifted very quickly. And you could argue "Well it's low unemployment economy so maybe that's why." But even in certain countries that we're in like Brazil which have a much higher unemployment. The enthusiasm there is still very high. >> All right, as I mentioned, there's a lot of data in there. Which person in the organization is driving this, where is the awareness? There's geographical cuts of it. >> Right. >> So if people what to find out more, how do they get that? >> So Economist was great. They said "Hey, we love your view of this automation first era like the cloud first era", Stu that we've all be involved in for so long. The automation first era's huge and so they said "Hey, automationfirst.economist.com would be a great URL". All the content's up there now. You can download the white papers, there's a great infographic and it's part of the Economist. So, automationfirst.economist.com. >> All right, thank you so much, Bobby. I love about it automationfirst.economist.com and really all you have to do is go to that website, click a button, you don't have to fill out a long form. >> No. >> I'm guessing some robot just populates all the stuff that you need there. >> Of course. >> All right, for Bobby Patrick, I'm Stu Miniman. Thanks for joining us as always on theCUBE. (upbeat music)

(energetic music) >> Live from Miami Beach, Florida. It's theCUBE covering UiPathForward Americas. Brought to you by UiPath. >> Welcome to Miami everybody. This is theCUBE the leader in live tech coverage. We're here covering the UiPathForward Americas conference. UiPath is a company that has come out of nowhere, really. And, is a leader in robotic process automation, RPA. It really is about software robots. I am Dave Vellante and I am here with Stu Miniman. We have one day of coverage, Stu. We are all over the place this weekend. Aren't we? Stu and I were in Orlando earlier. Flew down. Quick flight to Miami and we're getting the Kool-Aid injection from the RPA crowd. We're at the Fontainebleau in Miami. Kind of cool hotel. Stu you might remember, I am sure, you do, several years ago we did the very first .NEXT tour. .NEXT from Nutanix at this event. About this same size, maybe a little smaller. This is a little bigger. >> Dave, this is probably twice the size, about 1,500 people here. I remember about a year ago you were, started buzzing about RPA. Big growth in the market, you know really enjoyed getting into the keynote here. You know, you said we were at splunk and data was at the center of everything, and the CEO here for (mumbles), it's automation first. We talked about mobile first, cloud first, automation first. I know we got a lot of things we want to talk about because you know, I think back through my career, and I know you do too, automation is something we've been talking about for years. We struggle with it. There's challenges there, but there's a lot of things coming together and that's why we have this new era that RPA is striking at to really explode this market. >> Yeah, so I made a little prediction that I put out on Twitter, I'll share with folks. I said there's a wide and a gap between the number of jobs available worldwide and the number for people to fill them. That's something that we know. And there's a productivity gap. And the numbers aren't showing up. We're not seeing bump-ups in productivity even though spending on technology is kind of through the roof. Robotic Process Automation is going to become a fundamental component of closing that gap because companies, as part of the digital process transformation, they want to automate. The market today is around a billion. We see it growing 10 x over the next five to seven years. We're going to have some analysts on today from Forester, we'll dig into that a little bit, they cover this market really, really closely. So, we're hearing a lot more about RPA. We heard it last week at Infor, Charles Phillips was a big proponent of this. UiPath has been in this business now for a few years. It came out of Romania. Daniel Dines, former Microsoft executive, very interesting fellow. First time I've seen him speak. We're going to meet him today. He is a techy. Comes on stage with a T-shirt, you know. He's very sort of thoughtful, he's talking about open, about culture, about having fun. Really dedicated to listening to customers and growing this business. He said, he gave us a data point that they went from nothing, just a couple of million dollars, two years ago. They'll do 140 million. They're doing 140 million now in annual reccurring revenue. On their way to 200. I would estimate, they'll probably get there. If not by the end of year, probably by the first quarter next year. So let's take look at some of the things that we heard in the keynote. We heard from customers. A lot of partners here. Seen a lot of the big SIs diving in. That's always a sign of big markets. What did you learn today at the keynotes? >> Yeah, Dave, first thing there is definitely, one of the push backs about automation is, "Oh wait what is that "going to do for jobs?" You touched on it. There's a lot of staff they threw out. They said that RPA can really bring, you know, 75% productivity improvement because we know productivity improvement kind of stalled out over all in the market. And, what we want to do is get rid of mundane tasks. Dave, I spent a long time of my career helping to get, you know, how to we get infrastructure simpler? How do we get rid of those routine things? The storage robe they said if you were configuring LUNs, you need to go find other jobs. If you were networking certain basic things, we're going to automate that with software. But there are things that the automation are going to be able to do, so that you can be more creative. You can spend more time doing some higher level functions. And that's where we have a skills gap. I'm excited we're going to have Tom Clancy, who you and I know. I've got his book on the shelf and not Tom Clancy the fiction author, but you know the Tom Clancy who has done certifications and education through storage and cloud and now how do we get people ready for this next wave of how you can do people and machines. One of my favorite events, Dave, that we ever did was the Second Machine Age with MIT in London. Talking about it's really people plus machines, is really where you're going to get that boom. You've interviewed Garry Kasparov on this topic and it's just fascinating and it really excites me as someone, I mean, I've lived with my computers all my life and just as a technologist, I'm optimistic at how, you know, the two sides together can be much more powerful than either alone. >> Well, it's an important topic Stu. A lot of the shows that we go to, the vendors don't want to talk about that. "Oh, we don't want to talk about displacing humans." UiPath's perspective on that, and we'll poke them a little on that is, "That's old news. "People are happy because they're replacing their 'mundane tasks.'" And while that's true, there's some action on Twitter. (mumbles name) just tweeted out, replying to some of the stuff that we were talking about here, in the hashtag, which is UiPathForward, #UiPathForward, "Automation displaces unskilled workers, "that's the crux of the problem. "We need best algorithms to automate re-training and "re-skilling of workers. "That's what we need the most for best socio-economic "outcomes, in parallel to automation through "algorithm driven machines," he's right. That gap, and we talked about this at 2MA, is it going to be a creativity gap? It's an education issue, it's an education challenge. 'Cause you just don't want to displace, unskilled workers, we want to re-train people. >> Right, absolutely. You could have this hollowing out of the market place otherwise, where you have really low paid workers on the one end, and you have really high-end creative workers but the middle, you know, the middle class workers could be displaced if they are not re-trained, they're not put forward. The World Economic Forum actually said that this automation is going to create 60-million net new jobs. Now, 60-million, it sounds like a big number, but it is a large global workforce. And, actually Dave, one of the things that really struck me is, not only do you have a Romanian founder but up on stage we had, a Japanese customer giving a video in Japanese with the subtitles in English. Not something that you typically see at a U.S. show. Very global, in their reach. You talked about the community and very open source focus of something we've seen. This is how software grows very fast as you get those people working. It's something I want to understand. They've got, the UiPath that's 2,000 customers but they've got 114,000 certified RPA developers. So, I'm like, okay, wait. Those numbers don't make sense to me yet, but I'm sure our guests are going to be able to explain them. >> And, so you're right about the need for education. I was impressed that UiPath is actually spending some of it the money that it's raised. This company, just did a monster raise, 225-million. We had Carl Ashenbach on in theCUBE studio to talk about that. Jeff Freck interviewed him last week. You can find that interview on our YouTube play list and I think on out website as well. But they invested, I think it was 10-million dollars with the goal of training a million students in the next three years. They've hired Tom Clancy, who we know from the old EMC education world. EMC training and education world. So they got a pro in here who knows to scale training. So that's huge. They've also started a 20-million investment fund investing in start ups and eco-system companies, so they're putting their money where their mouth is. The company has raised over 400-million dollars to date. They've got a 3-billion dollar evaluation. Some of the other things we've heard from the keynote today, um, they've got about 1,400 employees which is way up. They were just 270, I believe, last year. And they're claiming, and I think it's probably true, they're the fastest growing enterprise software company in history, which is kind of astounding. Like you said, given that they came out of Romania, this global company maybe that's part of the reason why. >> I mean, Dave, they said his goal is they're going to have 4,000 employees by 2019. Wait, there are a software company and they raised huge amounts of money. AS you said, they are a triple unicorn with a three billion dollar valuation. Why does a software company need so many employees? And 3,000, at least 3,000 of those are going to be technical because this is intricate. This is not push button simplicity. There's training that needs to happen. How much do they need to engage? How much of this is vertical knowledge that they need to get? I was at Microsoft Ignite two weeks ago. Microsoft is going really deep vertically because AI requires specialized knowledge in each verticals. How much of that is needed from RPA? You've got a little booklet that they have of some basic 101 of the RPA skills. >> I don't know if you can see this, but... Is that the right camera? So, it's this kind of robot pack. It's kind of fun. Kind of go through, it says, you got to reliable friend you can automate, you know, sending them a little birthday wish. They got QR codes in the back you can download it. You know, waiters so you can order online food. There's something called Tackle, for you fantasy football players who help you sort of automate your fantasy football picks. Which is kind of cool. So, that's fun. There's fun culture here, but really it's about digital transformation and driving it to the heart of process automation. Daniel Dines, talked about taking things from hours to minutes, from sort of accurate to perfectly accurate. You know, slow to fast. From very time consuming to automated. So, he puts forth this vision of automation first. He talked about the waves, main frames, you know the traditional waves client server, internet, etc. And then, you know I really want to poke at this and dig into it a little bit. He talked about a computer vision and that seemed to be a technical enabler. So, I'm envisioning this sort of computer vision, this visual, this ability to visualize a robot, to visualize what's happening on the screen, and then a studio to be able to program these things. I think those are a couple of the components I discerned. But, it's really about a cultural shift, a mind shift, is what Daniel talked about, towards an automation first opportunity. >> And Dave, one of the things you said right there... Three things, the convergence of computer vision, the Summer of AI, and what he meant by that is that we've lived through a bunch of winters. And we've been talking about this. And, then the business.. >> Ice age of a, uh... >> Business, process, automation together, those put together and we can create that automation first era. And, he talked about... We've been talking about automation since the creation of the first computer. So, it's not a new idea. Just like, you know we've been talking on theCUBE for years. You know, data science isn't a new thing. We sometimes give these things new terms like RPA. But, I love digging into why these are real, and just as we've seen these are real indicators, you know, intelligence with like, whether you call it AI or ML, are doing things in various environments that we could not do in the past. Just borders of magnitude, more processing, data is more important. We could do more there. You know, are we on the cusp of really automation. being able to deliver on the things that we've been trying to talk about a couple of generations? >> So a couple of other stats that I thought were interesting. Daniel put forth a vision of one robot for every person to use. A computer for every person. A chicken for every pot, kind of thing (laughs) So, that was kind of cool. >> "PC for every person," Bill Gates. >> Right, an open and free mind set, so he talked a about, Daniel talked about of an era of openness. And UiPath has a market place where all the automations. you can put automations in there, they're all free to use. So, they're making money on the software and not on the automation. So, they really have this... He said, "We're making our competitors better. "They're copying what we're doing, "and we think that's a good thing. "Because it's going to help change the world." It's about affecting society, so the rising tides lift all boats. >> Yeah Dave, it reminds me a lot of, you know, you look at GitHub, you look at Docker Hub. There's lots of places. This is where code lives in these open market places. You know, not quite like the AWS or IBM market places where you can you can just buy software, but the question is how many developers get in there. They say they got 250,000 community members already there. So, and already what do they have? I think hundreds of processes that are built in there, so that will be a good metric we can see to how fast that scales. >> We had heard from a couple of customers, and Wells Fargo was up there, and United Health. Mr. Yamomoto from SNBC, they have 1,000 robots. So, they are really completely transforming their organization. We heard from a partner, Data Robot, Jeremy Atchins, somebody who's been on theCUBE before, Data Robot. They showed an automated loan processing where you could go in, talk to a chat bot and within minutes get qualified for a loan. I don't know if you noticed the loan amount was $7,000 and the interest rate was 13.6% so the applicant, really, must not of had great credit history. Cause that's kind of loan shark rates, but anyway, it was kind of a cool demo with the back end data robot munging all the data, doing whatever they had to do, transferring through a CSV into the software robot and then making that decision. So, that was kind of cool, those integrations seemed to be pretty key. I want to learn more about that. >> I mean it reminds me of chat box have been hot in a lot of areas lately, as how we can improve customer support and automate things on infrastructure in the likes of, we'll see how those intersections meet. >> Yeah, so we're going to be covering this all day. We got technologists coming on, customers, partners. Stu and I will be jamming. He's @Stu and I'm @Dvellante. Shoot us any questions, comments. Thanks for the ones we've had so far. We're here at the Fontainebleau in Miami Beach. Pretty crazy hotel. A lot of history here. A lot of pictures of Frank Sinatra on the wall. Keep it right there, buddy. You're watching theCUBE. We'll be right back after this short break. (energetic music)

