>> Narrator: Live, from Las Vegas, it's theCUBE, covering AWS re:Invent 2017, presented by AWS, intel, and our ecosystem of partners. Hello, everyone, welcome back to theCUBE. This is Silicon Angle's exclusive coverage with theCUBE, here at Amazon, re:Invent 2017. It's our 5th year covering Amazon's explosive growth. I'm John Furrier, the founder of Silicon Angle media. I'm here with Justin Warren, my cohost here, our next guest on set one is Tom Siebel, who is the founder and CEO of C3 IOT, industry legend, knows the software business, been around the block a few times, and now part of the new wave of innovation. Welcome to theCUBE. >> Thank you. >> I hear you just got in from San Francisco. What a world we're living in. You're at the front-end of your company that you founded and are running, an IOT big data play, doing extremely well. Even last year, the whisper in the hallway was C3 IOT is absolutely doing great, in the industrial side, certainly in the federal government side, and on commercial, congratulations! >> Thank you. >> What's the update, what's the secret formula? >> Well, we live at the convergence of elastic cloud computing, big data, AI, and IOT, and at the point where those converge, I think, is something called digital transformation, where you have these CEOs that, candidly, I think, they're concerned that companies are going through a mass-extinction event. I mean, companies are being, 52% of the Fortune 500 companies, as of 2000 are gone, right, they've disappeared and it's estimated as many 70% might disappear in the next 10 years, and we have this new species of companies with new DNA that look like Tesla and Uber, and Amazon, and, they have no drivers, no cars, and yet they own transportation, and I think that these CEOs are convinced that, unless they take advantage of this new class of technologies that they might be extinct. >> And it's certainly, we're seeing it, too, in a lot of the old guard, as Andy Jassy calls it, really talking about Oracle, IBM, and some of the other folks that are trying to do cloud, but they're winning. I gotta ask you, what's the main difference, from your perspective, that's different now that the culture of a company that's trying to transform, what's the big difference between the old way and new way now, that has to be implemented quickly, or extinction is a possibility? I mean, it's not just suppliers, it's the customers themselves. >> The customers have changed. >> What's the difference? >> So, this is my 4th decade in the information technology business and I've seen the business grow from a couple hundred billion to, say, two trillion worldwide, and I've seen it go from mainframe to mini-computers, to personal computers to the internet, all of that, and I was there when, in all of those generations of technology, when we brought those products to market, would come up in the organization, through the IT organization, to the CIO, and the CIO would say, "well, we're never gonna use a mini computer." or, "we're never gonna use relations database technology." or, "we're never gonna use a PC." And so, you'd wait for that CIO to be fired, then he'd come back two years later, right? Now, so meanwhile we build a two trillion dollar information technology business, globally. Now, what's happening in this space of big data, predictive analytics, IOT, is all of a sudden, it's the CEO at the table. CEO was never there before, and the CEO is mandating this thing called digital transformation, and he or she is appointing somebody in the person of a Chief Digital Officer, who has a mandate and basically a blank check to transform this company and get it done, and whereas it used to be the CIO would report to the CEO once a quarter at the quarterly off-site, the Chief Digital Officer reports to the CEO every week, so, and virtually everyone of our customers, CAT, John Deere, United Healthcare, you name, ENGIE, Enel, it's a CEO-driven initiative. >> You bring up a good point I wanna get your thoughts on, because the old way, and you mentioned, was IT reporting to the CIO. They ran things, they ran the business, they ran the plumbing, software was part of that, now software is the business. No one goes to the teller. The bank relationship's the software, or whatever vertical you're in there's now software, whether it's at the edge, whether it's data analytics, is the product to the consumer. So, the developer renaissance, we see software now changing, where the developer's now an influencer in this transformation. >> True. >> Not just, hey, go do it, and here's some tools, they're in part of that. Can you share your perspective on this because, if we're in a software renaissance, that means a whole new creativity's gonna unleash with software. With that role of the CDO, with the blank check, there's no dogma anymore. It's results. So, what's your perspective on this? >> Well, I think that there's enabling technologies that include the elastic cloud that include, computation and storage is basically free, right? Everything is a computer, so IOT, I used to think about IOT being devices, it's that IOT is a change in the form-factor of computers. In the future, everything's a computer, your eyeglasses, your watch, your heart monitor, your refrigerator, your pool pump, they're all computers, right, and then we have the network effect of Metcalfe's law, say we have 50 billion of theses devices fully connected and well, that's a pretty powerful network. Now, these technologies, in turn, enable AI, they enable machine learning and deep learning. Hey, that's a whole new ball game. Okay, we're able to solve classes of problems with predictive analytics and prescriptive analytics that were simply unsolvable before in history and this changes everything about the way we design products, the way we service customers, the way we manage companies. So, I think this AI thing is not to be underestimated. I think the cloud, IOT, big data, devices, those are just enablers, and I think AI is-- >> So, software and data's key, right? Data trains the AI, data is the fundamental new lifeblood. >> Big data, because now we're doing, what big data is about, people think that big data is the fact that an exabyte is more than a gigabyte, that's not it. Big data is about the fact that there is no sampling error. We have all the data. So, we used to, due to limitations to storage and processing we used to, you know, basically, take samples and infer results from those samples, and deal with it on the level of confidence error that was there. With big data, there's no sampling error. >> It's all there. >> It is a whole different game. >> We were talking before, and John, you mentioned before about the results that you need to show. Now, I know that you picked up a big new customer that I hope you can talk about publicly, which is a public-sector company, but that sounds like something where you're doing predictive maintenance for the Air Force, for the U.S. Air Force, so that's a big customer, good win there, but what is the result that they're actually getting from the use of big data and this machine learning analytics that you're doing? >> By aggregating all the telemetry and aggregating all their maintenance records, and aggregating all their pilot records, and then building machine learning class of ours, we can look at all the signals, and we can predict device failure or systems failure well in advance of failure, so the advantage is some pretty substantial percentages, say of F16s, will not deploy, of F18s will not deploy because, you know, they go to push the button and there's a system failure. Well, if we can predict system failure, I mean, the cost of maintenance goes down dramatically and, basically, it doubles the size of your fleet and, so the economic benefit is staggering. >> Tom, I gotta ask you a personal question. I mean, you've been through four decades, you're a legend in the industry, what was the itch that got you back with this company. Why did you found and run C3 IOT? What was the reason? Was it an itch you were scratching, like, damn, I want the action? I mean, what was the reason why you started the company? >> Well, I'm a computer scientist and out of graduate school, I went to work with a young entrepreneur by the name of Larry Ellison, turned out to be a pretty good idea, and then a decade later, we started Siebel Sytems, and I think, well, we did invent the CRM market and then it turned out to be a pretty good idea and I just see, at this intersection of these vectors we talked about, everything changes about computing. This has been a complete replacement market and I though, you know, there's opportunity to play a significant role in the game, and this what I do, you know. I collect talented people and try to build great companies and make customers satisfied. This is my idea of a good time. You're on the beach, you're on your board hangin' 10 on the big waves. What are the waves? We're seeing this inflection point, a lotta things comin' together, what are the waves that you're ridin' on right now? Obviously, the ones you mentioned, what's the set look like, if I can use a surfing analogy. What's coming in, what are the big waves? The two biggest ones are IOT and AI. I mean, since 2000 we've deployed 19 billion IOT sensors around the world. The next five years, we'll deploy 50 billion more. Everything will be a computer, and you connect all these things that they're all computing and apply AI, I mean we're gonna do things that were, you know, unthinkable, in terms of serving customers, building products, cost efficiencies, we're gonna revolutionize healthcare with precision health. Processes like energy extraction and power delivery will be much safer, much more reliable, much more environmentally-friendly, this is good stuff. So, what's your take on the security aspect of putting a computer in everything, because, I mean, the IT industry hasn't had a great track record of security, and now we're putting computers everywhere. As you say, they're gonna be in watches, they're gonna be in eyeglasses, what do you see as the trend in the way that security is gonna be addressed for this, computers everywhere? Well, I think that it is clearly not yet solved, okay, and it is a solvable problem. I believe that it's easier to secure data in cyber space than it is in your own data room. Maybe you could secure data in your data room when it took a forklift to move a storage device. It doesn't take a forklift anymore, right? It takes one of these little flash drives, you know, to move, to take all the data. So, I think the easiest place we can secure it is gonna be in cyber space. I think we'll use encryption, I think we'll be computing on encrypted data, and we haven't figured out algorithms to do that yet. I think blockchain will play an important role, but there's some invention that needs to happen and this is what we do. >> So, you like blockchain? >> I think blockchain plays a role in security. >> It does. So, I gotta ask you about the way, you're sinking your teeth into a new venture, exciting, it's on the cutting-edge, on the front lines of the innovation. There are a lotta other companies that are trying to retool. IBM, Microsoft, Oracle, if you were back them, probably not as exciting as what you're doing because you've got a new clean sheet of paper, but if you're Oracle, if you're Larry, and he went to be CTO, he's trying to transform, he's getting into the action, they got a lot to do there, IBM same thing, same with Microsoft, what's their strategy in your mind? If you were there, at the helm of those companies, what would you do? >> Well, number one, I would not bet against Larry. I know Larry pretty well and Larry is a formidable player in the information technology industry, and if you have to identify one of four companies that's surviving the long-run, it'll be Oracle that's in that consideration, in that set, so I think betting against Larry is a bad idea. >> He'll go to the mat big time, won't he? I mean, Jassy, there's barbs going back and forth, you gotta be careful there. >> Well, I mean, Andy Jassy is extraordinarily competent, I think, as it relates to this elastic cloud I think he's kinda got a lock on that, but, you know, IBM is hard to explain. I mean, IBM is a sad story. I think IBM is, there's some risk that IBM is the next Hewlett-Packard. I mean, they might be selling this thing off for piece parts this, you mean, if we look at the last 23 quarters, I mean, it's not good. >> And Microsoft's done a great job recently with Satya Nadella, and they're retooling fast. You can see them beavering away. >> But IBM, I mean, how do you bet against the cloud. I mean, are you kidding me? I mean, hello! IBM's a sad story. It's one of the world's great companies, it's an icon. If it fails, and companies like IBM's size do fail, I mean let's look at GE, that would be a sad state for America. >> Okay, on a more positive upbeat, what's next for you? Obviously, you're doing great, the numbers are good. Again, the rumors in the hallways we're hearing that you guys are doing great financially. Not sure if you can share any color on that, big wins, obviously, these are not little deals you're on, but what's next? What's the big innovation that you got comin' around the corner for C3 IOT. Well, so our business grew last year about 600%, this year it'll grow about 300%. We're a profitable, cash-positive business. Our average customer is, say, 20 to $200 billion business. We're engaged in very, very large transactions. In the last 18 months, we've done a lotta work in deep learning, okay. In the next 18 months, we'll do a lotta work in NLP. I think those technologies are hugely important. Technologically, this is where we'll be going. I think machine learning, traditional ML, we have that nailed, now we're exploiting deep learning in a big way using GPUs, and a lotta the work that Jensen Wang's doing at Nvidia, and now NLP, I think, is the next frontier for us. >> Final question for you, advice to other entrepreneurs. You're a serial entrepreneur. you've been very successful, inventive categories. You're looking at Amazon, how do you work with the Amazons of the world. What should entrepreneurs be thinking about in terms of how to enter the market, funding, just strategy in general. The rules have changed a little bit. What advice would you give the young entrepreneurs out there? >> Okay, become a domain expert at whatever domain you're proposing and whatever field you're gonna enter, and then surround yourself with people, whatever job they're doing, engineering, marketing, sales, F&A, who are better than you at what they do and, to the extent that I have succeeded, this is why I've succeeded. Now this might be easier for me than for others, but I try to surround myself with people who are better than me and, to the extent that I've been successful, that's why. >> We really appreciate you taking the time coming on. You're an inspiration, a serial entrepreneur, founder and CEO Tom Siebel of C3 IOT, hot company, big part of the Amazon Web Services ecosystem. Doing great stuff, again, serial entrepreneur. Great four-decade career. Thanks for coming on theCUBE, Tom Siebel. Here inside theCUBE, I'm John Furrier and Justin Warren, here in Las Vegas for AWS re:Invent. We'll be back with more live coverage after this short break. >> Thanks guys, good job.

(gentle upbeat music) >> People hate to be sold, but they love to buy. We become what we think about, think, and grow rich. If you want to gather honey, don't kick over the beehive. The world is replete with time-tested advice and motivational ideas for aspiring salespeople, Dale Carnegie, Napoleon Hill, Norman Vincent Peale, Earl Nightingale, and many others have all published classics with guidance that when followed closely, almost always leads to success. More modern personalities have emerged in the internet era, like Tony Robbins, and Gary Vaynerchuk, and Angela Duckworth. But for the most part, they've continued to rely on book publishing, seminars, and high value consulting to peddle their insights and inspire action. Welcome to this video exclusive on theCUBE. This is Dave Vellante, and I'm pleased to welcome back Professor Mark Roberge, who is one of the Managing Directors at Stage 2 Capital, and Paul Fifield, who's the CEO and Co-Founder of Sales Impact Academy. Gentlemen, welcome. Great to see you. >> You too Dave and thanks. >> All right, let's get right into it. Paul, you guys are announcing today a $4 million financing round. It comprises $3 million in a seed round led by Stage 2 and a million dollar in debt financing. So, first of all, congratulations. Paul, why did you start Sales Impact Academy? >> Cool, well, I think my background is sort of two times CRO, so I've built two reasonably successful companies. Built a hundred plus person teams. And so I've got kind of this firsthand experience of having to learn literally everything on the job whilst delivering these very kind of rapid, like achieving these very rapid growth targets. And so when I came out of those two journeys, I literally just started doing some voluntary teaching in and around London where I now live. I spend a bunch of time over in New York, and literally started this because I wanted to sort of kind of give back, but just really wanted to start helping people who were just really, really struggling in high pressure environments. And that's both leadership from sense of revenue leadership people, right down to sort of frontline SDRs. And I think as I started just doing this voluntary teaching, I kind of realized that actually the sort of global education system has done is a massive, massive disservice, right? I actually call it the greatest educational travesty of the last 50 years, where higher education has entirely overlooked sales as a profession. And the knock-on consequences of that have been absolutely disastrous for our profession. Partly that the profession is seen as a bit sort of embarrassing to be a part of. You kind of like go get a sales job if you can't get a degree. But more than that, the core fundamental within revenue teams and within sales people is now completely lacking 'cause there's no structured formal kind of like learning out there. So that's really the problem we're trying to solve on the kind of like the skill side. >> Great. Okay. And mark, always good to have you on, and I got to ask you. So even though, I know this is the wheelhouse for you and your partners, and of course, you've got a deep bench of LPs, but lay out the investment thesis here. What's the core problem that you saw and how are you looking at the market? >> Yeah, sure, Dave. So this one was a special one for me. We've spoken in the past. I mean, just personally I've always had a similar passion to Paul that it's amazing how important sales execution is to all companies, nevermind just the startup ecosystem. And I've always personally been motivated by anything that can help the startup ecosystem increase their success. Part of why I teach at Harvard and try to change some of the stuff that Paul's talking about, which is like, it's amazing how little education is done around sales. But in this particular one, not only personally was I excited about, but from a fun perspective, we've got to look at the economic outcomes. And we've been thinking a lot about the sales tech stack. It's evolved a ton in the last couple of decades. We've gone from the late '90s where every sales VP was just, they had a thing called the CRM that none of their reps even used, right? And we've come so far in 20 years, we've got all these amazing tools that help us cold call, that help us send emails efficiently and automatically and track everything, but nothing's really happened on the education side. And that's really the enormous gap that we've seen is, these organizations being much more proactive around adopting technology that can prove sales execution, but nothing on the education side. And the other piece that we saw is, it's almost like all these companies are reinventing the wheel of looking in the upcoming year, having a dozen sales people to hire, and trying to put together a sales enablement program within their organization to teach salespeople sales 101. Like how to find a champion, how to develop a budget, how to develop sense of urgency. And what Paul and team can do in the first phase of essay, is can sort of centralize that, so that all of these organizations can benefit from the best content and the best instructors for their team. >> So Paul, exactly, thank you, mark. Exactly what do you guys do? What do you sell? I'm curious, is this sort of, I'm thinking in my head, is this E-learning, is it really part of the sales stack? Maybe you could help us understand that better. >> Well, I think this problem of having to upscale teams has been around like forever. And kind of going back to the kind of education problem, it's what's wild is that we would never accept this of our lawyers, our accountants, or HR professionals. Imagine like someone in your finance team arriving on day one and they're searching YouTube to try and work out how to like put a balance sheet together. So it's a chronic, chronic problem. And so the way that we're addressing this, and I think the problem is well understood, but there's always been a terrible market, sort of product market fit for how the problem gets solved. So as mark was saying, typically it's in-house revenue leaders who themselves have got massive gaps in their knowledge, hack together some internal learning that is just pretty poor, 'cause it's not really their skillset. The other alternative is bringing in really expensive consultants, but they're consultants with a very single worldview and the complexity of a modern revenue organization is very, very high these days. And so one consultant is not going to really kind of like cover every topic you need. And then there's the kind of like fairly old fashioned sales training companies that just come in, one big hit, super expensive and then sort of leave again. So the sort of product market fit to solve, has always been a bit pretty bad. So what we've done is we've created a subscription model. We've essentially productized skills development. The way that we've done that is we teach live instruction. So one of the big challenges Andreessen Horowitz put a post out around this so quite recently, one of the big problems of online learning is that this kind of huge repository of online learning, which puts all the onus on the learner to have the discipline to go through these courses and consume them in an on-demand way is actually they're pretty ineffective. We see sort of completion rates of like 7 to 8%. So we've always gone from a live instruction model. So the sort of ingredients are the absolute very best people in the world in their very specific skill teaching live classes just two hours per week. So we're not overwhelming the learners who are already in work, and they have targets, and they've got a lot of pressure. And we have courses that last maybe four to like 12 hours over two to sort of six to seven weeks. So highly practical live instruction. We have 70, 80, sometimes even 90% completion rates of the sort of live class experience, and then teams then rapidly put that best practice into practice and see amazing results in things like top of funnel, or conversion, or retention. >> So live is compulsory and I presume on-demand? If you want to refresh you have an on demand option? >> Yeah, everything's recorded, so you can kind of catch up on a class if you've missed it, But that live instruction is powerful because it's kind of in your calendar, right? So you show up. But the really powerful thing, actually, is that entire teams within companies can actually learn at exactly the same pace. So we teach it eight o'clock Pacific, 11 o'clock Eastern, >> 4: 00 PM in the UK, and 5:00 PM Europe. So your entire European and North American teams can literally learn in the same class with a world-class expert, like a Mark, or like a Kevin Dorsey, or like Greg Holmes from Zoom. And you're learning from these incredible people. Class finishes, teams can come back together, talk about this incredible best practice they've just learned, and then immediately put it into practice. And that's where we're seeing these incredible, kind of almost instant impact on performance at real scale. >> So, Mark, in thinking about your investment, you must've been thinking about, okay, how do we scale this thing? You've got an instructor component, you've got this live piece. How are you thinking about that at scale? >> Yeah, there's a lot of different business model options there. And I actually think multiple of them are achievable in the longer term. That's something we've been working with Paul quite a bit, is like, they're all quite compelling. So just trying to think about which two to start with. But I think you've seen a lot of this in education models today. Is a mixture of on-demand with prerecorded. And so I think that will be the starting point. And I think from a scalability standpoint, we were also, we don't always try to do this with our investments, but clearly our LP base or limited partner base was going to be a key ingredient to at least the first cycle of this business. You know, our VC firm's backed by over 250 CRO CMOs heads of customer success, all of which are prospective instructors, prospective content developers, and prospective customers. So that was a little nicety around the scale and investment thesis for this one. >> And what's in it for them? I mean, they get paid. Obviously, you have a stake in the game, but what's in it for the instructors. They get paid on a sort of a per course basis? How does that model work? >> Yeah, we have a development fee for each kind of hour of teaching that gets created So we've mapped out a pretty significant curriculum. And we have about 250 hours of life teaching now already written. We actually think it's going to be about 3000 hours of learning before you get even close to a complete curriculum for every aspect of a revenue organization from revenue operations, to customer success, to marketing, to sales, to leadership, and management. But we have a development fee per class, and we have a teaching fee as well. >> Yeah, so, I mean, I think you guys, it's really an underserved market, and then when you think about it, most organizations, they just don't invest in training. And so, I mean, I would think you'd want to take it, I don't know what the right number is, 5, 10% of your sales budget and actually put it on this and the return would be enormous. How do you guys think about the market size? Like I said before, is it E-learning, is it part of the CRM stack? How do you size this market? >> Well, I think for us it's service to people. A highly skilled sales rep with an email address, a phone and a spreadsheet would do really well, okay? You don't need this world-class tech stack to do well in sales. You need the skills to be able to do the job. But the reverse, that's not true, right? An unskilled person with a world-class tech stack won't do well. And so fundamentally, the skill level of your team is the number one most important thing to get right to be successful in revenue. But as I said before, the product market for it to solve that problem, has been pretty terrible. So we see ourselves 100%. And so if you're looking at like a com, you look at Gong, who we've just signed as a customer, which is fantastic. Gong has a technology that helps salespeople do better through call recording. You have Outreach, who is also a customer. They have technologies that help SDRs be more efficient in outreach. And now you have Sales Impact Academy, and we help with skills development of your team, of the entirety of your revenue function. So we absolutely see ourselves as a key part of that stack. In terms of the TAM, 60 million people in sales are on, according to LinkedIn. You're probably talking 150 million people in go to market to include all of the different roles. 50% of the world's companies are B2B. The TAM is huge. But what blows my mind, and this kind of goes back to this why the global education system has overlooked this because essentially if half the world's companies are B2B, that's probably a proxy for the half of the world's GDP, Half of the world's economic growth is relying on the revenue function of half the world's companies, and they don't really know what they're doing, (laughs) which is absolutely staggering. And if we can solve that in a meaningfully meaningful way at massive scale, then the impact should be absolutely enormous. >> So, Mark, no lack of TAM. I know that you guys at Stage 2, you're also very much focused on the metrics. You have a fundamental philosophy that your product market fit and retention should come before hyper growth. So what were the metrics that enticed you to make this investment? >> Yeah, it's a good question, Dave, 'cause that's where we always look first, which I think is a little different than most early stage investors. There's a big, I guess, meme, triple, triple, double, double that's popular in Silicon Valley these days, which refers to triple your revenue in year one, triple your revenue in year two, double in year three, and four, and five. And that type of a hyper growth is critical, but it's often jumped too quickly in our opinion. That there's a premature victory called on product market fit, which kills a larger percentage of businesses than is necessary. And so with all our investments, we look very heavily first at user engagement, any early indicators of user retention. And the numbers were just off the charts for SIA in terms of the customers, in terms of the NPS scores that they were getting on their sessions, in terms of the completion rate on their courses, in terms of the customers that started with a couple of seats and expanded to more seats once they got a taste of the program. So that's where we look first as a strong foundation to build a scalable business, and it was off the charts positive for SIA. >> So how about the competition? If I Google sales training software, I'll get like dozens of companies. Lessonly, and MindTickle, or Brainshark will come up, that's not really a fit. So how do you think about the competition? How are you different? >> Yeah, well, one thing we try and avoid is any reference to sales training, 'cause that really sort of speaks to this very old kind of fashioned way of doing this. And I actually think that from a pure pedagogy perspective, so from a pure learning design perspective, the old fashioned way of doing sales training was pull a whole team off site, usually in a really terrible hotel with no windows for a day or two. And that's it, that's your learning experience. And that's not how human beings learn, right? So just even if the content was fantastic, the learning experience was so terrible, it was just very kind of ineffective. So we sort of avoid kind of like sales training, The likes of MindTickle, we're actually talking to them at the moment about a partnership there. They're a platform play, and we're certainly building a platform, but we're very much about the live instruction and creating the biggest curriculum and the broadest curriculum on the internet, in the world, basically, for revenue teams. So the competition is kind of interesting 'cause there is not really a direct subscription-based live like learning offering out there. There's some similar ish companies. I honestly think at the moment it's kind of status quo. We're genuinely creating a new category of in-work learning for revenue teams. And so we're in this kind of semi and sort of evangelical sort of phase. So really, status quo is one of the biggest sort of competitors. But if you think about some of those old, old fashioned sort of Miller Heimans, and then perhaps even like Sandlers, there's an analogy perhaps here, which is kind of interesting, which is a little bit like Siebel and Salesforce in the sort of late '90s, where in Siebel you have this kind of old way of doing things. It was a little bit ineffective. It was really expensive. Not accessible to a huge space of the market. And Salesforce came along and said, "Hey, we're going to create this cool thing. It's going to be through the browser, it's going to be accessible to everyone, and it's going to be really, really effective." And so there's some really kind of interesting parallels almost between like Siebel and Salesforce and what we're doing to completely kind of upend the sort of the old fashioned way of delivering sort of sales training, if you like. >> And your target customer profile is, you're selling to teams, right? B2B teams, right? It's not for individuals. Is that correct, Paul? >> Currently. Yeah, yeah. So currently we've got a big foothold in series A to series B. So broadly speaking out, our target market currently is really fast growth technology companies. That's the sector that we're really focusing on. We've got a very good strong foothold in series A series B companies. We've now won some much larger later stage companies. We've actually even won a couple of corporates, I can't say names yet, but names that are very, very, very familiar and we're incredibly excited by them, which could end up being thousand plus seat deals 'cause we do this on a per seat basis. But yeah, very much at the moment it's fast growth tech companies, and we're sort of moving up the chain towards enterprise. >> And how do you deal with the sort of maturity curve, if you will, of your students? You've got some that are brand new, just fresh out of school. You've got others that are more seasoned. What do you do, pop them into different points of the curriculum? How do you handle it? >> Yeah we have, I'll say we have about 30 courses right now. We have about another 15 in development where post this fundraise, we want to be able to get to around about 20 courses that we're developing every quarter and getting out to market. So we're literally, we've sort of identified about 20 to 25 key roles across everything within revenue. That's, let's say revenue ops, customer success, account management, sales, engineering, all these different kinds of roles. And we are literally plotting the sort of skills development for these individuals over multiple, multiple years. And I think what we've never ceases to amaze me is actually the breadth of learning in revenue is absolutely enormous. And what kind of just makes you laugh is, this is all of this knowledge that we're now creating it's what companies just hope that their teams somehow acquire through osmosis, through blogs, through events. And it's just kind of crazy that there is... It's absolutely insane that we don't already exist, basically. >> And if I understand it correctly, just from looking at your website, you've got the entry level package. I think it's up to 15 seats, and then you scale up from there, correct? Is it sort of as a seat-based license model? >> Yeah, it's a seat-based model, as Mark mentioned. In some cases we sell, let's say 20 or $30,000 deal out the gate and that's most of the team. That will be maybe a series A, series B deal, but then we've got these land and expand models that are working tremendously well. We have seven, eight customers in Q1 that have doubled their spend Q2. That's the impact that they're seeing. And our net revenue retention number for Q2 is looking like it's going to be 177% to think exceeds companies like Snowflakes. Well, our underlying retention metrics, because people are seeing this incredible impact on teams and performance, is really, really strong. >> That's a nice metric compare with Snowflake (Paul laughs) It's all right. (Dave and Paul laugh) >> So, Mark, this is a larger investment for Stage 2 You guys have been growing and sort of upping your game. And maybe talk about that a little bit. >> Yeah, we're in the middle of Fund II right now. So, Fund I was in 2018. We were doing smaller checks. It was our first time out of the gate. The mission has really taken of, our LP base has really taken off. And so this deal looks a lot like more like our second fund. We'll actually make an announcement in a few weeks now that we've closed that out. But it's a much larger fund and our first investments should be in that 2 to $3 million range. >> Hey, Paul, what are you going to do with the money? What are the use of funds? >> Put it on black, (chuckles) we're going to like- (Dave laughs) >> Saratoga is open. (laughs) (Mark laughs) >> We're going to, look, the curriculum development for us is absolutely everything, but we're also going to be investing in building our own technology platform as well. And there are some other really important aspects to the kind of overall offering. We're looking at building an assessment tool so we can actually kind of like start to assess skills across teams. We certify every course has an exam, so we want to get more robust around the certification as well, because we're hoping that our certification becomes the global standard in understanding for the first time in the industry what individual competencies and skills people have, which will be huge. So we have a broad range of things that we want to start initiating now. But I just wanted to quickly say Stage 2 has been nothing short of incredible in every kind of which way. Of course, this investment, the fit is kind of insane, but the LPs have been extraordinary in helping. We've got a huge number of them are now customers very quickly. Mark and the team are helping enormously on our own kind of like go to market and metrics. I've been doing this for 20 years. I've raised over 100 million myself in venture capital. I've never known a venture capital firm with such value add like ever, or even heard of other people getting the kind of value add that we're getting. So I just wanted to a quick shout out for Stage 2. >> Quite a testimony of you guys. Definitely Stage 2 punches above its weight. Guys, we'll leave it there. Thanks so much for coming on. Good luck and we'll be watching. Appreciate your time. >> Thanks, Dave. >> Thank you very much. >> All right, thank you everybody for watching this Cube conversation. This is Dave Vellante, and we'll see you next time.

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante cloud repatriation is a term often used by technology companies the ones that don't operate a public cloud the marketing narrative most typically implies that customers have moved work to the public cloud and for a variety of reasons expense performance security etc are disillusioned with the cloud and as a result are repatriating workloads back to their safe comfy and cost-effective on-premises data center while we have no doubt this does sometimes happen the data suggests that this is a single digit de minimis phenomenon hello and welcome to this week's wikibon cube insights powered by etr some have written about the repatriation myth but in this breaking analysis we'll share hard data that we feel debunks the narrative and is currently being promoted by some we'll also take this opportunity to do our quarterly cloud revenue update and share with you our latest figures for the big four cloud vendors let's start by acknowledging that the definition of cloud is absolutely evolving and in this sense much of the vendor marketing is valid no longer is cloud just a distant set of remote services that lives up there in the cloud the cloud is increasingly becoming a ubiquitous sensing thinking acting set of resources that touches nearly every aspect of our lives the cloud is coming on prem and work is being done to connect clouds to each other and the cloud is extending to the near and far edge there's little question about that today's cloud is not just compute storage connectivity and spare capacity but increasingly it's a variety of services to analyze data and predict slash anticipate changes monitor and interpret streams of information apply machine intelligence to data to optimize business outcomes it's tooling to share data protect data visualize data and bring data to life supporting a whole new set of innovative applications notice there's a theme there data increasingly the cloud is where the high value data lives from a variety of sources and it's where organizations go to mine it because the cloud vendors have the best platforms for data and this is part of why the repatriation narrative is somewhat dubious actually a lot dubious because the volume of data in the cloud is growing at rates much faster than data on prem at least by a couple thousand basis points by our estimates annually so cloud data is where the action is and we'll talk about the edge in a moment but a new era of application development is emerging with containers at the center the concept of write wants run anywhere allows developers to take advantage of systems that run on-prem say a transaction system and tap data from multiple sources in various locations there might be multiple clouds or at the edge or wherever and combine that with immense cheap processing power that we've discussed extensively in previous breaking analysis episodes and you see this new breed of apps emerging that's powered by ai those are hitting the market so this is not a zero-sum game the cloud vendors have given the world an infrastructure gift by spending like crazy on capex more than a hundred billion last year on capex for example for the big four and in our view the players that don't own a cloud should stop being so defensive about it they should thank the hyperscalers and lay out a vision as to how they'll create a new abstraction layer on top of the public cloud and you know that's what they're doing and they'll certainly claim to be actively working on this vision but consider the pace of play between the hyperscalers and their traditional on-prem providers we believe the innovation gap is actually widening meaning the public cloud players are accelerating their innovation lead and will 100 compete for hybrid applications they have the resources the developer affinity they're doing custom silicon and have the expertise there and the tam expansion goals that loom large so while it's not a zero-sum game and hybrid is definitely real we think the cloud vendors continue to gain share most rapidly unless the hybrid crowd can move faster now of course there's the edge and that is a wild card but it seems that again the cloud players are very well positioned to innovate with custom silicon programmable infrastructure capex build-outs at the edge and new thinking around system architectures but let's get back to the core story here and take a look at cloud adoptions you hear many marketing messages that call into question the public cloud at its recent think conference ibm ceo arvind krishna said that only about 25 of workloads had moved into the public cloud and he made the statement that you know this might surprise you implying you might think it should be much higher than that well we're not surprised by that figure especially especially if you narrow it to mission critical work which ibm does in its annual report actually we think that's probably high for mission critical work moving to the cloud we think it's a lot lower than that but regardless we think there are other ways to measure cloud adoption and this chart here from david michelle's book c seeing digital shows the adoption rates for major technological innovations over the past century and the number of years how many years it took to get to 50 percent household adoption electricity took a long time as did telephones had that infrastructure that last mile build out radios and tvs were much faster given the lower infrastructure requirements pcs actually took a long time and the web around nine years from when the mosaic browser was introduced we took a stab at estimating the pace of adoption of public cloud and and within a decade it reached 50 percent adoption in top enterprises and today that figures easily north of 90 so as we said at the top cloud adoption is actually quite strong and that adoption is driving massive growth for the public cloud now we've updated our quarterly cloud figures and want to share them with you here are our latest estimates for the big four cloud players with only alibaba left to report now remember only aws and alibaba report clean or relatively clean i ass figures so we use survey data and financial analysis to estimate the actual numbers for microsoft in google it's a subset of what they report in q121 we estimate that the big 4is and pas revenue approached 27 billion that's q121 that figure represents about 40 growth relative to q1 2020. so our trailing 12-month calculation puts us at 94 billion so we're now on roughly 108 billion dollar run rate as you may recall we've predicted that figure will surpass 115 billion by year end when it's all said and done aws it remains the leader amongst the big four with just over half of the market that's down from around 63 percent for the full year of 2018. unquestionably as we've reported microsoft they're everywhere they're ubiquitous in the market and they continue to perform very well but anecdotally customers and partners in our community continue to report to us that the quality of the aws cloud is noticeably better in terms of reliability and overall security etc but it doesn't seem to change the trajectory of the share movements as microsoft's software dominance makes doing business with azure really easy now as of this recording alibaba has yet to report but we'll update these figures once their earnings are released let's dig into the growth rates associated with these revenue figures and make some specific comments there this chart here shows the growth trajectory for each of the big four google trails the pack in revenue but it's growing faster than the others from of course a smaller base google is being very aggressive on pricing and customer acquisition to that we say good google needs to grow faster in our view and they most certainly can afford to be aggressive as we said combined the big four are growing revenue at 40 on a trailing 12-month basis and that compares with low single-digit growth for on-prem infrastructure and we just don't see this picture changing in the near to midterm like storage growth revenue from the big public cloud players is expected to outpace spending on traditional on on-prem platforms by at least 2 000 basis points for the foreseeable future now interestingly while aws is growing more slowly than the others from a much larger 54 billion run rate we actually saw sequential quarterly growth from aws and q1 which breaks a two-year trend from where aws's q1 growth rate dropped sequentially from q4 interesting now of course at aws we're watching the changing of the guards andy jassy becoming ceo of amazon adam silipsky boomeranging back to aws from a very successful stint at tableau and max peterson taking over for for aws public sector replacing teresa carlson who is now president and heading up go to market at splunk so lots of changes and we think this is actually a real positive for aws as it promotes from within we like that it taps previous amazon dna from tableau salesforce and it promotes the head of aws to run all of amazon a signal to us that amazon will dig its heels in and further resist calls to split aws from the mothership so let's dig in a little bit more to this repatriation mythbuster theme the revenue numbers don't tell the entire story so it's worth drilling down a bit more let's look at the demand side of the equation and pull in some etr survey data now to set this up we want to explain the fundamental method used by etr around its net score metric net score measures spending momentum and measures five factors as shown in this wheel chart that shows the breakdown of spending for the aws cloud it shows the percentage of customers within the platform that are either one adopting the platform new that's the lime green in this wheel chart two increasing spending by more than five percent that's the forest green three flat spending between plus or minus five percent that's the gray and four decreasing spend by six percent or more that's the pink and finally five replacing the platform that's the bright red now dare i say that the bright red is a proxy for or at least an indicator of repatriation sure why not let's say that now net score is derived by subtracting the reds from the greens anything above 40 percent we consider to be elevated aws is at 57 so very high not much sign of leaving the cloud nest there but we know it's nuanced and you can make an argument for corner cases of repatriation but come on the numbers just don't bear out that narrative let's compare aws with some of the other vendors to test this theory theory a bit more this chart lines up net score granularity for aws microsoft and google it compares that to ibm and oracle now other than aws and google these figures include the entire portfolio for each company but humor me and let's make an assumption that cloud defections are lower than the overall portfolio average because cloud has more momentum it's getting more spend spending so just stare at the red bars for a moment the three cloud players show one two and three percent replacement rates respectively but ibm and oracle while still in the single digits which is good show noticeably higher replacement rates and meaningfully lower new adoptions in the lime green as well the spend more category in the forest green is much higher within the cloud companies and the spend less in the pink is notably lower and you can see the sample sizes on the right-hand side of the chart we're talking about many hundreds over 1300 in the case of microsoft and if we look if we put hpe or dell in the charts it would say several hundred responses many hundreds it would look similar to ibm and oracle where you have higher reds a bigger fat middle of gray and lower greens it's just the way it is it shouldn't surprise anyone and it's you know these are respectable but it's just what happens with mature companies so if customers are repatriating there's little evidence here we believe what's really happening is that vendor marketing people are talking to customers who are purposefully spinning up test and dev work in the cloud with the intent of running a workload or portions of that workload on prem and when they move into production they're counting that as repatriation and they're taking liberties with the data to flood the market okay well that's fair game and all's fair in tech marketing but that's not repatriation that's experimentation or sandboxing or testing and deving it's not i'm leaving the cloud because it's too expensive or less secure or doesn't perform for me we're not saying that those things don't happen but it's certainly not visible in the numbers as a meaningful trend that should factor into buying decisions now we perfectly recognize that organizations can't just refactor their entire applications application portfolios into the cloud and migrate and we also recognize that lift and shift without a change in operating model is not the best strategy in real migrations they take a long time six months to two years i used to have these conversations all the time with my colleague stu miniman and i spoke to him recently about these trends and i wanted to see if six months at red hat and ibm had changed his thinking on all this and the answer was a clear no but he did throw a little red hat kool-aid at me saying saying that the way they think about the cloud blueprint is from a developer perspective start by containerizing apps and then the devs don't need to think about where the apps live whether they're in the cloud whether they're on prem where they're at the edge and red hat the story is brings a consistency of operations for developers and operators and admins and the security team etc or any plat on any platform but i don't have to lock in to a platform and bring that everywhere with me i can work with anyone's platform so that's a very strong story there and it's how arvin krishna plans to win what he calls the architectural battle for hybrid cloud okay so let's take a take a look at how the big cloud vendors stack up with the not so big cloud platforms and all those in between this chart shows one of our favorite views plotting net score or spending velocity on the vertical axis and market share or pervasiveness in the data set on the horizontal axis the red shaded area is what we call the hybrid zone and the dotted red lines that's where the elite live anything above 40 percent net score on the on on the vertical axis we consider elevated anything to the right of 20 on the horizontal axis implies a strong market presence and by those kpis it's really a two horse race between aws and microsoft now as we suggested google still