>> From Boston Massachusetts, it's The Cube! Covering LiveWorx 18. Brought to you by PTC. >> Welcome to Boston everybody. You're watching The Cube, the leader in live tech coverage. And we're here with a special presentation in coverage of the LiveWorx show sponsored by PTC of Needham, soon to be of Boston. My name is Dave Vellante. I'm here with my co-host Stu Miniman. And Stu, this is quite a show. There's 6,000 people here. Jim Heppelmann this morning was up giving the keynote. PTC is a company that kind of hit the doldrums in the early 2000s. A company that as manufacturing moved offshore, its core business was CAD software for manufacturers, and it went through a pretty dramatic transformation that we're going to be talking about today. Well, fast forward 10 years, 12 years, 15 years on, this company is smokin, the stock's up 50 percent this year. They got a billion dollars plus in revenue. They're growing at 10 to 15 percent a year. They've shifted their software business from a perpetual software license to a recurring revenue model. And they're booming. And we're here at the original site of The Cube, as you remember well in 2010, the Boston Convention Center down at the seaport. And Stu, what are your initial impressions of LiveWorx? >> Yeah, it's great to be here, Dave. Good to be here with you and they dub this the largest digital transformation conference in the world. (laughing) So, I mean, Dave, you and I have been to much bigger conferences and we've been to a lot of conferences that are talking about digital transformation. But, IOT, AI, Augmented Reality, Block Chain, Robotics, all of these things really are about software, it's about digital transformation, and a really interesting space as you mentioned kind of the legacy of PTC. I have been around long enough. I remember when we used to call them Parametric Technologies. They kind of rebranded themselves as PTC. Windchill brings back some memories for me. When I worked for a high tech manufacturing company, it was that's the life cycle management tool that we used back in the early 2000s. So, I had a little bit of background in them. And, as you said, they're based in Needham, and they're moving to the Seaport. Hot area, especially, as we've said Dave, Boston has the opportunity to be the hub of IOT. And it's companies like PTC that are going to help bring those partnerships and lots of companies to an event like this. >> Well PTC has always been an inquisitive company, as you were pointing out to me off camera. They brought Prime Computer, Computer Vision. A number of acquisitions that they made back in the late 90s, which essentially didn't pan out the way they had hoped. But now again, fast forward to the modern era, Jim Heppelmann came in I think around 2010, exceeded ThingWorx, a company called Cold Light, Kept Ware is another company that they purchased. And took these really sort of independent software components and put them together and created a platform. Everybody talks about platform. We'll be talking about that a lot today, where the number of customers and partners of PTC. And we even have some folks from PTC on. But, basically, talking about digital transformation earlier, Stu, IOT is a huge tailwind for a company like PTC. But they had to really deliberately pivot to take advantage of this market. And if you think about it, yes, it's about connecting and instrumenting devices and machines, it's about reaching them, creating whatever wireless connections. But it's also about the data. We talk about that all the time. And constructing data that goes from edge to core, and even into the cloud, whether that cloud's on prem or in the data center. So you're seeing the transformation of this company. Obviously, I talked about some of the financials. We'll go into some of that. But an evolving ecosystem we heard Accenture's here, Infosys is here, Deloitte is here. As I like to say, the SI's like to eat at the trough. If the SI's are here, that means there's money here, right? >> Yeah Dave and actually a number that jumped out at me when Microsoft was up on stage, and it wasn't that Microsoft is investing five billion dollars in diode, the number that caught my ear was the 20 to 25 partners that it takes to deploy a single IOT solution. So, anybody that's been in tech for a long time, when you see these complicated stack solutions, the SIs need to be here. It takes a long time to work through them, and integration is a big challenge. How do I get all of these pieces together? It's not something that I just tit buy off the shelf. It's not shrink wrap software. This is complicated solution. It is very fragmented in how we make them up. Very specific to the industry that we're building, so really fascinating stuff that's going on. But we are still very early in the life-cycle of IOT. Huge, huge, huge opportunities but big players like Microsoft, like Google, like Amazon are going to be here making sure that they're going to simplify that environment over time. Huge, you know Dave, what's the original forecast I think we did at Wiki Bon, was a 1.2 trillion dollar opportunity, which most of that, that was actually for the industrial Internet, which is not the commercial things that we think about all the time, when we talk about the home sensors and some of the things, some of the consumer stuff, but also the industrial here. >> Well, I think a couple of key points that you're making here. First of all, the market is absolutely enormous. It's almost impossible to size. I mean you're talking about a trillion dollars in sort of spending on hardware, software, services, virtually everything. But to your point, Stu. It's highly highly fragmented, virtually every industry. And a lot of different segmented technologies. But it's also important to point out this is the mashing together of operations technology, OT with Information Technology, IT, and those four leading companies IT is actually leaning in and embracing this notion of edge, computing, and IOT. Now, I wouldn't even say that IT and OT are Hatfield and McCoy's. They're not. They're parts of the organization that don't talk to each other. So they are cultural differences. They use different languages. They think differently. One is largely engineers who make machines work. The other IT guys, which we obviously know what they do, they keep information technology systems running. They deploy a lot of new IT projects. So, really different worlds that have to start coming together. Jim Heppelmann today I thought did a really good job in his keynote. He talked about innovation. Usually you start with okay we're here at point A, we want to go here. We want to get to point B. And we're going to take a straight line and have a bunch of linear steps and milestones to get there. He pointed out that innovation today is really sort of a non-linear process. And he talked about the combinatorial effects of really three things. Machines, or the physical, computers and humans. Machines are strong, they can do heavy lifting. Computers are fast, and they can do repetitive tasks very accurately. And humans are creative. And he talked about innovation in this new world coming together by combining those three aspects, finding new ways to attack problems, to solve nature's challenges. And bringing nature into that problem solving. He gave a lot of examples of how mother nature mimicking mother nature is now possible with AI and other technologies. Pretty cool. >> Yeah, absolutely Dave. I'm sure we'll be talking a lot today about the fourth Industrial Revolution. A lot of discussion as to what jobs are Robots going to take. I look around the show floor here and there's a lot of cool robotics going on. But as Eric Manou said and Aaron McAfee, the folks from MIT that we've interviewed a couple of times talked about the second machine age. Really the marring of people and machines that are going to be powerful. And absolutely Jim Heppelmann talked about that a lot. It's humans, it's physical, and it's digital. Putting those together and then, the other thing that he talked about is we're talking a lot about voice lightly with all of these assistants, but, you're really limited as to how much input and how fast you can take information in from an auditory standpoint. I mean, I know that I listen to podcasts at 1.5 to 2 X to try to get more information in faster, but it is sight that we're going to get 80 percent of the information in, and therefore, it's the VR and AR that are huge opportunities. I know when I've been talking to some of the large manufacturers, what they used to have in written documentations and then they went digital with, they're now getting you inside to be able to configure the systems with the hollow lens, or some of the AR headsets, the VR headsets, to be able to play with that. So, we're really early but excited to see where this technology has come so far. >> Yeah, we're seeing a lot of practical applications of VR and AR. We go to a lot of these shows and they'll have the demos, and you go, okay, what will I do with this? Well, you're really seeing here at LiveWorx some of the things you actually can do. One good example I thought they did was BEA Systems up in Nashua, actually showing the folks that are doing the manufacturing, little tutorial in how to do that. We're going to see some surgical examples today. Remote surgery. There are thousands, literally thousands of examples. In the time we have remaining, I want to just do the rundown on PTC. Cause it really is quite an amazing transformation story. You're talking about a company with 1.1 billion dollars in revenue. Their aspiration is by 2021 to be a two billion dollar company. They're growing at ten percent a year, their software business has grown at 12 to 15 percent a year. 15 percent is that annual recurring revenue. So this is an example of a company that has successfully shifted from that perpetual model to that recurring model. They got 200 million dollars this year in free cash flow. Their stock, as I said, is up 50 percent this year. They got 350 million dollars in cash, but they just got a billion dollar investment from Rockwell Automation that took about 8.4 percent of the company given them an implied evaluation of almost 11 billion dollars, which has got a little uplift from the stock market there. They're selling a lot of seven figure deals. Really, the core is manufacturing product life-cycle management, CAD. That's the stuff that we know PTC well from. And I talked about some of those acquisitions that they made. They sell products like Creo, which is their 3D CAD software. I think they're on Rev five or six by now. So they've taken their sort of legacy software and sort of updated that for the digital world. >> Yep ,it is version five that they were just announced today. Talking about really the 3D effort they're doing there. Some partnerships around it, and like every other software Dave that we've been hearing about AI is getting infused in here because with so many devices and so much data, we really need the machines to help us process that and do things that humans can't keep up with. >> And the ecosystem's grown. This is a complicated marketplace. If you look at the Gartner Magic Quadrant, there is no leader, even though PTC is the leader. But there is no leader. They're all sort of in the lower right, PTC is up highest. GE is interestingly is not in there, because it doesn't have an on prem solution. I don't know why GE doesn't have an on prem solution. And I don't know why they're not in there. >> Is there another version of the magic quadrant that includes the Amazons and GEs of the world? >> I don't know. So that's kind of interesting. We'll try to unpack that as we go on here. PTC announced today a relationship with a company called Ansys, which does simulation software. Normally, simulation comes sort of after the design. They're bringing those two worlds together. The CAD design piece and the simulation piece, sort of closer to real time. So, there's a lot of stuff going on. As you said, it's data, analytics, edge computing. It's cloud, it's on prim, it's block chain for security. We haven't talked about security. A lot bigger threat metrix, so block chain comes into play. >> Yeah, Dave. I saw a great joke. Do you realize that the S in IOT stands for security? Did you know that? (laughing) Oh wait, there's no S in IOT. Well, that's the point. >> All right, good. So Stu and I will be here all day today. This is actually a three day conference. The Cube will only be there for day one. Keep right there everybody. And we'll be right back. You're watching The Cube, Live from Liveworx in Boston. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCube covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back everyone to theCube's live coverage of ServiceNow Knowledge18 here in Las Vegas. I'm your host Rebecca Knight along with my cohost Dave Vellante. We're joined by Dave Wright. He is the chief innovation officer at ServiceNow. Thanks so much for coming on the program. >> It's a pleasure, always a pleasure. >> Good to see you again Dave. >> Good to see you as well. >> Yeah, you've been around the block. You've been around theCube a few times. >> Around the block, a bad way of putting it but yeah. (laughing) >> So chief innovation officer, we've had a lot of great new product launches at this show. What are you most excited about, and what are you already thinking about when you go back to your office? >> So I think what's been interesting to me is the different way of engaging now, we've got the concept of virtual agent technology and I don't just mean the fact that we've got virtual agents. The fact that it starts to give people alternatives and it gives people alternative ways to come into the system, whether it be through our interface or whether it be through someone else's interface, I start to wonder, what'll happen going forward as we get more and more bot type technologies out. How will you have that one interface that works with all those to get that information back of the chain? How will you almost have a single interface that allows you to connect to all these bots and solve your problems? Because the benefits kind of two fold. One is the bot technology you get from being a customer to coming in and actually doing a request. But the other is you'll eventually be able to take that same technology and apply it to the fulfilled user so the power user because if I'm doing something and I can have an agent that's helping me do it, almost like the agent assist concept, you saw this morning. If I can take that to a next level and have AI running on top of that, then I can make work easier for the people coming in but I can actually improve the people that are in the system and make them more effective. >> Go ahead. >> Go ahead, follow up please. >> No, I was just going to ask about, how you get your ideas? So you're here, you're interacting with customers, you're seeing how they're using your product. So is it interviewing customers to find out their pain points? Is it really just watching, I mean you're the chief innovation officer. How do you spark your own creativity? >> It's a really weird answer. I get most of it off kids, most of it off my kids. So I can tell you a story. We were in Barnes and Noble the other week and they had albums in the, plastic twelve inch albums. >> Rebecca: They're coming back. >> And they cost more than they use to. >> Dave Vellante: Yeah really. >> So I called the kids over, I said look, let's get educated. This is what I use to play music on. And now we moved to CD's and you guys miss CD's and this is why you guys buy music. Now I've got a 12 year old and seven year old. And the 12 year old was saying, well, we don't buy music. And I said yeah, and I thought, no you don't, you rent music. And then my youngest daughter said, why would you want to own a song forever? And I was like, this is interesting. We started having a discussion, >> These are deep, these are deep questions. >> It was while other kids we're over having a sleepover and they're all eating pizza and they were talking about the concept of having a job. They said, how do you decide what you want to do for the rest of your life and how do you do that? And we we're talking about how you do something, you get better. You go to another company, you get better at doing it. You go to another company. And one of them said, it sounds really boring just like doing the same thing. And then one of them had the best answer. She said, don't you think it's a waste of your time? And I said, why is it a waste? And she said, because if you're really good at something, why should you just do it for one company? And I was like, oh so, you're going to be a contactor. (laughing) But what I realize was because this whole generation don't need to own things, they just need to use things, so they don't need to know how to do something, they just know they want to do it. And they don't need to own something, they just need temporary access to it. Then it got me thinking when you talk about where could work go to. Do you get a whole concept of the gig economy becoming a gig enterprise. Because we've got a lot of people in work who've got all these different skills but we force them to do one job. And it might be that someone's doing a job but they've got skills that would be applicable outside of that job but they never get to use them. So have we seen the first generation arrive now where they expect everything to be tass based? And then it gives you control over your own career. Because then you say, well, actually I'm not good at this but I can start a bid for work. I can say to people, hey I'm only a three on a skills racing but if you don't need any complex, I'll take it cause I get to learn. So it's a whole new dynamic and I think when you ask whereabout