has a lot of work to do and if they're out buying market share that's a start now you see alibaba shown in the upper left hand corner high spending momentum but from a small sample size as etr's china respondent level is obviously much lower than it is in the u.s and europe and the rest of apac now that shaded res red zone is interesting and gives credence to the other big non-cloud owning vendor narrative that is out there that is the world is hybrid and it's true over the past several quarters we've seen this hybrid zone performing well prominent examples include vmware cloud on aws vmware cloud which would include vcf vmware cloud foundation dell's cloud which is heavily based on vmware and red hat open shift which perhaps is the most interesting given its ubiquity as we were talking about before and you can see it's very highly elevated on the net score axis right there with all the public cloud guys red hat is essentially the switzerland of cloud which in our view puts it in a very strong position and then there's a pack of companies hovering around the 20 vertical axis level that are hybrid that by the way you see openstack there that's from a large telco presence in the data set but any rate you see hpe oracle and ibm ibm's position in the cloud just tells you how important red hat is to ibm and without that acquisition you know ibm would be far less interesting in this picture oracle is oracle and actually has one of the strongest hybrid stories in the industry within its own little or not so little world of the red stack hpe is also interesting and we'll see how the big green lake ii as a service pricing push will impact its momentum in the cloud category remember the definition of cloud here is whatever the customer says it is so if a cio says we're buying cloud from hpe or ibm or cisco or dell or whomever we take her or his word for it and that's how it works cloud is in the eye of the buyer so you have the cloud expanding into the domain of on-premises and the on-prem guys finally getting their proverbial acts together with hybrid that they've been talking about since 2009 but it looks like it's finally becoming real and look it's true you're not going to migrate everything into the cloud but the cloud folks are in a very strong position they are on the growth flywheel as we've shown they each have adjacent businesses that are data based disruptive and dominant whether it's in retail or search or a huge software estate they are winning the data wars as well that seems to be pretty clear to us and they have a leg up in ai and i want to look at that can we all agree that ai is important i think we can machine intelligence is being infused into every application and today much of the ai work is being done in the cloud as modeling but in the future we see ai moving to the edge in real time and real-time inferencing is a dominant workload but today again 90 of it is building models and analyzing data a lot of that work happens in the cloud so who has the momentum in ai let's take a look here's that same xy graph with the net score against market share and look who has the dominant mind share and position and spending momentum microsoft aws and google you can see in the table insert in the lower right hand side they're the only three in the data set of 1 500 responses that have more than 100 n aws and microsoft have around 200 or even more in the case of microsoft and their net scores are all elevated above the 60 percent level remember that 40 percent that red line indicates the elevation mark the high elevation mark so the hyperscalers have both the market presence and the spend momentum so we think the rich get richer now they're not alone there are several companies above the 40 line databricks is bringing ai and data science to the world of data lakes with its managed services and it's executing very well salesforce is infusing infusing ai into its platform via einstein you got sap on there anaconda is kind of the gold standard that platform for data science and you can see c3 dot ai is tom siebel's company going after enterprise ai and data robot which like c3 ai is a small sample in the data set but they're highly elevated and they're simplifying machine learning now there's ibm watson it's actually doing okay i mean sure we'd like to see it higher given that ginny rometty essentially bet ibm's future on watson but it has a decent presence in the market and a respectable net score and ibm owns a cloud so okay at least it's a player not the dominance that many had hoped for when watson beat ken jennings in jeopardy back 10 years ago but it's okay and then is oracle they're now getting into the act like it always does they want they watched they waited they invested they spent money on r d and then boom they dove into the market and made a lot of noise and acted like they invented the concept oracle is infusing ai into its database with autonomous database and autonomous data warehouse and look that's what oracle does it takes best of breed industry concepts and technologies to make its products better you got to give oracle credit it invests in real tech and it runs the most mission critical apps in the world you can hate them if you want but they smoke everybody in that game all right let's take a look at another view of the cloud players and see how they stack up and where the big spenders live in the all-important fortune 500 this chart shows net score over time within the fortune 500 aws is particularly interesting because its net score overall is in the high 50s but in this large big spender category aws net score jumps noticeably to nearly 70 percent so there's a strong indication that aws the largest player also has momentum not just with small companies and startups but where it really counts from a revenue perspective in the largest companies so we think that's a very positive sign for aws all right let's wrap the realities of cloud repatriation are clear corner cases exist but it's not a trend to take to the bank although many public cloud users may think about repatriation most will not act on it those that do are the exception not the rule and the etr data shows that test and dev in the clouds is part of the cloud operating model even if the app will ultimately live on prem that's not repatriation that's just smart development practice and not every workload is will or should live in the cloud hybrid is real we agree and the big cloud players know it and they're positioning to bring their stacks on prem and to the edge and despite the risk of a lock-in and higher potential monthly bills and concerns over control the hyperscalers are well com positioned to compete in hybrid to win hybrid the legacy vendors must embrace the cloud and build on top of those giants and add value where the clouds aren't going to or can't or won't they got to find places where they can move faster than the hyperscalers and so far they haven't shown a clear propensity to do that hey that's how we see it what do you think okay well remember these episodes are all available as podcasts wherever you listen you do a search breaking analysis podcast and please subscribe to the series check out etr's website at dot plus we also publish a full report every week on wikibon.com and siliconangle.com a lot of ways to get in touch you can email me at david.velante at siliconangle.com or dm me at dvalante on twitter comment on our linkedin post i always appreciate that this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well and we'll see you next time you

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Moore's Law is dead, right? Think again. Massive improvements in processing power combined with data and AI will completely change the way we think about designing hardware, writing software and applying technology to businesses. Every industry will be disrupted. You hear that all the time. Well, it's absolutely true and we're going to explain why and what it all means. Hello everyone, and welcome to this week's Wikibon Cube Insights powered by ETR. In this breaking analysis, we're going to unveil some new data that suggests we're entering a new era of innovation that will be powered by cheap processing capabilities that AI will exploit. We'll also tell you where the new bottlenecks will emerge and what this means for system architectures and industry transformations in the coming decade. Moore's Law is dead, you say? We must have heard that hundreds, if not, thousands of times in the past decade. EE Times has written about it, MIT Technology Review, CNET, and even industry associations that have lived by Moore's Law. But our friend Patrick Moorhead got it right when he said, "Moore's Law, by the strictest definition of doubling chip densities every two years, isn't happening anymore." And you know what, that's true. He's absolutely correct. And he couched that statement by saying by the strict definition. And he did that for a reason, because he's smart enough to know that the chip industry are masters at doing work arounds. Here's proof that the death of Moore's Law by its strictest definition is largely irrelevant. My colleague, David Foyer and I were hard at work this week and here's the result. The fact is that the historical outcome of Moore's Law is actually accelerating and in quite dramatically. This graphic digs into the progression of Apple's SoC, system on chip developments from the A9 and culminating with the A14, 15 nanometer bionic system on a chip. The vertical axis shows operations per second and the horizontal axis shows time for three processor types. The CPU which we measure here in terahertz, that's the blue line which you can't even hardly see, the GPU which is the orange that's measured in trillions of floating point operations per second and then the NPU, the neural processing unit and that's measured in trillions of operations per second which is that exploding gray area. Now, historically, we always rushed out to buy the latest and greatest PC, because the newer models had faster cycles or more gigahertz. Moore's Law would double that performance every 24 months. Now that equates to about 40% annually. CPU performance is now moderated. That growth is now down to roughly 30% annual improvements. So technically speaking, Moore's Law as we know it was dead. But combined, if you look at the improvements in Apple's SoC since 2015, they've been on a pace that's higher than 118% annually. And it's even higher than that, because the actual figure for these three processor types we're not even counting the impact of DSPs and accelerator components of Apple system on a chip. It would push this even higher. Apple's A14 which is shown in the right hand side here is quite amazing. It's got a 64 bit architecture, it's got many, many cores. It's got a number of alternative processor types. But the important thing is what you can do with all this processing power. In an iPhone, the types of AI that we show here that continue to evolve, facial recognition, speech, natural language processing, rendering videos, helping the hearing impaired and eventually bringing augmented reality to the palm of your hand. It's quite incredible. So what does this mean for other parts of the IT stack? Well, we recently reported Satya Nadella's epic quote that "We've now reached peak centralization." So this graphic paints a picture that was quite telling. We just shared the processing powers exploding. The costs consequently are dropping like a rock. Apple's A14 cost the company approximately 50 bucks per chip. Arm at its v9 announcement said that it will have chips that can go into refrigerators. These chips are going to optimize energy usage and save 10% annually on your power consumption. They said, this chip will cost a buck, a dollar to shave 10% of your refrigerator electricity bill. It's just astounding. But look at where the expensive bottlenecks are, it's networks and it's storage. So what does this mean? Well, it means the processing is going to get pushed to the edge, i.e., wherever the data is born. Storage and networking are going to become increasingly distributed and decentralized. Now with custom silicon and all that processing power placed throughout the system, an AI is going to be embedded into software, into hardware and it's going to optimize a workloads for latency, performance, bandwidth, and security. And remember, most of that data, 99% is going to stay at the edge. And we love to use Tesla as an example. The vast majority of data that a Tesla car creates is never going to go back to the cloud. Most of it doesn't even get persisted. I think Tesla saves like five minutes of data. But some data will connect occasionally back to the cloud to train AI models and we're going to come back to that. But this picture says if you're a hardware company, you'd better start thinking about how to take advantage of that blue line that's exploding, Cisco. Cisco is already designing its own chips. But Dell, HPE, who kind of does maybe used to do a lot of its own custom silicon, but Pure Storage, NetApp, I mean, the list goes on and on and on either you're going to get start designing custom silicon or you're going to get disrupted in our view. AWS, Google and Microsoft are all doing it for a reason as is IBM and to Sarbjeet Johal said recently this is not your grandfather's semiconductor business. And if you're a software engineer, you're going to be writing applications that take advantage of all the data being collected and bringing to bear this processing power that we're talking about to create new capabilities like we've never seen it before. So let's get into that a little bit and dig into AI. You can think of AI as the superset. Just as an aside, interestingly in his book, "Seeing Digital", author David Moschella says, there's nothing artificial about this. He uses the term machine intelligence, instead of artificial intelligence and says that there's nothing artificial about machine intelligence just like there's nothing artificial about the strength of a tractor. It's a nuance, but it's kind of interesting, nonetheless, words matter. We hear a lot about machine learning and deep learning and think of them as subsets of AI. Machine learning applies algorithms and code to data to get "smarter", make better models, for example, that can lead to augmented intelligence and help humans make better decisions. These models improve as they get more data and are iterated over time. Now deep learning is a more advanced type of machine learning. It uses more complex math. But the point that we want to make here is that today much of the activity in AI is around building and training models. And this is mostly happening in the cloud. But we think AI inference will bring the most exciting innovations in the coming years. Inference is the deployment of that model that we were just talking about, taking real time data from sensors, processing that data locally and then applying that training that has been developed in the cloud and making micro adjustments in real time. So let's take an example. Again, we love Tesla examples. Think about an algorithm that optimizes the performance and safety of a car on a turn, the model take data on friction, road condition, angles of the tires, the tire wear, the tire pressure, all this data, and it keeps testing and iterating, testing and iterating, testing iterating that model until it's ready to be deployed. And then the intelligence, all this intelligence goes into an inference engine which is a chip that goes into a car and gets data from sensors and makes these micro adjustments in real time on steering and braking and the like. Now, as you said before, Tesla persist the data for very short time, because there's so much of it. It just can't push it back to the cloud. But it can now ever selectively store certain data if it needs to, and then send back that data to the cloud to further train them all. Let's say for instance, an animal runs into the road during slick conditions, Tesla wants to grab that data, because they notice that there's a lot of accidents in New England in certain months. And maybe Tesla takes that snapshot and sends it back to the cloud and combines it with other data and maybe other parts of the country or other regions of New England and it perfects that model further to improve safety. This is just one example of thousands and thousands that are going to further develop in the coming decade. I want to talk about how we see this evolving over time. Inference is where we think the value is. That's where the rubber meets the road, so to speak, based on the previous example. Now this conceptual chart shows the percent of spend over time on modeling versus inference. And you can see some of the applications that get attention today and how these applications will mature over time as inference becomes more and more mainstream, the opportunities for AI inference at the edge and in IOT are enormous. And we think that over time, 95% of that spending is going to go to inference where it's probably only 5% today. Now today's modeling workloads are pretty prevalent and things like fraud, adtech, weather, pricing, recommendation engines, and those kinds of things, and now those will keep getting better and better and better over time. Now in the middle here, we show the industries which are all going to be transformed by these trends. Now, one of the point that Moschella had made in his book, he kind of explains why historically vertically industries are pretty stovepiped, they have their own stack, sales and marketing and engineering and supply chains, et cetera, and experts within those industries tend to stay within those industries and they're largely insulated from disruption from other industries, maybe unless they were part of a supply chain. But today, you see all kinds of cross industry activity. Amazon entering grocery, entering media. Apple in finance and potentially getting into EV. Tesla, eyeing insurance. There are many, many, many examples of tech giants who are crossing traditional industry boundaries. And the reason is because of data. They have the data. And they're applying machine intelligence to that data and improving. Auto manufacturers, for example, over time they're going to have better data than insurance companies. DeFi, decentralized finance platforms going to use the blockchain and they're continuing to improve. Blockchain today is not great performance, it's very overhead intensive all that encryption. But as they take advantage of this new processing power and better software and AI, it could very well disrupt traditional payment systems. And again, so many examples here. But what I want to do now is dig into enterprise AI a bit. And just a quick reminder, we showed this last week in our Armv9 post. This is data from ETR. The vertical axis is net score. That's a measure of spending momentum. The horizontal axis is market share or pervasiveness in the dataset. The red line at 40% is like a subjective anchor that we use. Anything above 40% we think is really good. Machine learning and AI is the number one area of spending velocity and has been for awhile. RPA is right there. Very frankly, it's an adjacency to AI and you could even argue. So it's cloud where all the ML action is taking place today. But that will change, we think, as we just described, because data's going to get pushed to the edge. And this chart will show you some of the vendors in that space. These are the companies that CIOs and IT buyers associate with their AI and machine learning spend. So it's the same XY graph, spending velocity by market share on the horizontal axis. Microsoft, AWS, Google, of course, the big cloud guys they dominate AI and machine learning. Facebook's not on here. Facebook's got great AI as well, but it's not enterprise tech spending. These cloud companies they have the tooling, they have the data, they have the scale and as we said, lots of modeling is going on today, but this is going to increasingly be pushed into remote AI inference engines that will have massive processing capabilities collectively. So we're moving away from that peak centralization as Satya Nadella described. You see Databricks on here. They're seen as an AI leader. SparkCognition, they're off the charts, literally, in the upper left. They have extremely high net score albeit with a small sample. They apply machine learning to massive data sets. DataRobot does automated AI. They're super high in the y-axis. Dataiku, they help create machine learning based apps. C3.ai, you're hearing a lot more about them. Tom Siebel's involved in that company. It's an enterprise AI firm, hear a lot of ads now doing AI and responsible way really kind of enterprise AI that's sort of always been IBM. IBM Watson's calling card. There's SAP with Leonardo. Salesforce with Einstein. Again, IBM Watson is right there just at the 40% line. You see Oracle is there as well. They're embedding automated and tele or machine intelligence with their self-driving database they call it that sort of machine intelligence in the database. You see Adobe there. So a lot of typical enterprise company names. And the point is that these software companies they're all embedding AI into their offerings. So if you're an incumbent company and you're trying not to get disrupted, the good news is you can buy AI from these software companies. You don't have to build it. You don't have to be an expert at AI. The hard part is going to be how and where to apply AI. And the simplest answer there is follow the data. There's so much more to the story, but we just have to leave it there for now and I want to summarize. We have been pounding the table that the post x86 era is here. It's a function of volume. Arm volumes are a way for volumes are 10X those of x86. Pat Gelsinger understands this. That's why he made that big announcement. He's trying to transform the company. The importance of volume in terms of lowering the cost of semiconductors it can't be understated. And today, we've quantified something that we haven't really seen much of and really haven't seen before. And that's that the actual performance improvements that we're seeing in processing today are far outstripping anything we've seen before, forget Moore's Law being dead that's irrelevant. The original finding is being blown away this decade and who knows with quantum computing what the future holds. This is a fundamental enabler of AI applications. And this is most often the case the innovation is coming from the consumer use cases first. Apple continues to lead the way. And Apple's integrated hardware and software model we think increasingly is going to move into the enterprise mindset. Clearly the cloud vendors are moving in this direction, building their own custom silicon and doing really that deep integration. You see this with Oracle who kind of really a good example of the iPhone for the enterprise, if you will. It just makes sense that optimizing hardware and software together is going to gain momentum, because there's so much opportunity for customization in chips as we discussed last week with Arm's announcement, especially with the diversity of edge use cases. And it's the direction that Pat Gelsinger is taking Intel trying to provide more flexibility. One aside, Pat Gelsinger he may face massive challenges that we laid out a couple of posts ago with our Intel breaking analysis, but he is right on in our view that semiconductor demand is increasing. There's no end in sight. We don't think we're going to see these ebbs and flows as we've seen in the past that these boom and bust cycles for semiconductor. We just think that prices are coming down. The market's elastic and the market is absolutely exploding with huge demand for fab capacity. Now, if you're an enterprise, you should not stress about and trying to invent AI, rather you should put your focus on understanding what data gives you competitive advantage and how to apply machine intelligence and AI to win. You're going to be buying, not building AI and you're going to be applying it. Now data as John Furrier has said in the past is becoming the new development kit. He said that 10 years ago and he seems right. Finally, if you're an enterprise hardware player, you're going to be designing your own chips and writing more software to exploit AI. You'll be embedding custom silicon in AI throughout your product portfolio and storage and networking and you'll be increasingly bringing compute to the data. And that data will mostly stay where it's created. Again, systems and storage and networking stacks they're all being completely re-imagined. If you're a software developer, you now have processing capabilities in the palm of your hand that are incredible. And you're going to rewriting new applications to take advantage of this and use AI to change the world, literally. You'll have to figure out how to get access to the most relevant data. You have to figure out how to secure your platforms and innovate. And if you're a services company, your opportunity is to help customers that are trying not to get disrupted are many. You have the deep industry expertise and horizontal technology chops to help customers survive and thrive. Privacy? AI for good? Yeah well, that's a whole another topic. I think for now, we have to get a better understanding of how far AI can go before we determine how far it should go. Look, protecting our personal data and privacy should definitely be something that we're concerned about and we should protect. But generally, I'd rather not stifle innovation at this point. I'd be interested in what you think about that. Okay. That's it for today. Thanks to David Foyer, who helped me with this segment again and did a lot of the charts and the data behind this. He's done some great work there. Remember these episodes are all available as podcasts wherever you listen, just search breaking it analysis podcast and please subscribe to the series. We'd appreciate that. Check out ETR's website at ETR.plus. We also publish a full report with more detail every week on Wikibon.com and siliconangle.com, so check that out. You can get in touch with me. I'm dave.vellante@siliconangle.com. You can DM me on Twitter @dvellante or comment on our LinkedIn posts. I always appreciate that. This is Dave Vellante for theCUBE Insights powered by ETR. Stay safe, be well. And we'll see you next time. (bright 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.