ideas come from, some of the first stage ideas or the first horizon, I think they come form customers. Some of the second horizon, they come from people who aren't working. It's just trying to imagine how they all develop and whereabout that all goes. >> So you surround yourself with millennials? >> Not even millennials. >> Dave Vellante: They're kind of pre post millennials. >> Almost like the linksters, almost the people who've been born connected. It's definitely a Gen Z thing but it's beyond millennials. I think the millennials had a certain expectation around well it's kind of a negative connotation but before they were called millennials, people use to refer to it as the entitlement generation. And it wasn't because they were entitled, it was because they felt they just got access to everything. So it's like with my kids, they're kind of Gen Z and one of them is a linkster, but you never go to them and say, they never come to you and say, hey, I want to watch a movie and you go, great, let's go to Blockbuster's, let's rent it. They expect it to be just available on demand, available all the time. And that was what I think the kind of millennial generation started being entitled to access to data, then I think you went to the generation where it was everything always connected, no concept of banword. But now I think it's the, the real thing that's changing is the concept of ownership and I think that's where you start to see things like, will the car industry ever be the same because if you don't need to own a car because you're not driven by the same passions that people who own cars are driven by, it's just a way of communicating you don't need a garage on your house, you may as well park the car somewhere else. It comes when you need it. It can change the way cities are laid out. I mean there's so many different routes you can go down with this. >> SO how does that innovation, how does that knowledge that you gain get into ServiceNow products and services? >> That all comes back then to how you, how people are going to face new management dynamics or how people are going to manage things like IOT devices? How are people going to deal with managing work if it is a task based economy? How are people going to start to think about not just working in a system of record, or not just working in a system of engagements, but how are they going to start to build that mesh or that web that links all these different things together? And I think that's where our strand comes. Our strand comes in the ability to be able to link systems of records together. To link users with those backend systems, to be able to manage those complex work processes. That's kind of the core elements. Also I think when you look at what Fred Crasick when he built the platform and he had the whole work flow engine and it is that engine that's kind of the key pallet to the whole company. >> I think the metaphor of mesh, sometimes we talk about a matrix of digital services that becomes ubiquitous beyond a cloud of remote services, is really transforming to this mesh of digital capabilities that are everywhere that do things that Clouds don't do. They sense, they react, they respond, they read, they hear. It's an amazing time that we're entering in innovation. Andy McAfee and Erik Brynjolfsson when they wrote the book Second Machine Age talked about Moore's Law, power innovation but they also talked about the innovation curve reshaping from going from Linears Moore's Law which we've marched to the cadence of Moore's Law for decades in this industry to reshaping, to an expediential curve. And I wonder if we could get your thoughts. We've paused that it's accommodation of sort of data applying machine intelligence to that data and then leveraging Cloud economics at scale is really where the innovation is going to come from in the future. What are your thoughts on that? >> So let me try to understand the question. So you're talking about not actually the way that you've seen the growth from a process prospective but the way you actually see the growth from a machine learning capability being able to analyze that data? >> Applying that layer of machine learning. Maybe use that mesh metaphor, that top level. You know you've got horizontal technology services but then there's this new AI layer on top. The data is the fuel for that AI. >> Absolutely, I think it's the I think people can't even imagine what they can do with that data, people can't even contemplate some of the decisions they can make and it's when people start to look at things in completely different ways, it's when people start to say, well, if we apply machine learning to a user interface for example, could we come up with a better user interface because now if we understand how people interact with the system, could we actually build a better system? Or you see people starting to have this whole butterfly effect around the way that artificial intelligence works. So the best example I heard was from, I was actually at a convention with a girl called Louis Chang and she was talking to me about it. But they were speaking to hospitals. They we're talking about self drive cars and the application machine learning of being able to help cars drive. And they were saying the interest in knock on effect of this was a hospital saying it was going to be a real problem for them having self drive cars. And she said, why's it going to be a problem? And the problem was, if you look across the whole America you have about 20 people a day die because they can't get replacement organs. But 37 percent of the organs come from car crashes. So if you take car crashes out of the equation. So what they were investing in was actually looking at how they do cloning technology for organs. So no one would ever imagine (mumbled speaking) and this is going to improve cloning technology so much. And I think AI's in the same place. Everyone's using it in such a small area that they don't even see the potential of what they could do with it, they don't have any concept of what they could be starting to look at and how they could start to spot transvaterian people. Even on a base level, I was speaking to one of our customers the other night, and they managed to put an AI system in place that when they got a call in off the description of the call they could work out what the customer satisfaction was going to be and if it was going to be a bad satisfaction figure, they could preemp that and put different agents that were more skilled on that particular issue. And they said a few years ago all they were interested in was maybe one day we'll be able to categorize something asymmetrically. But now they can predict how well something's going to be resolved. >> It's very hard to predict isn't it? I mean who would of thought that Alexa would of emerged as one of the best if not the best natural language processing systems or that images of cats on the internet would lead to facial recognition in technology. >> That one especially. >> Could of never predicted that. So, but because you're such a clear thinker and a strategic thinker, I want to ask you to make some predictions. I'm going to run some things by you. You talked about autonomous vehicles for awhile. Do you believe that owning in the future, pick whatever time frame you want, that owning and driving your own car will become the exception? >> Yeah I think it will probably be the people who, well okay, so I definitely think driving your own car will become the exception. I think some people will always want that sense of ownership until we get to a generation that doesn't. I think they'll always be a hard core of people who do want to own and do want to drive and do want that experience, but I think you've already got the issue where congestion's such a level in most areas. Is there any enjoyment out of driving? So I love driving, I love sports cars, I collect them. But if someone said, hey you've got two options, you can sit in a high performance sports car to go to LA or you can sit in a Tesla and it will drive itself and you can read a book. I'm getting in the Tesla. (laughing) >> How about retail? Right for disruption, do you think that large retail stores will essentially, not essentially, it's never complete, but will largely go away? >> I think it depends on the nature of the experience. So I think for a lot of goods that are consumable goods, I can kind of see that going away. I don't think it will go away for luxury goods. I don't think it will go away fully for fashion. I think people always like to look at things and understand things and check fits but for some things that are high consumables maybe even for electronics, I can see those going or I can see it going for things where it's worn product. So something like a shop that just sells sneakers. I can see someone could easily offer a range and say, well look, here's what we sell. When you order something, we'll automatically ship you one size up, one size down, or two variations of color and it will be a free system return the ones you don't want. I think the whole experience of ordering one thing and hoping it works out, I think that will go away. It will be concept of ordering a group of things or maybe it will be applying to artificial intelligence to say, hey you've asked for this color, but we know that people who also ask for that color like this color as well. We're going to ship you them both. You can see how it goes and send us the one back you don't like. >> Okay, let's see. Will machines make better diagnosis than doctors? I've got to say I think you will get to a point where that will happen. Especially if it's things where it's image processing, where it's x-ray processing, MRI processing. Where it's something like process of mental health, then I don't know. Maybe, I'd probably rather have my mental health treated by a person than a questionnaire. But yeah I think the things we're using, image recognition, or things where you're looking at patent distribution or you're looking at even like virus distribution or virus structure, then I think those areas I think you will get to a point where diagnostic issue is better. But you look at where artificial intelligence is from diagnostics now and you go on doctor google and search for something, you know, everything finished with the bottom line, or it could be cancer. >> Dave Vennari: Yeah, you're dead. >> What about will there ever be a revolt, you know in the sense of, technology is so pervasive, and people just say forget it, I'm sick of just being tracked, I just kind of want to have a human to human connection and, >> Dave Vellante: Dream on. >> So are we done for? >> I was speaking to a girl who works for me, Menesha, and she was saying, we were talking on Friday and she said, hey, I was having a coffee with nother girl Cass, and Menesha's in Seattle and Cass in is San Francisco, and I said, oh was she in Seattle or were you in San Francisco and Menesha's a lot younger than me, and she went, no we weren't in the same room. We were just like doing it over video like a virtual coffee. And I was like what, so you both get coffee and sit and have a conversation? And she was like, oh yeah. >> Dave Vellante: Alright, I've got one more, I've got one more. >> Okay, let's hear it, let's hear it. >> Alright last one, it's great, thanks for playing along. >> I know this is fun. >> Financial services is an industry that really hasn't been disrupted. DO you feel like the banks will lose control, the major banks will lose control of payment systems? >> I think there's a lot of conversations now around how much those payment systems open up. Because if you, let's say you do a transaction with Amazon, you do a transaction with Google, how hard would it be for every transaction to be done that way? So rather than, if your setting off a payment for I don't know, gas bills or a car loan payments, rather than giving your bank details, why not give your PayPal details or your Amazon account details or your Google details? That could be, reduce all the banking transactions down to one interface. I think that could happen. I think you could get, well obviously you're already seeing the rise of Blockchain and I'm not a Blockchain expert. I'm itching to find a used case for us with Blockchain but I can't find it yet. But for direct transactions, if both sources can trust each other than yeah, that direct transaction between those two sources, I think that's completely possible. I think there's also areas where, you've seen happen in the past where a banking faces issues from retail coming into banking, so sometimes you'll get the big supermarket chains, especially in Europe they say, okay you're going to get (foreign name) or you're going to get Tesco's Bank, because they've got all our customer loyalty, they've got people waiting to give discounts to if they bank with them, so they can instantly bring, if you said to your shopping account base, hey, if you bank with me we'll give you 20 dollars a week off your grocery shopping, you could probably ring 10 million customers straight away. So I think banking's challenged from other industries that want to get into it, from places where you'll actually go and do each transactions now and from where places where you'll just go and order stuff online and you could filter all that through one place, I think they'll still always be the commercial side of banking. There's always going to be the stocks and bonds, there's still going to be the wealth management, but props for transactional banking, you could start to see a decline. >> Fantastic, thank you. >> I love this futurist talk, it's been a lot of fun. Thank you so much for coming on theCube Dave. >> Alright, thanks for having me, always a pleasure. >> Dave Vellante: Great to see you. >> We will have more from ServiceNow Knowledge18 theCube's live coverage just after this. (upbeat music)

>> Announcer: Live, from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17. Brought to you by ServiceNow. >> We're back. This is Dave Vellante with Jeff Frick. Chris Bedi is here, he's the CIO of ServiceNow. Chris, good to see you again. >> Good to see you as well. >> Yeah, so, lot going on this week, obviously. You said you're getting pulled in a million different directions. One of those, of course, is the CIO event, CIO Decisions, it's something you guys host every year. I had the pleasure of attending parts of it last year. Listened to Robert Gates and some other folks, which was great. What's happened this year over there? >> So, CIO Decisions, it's really where we bring together our forward thinking executives. We keep it intimate, about a hundred, because really it's about the dialogue. Us all learning from each other. It really doesn't matter, the industry, I think we're all after the same things, which is driving higher levels of automation, increase the pace of doing business, and innovating at our companies. So we had Andrew McAfee, MIT research scientist, really helping push the boundaries in our imagination on where machine learning and predictive analytics could go. And then we had Daniel Pink talking about his latest book, To Sell is Human. And really as CIOs, we often find ourselves selling new concepts, new business models, new processes, new analytics, new ways of thinking about things. And so, really trying to help, call it exercise, our selling muscle, if you will. Because we have to sell across, up, down, and within our own teams, and that is a big part of the job. Because as we move into this new era, I think the biggest constraint is actually between our own ears. Our inability to imagine a future where machines are making more decisions than humans, platforms are doing more work on behalf of humans. Intellectually, we know we're headed there, but he really helped to bring it home. >> Well, you know, it's interesting, we talk about selling and the CIOs. Typically IT people aren't known as sales people, although a couple years ago I remember at one of the Knowledges, Frank Slootman sort of challenged the CIO to become really more business people, and he predicted that more business people would become CIOs. So, do you consider yourself a sales person? >> I do. Selling people on a vision, a concept, the promise of automation. You know, technology, people fear it, right? You know, when you're automating people's work the fear and the uncertainty endowed, or what I call the organizational anti-bodies, start to come out. So you have to bust through that, and a large part of that is selling people on a promise of a better future. But, it's got to be real. It's got to be tied to real business outcomes with numbers. It can't be just a bunch of PowerPoint slides. >> So we always like to take the messaging from the main tent and then test it with the practitioners, and this year there's this sort of overall theme of working at lightspeed, you and I have talked about this, how does that resonate with CIOs and how do you put meaning behind that? 