>>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, 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 John and myself met with Jim Hempleman 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 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 to go to market and customer success and support. So really, on many fronts, that's with 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 your business going to sas what 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 company. That's been around as long as PTC. So So I'm wondering how much you know, I was just asking you what PC PTC brought 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 sales people, 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 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 customers? 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 or their distribution channels, 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, you 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 with 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 that'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. And 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 imagined, 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. 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, it was 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 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, was Are 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 the 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 could 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 off where to an engineer, >>that's a great story, and and again, it's gotta be exciting for you guys to see that on day with the added resource is that you have a PTC eso. Let's talk. I promise people we want to 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 cloudlike 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 diversions, 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 misty initiation 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 back in the mid 19 eighties, this 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 in data flowing through the ecosystem, powering you 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 with 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 interactions and everything that they dio 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 an 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 the top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of of 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, 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 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 501st 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 got 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 overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>The 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. Uh, 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. Who's >>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 to 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.

>>live from Boston, Massachusetts. It's the Q covering I. F s World Conference 2019. Brought to you by I. F. S. >>Welcome back to Boston, everybody. You're watching The Cube. The leader in live tech coverage is Day one coverage of the I. F s World Conference. Darren Russo's here is the CEO of F S Darren. Thanks for coming back in the Cube. Great TV again. So last year was your first year. He was kind of laid out your vision at the World Conference. How's progress? >>Yeah, Look, it's going incredibly well. We were really focused on how we go from being a pretty fragment of global business to being, you know, an integrated business where we were able to operate. You know, its scale globally in a very homogenous way, where the customer experience was the same, irrespective where they engaged with us. And, you know, we've made a tremendous amount of progress with it, So you know, the business is growing really strongly. Net revenues up 22% year on year. I lost its revenues up 40% year on year are clouds up in the triple digits, so you know it's tough to be critical of how it's going so far. >>That's great, Great. You're growing faster than your peers. I think the stat was you gave us three Ex factory except in the industry would be awesome. Is that means that your primary benchmark do you want? You want to gain share? You want to go faster than the big whales, I presume. I >>think two things One is customer satisfaction, we believe, is the key indicator of long term success. S O. You know, we're the number one ranked European efforts. Salmon gotten appearance sites. That's that is and always will be my number. One metric. Can we be way the number one from a customer satisfaction perspective? And then I believe the revenue stats will follow and you know that's where we are. So certainly, if you look at our our core peers, the big G R P vendors, all of them are flat on. Dhe were growing 20 ships since >>one of the things you mentioned in your Cube interview last year was one of the things that you wanted to focus on was I'll call regional alignment. Paul and I used to work for I D. G. I worked for I. D. C. You were editor in chief of Computer World. We work for a company, had more offices overseas and IBM, and it was really hard to herd the cats. And that was one of the things that you cited. Have you been able to get people generally poor or at the same time? And how has that affected your business? Yeah. Look, I >>think the big challenge before I arrived was that there wasn't really a strategy of global strategy for the business. My face had a way of working and there was a strong culture, but there wasn't really a strategy. And obviously it's difficult to be critical of people when they not following the strategy when there isn't one s o. You know, Step one was really making sure that we had a strategy on DDE that was really about being focused on the five industries that we focused on, focused on three solutions on dhe focused on the six segments of customer, which is half a 1,000,000,000 to 5 billion. So now, globally, you know, irrespective the office that you go to, um anywhere in the world, they're focused on those five industries they focused on those three solutions and they're focused on their customer segments. So it helps me. P. M >>I said during our preview video video this morning that I've been around this industry as long as I f s has, until last year had never even heard of it. Is that just me being clueless? There's something there >>that we were just saying before we started that we're the definitely the biggest software business you've never heard of. Um, and and and that's common, I think, you know, we were There are a couple of factors. One is that the business was very European centric. Andi didn't really engaged in a tremendous amount of marketing and media prison. So, you know, those are elements that, you know, I think we're doing a better job off now, But we have a long way to go. The challenge that we have is that where we compete, we win when we get in and were able to tell our story, and we're able to show the value we win. We just don't get into as many deals as we need to. And that's the challenge we have. >>Yeah, there was a lot of talk this morning about the importance of those five pillars of those five industries. If you're going to become the next S A P, you're gonna have to branch out beyond that. What is your thinking about diversify >>becoming the next? They say he is definitely not my ambition, You know, I think way remain focused on customer satisfaction. And, you know, I think that there's a there's a difference. Whatever it is leading them, it's not customer satisfaction. You worked >>there for four years. >>I worked there for four years. I know. I think the big thing for me is is that we've got to stay focused on their customer voice. They focused on what delivers value for our customers beyond just the rhetoric and hyperbole. You know, I think when you when you listen to a lot of the complexity that our customers are facing today, any customers are facing. Companies are facing increasingly disruptive times, and the tech industry is making life more difficult for them. The more best of breed solutions get both. The more fragments that potential the landscape is, the more complex it becomes for customers if they have to try and figure out. How do we integrate these things and derive value from this highly fragmented landscape? So you know, we're trying to solve that problem. How do we make it easier for customers to challenge in their industry? And that's where this whole for the challenges has check comes from. How do we help him to be disruptive in their industry? Have competitive advantage? >>That seems to be a sort of a fundamentally different thing about your approach, though. Is this focus on those vertical industry's most e r P companies did not do that. Is that something that is core to your values? >>Look, I >>think what we recognize is that as you move to the cloud, you have to drive to standard. That's just the reality of going to the cloud on what's happening for the horizontal E. R B vendors. So the locks of ASAP and Oracle is that they have one e r P solution that fits every industry. So if it's good for health insurance and it's good for a bank, then it's difficult to really get your head around the fact that it could be good for a defense manufacturer, but the functional requirements is simply vastly different on that means that you have to customize them. If you have to customize that, they can go to the cloud. So what we believe is that you have to have this vertical specialization, the five industries that we serve us all. A lot of commonality in the process is that they use. And that's why that vertical strategy is so key to our success. So you won't see us going into financial service is, or health care or retail worth that core application. We may in time in many years to come branch out. That will be a different solutions. >>So your tailor, that app for that module for that industry, Yes, just go deep, deep functionality. You're known for that, but at the same time you're also messaging. You want your customers to be able to tailor this for their environment. So square that circle for me. >>So I think when we talk about a choice and and I think tailoring is the wrong word, we talk about choice. We're talking about choice of deployments on Prem or in the cloud choice of customer choice of partner, rather who they're going to deploy with on Dhe, then The solution is really an industry solution that comes with that functional death. And we don't we don't advocate their customers customized that all. We really don't want them to customize it. What we explain to them in some detail is that the real value comes from adopting the solution for two standard and staying on a vanilla application. Because that vanilla application, you're going to be able to withstand future upgrades, the total cost of ownership gets lower. The processes that are embedded in that application or best of breed at the box. That's what they're intended to do, and that works when you have a vertical application. When you have a horizontal application and you're trying to have a do things that it shouldn't naturally be doing, that becomes company. >>Well, correct me if I'm wrong, but wasn't that essentially the message ASAP had when it went through? It's hyper growth in the late nineties. I mean, there was a Y two k thing there, too, but ah, lot of the message was around. Do it our way and and then you don't have to get stuck in a rut, >>So I think that when it came out with that generation of application. That certainly was what they had hoped would happen. But what happened in practice is that the system integrators came in and the whole business process reengineering explosion happened on Dhe. That's not how it how it manifested itself. So what you see is, you see, he's very large, monolithic ASAP applications that were customized over in some cases decades, not not. You know, if a customer is deploying for two standard, then they should be able to deploy in a period mission. In weeks, we spoke about our deployment with Racing Point. If one team and going live in 12 weeks, you know, we're a 700 million global business. We deployed a knife s in 24 weeks. You know, if a customer's deploying for two standard, it's measured in weeks. As soon as they start to talk about two years or three years or five years or seven years there, customizing the solution significantly. Yeah, I >>mean, it became just sort of a perpetual upgrade, maintenance and up for the time it had a business impact. But boy, you think a cloud today agility, you know, getting rid of waterfall approaches, Missus. Antithetical to today's Look >>what I don't point fingers here. I think that this just maturity come with experience. The line of business applications you'll see our EMS and your HR solutions have taught people that you can, if you think about this is look at sea. Are Emma's an example? You had Siebel before people would implement stable. They would customize Siebel that would take long implementations. They were highly bespoke applications and then sells. Force came along and just destroyed them, and they destroyed them. Because what people learned very quickly was that there was a really easy to consume, really easy to use application that functionally might be inferior. But the compromises that you'd make from a functionality perspective will weigh, outweighed by their time to value in ease of use. And and the learnings from CR mnh are in procurement. Those line of business applications have now being backed into in the e. R. P >>world. So in terms of capital allocation, you're owned by private equity, which is actually a public company. I'm interested in how you're allocating capital R and D, where you're where your emphasis is. You don't have to you have to do stock buy back, but, you know, describe the P relationship. >>So look, one of my learning's to see survive this is that not all private equity firms or equal they have different strategies are very fortunate to be with Ekiti, who are a growth investor. They're known as a growth investor on dhe, and they buy companies that are strong growth tech firms on dhe. They've been hugely supportive of us investing because they understand that the investment in technology is important. So, you know, just looking at some detail today we invest twice as much in R and D as we did three years ago, just to give you, you know, one data point. So there's a big focus on technology, and the thing is, is that we we have to invest in technology to drive those attributes that are discussed earlier. How do we How do we enable customers to adopt a solution? It's a standard so they can go alive quicker. How do we enable customers to be able to sit down in the front of the application like we do with the mobile phone and intuitively know how to use it? How do we reduce the total cost of ownership through automation. Those are capabilities that you know that they don't come for free. We have to invest in them. So big investments in technology. And >>I think the private equity guys, at least the modern ones, have realized Why should the V. C's have all the fun they realize? Hey, we can actually put some money in tow and the transforming we can have a bigger exit and actually make much better returns than sucking the company drive. Yeah, well, look, I think the other >>thing is is that you know, in public companies, you have the downside off. You know this this courtly metric Ondas quarterly cadence. Andi, you see very compromising decisions being made because you know, people can't afford to miss 1/4. There's no long term planning that's done on dhe. That's fundamentally not the case and the private equity world, you know, not unusual now for four p firms to hold companies for 5678 years on, and that allows you to take a very long term strategic view. If if if a shift from perpetual to subscription is the right thing to happen, they can do that without worrying that, you know, because of the definite earnings are revenue that you're going to get caned by the market next quarter. Andi. I think that that needs to, I think, better decision making for the long term. >>A lot of companies are struggling. >>If you have the right P for because you get bought by the firm of events, you want to go public. But the the you said something this morning that 50% of your customers each year or net knew, How are you pulling that off >>That 50% of our license revenue? Eso way we went about 300 odd new customers a year. Obviously, that's growing, as I said, you know, 40%. But you know, it's ah, I think, having done this for 25 years, there are companies that are or good at extracting revenue from their installed based. One of the analysts here has as a hashtag wallet Fracking is what do you think It's such a great So you know, they're good at Wallick fracking and and I think the customers that that our customers off those vendors know exactly who they are and you know I think that for us to that the fact that we're able to go out and win 50% of our license revenue from net new name customers, I think is a really strong indicator of the health of the business. It's much harder to do than just extracting revenue out of the install base. You know, we don't have a compliance practice. We've never charged a customer for you in direct access. You know, these are principles that we stand by, and it's easier to say that your customer centric on get 80% of your revenue, have your installed base because you're doing compliance rounds. But, you know, we put our money where our mouth is, and that's not that's not how we do it. >>Are these net new customers? Are they? Are they migrating from QuickBooks or they migrating from a Competitors >>know, because of the segment that we're in this half a 1,000,000,000 to 5 billion? I would say the majority of them are what I would call first generation the Rp solution. So you know you're talking about you know, the original generation of Microsoft's acquisitions, the divisions and the eggs actors and the Solomon's and so on on. And then, you know, it's a P R two and our three customers you're talking about customer sitting on, you know, the solutions that in for hoovered up the matrix B picks type customers, ace 400 customers. So they're you know, they're first generation your P solutions that simply don't have the flexibility to deal with the complexity and demands of modern business world. >>From 2009 about 2017 I f. S was pretty inquisitive and then just actually, I was gonna ask you >>when I started, you stopped >>it, right? But then, you know, today you announced an extra small acquisition, But how should we think about M and a >>look? The first year for me was really about trying to build a functional business. You know, we spoke about how fragmented this really hit to Jenna's business. Andi just occurred to me. You know, if we go out and we start to buy things, how do we integrate them into a business that's completely fragments? And you know, it had no identity or culture. So, you know, the last year has been focused on how do we build their common understanding of what it is that we're doing. We now have a very clear strategy. Five industries, three solutions, one segment. And you know, when you when you have that clarity of vision that it's really easy to guard and do him and I because you know what fits and what doesn't fit, you can understand exactly how you're gonna build value for customers on dhe. That's why the S t a deal is so good for us. Because we're now the undisputed leader in field service management, you know, 8000 our customers globally, which is way more than anybody else. Scott, Andi, you know, you should absolutely expect more from us. But it will be in the five industries, three technology segments and one customers. Isaac. >>Well, in the A p I enablement should obviously facility. >>Absolutely. I mean, I was just with a partner of ours now, and they have this amazing augmented reality solution. You know, it will be a combination of off going out there to build market, share a cz well, as finding you know, really innovative solutions that can help us advance the technology that we provide customers. >>You have a new slogan this year for the challengers, which seems to be aimed at companies that that imagine themselves as challenging the Giants, which is great. But if you're not a company that season sees themselves that way. Are the studies level home with I have s Look, >>I I think I was with a group of CEOs from one of the big analyst rooms, and they had the portfolio companies and their private equity firm and analysts that CEOs of the companies are having a conversation with him about digital transformation. And I I made a rather provocative statement which, you know, got unanimous agreement, which is that all of the CEOs there with either in an industry that was being disrupted and we're trying to figure out how they respond to that disruption or they would soon not every job and they all acknowledge that they absolutely fit into that category. In other words, all of them were being disrupted. All of them were facing a challenge. It was kind of like, you know, if it is happening to all of us at a more rapid pace than we have ever had before. So my view is, is that you know if if you're in the room and you're going, you know, if it's might not be for us because we're not a challenger. Yeah, The lights may not be on >>for Long s o double click on that. What role does I s play in terms of digital transformation? >>If I could just hold on there because the thing is, there are leaders in Mama, there challenges. And there are leaders. The leaders typically are gonna go with seif solution. They're gonna go with one of the legacy our peace. So I'm not suggesting that everybody necessarily is a challenger. There are leaders, you know, Nokia was a leader until they weren't because they were complacent. Andi, I think they you know, they didn't run on I office. So, you know, I think there are two segments. There are leaders and there are challenges, and we're there for the ones that are ready to disrupt. Sorry. >>Please clarify that. No. Good. So So get back to it. Sort of digital transformation and disruption. What do you see? Is the role of AARP generally, but specifically I f s. >>Look, I think we digital information. A lot of discussion about it on the stage this morning. I've just touched on it now. I think that it takes very different forms. What most industries are finding is that they're facing a lot of non traditional competition and they're having to innovate around their business models. They can't going to market in the same way as they did before. They're having to innovate because of this non traditional competition. Andi. Understanding your your customer's understanding, your your staff, understanding your supply chain understanding your financials are all critical parts of being able to respond to whatever their changes, and that's where the RP solution comes into it. I think there's an interesting challenge now, which is that as those applications have become more fragmented and you've got more based debris cloud applications Ah, lot of the value often E. R P was that you had this integrated set of applications that you had this one source of the truth andan. Fortunately for many customers today, they don't have that because they've got import all of these best of breed applications and they don't have one source of the truth that multiple invoices made it multiple versions of their customer in the databases. Andi we still stand for a single integrated the r p. So, you know, I think understanding those elements of your businesses key. I was with a customer of ours in Nebraska a short while ago, and they were talking about our existing office customer. They were talking about the steel import duties that were imposed through the trade war with China. And they were saying, Look, that they had been able to respond to that in a way that they had good visibility of the supply chain, who was improved, imposing the tariffs, how they were going to impact them when they were going to impact them. And because they had this integrated Siara AARP. They were able to pass those pricing changes onto their customers, and they survived this. What could have been a cataclysmic event for their business had they not had an integrated your pee? They not being able to have this visibility into the supply chain and the customer base. They may well have gone out of business just because of that one change >>to meet all day and all comes back to the data, putting their putting data at the core of their business. That integrated data pipeline is essentially what they get out of that last question. So thinking about the next 18 to 24 months, what are the milestones that observers should look for? One of the barometers that we should be watching. >>So look, in the next two years, it's it's really about us building incremental scale. We have, ah, four year plan, which I built when I came in. We're halfway through that plan. We've hit all of the metrics and exceeded most the metrics that we had on their plan. It's really continue to focus on the strategy. As I said, we focus on those five industries, continue to build market share, continue to focus on those three solution types and build market share and market dominance on those three solutions. Andi in that segment that I defined before, so no change from a strategy perspective. I think there's really value in the consistency that we bring on on their talk track and, you know, along the way we passed the $1,000,000,000 mark, which we will do, I think, in 2021 organically if we accelerate, some of the money will pass the 1,000,000,000 before, but you know business. The margins continue to expand. We focus on customer satisfaction and, you know, it's a It's a pretty straight, you know, traditional prey book that we have to execute on now. >>Well, congratulations. It's a great playbook, and you're growing very nicely. So love that. Look, we really an honor to the last couple of years. Learn a little bit about the company in your industry. So appreciate meeting you guys. Thank you. All right. And thank you for watching over right back with our next guest. Ready for this short break day Volonte with Paul Gill in. You're watching the Cube from I f s World Conference from Boston 2019 right back.