'Cause, you know, working at lightspeed, it's like, ooh that sounds good, but how do you put meat on that bone? >> So, the way I think about working at lightspeed is three dimensions, velocity, intelligence, and experience. And velocity is how fast is your company operating? I read a study that said 40% of Fortune 500 companies are going to disappear in the next 10 years. That's almost half, right? But I think what's going to separate the winners from the losers is the pace at which they can adapt and transform. And, with every business process being powered by IT platforms, I think CIOs and IT are uniquely positioned to explicitly declare ownership of that metric and drive it forward. So velocity, hugely important. Intelligence. Evolving from the static dashboards we know today, to real time insights delivered in context that actually help the human make decisions. And, BI in analytics as we know it today, needs to evolve into a recommendation engine, 'cause why do we develop BI in analytics? To make decisions, right? So why can't the platform, and it can, is the short answer, with the ability to rapidly correlate variables and recognize complex patterns, give recommendations to the humans, and I would argue, take it a step further, make decisions for the humans. ServiceNow did a study that said 70% of CIOs believe machines will make more accurate decisions than humans, now we just got to get the other 30% there. And then on experience, I think the right experience changes our behavior. I think we in IT need to be in the business of creating insanely great customer and employee experiences. Too often we lead with the goal of cost reduction or efficiency, and I think that's okay, but if we lead with the goal of creating great experiences, the costs and the inefficiencies will naturally drop out. You can't have a great experience and have it be clunky and slow, it's just impossible. >> And it's interesting on the experience because the changing behavior is the hardest part of the whole equation. And I always think back to kind of getting people off an old solution. People used to say, for start ups, you got to be 10x better or 1/10th the cost. 2x, 3x is not enough to get people to make the shift. And so to get the person to engage with the platform as opposed to firing off the text, or firing off an email, or picking up the phone, it's got to be significantly better in terms of the return on their investment. So now they get that positive feedback loop and, ah, this is a much better way to get work done. >> It has to. And we can't, you know, bring down the management hammer and force people to do things. It's just not the way, you know, people work. And very simple example of an experience driving the right behavioral outcome, so ServiceNow is a software company, very important for us to file patents. The process we had was clunky and cumbersome. You know, we're not perfect at ServiceNow either. So we re-imagined that process, made it a mobile first experience built on our platform, of course. But by simply doing that, there was no management edict, you have to, no coercion, if you will, we saw an 83% increase in the number of patent applications filed by the engineers. So the right experience can absolutely give you the right desired economic behavior. >> You talked about 70% of CIOs believe that machines will make better decisions than humans. We also talked about Andrew McAfee, who wrote a book with Eric Brynjolfsson. And in that book, The Second Machine Age, they talked about that the greatest chess player in the world, when the supercomputer beat Garry Kasparov, he actually created this contest and they beat the supercomputer with a combination of man and other supercomputers. So do you see it as machine, sort of, intelligence augmenting human intelligence, or do you actually see it as machines are going to take over most of the decisions. >> So, I actually think they are going to start to take over some basic decision making. The more complex ones, the human brain, plus a machine, is still a more, you know, advanced, right? Where it's better suited to make that decision. But I also think we need to challenge ourselves in what we call a decision. I think a lot of times, what we call a decision, it's not a decision. We're coming to the same conclusion over and over and over again, so if a computer looked at it, it's an algorithm. But in our brains, we think a human has to be involved and touch it. So I think it's a little bit, it'll challenge us to redefine what's actually a decision which is complex and nuanced, versus we're really doing the same thing over and over again. >> Right, and you're saying the algorithm is a pattern that repeats itself and leads to an action that a machine can do. >> Yeah. >> It doesn't require intuition >> And we don't call that a decision anymore. >> Right, right. So, in thinking about you gave us sort of the dimensions of lightspeed, what are some of the new metrics that will emerge as a result of this thinking? >> Yeah, I don't think any of the old metrics go away. I'll talk about a few. You know, in lightspeed, working at lightspeed, we need to start measuring, for one, back on that velocity vector, what is the percentage of processes in your company that have a cycle time of zero, or near zero. Meaning it just happens instantaneously. We can think of loads of examples in our consumer life. Calling a car with Uber, there's no cycle time on that process, right? So looking at what percentage of your processes have a cycle time of zero. How much work are you moving to the machines? What percentage of the work is the platform proactively executing for you? Meaning it just happens. I also think in an IT context of percentage of self healing events, where the service never goes down because it's resilient enough and you have enough automation and intelligence. But there are events, but the infrastructure just heals itself. And I think, you know, IT itself, we've long looked at IT as a percentage of revenue. I think with all of the automation and cost savings and efficiencies we drive throughout the enterprise, we need to be looking at IT as a margin contribution vehicle. And when we change that conversation, and start measuring ourselves in terms of margin, I think it changes the whole investment thesis, in IT. >> So that's interesting. Are you measured on margin contribution? >> We're doing that right now. I don't, if an IT organization is waiting for the CFO or CEO to ask them about their margin contribution, they're playing defense. I think IT needs to proactively measure all of it's contributions and express it in terms of margin. 'Cause that's the language the CEO, and COO, and CFO are talking about, so meet them in a language that they understand better. >> So how do you do, I mean, you certainly can create some kind of conceptual value flow. IT supports this sort of business process and this business process drives this amount of revenue or margin. >> So I stay away from revenue, because I think any time IT stands up and says, we're driving revenue, it's really hard. Because there's so many external and internal factors that contribute to that. So we more focus on automation, in terms of hours saved, expressing and dollarizing that. Hard dollars, that we're able to take out of the organization and then bubbling that into an operating margin number. >> Okay, so you sort of use the income statement below the revenue line to guide you and then you fit into that framework. >> Absolutely. >> When you talk to other CIOs about this, do they say, hey, that sounds really interesting, how do I get started on that, or? >> I think it resonates really well, because, again, IT as percentage of revenue is an incredibly incomplete metric to measure our contribution. With everything going digital, you want to pour more money into technology. I mean, studies have shown, and Andrew McAfee talked about this, over the last 50, 100 years, the companies that have thrived have poured more, disproportionally more, into technology and innovation than their competitors. So, if we only measure the cost side of the equation we're doing ourselves a disservice. >> And so, how do you get started on this path, I mean, let's call this path, sort of, what we generally defined as lightspeed, measured on margin, how do you get started on that? >> First step is the hardest. But, it's declaring that your going to do it. So we've come up with a framework, you know, that maps at a process level, at a department level, and at a company level, where are we on this journey to lightspeed? If lightspeed is the finish line, where are we? And I define three stages, manual, automated, cloud, before you get to lightspeed. And then, using those same three dimensions of velocity, intelligence, and experience, to tell you where you are. And, the very first thing we did was baseline all of our business processes, every single one, and mapped it. But once you have it mapped on that framework then you can say, how do we advance the ball to the next level? And, it's not going to magically happen overnight. This is hard work. It's going to happen one process at a time, right? But pretty soon everything starts to get faster and I think things will start to really accelerate. >> When you think about, sort of, architecting IT, at ServiceNow versus some other company, I mean, you come into ServiceNow as the CIO, everything runs on ServiceNow, that is part of the mandate, right? But that's not the mandate at every company, now increasingly may be coming that way in a lot of companies, but how is your experience at ServiceNow differ from the some of the traditional G2000? >> Probably the unique part about being the CIO at ServiceNow is actually really fun, in that I get to be customer zero in that I implement our products before all of our customers. You know, get to sit down with the product managers, discuss real business problems that all of our customers are facing, and hopefully be their voice inside the four walls of service now, and be the strategic partner to the product organization. Now implementing everything, our goal is to be the best possible implementation of ServiceNow on the planet. And that's not just demonstrated by go lives, it's demonstrated by, again, the economic and business outcomes we're deriving from using the platform. So, that part is fun, challenging, and hard work all at the same time. >> So how's Jakarta lookin'? >> Fantastic. We're super excited about everything that's coming out, whether it's the communities on customer service, or our software asset management. That's been a pain, right, for IT organizations for a long time, which is these inbound software audits, from other companies, and you're responding to them and it's a fire drill. In my mind, our software asset management transforms software audits from a once a year, twice a year event, to always-on monitoring, where you're just fixing it the whole time. And it's not an event anymore. I mean, the intelligence that we're baking into the platform now, super exciting around the machine learning and the predictive analytics concepts, we have more analytics than we had before, I mean there's just so much in there, that's just exciting. We're already using it, I can't wait for our customers to get a hold of it. >> Well, CJ this morning threw out a number of 30-plus percent performance improvement. I had said to myself, your saying that with conviction, that's 'cause you guys got to be running it yourselves. >> Yeah, we are. >> What are you seeing there? >> That's not a trivial number, and I think the product teams have done a great job really digging in and makin' sure our platform operates at lightspeed. >> One of the things that Jeff and I have been talking about this week, and really this is your passion here, is adoption, how do you get people to stop using all these other tools like email, and kind of get them to use the system? >> I think, showing them the promise of what it can bring. I think it's different conversations at different levels. I think, too, an operator, someone who's using the email to manage their work, they're hungry for a different solution. Life, working, and email, and managing your business that way, it's hard, right? To a mid-level manager, I think the conversation is maybe about the experience, how consumers of their service will be happier and more satisfied. At executive level, it gets maybe more into some of the economic outcomes, of doing it. Because implementing our platform, you know, you're going to burn some calories doing it, not a lot. Our time to value is really really quick, but still, it's a project and it's initiative and it's got to have an outcome tied to it. >> You know, Chris, as you're saying that it's always tough to be stuck kind of half way. You know, you're kind of on the tool internally and it's great. >> We don't use the word tool. >> Excuse me, not the tool. The app, the platform, actually. But then you still got external people that are coming at you through text, email, et cetera. I mean, is part of the vision, and maybe it's already there, I'm not as familiar with the parts I should be, in terms of enabling kind of that next layer of engagement with that next layer of people outside the four walls, to get more of them in it as well. Because the half-pregnant stage is almost more difficult because you're going back and forth between the two. >> And our customer service product does a lot of that. If you look at what Abhijit showed today, which is fantastic, Communities is another modality to start to interact with people. Certainly, we have Connect, part of our platform, is a collaboration app within the overall platform, so you can chat, just like you would with any consumer app, in terms of chatting capabilities, and that mobile first experience. We're thinking about other modalities too. Should you be able to talk to ServiceNow, just like you talk to Alexa, and converse with ServiceNow, Farrell touched on this a little bit, through natural language, right? We all know it's coming, and it's there, it's just pushing in that direction. >> How about the security piece? You know, Shawn shared this morning, you guys are well over year in now, and he talked about that infamous number of 200 plus days-- >> Chris: Nine months, yeah. >> Yeah, compressing that. Are you seeing that internally in your own? >> We are. We use Shawn's product, we're a happy customer. The vulnerability management, the security incident response, and very very similar results. And just like the customer who was on stage said, go live in Iterate, and that's exactly what we did. Everyone has a vulnerability management tool, like a Qualys, that's feeding in. Bring in all those Qualys alerts, our platform will help you normalize them and just start to reduce the level of chaos for the SOC and IT operations. Then make it better, then drive the automation, so we're seeing very similar benefits. >> How do you manage the upgrade side, we've been asking a lot of customers this week in the upgrade cycle. Some say, ah, I'll do in minus one just to sort of let the thing bake a little bit. You guys are in plus one. How do you manage that in production, though? >> Sure, so we upgrade before our customers, and that's part of our job, right? To make sure we test it out before our customers. But I'll say something in general about enterprise software upgrades, which is, there is a cost to them and the cost is associated with business risk. You want to make sure you're not going to disrupt your business. There is some level of regression testing you just have to do. Now, strategies I think that would be wise are automating as much of that testing as you can, through a testing framework, which we're helping our customers do now. And I think with some legacy platforms, that was incredibly expensive and hard and you could never quite get there. Us being a modern cloud platform, you can actually get there pretty quickly to the point where the 80, 90% of your regression testing is automated and you're doing that last 10 to 20%. 'Cause at the end of the day, IT needs to make sure the enterprise is up and running, that's job number one. But that's a strategy we employ to make upgrades as painless as possible. >> That's got to be compelling to a lot of the customers that you talk to, that notion of being able to automate the upgrade process. >> For sure, it is. >> You're eliminating a lot of time and they count that as money. >> It is money, and automating regression testing, it's a decision and a strategy but the investment pays off very very quickly. >> Dave: So there's an upfront chunk that you have to do to figure out how to make that work? >> Just like anything worth doing. >> Dave: Yeah, right. >> Right? >> Excellent. What's left for you at the show? >> What's left for me? I love interacting with customers. I got to talk with a lot of CIOs at CIO Decisions. I actually enjoy walking through the partner pavilion and meeting a lot of our partners and seeing some of the innovation that their driving on the platform. And then just non-stop, I get ideas all day from meeting with customers. It's so fun. >> Dave: Chris, thanks very much for coming to theCube. >> Thank you. >> We appreciate seeing you again. >> Chris: Good seeing you. >> Alright, keep it right there everybody. Jeff and I will be back with our next guest. This is theCube, we're live from Knowledge17. We'll be right back.

>> Announcer: Live from Boston, Massachusetts, it's theCUBE, covering Red Hat Summit 2017, brought to you by Red Hat. >> In 1993, two years before the height of Microsoft's dominance and amidst a sea of Unix competitors, Red Hat was founded. The company baked over the course of about 20 years and became a dominant open source company and is leading the trend towards cloud and hybrid cloud and containers. Welcome to Boston, everybody. Welcome to Red Hat Summit. This is theCUBE, the worldwide leader in live tech coverage. I'm here with Stu Miniman and Rebecca Knight, my co-hosts for the week, folks. Great to see you guys. Stu, this is your hundredth Red Hat Summit. >> Stu: It's only my fourth because it's the fourth of theCUBE, 13th year of the show itself, Dave, but great to be back here in Boston, you know, our home stadium for Rebecca, you, and me. Glad to have, a little gloomy today, but it's supposed to be nice weather by the time they take 4,000 of the 6,000 attendees here to Fenway on Wednesday, it's supposed to be some nice weather. Beautiful in New England, Red Hat Summit this week, OpenStack Summit next week, so great to be in the hub. >> Dave: And Rebecca, I felt like, well, first of all, great to be working with you. First time for us together. I thought the open was right in your wheelhouse. They opened with a video and the theme was can machines think. What did you make of that? >> So, what really strikes me about this conference is that it's about the technology, it's about the new, the digital transformation that Red Hat is helping facilitate all these companies making, but it's also about really reimagining the workplace of the future. The theme this year is about the individual and powering the individual. So much of what we're going to hear is about how do we engage developers to, to make this digital transformation for these companies? How do we give them the tools they need, not only just the technology, but also the change in mindset and the change in behaviors that they need, to collaborate with others, not only within their own teams, but within different parts of the organization to make these changes? >> So Red Hat's been on a tier, for anybody who follows the company, they do about 2.4 billion dollars a year in revenue, but more importantly, 3 billion dollars in bookings. Unlike many companies who are doing a shift from legacy, you know, trying to keep alive their old business and bring up the new business, Red Hat has a number of tailwinds and one of those is subscription business. Take a company like Oracle for instance, or IBM, that's shifting from a model of upfront, perpetual license into a subscription model. Red Hat, Stu, has always been there and you're seeing it in the numbers, a billion dollars plus on the balance sheet, just really great momentum. The stock price is up. What's your take on all of it? >> Dave, we've watched so many companies in technologies, where you have this huge wave of hype and then how does revenue go? Does it follow, does it peak, and then does it crash? Linux is one of those kind of slow-burn growths. I mean, I remember back, I started working with Red Hat back in 2000, and when I talked to enterprises back then, it was like, "Hey, are you using Linux?" They were like, "No." And they were like, "Wait, Bob in the back corner, "he's been using Linux stuff, "and he's doing some cool stuff." I watched over the next, you know, five to 10 years. It was a slow growth. It just kind of permeated every corner of what we did. I've mentioned, when we do this show, it's like, you know, Red Hat, a 15 billion dollar market cap or whatever, but we wouldn't have Google if it wasn't for the Linux adoption in the world today. So much of the Internet is based on that. You commented during the keynote, Dave, you look at the developer wave, the cloud wave, containers, you know, the shifting to kind of a subscription model rather than kind of the capping. All of those are things that kind of help lift Red Hat. It's where they're growing. It's why they've had 60 consecutive quarters of revenue growth. Now, it's not the 50% revenue growth like some of the cloud guys today or not explosive, but steady, solid, they're customers love them, great excitement here, great geek show, lots of hoodies and backpacks at the show here and exciting to watch. We've got lots of new technologies and announcements and things to dig into the next three days. >> It's interesting, you know, Rebecca, Stu and I had the pleasure of-- We were handing out with some big MIT brains last year in London talking about the second Machine Age and how humans have always replaced machines or machines have always replaced humans. Now, it's in the cognitive world. You see, again, the theme of this morning, a lot of it was AI related. Of course, the controversy there is that as machines replace humans, it hollows out the core of the middle class, the middle working class. But, the reality is that everything is getting digitized and those types of skills are going to be fundamental for growth in personal vocations, the economy. What do you think? >> I agree completely. I think that really the future is going to be humans and machines working side by side together. Last year, Jim Whitehurst was up here at Red Hat talking about how so much of what we still need to see from human workers is creativity, is judgment, is thought, is insight. Right now, machines still aren't quite there yet. The question is teaching machines to think and really having these two beings working together, collaborating together, and that really is where we're seeing things change. >> We talk all the time on theCUBE about companies are essentially, all companies are becoming software companies. Marc Andreessen said software's leading the world. Marc Benioff said they'll be more SAS companies coming from non-tech firms than tech firms. Behind all that, Stu, we heard a bunch of sort of geeky technologies today, but what are the things that are powering Red Hat's momentum? We talked about hybrid cloud, open source, containers. Help us unpack all that stuff. >> Yeah, so first of all, right, what is that next kind of billion dollar opportunity? One of the main pieces for Red Hat is OpenShift. Now, when we first started covering this show, it was like, ah, we know about infrastructures as a service and software as a service, but maybe platform as a service is where it's going. That's kind of where OpenShift was. Today, Paths, we said it a year or two ago, Paths is kind of passe, where OpenShift is a solution that creates a platform, that allows Red Hat to deliver newer technologies as a service. Containers and Kubernetes, I didn't hear Kubernetes mentioned in the keynote, but Red Hat is the largest enterprise contributor. It's basically Google, a bunch of independent people, and then Red Hat is a major contributor to Kubernetes, helping to drive that adoption, that whole next generation application development is where Red Hat is key, that migration to microservices. As we see that transition, it was interesting to see kind of the application discussion. It was how can we take, how can we help you build those new apps, but then how do we take our existing apps? At the Google show, at this show, and some other shows, it's been kind of the lift if shift movement, it's kind of cool again and not cool because we're doing, it's helping to take those legacy applications, move them into a more modern era and that's where OpenShift, there was like the announcement of the OpenShift.io, all the tools they have from Ansible and Jboss, all of these open source projects that Red Hat is very much a core part of that are going to help drive that next wave and help drive them-- There was an announcement, it was mentioned briefly today. I know they're going to talk more about it tomorrow, but the press release went out about a deeper partnership with Amazon Web Services. I think this is likely going to be the number one thing we talk about leaving the show, which is deeper partnership to say my application can live in AWS on OpenShift or can live in my data center on premises and still using AWS services with OpenShift. That whole hybrid or multicloud story that we built out, Red Hat's trying to make a good place why they should be there and extend for AWS because we know that that's the place that they need to compete against Microsoft with all their entire Azure play, Vmware trying to play that, so multifaceted, really interesting dynamic from a competitive standpoint. The opportunity would be billions of dollars opportunity for a company like Red Hat. >> Great, alright, we've got to wrap, but we will be covering those announcements and others. That AWS announcement knocks down all the major clouds now: Azure, Google, AWS, IBM. I guess Oracle's left., but in China. >> Stu: Support Oracle in application, but, you know. >> In terms of clouds. Alright, so keep it right there everybody. We'll be back. Wall-to-wall coverage here from Boston at the Red Hat Summit. This is theCUBE. We'll be right back.

>> Narrator: Live from New York, it's The Cube covering the IBM Machine Learning Launch Event brought to you by IBM. Here are your hosts, Dave Vellante and Stu Miniman. >> Good morning everybody, welcome to the Waldorf Astoria. Stu Miniman and I are here in New York City, the Big Apple, for IBM's Machine Learning Event #IBMML. We're fresh off Spark Summit, Stu, where we had The Cube, this by the way is The Cube, the worldwide leader in live tech coverage. We were at Spark Summit last week, George Gilbert and I, watching the evolution of so-called big data. Let me frame, Stu, where we're at and bring you into the conversation. The early days of big data were all about offloading the data warehouse and reducing the cost of the data warehouse. I often joke that the ROI of big data is reduction on investment, right? There's these big, expensive data warehouses. It was quite successful in that regard. What then happened is we started to throw all this data into the data warehouse. People would joke it became a data swamp, and you had a lot of tooling to try to clean the data warehouse and a lot of transforming and loading and the ETL vendors started to participate there in a bigger way. Then you saw the extension of these data pipelines to try to more with that data. The Cloud guys have now entered in a big way. We're now entering the Cognitive Era, as IBM likes to refer to it. Others talk about AI and machine learning and deep learning, and that's really the big topic here today. What we can tell you, that the news goes out at 9:00am this morning, and it was well known that IBM's bringing machine learning to its mainframe, z mainframe. Two years ago, Stu, IBM announced the z13, which was really designed to bring analytic and transaction processing together on a single platform. Clearly IBM is extending the useful life of the mainframe by bringing things like Spark, certainly what it did with Linux and now machine learning into z. I want to talk about Cloud, the importance of Cloud, and how that has really taken over the world of big data. Virtually every customer you talk to now is doing work on the Cloud. It's interesting to see now IBM unlocking its transaction base, its mission-critical data, to this machine learning world. What are you seeing around Cloud and big data? >> We've been digging into this big data space since before it was called big data. One of the early things that really got me interested and exciting about it is, from the infrastructure standpoint, storage has always been one of its costs that we had to have, and the massive amounts of data, the digital explosion we talked about, is keeping all that information or managing all that information was a huge challenge. Big data was really that bit flip. How do we take all that information and make it an opportunity? How do we get new revenue streams? Dave, IBM has been at the center of this and looking at the higher-level pieces of not just storing data, but leveraging it. Obviously huge in analytics, lots of focus on everything from Hadoop and Spark and newer technologies, but digging in to how they can leverage up the stack, which is where IBM has done a lot of acquisitions in that space and leveraging that and wants to make sure that they have a strong position both in Cloud, which was renamed. The soft layer is now IBM Bluemix with a lot of services including a machine learning service that leverages the Watson technology and of course OnPrem they've got the z and the power solutions that you and I have covered for many years at the IBM Med show. >> Machine learning obviously heavily leverages models. We've seen in the early days of the data, the data scientists would build models and machine learning allows those models to be perfected over time. So there's this continuous process. We're familiar with the world of Batch and then some mini computer brought in the world of interactive, so we're familiar with those types of workloads. Now we're talking about a new emergent workload which is continuous. Continuous apps where you're streaming data in, what Spark is all about. The models that data scientists are building can constantly be improved. The key is automation, right? Being able to automate that whole process, and being able to collaborate between the data scientist, the data quality engineers, even the application developers that's something that IBM really tried to address in its last big announcement in this area of which was in October of last year the Watson data platform, what they called at the time the DataWorks. So really trying to bring together those different personas in a way that they can collaborate together and improve models on a continuous basis. The use cases that you often hear in big data and certainly initially in machine learning are things like fraud detection. Obviously ad serving has been a big data application for quite some time. In financial services, identifying good targets, identifying risk. What I'm seeing, Stu, is that the phase that we're in now of this so-called big data and analytics world, and now bringing in machine learning and deep learning, is to really improve on some of those use cases. For example, fraud's gotten much, much better. Ten years ago, let's say, it took many, many months, if you ever detected fraud. Now you get it in seconds, or sometimes minutes, but you also get a lot of false positives. Oops, sorry, the transaction didn't go through. Did you do this transaction? Yes, I did. Oh, sorry, you're going to have to redo it because it didn't go through. It's very frustrating for a lot of users. That will get better and better and better. We've all experienced retargeting from ads, and we know how crappy they are. That will continue to get better. The big question that people have and it goes back to Jeff Hammerbacher, the best minds of my generation are trying to get people to click on ads. When will we see big data really start to affect our lives in different ways like patient outcomes? We're going to hear some of that today from folks in health care and pharma. Again, these are the things that people are waiting for. The other piece is, of course, IT. What you're seeing, in terms of IT, in the whole data flow? >> Yes, a big question we have, Dave, is where's the data? And therefore, where does it make sense to be able to do that processing? In big data we talked about you've got masses amounts of data, can we move the processing to that data? With IT, the day before, your RCTO talked that there's going to be massive amounts of data at the edge and I don't have the time or the bandwidth or the need necessarily to pull that back to some kind of central repository. I want to be able to work on it there. Therefore there's going to be a lot of data worked at the edge. Peter Levine did a whole video talking about how, "Oh, Public Cloud is dead, it's all going to the edge." A little bit hyperbolic to the statement we understand that there's plenty use cases for both Public Cloud and for the edge. In fact we see Google big pushing machine learning TensorFlow, it's got one of those machine learning frameworks out there that we expect a lot of people to be working on. Amazon is putting effort into the MXNet framework, which is once again an open-source effort. One of the things I'm looking at the space, and I think IBM can provide some leadership here is to what frameworks are going to become popular across multiple scenarios? How many winners can there be for these frameworks? We already have multiple programming languages, multiple Clouds. How much of it is just API compatibility? How much of work there, and where are the repositories of data going to be, and where does it make sense to do that predictive analytics, that advanced processing? >> You bring up a good point. Last year, last October, at Big Data CIV, we had a special segment of data scientists with a data scientist panel. It was great. We had some rockstar data scientists on there like Dee Blanchfield and Joe Caserta, and a number of others. They echoed what you always hear when you talk to data scientists. "We spend 80% of our time messing with the data, "trying to clean the data, figuring out the data quality, "and precious little time on the models "and proving the models "and actually getting outcomes from those models." So things like Spark have simplified that whole process and unified a lot of the tooling around so-called big data. We're seeing Spark adoption increase. George Gilbert in our part one and part two last week in the big data forecast from Wikibon showed that we're still not on the steep part of the Se-curve, in terms of Spark adoption. Generically, we're talking about streaming as well included in that forecast, but it's forecasting that increasingly those applications are going to become more and more important. It brings you back to what IBM's trying to do is bring machine learning into this critical transaction data. Again, to me, it's an extension of the vision that they put forth two years ago, bringing analytic and transaction data together, actually processing within that Private Cloud complex, which is what essentially this mainframe is, it's the original Private Cloud, right? You were saying off-camera, it's the original converged infrastructure. It's the original Private Cloud. >> The mainframe's still here, lots of Linux on it. We've covered for many years, you want your cool Linux docker, containerized, machine learning stuff, I can do that on the Zn-series. >> You want Python and Spark and Re and Papa Java, and all the popular programming languages. It makes sense. It's not like a huge growth platform, it's kind of flat, down, up in the product cycle but it's alive and well and a lot of companies run their businesses obviously on the Zn. We're going to be unpacking that all day. Some of the questions we have is, what about Cloud? Where does it fit? What about Hybrid Cloud? What are the specifics of this announcement? Where does it fit? Will it be extended? Where does it come from? How does it relate to other products within the IBM portfolio? And very importantly, how are customers going to be applying these capabilities to create business value? That's something that we'll be looking at with a number of the folks on today. >> Dave, another thing, it reminds me of two years ago you and I did an event with the MIT Sloan school on The Second Machine Age with Andy McAfee and Erik Brynjolfsson talking about as machines can help with some of these analytics, some of this advanced technology, what happens to the people? Talk about health care, it's doctors plus machines most of the time. As these two professors say, it's racing with the machines. What is the impact on people? What's the impact on jobs? And productivity going forward, really interesting hot space. They talk about everything from autonomous vehicles, advanced health care and the like. This is right at the core of where the next generation of the economy and jobs are going to go. >> It's a great point, and no doubt that's going to come up today and some of our segments will explore that. Keep it right there, everybody. We'll be here all day covering this announcement, talking to practitioners, talking to IBM executives and thought leaders and sharing some of the major trends that are going on in machine learning, the specifics of this announcement. Keep it right there, everybody. This is The Cube. We're live from the Waldorf Astoria. We'll be right back.