>> from atop the Salesforce Tower in downtown San Francisco. It's the Q covering Accenture Innovation Date brought to you by ex center >> Hey, welcome back Your body jefe Rick here from the Cube were high atop San Francisco in the essential innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. They worry about security and all kinds of other things. So centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but you're absolutely Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to which all of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know, you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in here, and everyone all right, everyone's >> had a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember We used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service. Now I mean, we went through on premise collaboration, email todo 360 5 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really start to see some scale around it >> and tell me if you agree. I think really, what? The sales forces of the world and the service now is of the world off. 3 65 kind of broke down some of those initial barriers which were all really about security and security. Security secure. It's always too here where now security is actually probably an attribute >> and loud can brink Absolutely. In fact, I'm in those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service. Now to put you know instances on Prime, and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know, there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when you happen to sail sports, it's a lot harder. And so you know. So I think that security problems, I've certainly got away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it's all by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the public domain, right? Not public. >> I think it also help them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So Let's back up 1/2 a step cause then, as you said, a bunch of stuff then went into Public Cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be. Um, but then we ran into a whole new home, Those of issues, right, Which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds there certain attributes that you need to think about and yet from the application point of view, before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How, after they think about what to deploy where I >> think I'll start in the, You know, Larry has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspectives. You got to take a look at you know where your applications have to live water. What are some of the data implications on the applications or do you have by way of regulatory and compliance issues? Or do you have to do as faras performance because certain applications have to be in a high performance environment? Certain other applications don't think a lot of these factors will then drive where these applications need to recite. And then what we're seeing in today's world is really accomplish. Complex, um, situation where you have a lot of legacy, but you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know, clients typically have application portfolios ranging from 520,000 applications. And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms. Guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications going to evolve with its 520,000 and determined hey, and usually using some like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi in and, you know, hybrid cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, et cetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we're gonna modernize that >> it hadn't had a you segment. That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size? Where they should be focusing on. Yes, >> it. Typically, what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications have moved to sass certain other applications you moved past. So you know, you're basically doing the re factoring and the modernization, and then certain others, you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, where is cost savings? Where is, uh, this is just old and where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. >> If >> you could go back three or four years and we had there was a lot of CEO discussions around cost savings. I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get, get new capabilities, market faster to change my customer experience. So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. So we're seeing a huge shift in emphasis or focus at least starting with, you know, how do I get better business agility outta leverage to cloud and cloud native development to get there upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress, So obviously cost still remains a factor, but we seem much more, you know, much more emphasis on agility, you know, enabling the business on giving the right service levels of right experience to the user. Little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds. Easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define them? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talk to my clients and our partners, I think we're all starting to come toe. You know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific workload >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera, so that's the innovations. There obviously agility. You could spend up environments very quickly which is, you know, one of the big benefits of it. The consumption economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it performance, you know, if you think the public world, you know, although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business critical workloads like that article, article rack. You know, the Duke clusters everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terrified Hana database, you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The Laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, You know, as we start to look at the world a lot, there's a ton of Could still living in, You know, whether it's you, Nick system, that IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right. And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take the reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or every three or four days for my mobile application and It's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, but we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're saying is this emerging approach where I can start to take advantage of the innovation cycles that land is that you know, the red shifts the azure functions of the public world. But then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip data that I need to worry about GDP are you know, the whole set of regular two requirements Over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're Still not a number of clients are still, you know, not 100% comfortable from rail client's perspective. >> Gotta meet Teresa Carlson. She'll change him. Who runs that AWS Public Sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this thing. This hotel example that you use because it's is, you know, kind of break in the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move Works fine. Be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where but finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it, the business value, replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and you know the micro service's architecture now. D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The the innovation cycles by public. Bye bye. Wrapping my legacy environment >> in person, you rated jump in and I'll give you something to react to, Which is which is the single glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications and the thing that you just described and everyone wants to be that single pane of glass Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers. Goto private cloud and so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, the cantinas and Cuban Edie's. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients. >> Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promise of cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that one application for the hotel, they're actually started, and they've got some actually, now running a native us of their containers and looking at serverless. So you gonna even a single application can span that and one of things we've seen is is first. You know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application. You know, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talked it. It's a very well, despite the power, very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, application service is teams that do the application manager an optimization cloud infrastructure, you know, how do we get better alignment that are embedded security, You know, how do you know what are managed to Security Service's and bringing those together? And then what we did was we looked at, you know, we got very aggressive of cloud for a strategy and, you know, how do we manage the world of public. But when looking at the public providers of hyper scale er's and how they hit incredible degrees of automation, we really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys they're doing that? We came up with this concept We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy environment and started looking say OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl and >> my business is so unique. The Larry no business out there has the same process that we have. So we started make you know how to be >> standardized like center hybrid cloud solution apart with HP. Envy em where we, you know, how do we that was an example. So we can get thio because you can't automate unless you standardise. So that was the first thing you know, standardizing service catalog. Standardizing that, um, you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now, but truly putting the security and and operations into Deb set cops of bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're writing the automation script to take work, you know, test work out. Right. And over time, they'll be tuned in the air. Aye, aye. Engines to really optimize the environment and then finally has presided. Looted thio. Is that the platforms that control planes? That doing that? So, you know, we What we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms and then the application teams with it with our my wizard framework, and we've been starting to bring that together. You know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide, you know, automation Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a iob is right. I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops, that's what we use. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control, I reporting et cetera. Right >> Exactly. Then can plug in and integrate, you know, third party tools. I had to do some strategic function. >> I'm just I'm just >> curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app. Some of them are coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds, that just with the wrong it was just the wrong application? The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, >> I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options, like Aunt Ours and out pulls and other stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that and you see many more options around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, you know, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know, that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed that look >> e. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were big cap ex businesses, and all of a sudden they're using this consumption consumption model. And they weren't really They didn't have a function to go and look at the thousands or millions of lines of it, right? You know, as your statement, exactly think they misjudged, you know, some of the scale on B e e. I mean, that's one of the reasons we started. It's got to be an application lead modernization that really that will dictate that. And I think in many cases, people didn't may not have thought through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. You know, I've got a 64 terabyte hana, and that's the core. My crown jewels. That data, you know, how do I get that to tensorflow? How'd I get that >> right? But if Andy was >> here, though, Andy would say, we'll send down the snow. The snow came from which virgin snow plows Snowball snowball. Well, they're snowballs. But we've seen the >> hold of a truck killer >> that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they you know they're pushing. Get that date end in this single source course than to move it, change it, you know you run it. All these micro lines of billing statement take >> the hotel. I mean, their data stolen the mainframe. So if they may want need to expose it? Yeah, they have a database cash, and they move it out. You know, the particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue. Because no matter how much you know, while Moore's law might be might have elongated from 18 to 24 months, the network will always be the bottle, Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better than network becomes more of a bottleneck. Conned. That's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get. Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith o r. Right Or, you know, highlight and see type or so egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know that That's been a big issue. >> You know, it's funny, I think, and I think a lot of the issue, obviously complexity building. It's a totally different building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it. And they're running in the data center in this kind of this. Turn it on, turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But but the kind of clothes on our conversation I won't talk about a I and applied a I. CoSine is a lot of talk in the market place, but a time machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely completely agree with you in fact. Ah, essential. We actually referred to the Seoul area as Applied intelligence. Ah, and that's our guy, right? And, uh, it is absolutely to add more and more automation Move everything Maur toe where it's being run by the machine rather than, you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environment is important, right? What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken routing, et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space. Less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, and then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate ones who then tune the aye aye engines that will manage our environment, right. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement between >> when the best thing to you. Then you have dynamic optimization can. You might be up to my tanks at us right now, but you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending >> when you got you got to see them >> together with it. And multi dimension optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the table. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you. Raise Prasad is Larry. I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower. Theis Center. Innovation have in San Francisco. Thanks for watching. We'll see you next time

>> Hey, welcome back. Your body, Jefe Rick here from the Cube were high atop San Francisco in the century innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. There were about security and all kinds of other things, so centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but yeah, absolutely. Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to reach. All of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in >> everyone's, you know, everyone's got a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember we used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service now. I mean, we've went through on premise collaboration, email thio 3 65 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really started. See some scale around it. >> And I think and tell me if you agree, I think really, what? The sales forces of the world and and the service now is of the world office 3 65 kind of broke down some of those initial beers, which are all really about security and security, security, security, Always to hear where now security is actually probably an attributes and loud can brink. >> Absolutely. In fact, I mean, those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service Now to put, you know, instances on prime and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when Europe into sales force, it's a lot harder. And so you know. So I think that security problems have certainly gone away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it sold by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the in the public domain, right? Not public. >> And I think it also helped them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So let's back up 1/2 a step, because then, as you said, a bunch of stuff then went into public cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be, Um, but then we ran into a whole new host of issues, right, which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds. There's certain attributes is that you need to think about and yet from the application point of view before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How should they think about what to deploy where I think >> I'll start in? The military has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspective. You go to take a look at you know where your applications have to live water. What are some of the data implications on the applications, or do you have by way of regulatory and compliance issues, or do you have to do as faras performance because certain applications have to be in a high performance environment. Certain other applications don't think a lot of these factors will. Then Dr where these applications need to recite and then what we think in today's world is really accomplish. Complex, um, situation where you have a lot of legacy. But you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know how clients typically have application portfolios ranging from 520,000 applications? And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms, guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications gonna evolve with its 520,000 and determined hey, and usually using some, like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And, you know, I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi and, you know, every cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, etcetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we gonna modernize that >> it had. And how do you segment? That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size where they should be focusing on us? >> So typically what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications he moved to sass certain other applications you move to pass. So you know, you're basically doing the re factoring and the modernization and then certain others you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have to initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, um, where is cost savings? Where is, uh, this is just old. And where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. If >> you could go back through four years and we had there was a lot of CEO discussions around cost savings, I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get getting your capabilities to market faster, to change my customer experience. So So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. We're seeing a huge shift in emphasis or focus at least starting with, you know, how'd I get better business agility outta leverage to cloud and cloud native development to get their upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress. So So Obviously, cost still remains a factor, but we seem much more for, you know, much more emphasis on agility, you know, enabling the business on, given the right service levels of right experience to the user, little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds, easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define him? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talked more clients and our partners, I think we're all starting to, you know, come to ah, you know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific look >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera. So that's the innovations there obviously agility. You could spend up environments very quickly, which is, you know, one of the big benefits of it. The consumption, economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it, um, performance if you think the public world, you know, Although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business. Critical workloads like that article, article rack, the Duke clusters, everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terabyte Hana database you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, you know, as we start to look at the world a lot, there's a ton of code still living in, You know, whether it's you, nick system, just IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right? And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take their reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now, when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or everything three or four days for my mobile application. And it's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, But we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're seeing is this emerging approach where I can start to take advantage of the innovation cycles. The land is that, you know, the red shifts the functions of the public world, but then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip, a data that I need to worry about GDP are there, you know, the whole set of regular two requirements. Now, over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're still not a number of clients are still, you know, not 100% comfortable from my client's perspective. >> Gotta meet Teresa Carlson. She'll change him, runs that AWS public sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this in this hotel example that you use because it's is, you know, kind of breaking the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move. Works fine, be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where? But finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it the business value of replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and in a micro service's architecture now D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The innovation cycles by public. Bye bye. Wrapping my legacy environment >> and percent you raided, jump in and I'll give you something to react to, Which is which is the single planet glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications in the and the thing that you just described and everyone wants to be that single pane of glass. Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you will Yeah, >> I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers go to private cloud. And so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, cantinas and Cuba needs. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients, >> right? Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promises, cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that that one application for the hotel, they're actually started in. They've got some, actually, now running a native us of their containers and looking at surveillance. So you're gonna even a single application can span that. And one of things we've seen is is first, you know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM, where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talk to it. It's a very well. Despite the power, it's a very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, Application Service's teams that do that Application manager, an optimization cloud infrastructure. How do we get better alignment that are embedded security, You know, how do you know what are managed to security service is bringing those together. And then what we did was we looked at, you know, we got very aggressive with cloud for a strategy and, you know, how do we manage the world of public? But when looking at the public providers of hyper scale, er's and how they hit Incredible degrees of automation. We really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys we're doing that We came up with this concept. We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy, environment, and start a look and say, OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl >> and my business is so unique. The Larry no business out there has the same process that way. So >> we started make you know how to be standardized like center hybrid cloud solution important with hp envy And where we how do we that was an example of so we can get to you because you can't automate unless you standardise. So that was the first thing you know, standardizing our service catalog. Standardizing that, um you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now. But truly putting the security and and operations into Deb said cops are bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re Skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're riding the automation script to take work, you know, test work out right. And over time they'll be tuning the aye aye engines to really optimize environment. And then finally, has Prasad alluded to Is that the platforms that control planes? That doing that? So, you know what we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms, and then the application teams with it with my wizard framework, and we started to bring that together you know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide. You know, it's automation. Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a I ops, right? I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops. That's what we you A ups. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control? Aye, aye. Reporting et cetera. Right? >> Exactly. Then can plug in and integrate, you know, third party tools to do straight functions. >> I'm just I'm just curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app, something we're coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds that just with the wrong. It was just the wrong application. The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options like an tars and out pulls an actor stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that, then you see many more options around around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed. That left >> E. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were a big cap ex businesses, and all of a sudden they're using this consumption, you know, consumption model. And they went, really, they didn't have a function to go and look at be thousands or millions of lines of it, right? You know, as your statement Exactly. I think they misjudged, you know, some of the scale on Do you know e? I mean, that's one of the reasons we started. It's got to be an application led, you know, modernization, that really that will dictate that. And I think In many cases, people didn't. May not have thought Through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. And if I've got a 64 terabyte Hana and that's the core, my crown jewels that data, you know, how do I get that to tensorflow? How'd I get that? >> Right? But if Andy was here, though, and he would say we'll send down the stove, the snow came from which virgin snow plows? Snowball Snowball. Well, they're snowballs. But I have seen the whole truck killer that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they, you know, they're pushing. Get that date end in this single source. Of course. Then to move it, change it. You know, you run into all these micro lines of billing statement, take >> the hotel. I mean, their data stolen the mainframe, so if they anyone need to expose it, Yeah, they have a database cash, and they move it out, You know, particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue because no matter how much you know, while Moore's Law might be might have elongated from 18 to 24 months, the network will always be the bottle Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better. The network becomes more of a bottleneck. And that's a It's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith. Oh, all right. Or, you know, highlight and see type. Also, egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know, that's being a big issue, >> you know, it's funny, I think, and I think a lot of the the issue, obviously complexity building. It's a totally from building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it and they're running in the data center in this kind of this. Turn it on, Turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But it kind of close on our conversation. I won't talk about a I and applied a Iot because he has a lot of talk in the market place. But, hey, I'm machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. Yeah, yeah, >> absolutely. Completely agree with you. In fact, attack sensual. We actually refer to this whole area as applied intelligence on That's our guy, right? And it is absolutely to add more and more automation move everything Maur toe where it's being run by the machine rather than you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environments comported right. What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken rounding et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space, less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, And then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate one too. Then tune the aye aye engines that will manage our environment. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement. You know, between >> when the best thing to you, then you have dynamic optimization. Could you might be optimizing eggs at us right now. But you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending when you got me. They got to see them >> together with you and multi dimension. Optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the tables. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you, Grace. Besides Larry, I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower, Theis Center, Innovation hub in San Francisco. Thanks for watching. We'll see you next time.