>> Presenter: Live from the Wynn Resort in Las Vegas, it's theCUBE, covering .NEXT Conference 2016. Brought to you by Nutanix. Now here are your hosts, Dave Vellante and Stu Miniman. >> Welcome back to Las Vegas everybody. Mark Templeton is here, industry legend, former CEO of Citrix. Mark, really a pleasure having you on. >> Thanks, thanks, really great to be here. >> So what are you doing these days? (laughter) >> Enjoying retirement, right, way more than I thought. But earlier today at the Nutanix NEXT Conference, Mark Leslie, the legend, icon, talked about the Ark of Life. And he had this one slide that said, "There is no finish line." And I think anyone who is blessed to have worked their career around their passion, he just captured it all in that one slide. And so there's no finish line, it's just sort of continuing the journey with maybe some new friends and colleagues. >> Right, no hammock, no umbrella drinks. >> Oh plenty of drinks-- >> But it doesn't end there. >> No, plenty of drinks as always but no hammock. >> So we heard your keynote yesterday, which is outstanding. You're spending a lot of time thinking about the future. >> Yes. >> So you've got time to do that now, what are you seeing? What's in the binoculars of Mark Templeton. >> Well, a big thing for me is people and how generations of people actually influence changes in our environment and how they drive different ages in the sense of descriptions of time. So I think for me, I was born analog, I'm a boomer, and boomers generally, born analog, but I fell in love with digital and made it my career. My children are XY geners. They were born digital mainly because of my career, but many in their generation we're actually born analog but learned digital pretty quickly. Now Millennials, they're born digital and they're not interested in how things work from a computing perspective. They want to know what can it do. And so the question is now what's next? And as I sort of talked to a lot of Millennials, talked to a lot of companies that are out there with ideas, I've concluded that we're actually at the end of the digital age because we're on digital overload. There are too many devices, there are too many apps, too much data, too many social connections. I mean, no one can handle and manage it all and the only way we can keep going in terms of leveraging technology to the benefit of humankind is for it to become invisible. And the way it becomes invisible is to take what we've accepted as analog for a long, long time, human emotion, relationships, location of people, intersections amongst people, et cetera, and start creating context out of that through digital mechanisms. So I think this next, where things are going, is away from digital, toward contextual. And it's through contextual that we can actually have a greater experience with technology underneath. And yeah, tremendous opportunities for invention, innovation, et cetera. You asked the question yesterday to the audience, who can program an assembler. I put my hand up. I don't know if I still could, but I certainly have. But your point was that everybody who's programming today is programming an assembler, it's just invisible. >> It's invisible, that's right. Every layer of extraction makes the layers below invisible. And that's one of the things I love about Nutanix because they're making cloud infrastructure, hypervisors, kind of all this componentry, invisible, allowing the focus on a common set of services that are exposed. And for a whole set of people, that's great, right? And that means you can move on to the higher layers of the stack. Same thing goes for contextuality. Contextuality will create layers of abstraction that when you enter the room, the right things happen. You don't have to think about oh, I'm using Lutron switches or I've got a nest going on here, did it move from away to home? All of that, it becomes invisible and goes away. It's just early in the cycle of getting there. >> Yeah, so what do you see that having an impact on the jobs that people are having? You talked about moving up the stack. Even in IT here and for Nutanix, it's oh wow, this is what my job's been for years and now I don't need to do that, I'm retraining, moving up the stack, those challenges. >> Well, I think history shows that every generation where there's a layer of abstraction that has lots of staying power, what it does is it takes a bunch of people and it says okay, you stay below that stack if you're a specialist and you stay deep on it. I mean, let's face it, you put Nutanix technology in place, you have to have deep specialists under that. It's just that the DevOps people don't have to know anything about how it works underneath. The business units don't have to know anything about that, and so they can take all of that stuff that's cluttering their time and mind and focus on the missions that are important to them. So it creates layers of specialization along the way, and then it pushes generalists up, up, up. And look, I mean I think the Nutanix team I think adequately talked about the notion of what do we do when we get time back, whether we're admins or whether we're CIOs or whether we're CEOs or whether we're just individuals? And I think that's where humankind seems to not have a problem in consuming that extra time, whether it's recreational or maybe more return to some of the basic values of families and relationships, or new levels of innovation and invention. I think there are a lot of things that get done with that extra time. >> If I infer from your talk yesterday, you don't like the term consumerization of IT. You used a different term. >> Yeah, I actually... Jeff with Slack made that point around consumerization of IT, and he said really, it's about humanization of IT. I think these terms serve purposes along the way, and I think that we're still in the process of consumerizing IT. It's just that the purpose of the consumerization is to humanize it. And the consumerization basically is making things, making the IT experience much more retail, right? Where people get choice, where they get self service, and IT organizations actually describe themselves in a way where they're merchandising services that benefit the business. So I don't dislike consumerization as much as I really like the idea of moving the idea forward to humanization, because that's the outcome you're looking for. >> So square or circle for me because you said something that surprised me, the end of the digital age, right? And you defended that position, but I want to ask you about something like autonomous vehicles. I was talking to my teenage daughters the other day, and one of them made the point that turning 16 is a symbol of freedom. And one of the pieces of that freedom is you get to drive a car. And so I thought you were going to say this is just the beginning of the digital age. What do you make of that in terms of the impact on society and its humanization aspect? >> Well, so the end of the digital age includes it's the end of the visibility of digital, because it's just peaked out. And so digital and technologies around digital, you're just becoming more and more and more invisible as machines do more work that humans used to do. I mean, here's a question. Why is it so hard for older people to adopt new technologies? If they're so simple and they're so great, why do they have a hard time adopting? >> Dave: Because they're complicated. >> They're complicated, right? When you're doing it over and over, you don't realize how much knowledge you're applying to something that's so simple, all right? So all I'm saying is that the test will be when a generation that's behind us can actually consume it in pretty ubiquitous ways. And so it's the boomerang kind of effect, all right? >> So Stu, you were talking a little bit about the work that we did with the guys at MIT and Brynjolfsson and McAfee of The Second Machine Age. So do you think much about, I'm sure you do, about the impact of machines? Machines have always replaced humans. They seem to be now doing it at a cognitive level. What are your thoughts and the state of education in this country in particular? >> Well, I mean there are two ways to answer that, half-full, half-empty. I'm an optimist, and I think that these kinds of things I'm talking about actually will serve to make education more personalized by individual. When I look at the things like Khan Academy, right, and the impact the Khan Academy has made in public school systems, and you squint at it so that you only see the shapes and forms, here's what it's done. It's allowed the teachers to focus on the students by exception and where they need help as opposed to mass kind of education, an entire classroom. That's been one of the big effects of Sal Kahn's work. So I'm optimistic about machines, contextuality, and the intersection of all of that when it comes to education. Because I think the more context a teacher has around a student, what's going on at home, what's happening in other classes, extracurricular activities or lack thereof gives them a better ability to actually teach them, and gives them a better ability to learn if the systems are set up to make that connection. >> And we're optimists too. I mean, I think the observation is that the industry has marched to the cadence of Moore's Law for decades, and that's what's driven innovation. And it's not driving innovation anymore, it's the combination of technologies. We think that creativity, teaching, I don't know if you could teach creativity, I guess you can-- >> Yes you can. >> Why can't you, right? That seems to be the new frontier of education, in our view anyways. That make sense to you? >> It makes total sense. By the way, you travel the world and you characterize various educational methodologies and priorities around the world. I mean, a lot of people throw rocks at the educational system in the U.S. It's actually a system that promotes creativity more than any other educational system in the world, okay? You go to certain countries in Asia and they promote knowledge and knowing facts and being able to state facts and correlate fact, all right? And there's nothing fundamentally wrong with that, it's just that you're not driving a creative sort of process, you aren't teaching creativity. So yes, I'm optimistic about where we're headed in the sense of how this age of contextuality can actually propel us forward as a nation around education. >> And that's, Stu, why I hear so much criticism about teaching the test. You got little young kids and you hear a lot of that backlash. >> Yeah, yeah absolutely. Mark, I want to go back. You talked a lot about kind of generations and journeys. When we look in the IT space, the pace of change is just faster than ever. What advice do you give to, how do you get, by now, by the time you're relevant, you're almost irrelevant soon after. So how do you plan for that? >> So first of all, I think you always have to start with an opinion about the future that you believe in so strongly that you're willing to make bets, okay? And some of the bets, there are low-risk bets, there are high-risk bets. Mark Leslie talked about transformation, et cetera, today, and that's really about having an opinion about the future and making a bet. And he gave some great case studies. But if you look at those case studies, you ask the CEOs, the leaders there, they didn't think they were high risk because they thought the greater risk was not betting, right? And it's because of their opinion of the future. So I think you have to start there. Too many, my observation, opinion, is too many people read too many books, too much of the net and form their opinions based upon what they read as opposed to forming an opinion on their own through some amount of introspection and experience, okay? And I think that, I'll give you an example. I remember, it was probably 1999. I was newly CEO of Citrix and I had a whole faction of our dev team saying, Mark it's all about WAP. (host chuckles) I was like, what do you mean it's all about WAP? It's like, it's all about WAP. I said, what's WAP? Well, it's the wireless, I can't remember what it stood for, something protocol. Access protocol. (crosstalk) So okay, I said fine, all right. Let's meet on that like next week. Okay, fine. So over the weekend, I go somewhere and I bought a WAP phone, a Nokia WAP phone that supported WAP. So I get on there over the weekend and blah, blah, blah, blah, blah, fine. I go to the meeting next week, sit down, and the whole team comes, it's all about WAP, here's why. I said okay, let me start with a question. Can everyone showed me their WAP phones? No one had one. And I pulled mine out and I said hey, let me give you a demo. So yeah, you form an opinion about something and then you can, and so I said we're not spending one nickel on WAP, right? Right. So I think that's the number one advice I would give. Because then when you have a belief and an opinion about the future, you feel they're low risk for the right reasons. >> I want to ask you as a CEO, a former CEO of a public company, you heard Mark Leslie talk about, today, the short-term focus. A lot of people talk about that. Ever since I've been in the business, people talk about, particularly US companies, short-term focus, Wall Street, now you're seeing activist investors. Maybe it's gone to a new level. I presume you agree, but it's worked. United States is dominant, and they've always had the short-term focus. Have we gone beyond a point though of rationality? >> Well, I think this is a semantical problem. So I think I probably don't agree with Mark, all right? And along the way, when people said public CEO, go with the PE guys, do that. Well, why would I do that? Well, because you don't have the short-term focus like the quarterly thing. I was like, are you kidding me? (host chuckles) You don't know PE guys, first of all. Secondly, I disagree because you're measured as a public company against the expectations that you set. So if you set the wrong expectations and miss them, then you're in trouble. If you set the right expectations, whether those expectations are financial, strategic, operational, and you exceed them, there's no problem with it. And our system is successful because there's a quarterly rhythm to measuring the path of companies that are public. And so there's no law out there that says every time you measure, it has to be something prescribed. It is prescribed, it's prescribed by the CEO and board-- >> Dave: And the expectations that get set. >> And the expectations that get set. So I was CEO of Citrix for many, many years. And when I retired, it was my 70th earnings report, all right? And I figured, I figured 70 years in jail is enough. I applied for parole a few times and it was denied. But seriously, the idea of a quarterly report against the expectations you set is not a bad thing. >> Yeah, Michael Dell talks about the 90-day shot clock, but I bet you he has a 90-day shot clock internally. >> Sure. I mean, absolutely. >> I don't know if this is the case, but it seems to me that some of the companies that I observed today, that are successful, in particular, Nutanix, I would put service now in that category, Tableau, Splunk, they seem to be highly transparent, maybe more transparent than I'm used to. Maybe I just wasn't paying attention before. Have you observed that? Do you think it's just a function of their success and their size, allows them to be more transparent than-- >> I think that... I think that's a big change that's taken place. So more newly public companies like Splunk, for example, have to be more transparent around the core metrics they use to measure success. So if you look at some of the, like Adobe, hugely successful transformation story. They did it through obviously the right strategic mechanisms to move to a different business model, but they had to create a level of transparency to get there in order to successfully make that transformation. Companies like Splunk started there, all right? And so that is the standard for a more of a subscription cloud-based SAS-oriented type business model. And investors reward that, I think. And so therefore, it's confirms, it's like positive strokes to transparency, which I'm all for. >> I wish we had more time to talk about things like culture. There's so many different different topics, but we'll leave it at what's next for you, what are you spending your time on, any fun projects that you're working on? >> Yeah, I'm spending all my time on technologies that increase contextuality. So for example, one of them is a web psychographics company. So when you surf the web now, their web analytics really does more demographical kinds of things, right? But the science of psychographics actually takes a lot of that and actually figures out what's the why, your behavior, what's in your head. So I think that's a context that's important to add, again, to make the technology more invisible. Spending time on autonomic security, security that actually not only dynamically sees attacks and discontinuities, it fixes them and then tells you later, okay? Spending time on something really exciting called human location analytics, which basically is technology that can passively track human motion, and very precisely, so that as people occupy various spaces and have paths and interactions, systems around it can respond. So like in a retail environment, maybe if you're spending a lot of time at an N cap, somebody will come and help you. And if you combine some of these things, the psychographics and the human location, you'll get the right kind of help and so forth. And that all becomes invisible and we just have a great experience. >> Combining innovations, right, taking advantage of this invisible digital matrix. >> Yeah. And the thing that I'm really psyched about, and most people that have known me for some time know that I have a particular weakness for things that have round rubber tires, okay? So deeply involved in a company, an e-bike company that is called Vintage Electric Bikes. It's an e-bike you love and you want to ride because of the joy that it gives you, all right? So yeah, so things that... Greater context, so technology can be invisible, and things that bring out emotional kinds of pleasure and joy. That's where I'm spending my time. By the way, it's fun, which is the first bar I have. Number two, great people, the second bar, all right? And then the third bar is I think they actually, these things are important for a better world and creating opportunity for people, et cetera. And I like doing that. >> Well, thanks for coming on theCUBE and delighting our audiences. It was really a pleasure having you. You look great, you sound great, congratulations. >> Mark: Thanks, thanks. Having a great time, thank you very much-- >> You're welcome. All right, keep it right there everybody. Stu and I will be back with our next guest. This is SiliconANGLE's theCUBE. We'll be right back. (upbeat electronic music)

>> live from the Congress Centre in London, England. It's the queue at M I t. And the digital economy. The second machine Age Brought to you by headlines sponsor M I T. >> Everybody, welcome to London. This is Dave along with student men. And this is the cube. The cube goes out, we go to the events. We extract the signal from the noise. We're very pleased to be in London, the scene of the first machine age. But we're here to talk about the second Machine age. Andrew McAfee and Erik Brynjolfsson. Gentlemen, first of all, congratulations on this fantastic book. It's been getting great acclaim. So it's a wonderful book if you haven't read it. Ah, Andrew, Maybe you could hold it up for our audience here, the second machine age >> and Dave to start off thanks to you for being able to pronounce both of our names correctly, that's just about unprecedented. In the history of this, >> I can probably even spell them. Whoa, Don't. So, anyway, welcome. We appreciate you guys coming on and appreciate the opportunity to talk about the book. So if you want to start with you, so why London? I mean, I talked about the first machine age. Why are we back here? One of the >> things we learned when we were writing the book is how big deal technological progress is on the way you learn that is by going back and looking at a lot of history and trying to understand what bet the curve of human history. If we look at how advanced our civilizations are, if we look at how many people there are in the world, if we look at GDP per capita around the world, amazingly enough, we have that data going back hundreds, sometimes thousands of years. And no matter what data you're looking at, you get the same story, which is that nothing happened until the Industrial Revolution. So for us, the start of the first machine machine age for us, it's a real thrill to come to London to come to the UK, which was the birthplace of the Industrial Revolution. The first machine age to talk about the second. >> So, Eric, I wonder if you could have with two sort of main vectors that you take away from the book won is that you know, machines have always replaced humans and maybe doing so at a different rate of these days. But the other is the potential of continued innovation, even though many people say Moore's law is dead. You guys have come up with sort of premises to how innovation will continue to double. So boil it down for the lay person. What should we think about? Well, sure. >> I mean, let me just elaborate on what you just said. Technology's always been destroying jobs, but it's also always been creating jobs, you know, A couple centuries ago, ninety percent of Americans worked in agriculture on farms in nineteen hundred is down to about forty one percent. Now is less than two percent. All those people didn't simply become unemployed. Instead, new industries were invented by Henry Ford, Steve Jobs, Bill Gates. Lots of other people and people got rather unemployed, became redeployed. One of the concerns is is, Are we doing that fast enough? This time around, we see a lot of bounty being created by technology. Global poverty rates are falling. Record wealth in the United States record GDP per person. But not everyone's participating in that. Not even when sharing the past ten fifteen years, we've actually to our surprise seem median income fall that's income of the person the fiftieth percentile, even though the overall pie is getting bigger. And one of the reasons that we created the initiative on the digital economy was to try to crack that, not understand what exactly is going on? How is technology behaving differently this time around in earlier eras and part that has to do with some of the unique characteristics of eventual goods? >> Well, your point in the book is that normally median income tracks productivity, and it's it's not this time around. Should we be concerned about that? >> I think we should be concerned about it. That's different than trying to stop for halt course of technology. That's absolutely not something you >> should >> be more concerned about. That way, Neto let >> technology move ahead. We need to let the innovation happen, and if we are concerned about some of the side effects or some of the consequences of that fine, let's deal with those. You bring up what I think is the one of most important side effects to have our eye on, which is exactly as you say when we look back for a long time, the average worker was taking home more pay, a higher standard of living decade after decade as their productivity improved. To the point that we started to think about that as an economic law, your compensation is your marginal productivity fantastic what we've noticed over the past couple of decades, and I don't think it's a coincidence that we've noticed this, as the computer age has accelerated, is that there's been a decoupling. The productivity continues to go up, but the wage that average income has stagnated. Dealing with that is one of our big challenges. >> So what you tell your students become a superstar? I mean, not everybody could become a superstar. Well, our students cats, you know, maybe the thing you know they're all aspired to write. >> A lot of people focus on the way that technology has helped superstars reach global audiences. You know, I had one student. He wrote an app, and about two or three weeks, he tells me, and within a few months he had reached a million people with that app. That's something that probably would have been impossible a couple of decades ago. But he was able to do that because he built it on top of the Facebook platform, which is on top of the Internet and a lot of other innovations that came before. So in some ways it's never been easier to become a superstar and to reach literally not just millions, but even billions of people. But that's not the only successful path in the second machine age. There's also other categories where machines just aren't very good. Yet one of the ones that comes to mind is interpersonal skills, whether that's coaching or underst picking up on other cues from people nurturing people carrying for people. And there are a whole set of professions around those categories as well. You don't have to have some superstar programmer to be successful in those categories, and there are millions of jobs that are needed in those categories for to take care of other P people. So I think there's gonna be a lot of ways to be successful in the second machine age, >> so I think >> that's really important because one take away that I don't like from people who've looked at our work is that only the amazing entrepreneurs or the people with one forty plus IQ's are going to be successful in the second machine age. That's it's just not correct. As Eric says, the ability to negotiate the ability Teo be empathetic to somebody, the ability to care for somebody machines they're lousy of thes. They remain really important things to do. They remain economically valuable things >> love concern that they won't remain louse. If I'm a you know, student listening, you said in your book, Self driving cars, You know, decade ago, even five years ago so it can happen. So how do we predict with computers Will and won't be good at We >> basically don't. Our track record in doing that is actually fairly lousy. The mantra that I've learned is that objects in the future are closer than they appear on the stuff that seem like complete SciFi. You're never goingto happen keeps on happening now. That said, I am still going to be blown away the first time I see a computer written novel that that that works, that that I find compelling, that that seems like a very human skill. But we are starting to see technologies that are good at recognizing human emotions that can compose music that can do art paintings that I find pretty compelling. So never say never is another. >> I mean right, right. If if I look some of the examples lately, you know, basic news computers could do that really well. IBM, you know, the lots of machine can make recipes that we would have never thought of. Very things would be creative. And Ian, the technology space, you know, you know, a decade ago computer science is where you tell everybody to go into today is data scientists still like a hot opportunity for people to go in And the technology space? Where, where is there some good opportunity? >> Or whether or not that's what the job title on the business card is that going to be hot being a numerous person being ableto work with large amounts of data input, particular being able to work with huge amounts of data in a digital environment in a computer that skills not going anywhere >> you could think of jobs in three categories is ready to technology. They're ones that air substitutes racing against machine. They're ones that air compliments that are using technology under ones that just aren't really affected yet by technology. The first category you definitely want to stay away from. You know, a lot of routine information processing work. Those were things machines could do well, >> prepare yourself as a job. Is that for a job as a payroll clerk? There's a really bad wait. >> See that those jobs were disappearing, both in terms of the numbers of employment and the wages that they get. The second category jobs. That compliment data scientist is a great example of that or somebody who's AP Writer or YouTube. Those are things that technology makes your skills more and more valuable. And there's this huge middle category. We talked earlier about interpersonal skills, a lot of physical task. Still, where machines just really can't touch them too much. Those are also categories that so far hell >> no, I didnt know it like middle >> school football, Coach is a job. It's going to be around a human job. It's going to be around for a long time to come because I have not seen the piece of technology that can inspire a group of twelve or thirteen year olds to go out there and play together as a team. Now Erik has actually been a middle school football coach, and he actually used a lot of technology to help him get good at that job, to the point where you are pretty successful. Middle school football coach >> way want a lot of teams games, and part of it was way could learn from technology. We were able to break down films in ways that people never could've previously at the middle school level. His technology's made a lot of things much cheaper. Now then we're available. >> So it was learning to be competitive versus learning how to teach kids to play football. Is that right? Or was a bit? Well, actually, >> one of the most important things and being a coach is that interpersonal connection is one thing I liked the most about it, and that's something I think no robot could do. What I think it be a long, long time. If ever that inspiring halftime speech could be given by a robot >> on getting Eric Gipper bring the Olsen Well, the to me, the more, most interesting examples I didn't realise this until I read your book, is that the best chess player in the world is not a computer, it's a computer and a human. That's what those to me. It seemed to be the greatest opportunities for innovative way. Call a >> racing with machines, and we want to emphasize that that's what people should be focusing. I think there's been a lot of attention on how machines can replace humans. But the bigger opportunities how humans and machines could work together to do things they could never have been done before in games like chess. We see that possibility. But even more, interestingly, is when they're making new discoveries in neuroscience or new kinds of business models like Uber and others, where we are seeing value creation in ways that was just not possible >> previously, and that chess example is going to spill over into the rest of the economy very, very quickly. I think about medicine and medical diagnosis. I believe that work needs to be a huge amount, more digital automated than it is today. I want Dr Watson as my primary care physician, but I do think that the real opportunities we're going to be to combine digital diagnosis, digital pattern recognition with the union skills and abilities of the human doctor. Let's bring those two skill sets together >> well, the Staton your book is. It would take a physician one hundred sixty hours a week to stay on top of reading, to stay on top of