>> Hey, welcome back. Your body, Jefe Rick here from the Cube were high atop San Francisco in the century innovation hub. It's in the middle of the Salesforce Tower. It's a beautiful facility. They think you had it. The grand opening about six months ago. We're here for the grand opening. Very cool space. I got maker studios. They've got all kinds of crazy stuff going on. But we're here today to talk about Cloud in this continuing evolution about cloud in the enterprise and hybrid cloud and multi cloud in Public Cloud and Private Cloud. And we're really excited to have a couple of guys who really helping customers make this journey, cause it's really tough to do by yourself. CEOs are super busy. There were about security and all kinds of other things, so centers, often a trusted partner. We got two of the leaders from center joining us today's Prasad Sankaran. He's the senior managing director of Intelligent Cloud infrastructure for Center Welcome and Larry Soccer, the global managing director. Intelligent cloud infrastructure offering from central gentlemen. Welcome. I love it. It intelligent cloud. What is an intelligent cloud all about? Got it in your title. It must mean something pretty significant. >> Yeah, I think First of all, thank you for having us, but yeah, absolutely. Everything's around becoming more intelligent around using more automation. And the work that, you know we delivered to our clients and cloud, as you know, is the platform to reach. All of our clients are moving. So it's all about bringing the intelligence not only into infrastructure, but also into cloud generally. And it's all driven by software, >> right? It's just funny to think where we are in this journey. We talked a little bit before we turn the cameras on and there you made an interesting comment when I said, You know, when did this cloud for the Enterprise start? And you took it back to sass based applications, which, >> you know you were sitting in the sales force builder. >> That's true. It isn't just the tallest building in >> everyone's, you know, everyone's got a lot of focus on AWS is rise, etcetera. But the real start was really getting into sass. I mean, I remember we used to do a lot of Siebel deployments for CR M, and we started to pivot to sales, for some were moving from remedy into service now. I mean, we've went through on premise collaboration, email thio 3 65 So So we've actually been at it for quite a while in the particularly the SAS world. And it's only more recently that we started to see that kind of push to the, you know, the public pass, and it's starting to cloud native development. But But this journey started, you know, it was that 78 years ago that we really started. See some scale around it. >> And I think and tell me if you agree, I think really, what? The sales forces of the world and and the service now is of the world office 3 65 kind of broke down some of those initial beers, which are all really about security and security, security, security, Always to hear where now security is actually probably an attributes and loud can brink. >> Absolutely. In fact, I mean, those barriers took years to bring down. I still saw clients where they were forcing salesforce tor service Now to put, you know, instances on prime and I think I think they finally woke up toe. You know, these guys invested ton in their security organizations. You know there's a little of that needle in the haystack. You know, if you breach a data set, you know what you're getting after. But when Europe into sales force, it's a lot harder. And so you know. So I think that security problems have certainly gone away. We still have some compliance, regulatory things, data sovereignty. But I think security and not not that it sold by any means that you know, it's always giving an ongoing problem. But I think they're getting more comfortable with their data being up in the in the public domain, right? Not public. >> And I think it also helped them with their progress towards getting cloud native. So, you know, you pick certain applications which were obviously hosted by sales force and other companies, and you did some level of custom development around it. And now I think that's paved the way for more complex applications and different workloads now going into, you know, the public cloud and the private cloud. But that's the next part of the journey, >> right? So let's back up 1/2 a step, because then, as you said, a bunch of stuff then went into public cloud, right? Everyone's putting in AWS and Google. Um, IBM has got a public how there was a lot more. They're not quite so many as there used to be, Um, but then we ran into a whole new host of issues, right, which is kind of opened up this hybrid cloud. This multi cloud world, which is you just can't put everything into a public clouds. There's certain attributes is that you need to think about and yet from the application point of view before you decide where you deploy that. So I'm just curious. If you can share now, would you guys do with clients? How should they think about applications? How should they think about what to deploy where I >> think I'll start in? The military has a lot of expertise in this area. I think you know, we have to obviously start from an application centric perspective. You go to take a look at you know where your applications have to live water. What are some of the data implications on the applications, or do you have by way of regulatory and compliance issues, or do you have to do as faras performance because certain applications have to be in a high performance environment. Certain other applications don't think a lot of these factors will. Then Dr where these applications need to recite and then what we think in today's world is really accomplish. Complex, um, situation where you have a lot of legacy. But you also have private as well as public cloud. So you approach it from an application perspective. >> Yeah. I mean, if you really take a look at Army, you look at it centers clients, and we were totally focused on up into the market Global 2000 savory. You know how clients typically have application portfolios ranging from 520,000 applications? And really, I mean, if you think about the purpose of cloud or even infrastructure for that, they're there to serve the applications. No one cares if your cloud infrastructure is not performing the absolute. So we start off with an application monetization approach and ultimately looking, you know, you know, with our tech advisory guys coming in, there are intelligent engineering service is to do the cloud native and at mod work our platforms, guys, who do you know everything from sales forward through ASAP. They should drive a strategy on how those applications gonna evolve with its 520,000 and determined hey, and usually using some, like the six orders methodology. And I'm I am I going to retire this Am I going to retain it? And, you know, I'm gonna replace it with sass. Am I gonna re factor in format? And it's ultimately that strategy that's really gonna dictate a multi and, you know, every cloud story. So it's based on the applications data, gravity issues where they gonna reside on their requirements around regulatory, the requirements for performance, etcetera. That will then dictate the cloud strategies. I'm you know, not a big fan of going in there and just doing a multi hybrid cloud strategy without a really good up front application portfolio approach, right? How we gonna modernize that >> it had. And how do you segment? That's a lot of applications. And you know, how do you know the old thing? How do you know that one by that time, how do you help them pray or size where they should be focusing on us? >> So typically what we do is work with our clients to do a full application portfolio analysis, and then we're able to then segment the applications based on, you know, important to the business and some of the factors that both of us mentioned. And once we have that, then we come up with an approach where certain sets of applications he moved to sass certain other applications you move to pass. So you know, you're basically doing the re factoring and the modernization and then certain others you know, you can just, you know, lift and shift. So it's really a combination off both modernization as well as migration. It's a combination off that, but to do that, you have to initially look at the entire set of applications and come up with that approach. >> I'm just curious where within that application assessment, um, where is cost savings? Where is, uh, this is just old. And where is opportunities to innovate faster? Because we know a lot of lot of talk really. Days has cost savings, but what the real advantages is execution speed if you can get it. If >> you could go back through four years and we had there was a lot of CEO discussions around cost savings, I'm not really have seen our clients shift. It costs never goes away, obviously right. But there's a lot greater emphasis now on business agility. You know, howto innovate faster, get getting your capabilities to market faster, to change my customer experience. So So it's really I t is really trying to step up and, you know, enabled the business toe to compete in the marketplace. We're seeing a huge shift in emphasis or focus at least starting with, you know, how'd I get better business agility outta leverage to cloud and cloud native development to get their upper service levels? Actually, we started seeing increase on Hey, you know, these applications need to work. It's actress. So So Obviously, cost still remains a factor, but we seem much more for, you know, much more emphasis on agility, you know, enabling the business on, given the right service levels of right experience to the user, little customers. Big pivot there, >> Okay. And let's get the definitions out because you know a lot of lot of conversation about public clouds, easy private clouds, easy but hybrid cloud and multi cloud and confusion about what those are. How do you guys define him? How do you help your customers think about the definition? Yes, >> I think it's a really good point. So what we're starting to see is there were a lot of different definitions out there. But I think as I talked more clients and our partners, I think we're all starting to, you know, come to ah, you know, the same kind of definition on multi cloud. It's really about using more than one cloud. But hybrid, I think, is a very important concept because hybrid is really all about the placement off the workload or where your application is going to run on. And then again, it goes to all of these points that we talked about data, gravity and performance and other things. Other factors. But it's really all about where do you place the specific look >> if you look at that, so if you think about public, I mean obviously gives us the innovation of the public providers. You look at how fast Amazon comes out with new versions of Lambda etcetera. So that's the innovations there obviously agility. You could spend up environments very quickly, which is, you know, one of the big benefits of it. The consumption, economic models. So that is the number of drivers that are pushing in the direction of public. You know, on the private side, they're still it's quite a few benefits that don't get talked about as much. Um, so you know, if you look at it, um, performance if you think the public world, you know, Although they're scaling up larger T shirts, et cetera, they're still trying to do that for a large array of applications on the private side, you can really Taylor somethingto very high performance characteristics. Whether it's you know, 30 to 64 terabyte Hana, you can get a much more focused precision environment for business. Critical workloads like that article, article rack, the Duke clusters, everything about fraud analysis. So that's a big part of it. Related to that is the data gravity that Prasad just mentioned. You know, if I've got a 64 terabyte Hana database you know, sitting in my private cloud, it may not be that convenient to go and put get that data shared up in red shift or in Google's tensorflow. So So there's some data gravity out. Networks just aren't there. The laden sea of moving that stuff around is a big issue. And then a lot of people of investments in their data centers. I mean, the other piece, that's interesting. His legacy, you know, you know, as we start to look at the world a lot, there's a ton of code still living in, You know, whether it's you, nick system, just IBM mainframes. There's a lot of business value there, and sometimes the business cases aren't aren't necessarily there toe to replace them. Right? And in world of digital, the decoupling where I can start to use micro service is we're seeing a lot of trends. We worked with one hotel to take their reservation system. You know, Rapid and Micro Service is, um, we then didn't you know, open shift couch base, front end. And now, when you go against, you know, when you go and browsing properties, you're looking at rates you actually going into distributed database cash on, you know, in using the latest cloud native technologies that could be dropped every two weeks or everything three or four days for my mobile application. And it's only when it goes, you know, when the transaction goes back, to reserve the room that it goes back there. So we're seeing a lot of power with digital decoupling, But we still need to take advantage of, you know, we've got these legacy applications. So So the data centers air really were trying to evolve them. And really, just, you know, how do we learn everything from the world of public and struck to bring those saints similar type efficiencies to the to the world of private? And really, what we're seeing is this emerging approach where I can start to take advantage of the innovation cycles. The land is that, you know, the red shifts the functions of the public world, but then maybe keep some of my more business critical regulated workloads. You know, that's the other side of the private side, right? I've got G X p compliance. If I've got hip, a data that I need to worry about GDP are there, you know, the whole set of regular two requirements. Now, over time, we do anticipate the public guys will get much better and more compliant. In fact, they made great headway already, but they're still not a number of clients are still, you know, not 100% comfortable from my client's perspective. >> Gotta meet Teresa Carlson. She'll change him, runs that AWS public sector is doing amazing things, obviously with big government contracts. But but you raise real inching point later. You almost described what I would say is really a hybrid application in this in this hotel example that you use because it's is, you know, kind of breaking the application and leveraging micro service is to do things around the core that allowed to take advantage of some this agility and hyper fast development, yet still maintain that core stuff that either doesn't need to move. Works fine, be too expensive. Drea Factor. It's a real different weight. Even think about workloads and applications into breaking those things into bits. >> And we see that pattern all over the place. I'm gonna give you the hotel Example Where? But finance, you know, look at financial service. Is retail banking so open banking a lot. All those rito applications are on the mainframe. I'm insurance claims and and you look at it the business value of replicating a lot of like the regulatory stuff, the locality stuff. It doesn't make sense to write it. There's no rule inherent business values of I can wrap it, expose it and in a micro service's architecture now D'oh cloud native front end. That's gonna give me a 360 view a customer, Change the customer experience. You know, I've got a much you know, I can still get that agility. The innovation cycles by public. Bye bye. Wrapping my legacy environment >> and percent you raided, jump in and I'll give you something to react to, Which is which is the single planet glass right now? How do I How did I manage all this stuff now? Not only do I have distributed infrastructure now, I've got distributed applications in the and the thing that you just described and everyone wants to be that single pane of glass. Everybody wants to be the app that's upon everybody. Screen. How are you seeing people deal with the management complexity of these kind of distributed infrastructures? If you >> will Yeah, I think that that's that's an area that's, ah, actually very topical these days because, you know, you're starting to see more and more workers go to private cloud. And so you've got a hybrid infrastructure you're starting to see move movement from just using the EMS to, you know, cantinas and Cuba needs. And, you know, we talked about Serval s and so on. So all of our clients are looking for a way, and you have different types of users as well. Yeah, developers. You have data scientists. You have, you know, operators and so on. So they're all looking for that control plane that allows them access and a view toe everything that is out there that is being used in the enterprise. And that's where I think you know, a company like Accenture were able to use the best of breed toe provide that visibility to our clients, >> right? Yeah. I mean, you hit the nail on the head. It's becoming, you know, with all the promises, cloud and all the power. And these new architectures is becoming much more dynamic, ephemeral, with containers and kubernetes with service computing that that that one application for the hotel, they're actually started in. They've got some, actually, now running a native us of their containers and looking at surveillance. So you're gonna even a single application can span that. And one of things we've seen is is first, you know, a lot of our clients used to look at, you know, application management, you know, different from their their infrastructure. And the lines are now getting very blurry. You need to have very tight alignment. You take that single application, if any my public side goes down or my mid tier with my you know, you know, open shipped on VM, where it goes down on my back and mainframe goes down. Or the networks that connected to go down the devices that talk to it. It's a very well. Despite the power, it's a very complex environment. So what we've been doing is first we've been looking at, you know, how do we get better synergy across what we you know, Application Service's teams that do that Application manager, an optimization cloud infrastructure. How do we get better alignment that are embedded security, You know, how do you know what are managed to security service is bringing those together. And then what we did was we looked at, you know, we got very aggressive with cloud for a strategy and, you know, how do we manage the world of public? But when looking at the public providers of hyper scale, er's and how they hit Incredible degrees of automation. We really looked at, said and said, Hey, look, you gotta operate differently in this new world. What can we learn from how the public guys we're doing that We came up with this concept. We call it running different. You know, how do you operate differently in this new multi speed? You know, you know, hot, very hybrid world across public, private demon, legacy, environment, and start a look and say, OK, what is it that they do? You know, first they standardize, and that's one of the big challenges you know, going to almost all of our clients in this a sprawl. And you know, whether it's application sprawl, its infrastructure, sprawl >> and my business is so unique. The Larry no business out there has the same process that way. So >> we started make you know how to be standardized like center hybrid cloud solution important with hp envy And where we how do we that was an example of so we can get to you because you can't automate unless you standardise. So that was the first thing you know, standardizing our service catalog. Standardizing that, um you know, the next thing is the operating model. They obviously operate differently. So we've been putting a lot of time and energy and what I call a cloud and agile operating model. And also a big part of that is truly you hear a lot about Dev ops right now. But truly putting the security and and operations into Deb said cops are bringing, you know, the development in the operations much tied together. So spending a lot of time looking at that and transforming operations re Skilling the people you know, the operators of the future aren't eyes on glass there. Developers, they're writing the data ingestion, the analytic algorithms, you know, to do predictive operations. They're riding the automation script to take work, you know, test work out right. And over time they'll be tuning the aye aye engines to really optimize environment. And then finally, has Prasad alluded to Is that the platforms that control planes? That doing that? So, you know what we've been doing is we've had a significant investments in the eccentric cloud platform, our infrastructure automation platforms, and then the application teams with it with my wizard framework, and we started to bring that together you know, it's an integrated control plane that can plug into our clients environments to really manage seamlessly, you know, and provide. You know, it's automation. Analytics. Aye, aye. Across APS, cloud infrastructure and even security. Right. And that, you know, that really is a I ops, right? I mean, that's delivering on, you know, as the industry starts toe define and really coalesce around, eh? I ops. That's what we you A ups. >> So just so I'm clear that so it's really your layer your software layer kind of management layer that that integrates all these different systems and provides kind of a unified view. Control? Aye, aye. Reporting et cetera. Right? >> Exactly. Then can plug in and integrate, you know, third party tools to do straight functions. >> I'm just I'm just curious is one of the themes that we here out in the press right now is this is this kind of pull back of public cloud app, something we're coming back. Or maybe it was, you know, kind of a rush. Maybe a little bit too aggressively. What are some of the reasons why people are pulling stuff back out of public clouds that just with the wrong. It was just the wrong application. The costs were not what we anticipated to be. We find it, you know, what are some of the reasons that you see after coming back in house? Yeah, I think it's >> a variety of factors. I mean, it's certainly cost, I think is one. So as there are multiple private options and you know, we don't talk about this, but the hyper skills themselves are coming out with their own different private options like an tars and out pulls an actor stack and on. And Ali Baba has obsessed I and so on. So you see a proliferation of that, then you see many more options around around private cloud. So I think the cost is certainly a factor. The second is I think data gravity is, I think, a very important point because as you're starting to see how different applications have to work together, then that becomes a very important point. The third is just about compliance, and, you know, the regulatory environment. As we look across the globe, even outside the U. S. We look at Europe and other parts of Asia as clients and moving more to the cloud. You know that becomes an important factor. So as you start to balance these things, I think you have to take a very application centric view. You see some of those some some maps moving back, and and I think that's the part of the hybrid world is that you know, you can have a nap running on the private cloud and then tomorrow you can move this. Since it's been containerized to run on public and it's, you know, it's all managed. That >> left E. I mean, cost is a big factor if you actually look at it. Most of our clients, you know, they typically you were a big cap ex businesses, and all of a sudden they're using this consumption, you know, consumption model. And they went, really, they didn't have a function to go and look at be thousands or millions of lines of it, right? You know, as your statement Exactly. I think they misjudged, you know, some of the scale on Do you know e? I mean, that's one of the reasons we started. It's got to be an application led, you know, modernization, that really that will dictate that. And I think In many cases, people didn't. May not have thought Through which application. What data? There The data, gravity data. Gravity's a conversation I'm having just by with every client right now. And if I've got a 64 terabyte Hana and that's the core, my crown jewels that data, you know, how do I get that to tensorflow? How'd I get that? >> Right? But if Andy was here, though, and he would say we'll send down the stove, the snow came from which virgin snow plows? Snowball Snowball. Well, they're snowballs. But I have seen the whole truck killer that comes out and he'd say, Take that and stick it in the cloud. Because if you've got that data in a single source right now, you can apply multitude of applications across that thing. So they, you know, they're pushing. Get that date end in this single source. Of course. Then to move it, change it. You know, you run into all these micro lines of billing statement, take >> the hotel. I mean, their data stolen the mainframe, so if they anyone need to expose it, Yeah, they have a database cash, and they move it out, You know, particulars of data sets get larger, it becomes, you know, the data. Gravity becomes a big issue because no matter how much you know, while Moore's Law might be might have elongated from 18 to 24 months, the network will always be the bottle Mac. So ultimately, we're seeing, you know, a CZ. We proliferate more and more data, all data sets get bigger and better. The network becomes more of a bottleneck. And that's a It's a lot of times you gotta look at your applications. They have. I've got some legacy database I need to get Thio. I need this to be approximately somewhere where I don't have, you know, high bandwith. Oh, all right. Or, you know, highlight and see type. Also, egress costs a pretty big deals. My date is up in the cloud, and I'm gonna get charged for pulling it off. You know, that's being a big issue, >> you know, it's funny, I think, and I think a lot of the the issue, obviously complexity building. It's a totally from building model, but I think to a lot of people will put stuff in a public cloud and then operated as if they bought it and they're running in the data center in this kind of this. Turn it on, Turn it off when you need it. Everyone turns. Everyone loves to talk about the example turning it on when you need it. But nobody ever talks about turning it off when you don't. But it kind of close on our conversation. I won't talk about a I and applied a Iot because he has a lot of talk in the market place. But, hey, I'm machine learning. But as you guys know pride better than anybody, it's the application of a I and specific applications, which really on unlocks the value. And as we're sitting here talking about this complexity, I can't help but think that, you know, applied a I in a management layer like your run differently, set up to actually know when to turn things on, when to turn things off when you moved in but not moved, it's gonna have to be machines running that right cause the data sets and the complexity of these systems is going to be just overwhelming. >> Yeah, yeah, absolutely. Completely agree with you. In fact, attack sensual. We actually refer to this whole area as applied intelligence on That's our guy, right? And it is absolutely to add more and more automation move everything Maur toe where it's being run by the machine rather than you know, having people really working on these things >> yet, e I mean, if you think you hit the nail on the head, we're gonna a eyes e. I mean, given how things getting complex, more ephemeral, you think about kubernetes et cetera. We're gonna have to leverage a humans or not to be able to get, you know, manage this. The environments comported right. What's interesting way we've used quite effectively for quite some time. But it's good at some stuff, not good at others. So we find it's very good at, like, ticket triage, like ticket triage, chicken rounding et cetera. You know, any time we take over account, we tune our AI ai engines. We have ticket advisers, etcetera. That's what probably got the most, you know, most bang for the buck. We tried in the network space, less success to start even with, you know, commercial products that were out there. I think where a I ultimately bails us out of this is if you look at the problem. You know, a lot of times we talked about optimizing around cost, but then performance. I mean, and it's they they're somewhat, you know, you gotta weigh him off each other. So you've got a very multi dimensional problem on howto I optimize my workloads, particularly. I gotta kubernetes cluster and something on Amazon, you know, sums running on my private cloud, etcetera. So we're gonna get some very complex environment. And the only way you're gonna be ableto optimize across multi dimensions that cost performance service levels, you know, And then multiple options don't do it public private, You know, what's my network costs etcetera. Isn't a I engine tuning that ai ai engines? So ultimately, I mean, you heard me earlier on the operators. I think you know, they write the analytic albums, they do the automation scripts, but they're the ultimate one too. Then tune the aye aye engines that will manage our environment. And I think it kubernetes will be interesting because it becomes a link to the control plane optimize workload placement. You know, between >> when the best thing to you, then you have dynamic optimization. Could you might be optimizing eggs at us right now. But you might be optimizing for output the next day. So exists really a you know, kind of Ah, never ending when you got me. They got to see them >> together with you and multi dimension. Optimization is very difficult. So I mean, you know, humans can't get their head around. Machines can, but they need to be trained. >> Well, Prasad, Larry, Lots of great opportunities for for centuries bring that expertise to the tables. So thanks for taking a few minutes to walk through some of these things. Our pleasure. Thank you, Grace. Besides Larry, I'm Jeff. You're watching the Cube. We are high above San Francisco in the Salesforce Tower, Theis Center, Innovation hub in San Francisco. Thanks for watching. We'll see you next time.