all the new That's publication. That's the >> estimate. And but there's no amount of time that watching could learn how to do that empathy that requires to communicate that and learn from a patient so that humans and machines have complementary skills. The machines are strong in some categories of humans and others, and that's why a team of humans and computers could be so >> That's the killer. Since >> the book came out, we found another great example related to automation and medicine in science. There's a really clever experiment that the IBM Watson team did with team out of Baylor. They fed the technology a couple hundred thousand papers related to one area of gene expression and proteins. And they said, Why don't you predict what the next molecules all we should look at to get this tart to get this desired response out on the computer said Okay, we think these nine are the next ones that are going to be good candidates. What they did that was so clever they only gave the computer papers that had been published through two thousand three. So then we have twelve years to see if those hypotheses turned out to be correct. Computer was batting about seven hundred, so people say, didn't that technology could never be creative. I think coming up with a a good scientific hypothesis is an example of creative work. Let's make that work a lot more digital as well. >> So, you know, I got a question from the crowd here. Thie First Industrial Revolution really helped build up a lot of the cities. The question is, with the speed and reach of the Internet and everything, is this really going to help distribute the population? Maur. What? The digital economy? I don't I don't think so. I don't think we want to come to cities, not just because it's the only waited to communicate with somebody we actually want to be >> face to face with them. We want to hang out with urbanization is a really, really powerful trend. Even as our technologies have gotten more powerful. I don't think that's going to revert, but I do think that if you if you want to get away from the city, at least for a period of time and go contemplate and be out in the world. You can now do that and not >> lose touch. You know, the social undistributed workforce isn't gonna drive that away. It's It's a real phenomenon, but it's not going to >> mean that cities were going >> to be popular. Well, the cities have two unique abilities. One is the entertainment. If you'd like to socialize with people in a face to face way most of the time, although people do it online as well, the other is that there's still a lot of types of communication that are best done in person. And, in fact, real estate value suggests that being able to be close toe other experts in your field. Whether it's in Silicon Valley, Hollywood, Wall Street is still a valuable asset. Eric and I >> travel a ton not always together. We could get a lot of our work done via email on via digital tools. When it comes time to actually get together and think about the next article or the next book, we need to be in the same room with the white bored doing it. Old school >> want to come back to the roots of innovation. Moore's law is Gordon Mohr put forth fiftieth anniversary next week, and it's it's It's coming to an end in terms of that actually has ended in terms of the way it's doubling every eighteen months, but looks like we still have some runway. But you know, experts can predict and you guys made it a point you book People always underestimate, you know, human's ability to do the things that people think they can't do. But the rial innovation is coming from this notion of combinatorial technologies. That's where we're going to see that continued exponential growth. What gives you confidence that that >> curve will continue? If you look at innovation as the work, not of coming up with some brand new Eureka, but as putting together existing building blocks in a new and powerful way, Then you should get really optimistic because the number of building blocks out there in the world is only going up with iPhones and sensors and banned weapon and all these different new tools and the ability to tap into more brains around the world to allow more people to try to do that recombination. That ability is only increasing as well. I'm massively optimistic about innovation, >> yet that's a fundamental break from the common attitude. We hear that we're using up all the low hanging fruit, that innovation. There's some fixed stock of it, and first we get the easy innovations, and then it gets harder and harder to innovate. We fundamentally disagree with that. You, in fact, every innovation we create creates more and more building blocks for additional innovations. And if you look historically, most of the breakthroughs have been achieved by combining previously existing innovations. So that makes me optimistic that we'LL have more and more of those building blocks going >> forward. People say that we've we've wrung all of the benefit out of the internal combustion engine, for example, and it's all just rounding error. For here. Know a completely autonomous car is not rounding error. That's the new thing that's going to change. Our lives is going to change our cities is going to change our supply chains, and it's making a new, entirely new use case out of that internal combustion. >> So you used the example of ways in the book, Really, you know, their software, obviously was involved, but it really was sensors and it was social media. And we're mobile phones and networks, just these combinations of technologies for innovation, >> none of which was an invention of the Ways team, none of which was original. Theyjust put those elements together in a really powerful way. >> So that's I mean, the value of ways isn't over. So we're just scratching the surface, and we could talk about sort of what you guys expect. Going forward. I know it's hard to predict well, another >> really important thing about wages in addition to the wake and combined and recombined existing components. It's available for free on my phone, and GPS would've cost hundreds of dollars a few years ago, and it wouldn't have been nearly as good at ways. And in a decade before that, it would have been infinitely expensive. You couldn't get it at any price, and this is a really important phenomenon. The digital economy that is underappreciated is that so much of what we get is now available at zero cost. Our GDP measures are all the goods and services they're bought and sold. If they have zero price, they show up is a zero in GDP. >> Wikipedia, right? Wikipedia, but that just wait here overvalue ways. Yeah, it doesn't. That >> doesn't mean zero value. It's still quite valuable to us. And more and more. I think our metrics are not capturing the real essence of the digital economy. One of the things we're doing at the Initiative initiative, the addition on the usual economy is to understand better what the right metrics will be for seeing this kind of growth. >> And I want to talk about that in the context of what you just said. The competitiveness. So if I get a piece of fruit disappears Smythe Digital economy, it's different. I wonder if you could explain that, >> and one of the ways it's different will use waze is an example here again, is network effects become really, really powerful? So ways gets more valuable to me? The more other ways er's there are out there in the world, they provide more traffic information that let me know where the potholes and the construction are. So network effects lead to really kind of different competitive dynamics. They tend to lead toward more winner, take all situations. They tend to lead toward things that look more not like monopolies, and that tends to freak some people out. I'm a little more home about that because one of the things we also know from observing the high tech industries is that today's near monopolist is yesterday's also ran. We just see that over and over because complacency and inertia are so deadly, there's always some some disruptor coming up, even in the high tech industries to make the incumbents nervous. >> Right? Open source. >> We'LL open source And that's a perfect example of how some of the characteristics of goods in the digital economy are fundamentally different from earlier eras and microeconomics. We talk about rival and excludable goods, and that's what you need for a competitive equilibrium. Digital goods, our non rival and non excludable. You go back to your micro economics textbook for more detail in that, but in essence, what it means is that these goods could be freely coffee at almost zero cost. Each copy is a perfect replica of the original that could be transmitted anywhere on the planet almost instantaneously, and that leads to a very different kind of economics that what we had for the previous few hundred years, >> or you don't work to quantify that. Does that sort of Yeah, wave wanted >> Find the effect on the economy more broadly. But there's also a very profound effects on business and the kind of business models that work. You know, you mentioned open source as an example. There are platform economics, Marshall Banal Stein. One of the experts in the field, is speaking here today about that. Maybe we get a chance to talk about it later. You can sometimes make a lot of money by giving stuff away for free and gaining from complimentary goods. These are things that >> way started. Yeah, Well, there you go. Well, that would be working for you could only do that for a little >> while. You'll like you're a drug dealer. You could do that for a little while. And then you get people addicted many. You start charging them a lot. There's a really different business model in the second machine age, which is just give stuff away for free. You can make enough off other ancillary streams like advertising to have a large, very, very successful business. >> Okay, I wonder if we could sort of, uh, two things I want first I want to talk about the constraints. What is the constraints to taking advantage of that? That innovation curve in the next day? >> Well, that's a great question, and less and less of the constraint is technological. More and more of the constraint is our ability as individuals to cope with change and said There's a race between technology and education, and an even more profound constraint is the ability of our organisations in our culture to adapt. We really see that it's a bottleneck. And at the MIT Sloan School, we're very much focused on trying to relieve those constraints. We've got some brilliant technologists that are inventing the future on the technology side, but we've got to keep up with our business. Models are economic systems, and that's not happening fast enough. >> So let's think about where the technology's aren't in. The constraints aren't and are. As Eric says, access to technology is vanishing as a constraint. Access to capital is vanishing as a constraint, at least a demonstrator to start showing that you've got a good idea because of the cloud. Because of Moore's law and a small team or alone innovator can demonstrate the power of their idea and then ramp it up. So those air really vanishing constraints are mindset, constraints, our institutional constraints. And unfortunately, increasingly, I believe regulatory constraints. Our colleague Larry Lessing has a great way to phrase the choice, he says, With our policies, with our regulations, we can protect the future from the past, or we could protect the past from the future. That choice is really, really write. The future is a better place. Let's protect that from the incumbents in the inertia. >> So that leads us to sort of some of the proposals that you guys made in terms of how we can approach this. Good news is, capitalism is not something that you're you're you're you're very much in favor of, you know, attacking no poulet bureau, I think, was your comments on DH some of the other things? Actually, I found pretty practical, although not not likely, but practical things, right? Yes, but but still, you know, feasible certainly, certainly, certainly intellectually. But what have you seen in terms of the reaction to your proposals? And do you have any once that the public policy will begin to shape in a way that wages >> conference that the conversation is shifting. So just from the publication date now we've noticed there's a lot more willingness to engage with these ideas with the ideas that tech progress is racing ahead but leaving some people behind in more people behind in an economic sense over time. So we've talked to politicians. We've talked to policy makers. We've talked to faint thanks. That conversation is progressing. And if we want to change our our government, you want to change our policies. I think it has to start with changing the conversation. It's a bottom out phenomenon >> and is exactly right. And that's really one of the key things that we learned, you know well, we talked to our political science friends. They remind us that in American other democracies, leaders are really followers on. They follow public opinion and the people are the leaders. So we're not going to be able to get changes in our policies until we change the old broad conversation. We get people recognizing the issues they're underway here, and I wouldn't be too quick to dismiss some of these bigger changes we describe as possible the book. I mean, historically, there've been some huge changes the cost of the mass public education was a pretty radical idea when it was introduced. The concept of Social Security were recently the concept of marriage. Equality with something I think people wouldn't have imagined maybe a decade or two ago so you could have some big changes in the political conversation. It starts with what the people want, and ultimately the leaders will follow. >> It's easy to get dismayed about the logjam in Washington, and I get dismayed once in a while. But I think back a decade ago, if somebody had told me that gay marriage and legal marijuana would be pretty widespread in America, I would have laughed in their face. And, you know, I'm straight and I don't smoke dope. I think these were both fantastic developments, and they came because the conversation shifted. Not not because we had a gay pot smoker in the white. >> Gentlemen, Listen, thank you very much. First of all, for running this great book, well, even I got one last question. So I understand you guys were working on your topic for you next, but can you give us a little bit of, uh, some thoughts as to what you're thinking. What do we do? We tip the hand. Well, sure, I think that >> it's no no mystery that we teach in a business school. And we spent a lot of time interacting with business leaders. And as we've mentioned in the discussion here, there have been some huge changes in the kind of business models that are successful in the second machine age. We want to elaborate on those describe nuts what were seeing when we talk to business leaders but also with the economic theory says about what will and what? What won't work. >> So second machine age was our attempt it like a big idea book. Let's write the Business guide to the Second Machine Age. >> Excellent. First of all, the book is a big idea. A lot of big ideas in the book, with excellent examples and some prescription, I think, for moving forward. So thank you for writing that book. And congratulations on its success. Really appreciate you guys coming in the Cube. Good luck today and we look forward to talking to in the future. Thanks for having been a real pleasure. Keep right. Everybody will be right back. We're live from London. This is M I t E. This is the cube right back