(upbeat music) >> Narrator: From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello and welcome to theCUBE studios in Palo Alto, California for another CUBE conversation, where we go in-depth with thought leaders driving innovation across the tech industry. I'm today's host, Peter Burris. Every business is talking about cloud transformation as a consequence of their effort to do a better job with digital business transformation. But cloud transformation too often is associated with just thinking about moving applications and data to some as yet undefined location. Whatever approach enterprises take, they will absolutely have to touch upon a couple of crucial steps along the way. At the center of those steps will be how do we think about the network transformation that's going to be required to achieve and attain our cloud objectives? How do we do it? Well to have that conversation, we're here today with Jay Chaudhry who's a CEO of Zscaler. Jay, welcome to theCUBE, welcome back to theCUBE. >> Thank you. >> So before we get into this very important conversation, give us an update on Zscaler. >> So Zscaler was designed as a cloud security platform for the world of cloud and mobility. When applications are in the cloud, users are everywhere, the traditional security that builds a castle and moat model no longer works. So I start with clean slate, 11 years ago to start this company. Today, some of the largest companies in the world are protected by Zscaler. We went public last year, on NASDAQ, the sales have done very well, our customers are very happy our employees are very happy, so we are having fun building this lasting company and making cloud and internet a safe place to do business. >> Now that's great. Now let's talk about that, 'cause you're talking to a lot of customers, about making the internet a safe place to do business. >> Yep. >> What are you encountering as you discuss their challenges? >> So with the mobility, with the desire to do digital transformation, CIOs and CTOs and CISOs, are trying to figure out, how do I get there? The biggest thing that's holding them back, is security. It's a new thing for them. If my data is sitting in the cloud somewhere, who is protecting it? How do my users access it while the bad guys don't? So security ends up being at the center of the whole discussion. In fact a few years ago, CISOs would talk to me and say, "Security is not getting enough attention, "it's being ignored." Now the same CISOs are complaining a little bit that I'm being asked to present to the board every quarter. >> Right >> So it's a good thing but the CISOs have a challenge of figuring out what solutions work for the cloud, what do not, because quite often, when the market changes, the incumbents, the legacy vendors, kind of whitewash the solutions overnight and everyone becomes a cloud security provider. >> We get a lot of marketing responses, I think one of the centerpieces of this whole thing is, digital business really places an emphasis on the value of data as an asset. >> Yep. >> And how it changes the way you engage your customers, how it changes the way they think about operations, how it impacts the way you govern the overall business. >> Yep. >> When data emerges as the asset, we move away from a focus especially in the security world, from securing devices to securing the new classes of data. >> Yep. >> Is that kind of solution direction that you're seeing companies taking, is how do I think about up leveling beyond perimeter to actually building security. >> Yeah. >> Embedded deep within my workings? >> To really understand how security came about. Earlier on it used to be, I protect my device with antivirus software, then we built networks and we expected users to be on the network and applications and data to be sitting in my data center on my network. So the easiest way to secure your enterprise was, to secure the network. >> Mm. By building a moat around your data center. That's why we call it network security, securing your network, it made sense for years but now, with applications sitting in Azure or AWS Office 365, Workday, the like. And the users being everywhere, at airport, coffee shops, at home and wherever. How do you protect the network? The users aren't even on your network and applications aren't even on your network. So the notion of network security is becoming irrelevant. At the end of the day, the sole purpose of IT is, that a user should be able to access an application, no matter where the application is and no matter where the user is. So all this network and security and all, are a byproduct of that. So when I start Zscaler, I said, what needs to be protected? Data. Where is data? Data is generally sitting with the application, behind the application. So rather than building this moat, rather than doing this network security, rather than trying to build an appliance and try to move it to the cloud, let's take a look at it totally different. Assume that we need a policy engine, a business policy engine that sits in, 100s of locations around the globe, a user connects to the policy engine, the policy engine looks and says, should this user have access to this application or not? Based on that, we connect a user to an application, internal or external, no matter where the user is coming from. So that's the approach that's needed and that's the approach Zscaler pioneered and that's why the biggest of the big companies from GE, to Siemens, to DHL, they all are becoming Zscaler customers. So we are helping them transform from this old world where network is a hub-and-spoke network, security is this castle and moat to the new world, where a user can go directly to the application over any network. And network is important, it's an important transport but it doesn't need to be secure. Security is about, securing the right user to a right application, irrespective of the location of the user or the application. >> So I want to build on this because, what a lot of companies are starting to recognize is that, they want to get their application and the services provided by the application and the data proximate to the commercial activity that generates, you know, that pays the rent so to speak. >> Yep, yep. >> And that means, an increase in distribution of function offer. >> Of course. >> So the notion of the cloud as a place where we're going to centralize things, is giving way to a notion of the cloud as a technique for further distributing. >> Yes. >> And that means ultimately that, the services that we're going to provide have to have security embedded in them, in policy so that the data, the security and all those services are moving to where they're required. >> Yes, so in my view, cloud was never meant to say, things must be centralized. Actually a data centers were highly centralized. >> Right. >> The cloud notion should be, it's a responsibility of the cloud provider to make sure that data and application can be pushed where there needs to be. So when Microsoft is offering Office 365, your emails aren't sitting at one place, it's Microsoft's job to make sure if your employees are in Singapore, some of these things move to Singapore so you can have faster access to it. So that's the application side or for the data side of it. A company like Zscaler, we sit between the user and the application as a check post. In fact, think of us as an international airport. >> mm >> When you go in and out, you need to make sure that, the person is authorized to do so and isn't carrying any guns and weapons that could cause damage to somebody out there. So a user going to Salesforce or user going to Office 365 or a user going to application Azure, they simply connect with us, the business defines a policy, says, this person is okay to go here and based on then, we are connecting those people securely. Now if you're in London, you want to go through Zscaler's check post in London, if you're in Tokyo, you want to go through a check post in Tokyo because you want the shortest path. The old approach where we built a hub-and-spoke network, you brought people back to the data center. >> Back to the hub. >> To a hub, to go out. It's very painful. Imagine flying from San Fran to Chicago, via Houston? It's very painful and that's what gets done in the old world of security appliances because you can build only so many moats and that's what Zscaler is making redundant or irrelevant. So with a 100 plus locations around the globe with multi-tenant technology, you fly to Paris tomorrow, as soon as you connect to the internet from your hotel or the airport, we automatically redirect your traffic through our Paris data center. Your policy and security magically shows up, gets enforced, you're getting localized content, you're getting amazing response time without having to do anything. >> You're getting the same services that you get anywhere else 'cause it's policy driven with a common infrastructure for ensuring that-- >> And-- >> The issue of distribution is not the determining consideration. >> So it is the heavy lifting we did. >> Right. >> To make sure your policy can automatically show up where it is. And to do that, you're to build some serious technology. The old technology was, policy needs to be pushed once in a while, let's do a batch push. That's what traditional security appliances like firewalls do, they're single tenant, we came with a concept policy on demand per user, it works beautifully and then logs. Any time you go through any check post, the logs are created just like when I go in a building, they have me sign that say Jay went to see Peter at this time, same colored logs are created and they must be secured. So, you may be going to our 50 data centers but your logs are created in 50 locations but in line in real time, without ever writing the disk locally, they get sent to one central logging cluster and they're available within seconds. That's really an example of a purpose-built security cloud as compared to what we are calling imitation clouds. >> Mm >> Where people take a stack of appliances, stick them as virtual machines in Google or AWS cloud and they become a cloud service. I was talking to a customer the other day, he said hey, here was a network security vendor making a pitch and he said, "I thought of it, "as if someone is trying to build a Netflix service "using a bunch of DVD appliances." >> Mm-hmm >> All right so, to do security right, one has to build it for the world of cloud, it's multi-tenant, it's distributed, have you seen it before? Think of Salesforce.com, think of Workday, these were young companies a few years ago like Siebel used to dominate CRM. >> Right. >> PeopleSoft used to dominate HR, what happened to them? Well the world moved to its cloud, the world move to SAS service and these companies tried to use that legacy technology, tried to move to the cloud, it just doesn't work and that's why all these investors and customers love Zscaler's platform. We like to call it born in the cloud for the cloud platform. >> One of the things you didn't mention is that, when you're not doing that huge amount of backhaul traffic, your costs are going to go down pretty dramatically. So if I kind of summarize what you've talked about, we're going to go through, we're in the midst of a cloud transformation. >> Mm-hmm >> We have to rethink applications in the context of improve security, bake it right in which is going to lead to a rethinking of network and finally a rethinking of security. >> That's correct. When your network changes from hub-and-spoke to direct to cloud, you can't have a direct path without security so it drives security transformation. So that's where a security platform like Zscaler comes in. So your traffic from any of your say, X 100 branches or from your mobile device or from your laptop, it simply goes through Zscaler to get the same policy, same protection. So Zscaler gets viewed as an enabler of cloud transformation because without us, you can't transform the network and then security has to be done right. >> Right, so you've had a lot of conversations with customers, give us some sense of what kinds of how it's changing the way they work, how it's changing their operations, how it's changing their cost profiles. >> You know three, four or five years ago, we had to do a fair amount of evangelism but when you're the pioneers, you expect to do that. Like three years ago, three CIOs will tell me, "I like cloud, I'm moving in that direction." Three will say, "I'm thinking about it." And remaining four will say, "Mm-hmm I don't think cloud will happen." Today, all of them want to embrace cloud because they've seen the benefits of it. It's making business more agile, more competitive. Now they're figuring out, how do we do security right, how do I do this transformation without, if I may say, messing it up? >> Mm-hmm >> And that's where, it all starts with thought leader, visionary customers. When I saw GE, Larry Biagini, a global CTO or global CISO driving cloud eight, nine years ago, seeing Siemens saying, I need to make my business more competitive and these are the type of leaders who actually help drive adoption because when they do this stuff, others followed. >> Yeah the recode system responds. >> Exactly, exactly >> Jay Chaudhry, talking about cloud transformation and the crucial role that security is going to play in that transformation. Thanks very much for being on theCUBE. >> Peter, thank you, I appreciate the opportunity. >> And once again we've been speaking with Jay Chaudhry who's the CEO of Zscaler. Thanks for joining us for another CUBE conversation, I'm Peter Burris, see you next time. (upbeat music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host stool minimun hi I'm Stu minimun and this is a special cube conversation from our Boston area studio I'm happy to welcome back to the program Bobbie Patrick who's the chief marketing officer of uipath Bobby great thank you sue thank you she's great to be here all right so Bobby you know we've known you for many years there were a couple of jobs you know you and I've talked at many the cloud shows over the year and especially companies that were at the lead of that wave they talked about cloud first right and so now you know not surprising at uipath who is one of the leaders in robotic process automation the tagline I'm hearing is automation first a uipath so a bunch of news a lot of updates we had the cube at uipath forward in Miami last year we're gonna have it back in Las Vegas so a lot of ground to cover but I guess set the stage for us you know our PA is might not be an acronym that comes off of everybody's tongue just yet but boy there's a lot of buzz in the marketplace companies growing like wildfire so you know give us kind of the dynamics to set things yeah absolutely I think you know people spent the last 5-10 years trying to go digital write digital transformation has been really hard it's largely been IT led and IT swamped and has a million things to do and along comes a technology that actually you know business users and business analysts and subject matter experts can use and and go digital quite quickly get real outcomes fast and and a complete payback on all the entire projects in less than six months or nine months it's kind of unheard of an IT and so you know our PA is now established itself now as as really the best path to digital going digital it's actually the best path to using AI as well that's coming together about quickly but I think what's what's if you step back in the zoom out a bit you know the cloud first era brought brought incredible agility to organizations right and the very beginning a cloud for your calls to do right you know IT was kind of against cloud right we're never gonna go out of our data center right we're never going to go off Siebel and sales to Salesforce all those kind of things right and but cloud the business talk cloud as a mechanism to drive fast agility and to you know drive new economics for the business and and so on well you know the cloud air is kind of behind us now and it's obvious right today the automation first era has a very similar view to it right it is about rapid agility mass productivity competitive complete company transformation and in that era we know we call it the automation first error so it's less a tagline for us we want our competitors to use it we want the market to use that we want our partners to use it we want to talk about this automation first error and we think it's a sea level conversation it's a board level conversation and it's it's gonna completely change the landscape of how companies work over the next 20 years yeah it definitely reminds me much about you know that stealth IT and then IT as we said IT needs to respond to this because if they don't the business will just go elsewhere so right ah absolutely this wave of automation it's something that we see in the you know so many aspects of the market intelligence and automation is something that we talked about for decades but is real today and in our industry there's no better proof point that something has reached a certain stage of the market then you know the venerable Gartner has come out with a Magic Quadrant first of all congratulations we're gonna thanks let the graphic and talk a little bit about it up here the Gartner Magic Quadrant uipath you know it is up in front yeah that's terrific it's uh I I think you know Gartner Magic Quadrant much like the Forester ways the Forester in the last two years has had several waves on the on our PA prior to that uh horses for sources and and in Everest and others had kind of uncovered and discovered our PA I think what the Gartner Magic Quadrant does is it is it is a one I think it's a great articulation of the state of the market today I think it's helpful to IT and to businesses to see and understand the market is legitimate its long-term several years ago many people said our PA was sort of a short-term it was a band-aid that's not the case at all RP is becoming a platform and and so we're excited because the quadrant really I think accurately shows the state you know we're obviously happy to be number one you know blue prism in at number two and obligation anywhere number three in the leaders quadrant I think the three of us you know really are the vast majority of the market there's a few other players in there that are traditional you know pegye sort of tries to have an RPA product but they're still focused on cloud I think and and the you know there's a number of other players that have kind focuses around certain parts of our PA like nice systems around attended but really the leader quadrant I think does does accurately show the the market yeah it reminds me of some of the software define products in traditional IT is that today relatively speaking the dollars are small compared to the overall IT but Gartner said this is the fastest software group of anything that it tracks and you know billions of dollars in it forecasted in kind of the next five years this is really important right because gardner size to the 890 million i think next year or this year foresters at one point one point nine billion you know will have twenty percent market share this year thirty thirty-five percent market share next year either way the numbers are accelerating and every time a forecast comes out they raise guidance and that's going to happen again this year because our PA is becoming more critical and core to enabling technologies like blockchain even and like Internet of Things and and nai obviously and so I think you're gonna see the Tam grow considerably but I think look it's the fastest growing market we're the fastest growing enterprise software company in history when we went from one to one hundred million arr in about twenty months you know no other company has done that we're considerably larger right now and but we say that you know kind of in a humble way as an example of it's a fact we actually put our numbers out even though we're a private company because we do want to show the market hey this is really excited exciting what's going on here we add eight new enterprise customers a day we have a to the fortune 10 as as customers today right we have companies grow and robots robots out to a hundred thousand employees right so it's it's it's very exciting what's going on here and the enthusiasm mean there's not many technologies to where employees show extreme excitement when they realize this robots will take this kind of mundane task from you and that I think that is just fantastic yeah it's definitely something I saw when I attended your conference I know some of the employees from previous jobs some that I've worked with at other vendors as well as the customers are all super excited in sharing their story let's get in you talked about you know that that customer growth obviously is one of the execution arms of Gartner if you've got revenue you've got customers you're executing there that completes this vision you know look like there there's still room for everybody in that space Gartner had some some ways that they think the market needs to mature in there but you know what are some of the key factors that led to UI performance you know so I think I think you know what did this come our companies done right and I you know our founder Daniel Dinah's is absolutely amazing is we built a company people love to work at our culture is is one where we've won a a dozens of awards from inc magazine compared ibly recently daniel Dinah's was voted by employees as a best work place for women right next to Satya Nadella right none of our competitors are anywhere on these cultural landscapes culture is extremely important we want to build a company that is is the epitome of the next generation of businesses right I think I think the next would be the product then we built a product that's open we built a product that is extensible with open api's we embed and best-of-breed components we don't build our stuff a lot of our competitors have proprietary components like proprietary AI or others no we're very open in architecture and we've made that product easily available through our community and that's that's been a big difference between us and our competitors communities not just a free download though communities how you embrace your your your your users how you how you give them you know whole experience training and they're willing to share their skills and best practices as well as as obviously access to software and then finally I think our customer success so one of the best things last years we've watched hundreds of customers begin to really scale we're talking hundreds thousands and even hundreds of thousands of robots right and as they go from in to HR and they work on robots to help with HR admin and HR recruiting right or they go into legal or over contact centers call centers are really popular right now a lot of our airline customers you know they really want to help improve the experience not only for their customers but their employees their employees don't want to be on a phone 25 minutes either to a disgruntled person but they have to check your employee goes and looks like 10 different systems sometimes to go solve a problem robots can do all that work and cut the entire call center experience down by 60% everybody benefits so we're seeing you know we're seeing you know again you know great company great product and an amazing customer scaling all right we always know Gartner does a very kind of point in time look at what they're doing you know you mentioned the kind of the open an environment there one of the things they were tracking is the ecosystem because obviously there's a lot of software's that you need to integrate with our software is always changing so how does the the technology deal with those changes you know we all would complain is like oh geez I went in Gmail and my interface looks totally different today than it did before how does that impact stuff so well you know what's changing is are there things in the last kind of six to twelve months that maybe the report doesn't catch or you know what should be one of the challenges with the report is that it took a long time to complete we started they started this I think it was last October so for us it's multiple versions ago right but we still had a great spot one of our competitors I think decided that you know they didn't like their at their result and hence MQ took a little longer than then it showed up so yes it's from a product perspective we've gone to look in a long way since since in October I think a number of things are important one is you know we embed AI into the product and use different components around helping with document understanding visual understanding conversational understanding and so there's a lot of advancements on the ability for a robot whose robots learn new skills is a phrase we often use for robot to do more and more you know it with every release that a lot of those can be you know our components or or our partners we have 700 companies today they're in our ecosystem right so maybe a natural image processing company like core AI right or or an AI ml company like element AI or sky mind right Dayna robot these are all amazing companies that have great algorithms but they don't have access to the data right well the customers data is flowing through our platform and in these automation so we've made it very easy to drag and drop AI you know it's a drag and drop in Watson for example to apply to an automation flowing through our platform right so you know with every release you know robots getting new skills we make the products easier easier to use we're making it easier from four more people who have even less technical skills to be able to automate almost Excel users will be able to automate with them within Excel with a new version that's coming up right so you know all axes you know we're a three thousand person company now right so we've got a lot of developers so you know all axes ease-of-use scalability they're all they're all growing fast ya want to unpack that what you just brought up there a little bit this is not necessarily IT rolling out these environments we know if it's gonna be fast and you know tied to the business oftentimes it will start on the business how is that dynamic working you know your customers that you've been with for a while you know how do they work through that dynamic there are four phases in the maturity of kind of an RPA program right the first phase is citizen development led it's often led within a business like within finance or with an HR with a call center the second phase IT gets involved in the CIO gets involved this is where they say okay I've got to govern this you know robots are like or like human workers they have to have credentials and and login and passwords and things so to manage them and and robots actually bring a lot of compliance and auditability right everything a robot does is tracked and stored and and so CIOs get involved in Phase two that's when they build out we call the ROC a robotic operations center right and this is where they scale you see hundreds of robots lots of automations and they're really building a pipeline to serve their company phase three is when the CEO gets involved this is where around our vision of a robot for every person this is when CEO the board begin to think about automation and its impact across the entire enterprise and then they kind of I would say the aspirational phase and which we see some today is what we call phase 4 which is the gigabyte economy these are where robots are working up and down a value chain and a supply chain supply chain shared amongst companies in a way that the entire chain benefits right and this is actually where we see some blockchain use cases coming in where blockchain becomes the immutable source of truth for the actions the robot does between a customer and say and say a manufacturer so those four phases that maturity model is absolutely critical but I think it's important to note in phase two you know serving IT providing a platform that they can that they know is secure that they can that has good auditing that that they can scale efficiently and effectively it's really important so we often say you know we're built for both business and for IT all right October you've got uipath or come to the Bellagio in Las Vegas give us a little bit of a you know sneak peek as to you know what people can be expecting when they come to your big of yeah for it's gonna be amazing this year and you know as you know we host events all around the world this year will host 23,000 people in our own uipath events which is absolutely incredible this will be our kind of flagship signature event where we will unveil a stream of new products we have made some acquisitions that we have not announced that are part of that we will be taking the platform in making it much more kind of easy to implement on one side the higher scalability on the other side and will show a lot of innovations around that we're gonna also show some disruption in some other markets our PA can really extend itself into other technologies and do other markets that exist today as a new way of doing things and so we're excited to unveil what I think will be some pretty strategic directions for for our PA and finally the real focus of this event will be about customer stories particularly customers that have scale we'll have about two dozen customers who will talk about how they've scaled their operations how they're adding you know they're doubling their automations every month hundreds or thousands of robots how they manage that how they deploy that how they market internally even how do they you know what are the challenges they have is how do i educate within my own company right one of my favorite stories last week on art weeks ago on linkedin was a CEO of SingTel out of singapore you know he put out a post showing a hackathon that they ran where and he said we're now a believer in a robot for every sink tell employee and the employee that won the hackathon had been there 46 years the robot saw the problem that drove her nuts every week of her career and she was thrilled so you know this is gonna be an event to celebrate also celebrate the community celebrate success celebrate automation yeah final question I have for you Bobby I love talking to CMOS about how technology is impacting your job so you know what's new about you know the digital transformation our PA automation first cloud first era for you know for CMO like yourself both so we have you know dozen robots in marketing I have my favorite one I think I did a post on this one my favorite one was I would wah I wake up every morning and I would go to my my device mobile I'd go look up Google Trends how are we doing you like go to alexa.com or similar web duck how would you answer competitors and I'd you know it's great take this take the screen look in there okay great we're doing great well that was ten minutes of my day every day well now we have a robot that does that every morning for me and it takes the data puts it into a Google sheet and I can track it over time right you know that's an easy example but we actually use robots in a much more serious way where we move data between different systems between eventbrite systems or between our CRM systems and our leads when we get leads that come in our robots actually take the lead based on the location and and and notify the right people in each each each region right so robots are you know kind of kind of running you know throughout how we operate it's a company we have our own rock our own robotic operations that are in our business we think about automations you know throughout our entire organization and and it's exciting we have interns this summer and there's a intern contest and they're building the robots and we have fun robots - robots that help a fantasy football right and if you forget to make your selections it will go fix it for you so you don't miss out you know perhaps on on moving a player it's not playing out so all kinds of you know fun with with robots whether it's marketing HR a little legal it's it's exciting all right well Bobby Patrick thanks so much for all the updates congratulations on the momentum the updates in the Gartner MQ and I know we look forward to you iPad forward in Las Vegas later thanks - all right as always check out the cube dotnet to see all of the content we've done if you go in the search in search uipath you can see Daniel there CEO of the previous conversation with Bobby as well as who will have on at the show there on Stu minimun and thanks as always for watching the cube

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody Dave Volante here with Stu minumum we have some breaking analysis we're gonna break down the acquisition of IBM Red Hat by IBM was announced today that it closed Stu was originally announced in October a 34 billion dollar acquisition so not a surprise surprise that it closed a little bit earlier than people thought people would thinkin you know well into the second half closed in July they got through all the all the issues in Europe what does this mean in your view to the industry yeah so Dave we did a lot of analysis when the deal was announced absolutely the the cloud and the ripples of change that are happening because of cloud are the impetus for this and you know the the question we've been having for years Dave is you know how many companies can stay kind of independent in you know their swimlane to what they're doing or are we going to see more massive consolidations we're not that far off of the 67 billion dollar acquisition of Dell buying EMC to go heavily into the enterprise market and of course there are cloud implications what happened there and you know we're watching the growth of cloud what's happening in the developer world you know we've watched Red Hat for a long time and you know Red Hat has a nice position in the world and it carved themselves out a nice role into what has been emerging as hybrid and multi cloud and in my opinion that's you know the number one reason why arvind and the IBM team you know when to take that 20-year partnership and turn it into you know now just part of the IBM portfolio Arvind Krishna executive at IBM a longtime player there so the the the deal is so you talked about Dells acquisition we've talked a lot about the VMware model keeping the company separate and of course Red Hat is not going to be a separately traded public company it is going to be a distinct unit inside of IBM's cloud and cognitive software group as I understand it is that right so the question is will it be reported separately or is it going to be oh we're gonna throw everything into our cloud number yeah so Dave this is where all of us that have watched and known IBM you know for our entire careers because they've been around over a hundred years on ask what's going to happen so from a reporting structure Jim Whitehurst reports to Ginny from a Wall Street standpoint it sounds like it's gonna be just thrown into the cloud piece you know Dave isn't it that the the the standard practice today that you throw lots of stuff in there so we can't figure out what your cloud business really is I mean let's look at Oracle or even Microsoft and what they had you know Amazon's probably the only one that clearly differentiates you know this is revenue that we all understand is cloud and can you know touch and feel it so sure I IBM you know you've got all of the the piece that used to be soft layer it's now the IBM cloud piece there are lots of software pieces in that mix the cloud and cognitive is a big umbrella and you know Red Hat adds a few billion dollars worth of revenue into that stream so IBM's assumptions here juni talks a lot about chapter two chapter one was a lot of front-end systems that sort of the growth was everybody thought everything was going into the cloud that's really not the way it is 80% of the workloads are still on Prem and in Chapter two was all about you know connecting those to any cloud multi-cloud heard her words the IBM cloud or the Amazon Google or Microsoft cloud etc etc she made the statement that that we are the only hybrid multi-cloud open source company okay I guess that's true does it matter that they're the only hybrid multi-cloud open source company and are they yeah so I mean Dave anytime a vendor tries to paint themselves as the number one or you know leader in the space it's you know that's how they're defining it that's not how customers think of it customers you know don't think is much about whether it's multi cloud or hybrid cloud they're doing cloud and they're working with you know more than one supplier it is very rare that you find somebody I'm all-in and then you dig in oh yeah wait I'm using office 365 and Salesforce and oh wait there was that cool new thing that Google announced that somebody off on the sides doing so we understand that today it's a multi cloud world tomorrow to be a multi cloud we're absolutely open source is growing you know at great leaps and bounds Red Hat is you know the you know best example we've had of that that trend something I've been watching for the last 20 years and you know it is impressive to see it but you know even when you talk to customers of you know most customers are not you know flag-waving I must do everything open-source you know that they have a little bit more nuanced view of it sure lots of companies are participating in contributing to open source but you know I've yet to talk to too many companies that were like well when I'm making this decision you know this is absolutely what it is am i concerned about my overall costs and I'm concerned about transparency am i concerned about you know security and how fast I can get things resolved and by the way open-source can help with a lot of those things that's what they need to think about but look IBM you know had a longtime partnership with Red Hat Red Hat has a strong position in the marketplace but they're not the only ones there you know you mentioned VMware Dave VMware cross has a strong play across multi cloud environments you know we see Red Hat at all of the cloud shows you see yeah IBM at many of the cloud shows but you've got Cisco out there with their play it is still you know this this chapter - if you agree with Ginny's terminology we are relatively early in that but you know IBM I believe is strengthened in their positioning I don't think it radically changes the landscape just because you know Red Hat is still going to stay you know working with the Amazons and Microsoft and Google's and and and other players out there so it doesn't dramatically change the landscape it just consolidates two players that already worked closely let me ask a question so I mean was clearly positioning this as a cloud play you know generally and you know in a multi cloud specifically is this a cloud play okay um so I'll say yes but Dave so absolutely the future and where the growth for Red Hat and where IBM and for this thirty four billion dollars to be successful the tip of the spear is open shift and therefore you know how does that new cloud native multi cloud environment you know where do they play but at its core you know red heads still Linux Red Hat Enterprise Linux you know is it stills you know that is the primary driver of revenue and Linux isn't going away as a matter of fact Linux is growing Microsoft you know just revealed that there are more Linux workloads sitting in Azure than there are windows we already knew that there were you know strong Linux out there and Microsoft is embrace Linux we saw Satya Nadella at Red Hat summit and you know we've seen that proliferation of linux out there so linux is still you know growing in it where it's being used out there and in the cloud you know linux is what most people are using so the reason why I think this acquisition is interesting Jim Whitehurst today said publicly that it was a great deal that IBM was getting but then he couched he said of course it's a great deal for our shareholders too so and Ginni chimed in and said yes it was a fair deal okay fine 34 billion you know we'll see the reason why I think IBM likes this deal and IBM you know generally has been been good over in history with acquisitions you know clearly some mega acquisitions like PwC which was transformative me we have time to talk about that Cognos and some of the other software acquisitions done quite well not a hundred percent but the reason why I think IBM likes this deal is because it's a good cash flow deal so I think in many ways and they don't talk about this because it's not sexy marketing but iBM is a services company over 60% of the company's revenue comes from professional services IBM loves complexity because they can bring in services throw the big blue blanket around you and do a lot of integration work and the reason is that I think this is an interesting acquisition from from a financial standpoint and Ginny says this all the time this is not about cost synergies this is about revenue opportunities when you try to put everything in the cloud you always run into the back-end systems and her point is that those back-end systems need to be modernized how do you modernize those back-end systems openshift it's not trivial to do that you need services and so iBM has a large install base probably by my estimate you know certainly tens of billions of dollars of opportunity there to modernize back-end systems using Red Hat technology and that means that it's a front-loaded deal from a cash flow standpoint that they will find automatically revenue Cyn to plug in to IBM's captive install base what are your thoughts yeah Dave III think that your analysis is spot-on so RedHat has been one of these most consistent you know revenue companies out there you steadily when they went from a billion dollars to now they're right around three billion dollars they had the March to five billion dollars they had a couple of minor blips in their quarterly earnings but if you plug in that IBM services organization you really have the opportunity to supercharge this is not the opportunity is to have that that huge IBM services organization really helped you know grow those engagements do more openshift you know get more Linux help ansible you know really become the standard for you know automation in the modern workplace the challenge is that too many IBM people get involved because the the thing that everybody's a little worried about is IBM's done well with a lot of those acquisitions but they don't leave them stand alone even you know VMware for many years was a standalone company today VMware in Dell they're one company they're in lockstep from a management standpoint and they're working closely together what differentiates RedHat is you know iBM has groups that are much larger than RedHat that do some of the same things but RedHat with their open-source mission and and where they're driving things and the innovation they drive they move a little bit faster than IBM traditionally does so can will the Red Hat brand the Red Hat people and Red Hat still stay independent enough so that they can till you know hop on that next wave you know they they jumped early into kubernetes and that was the wave that really helped them drive for what they're doing the open shift you know even Dave you know Red Hat ahead bought core OS which was a smaller company moving even faster than Red Hat and while they've done a really good job of integrating those people absolutely from what I've heard it is slowed things down a little bit just because Red Hat compared to core OS was a much bigger company and of course IBM is a be a myth compared to Red Hat so will they throw these groups together and you know who will be making the decisions and can they you know maintain that that culture and that growth mindset well the point is structure we bring up VMware a lot as the model and of course when EMC bought VMware for paltry six hundred million six thirty five million dollars it folded it in and then spun it back out which was the right move certainly allowed the ecosystem to blossom I don't think IBM is gonna take that same approach blue wash is the term they'll probably blue wash that now cuz no Dave they said iBM has said they will not blue eyes there's no purple red stay separate absolutely there's concerns you know so to get those revenue synergies there's there's you're gonna have to plug into IBM systems and that requires some some work and IBM generally good at that so we'll see we'll keep our eyes on that it's but but I would predict that IBM is not going to do a VMware like well it's going to be some kind of hybrid Dave one of the other things is you talked about so Jim Whitehurst you know executive respective had him on the cube a lot he's reporting to Ginny you know the question is is this Ginny's last big move and who replaces her yeah let's talk about succession planning so a lot of a lot of rumors that Whitehurst is is next he's 52 years old I've said I don't I don't think they would do that but but let's talk about it first of all just you know Jim white her side sort of interviewed him the number of times but but you know I'm quite well you think even watch the job so you know I talked with Jim a little bit at red hat summit you know he kind of makes light of it he said you know knowing IBM the way we all know IBM IBM has always taken somebody from inside to do that he feels that he has a strong mission still to drive Red Hat he is super passionate about Red Hat he wrote a book book about the open source culture and is still driving that so I think from everything I see from him that's still the job that he loves and wants to do and you know it's a very different challenge to run IBM I'm not saying he would turn it down if that was the direction that it went if it went down to it but I did not see him angling and positioning like that would be where he wants to go well and of course you know Jim is from North Carolina he's got that kind of southern folksy demeanor you know comes across as the so the nicest guy in the room he's also the smartest guy in the room but oh we'll see we'll see what happens there I've said that I think Martin Schroder is going to be the next CEO of IBM Martin Schroder did three years of combat duty as the CFO in in what was a tough time for IBM to be a CFO they were going through those big transitions talking about you know they had to had to do the the SoftLayer acquisition they had to put together those strategic initiatives and so he's has he has CFO chops so he understands finance deeply he ran you know when IBM's big services business he's now responsible for IBM's revenue generation he's a spokesperson you know in many ways for the company he's like the prototypical choice he would not be surprising at all to see IBM plug him right in a little bit of history as you know still him a bit of a history historian of the industry have been around for a while John Akers back in the early 1990s when IBM's mainframe business was was tanking and the whole company was was tanking and it was at the risk of actually believe it or not running out of money they were gonna split up the company because the industry was breaking apart Intel and microprocessors Microsoft and software C gated disk drives you know Oracle and databases and to be more competitive from a product standpoint they were gonna split the company up into pieces Gerstner came in and said no way Gerson it was you know CEO of American Express said no that's not how customers want to buy he bought PwC for a song compared to what Carly Fiorina at HP a Carly Fiorina at HP wanted to pay I think 15 billion for it I want to say IBM paid five billion or maybe even less for PwC it completely transformed the company it transformed IBM into a services company and that's where what IBM is today they don't like when you say that but that's where the revenue was coming from what that did now and they also started to buy software companies IBM was restricted from getting into applications for years and years and years because of the DOJ because they owned the mainframe they had a monopoly while Microsoft and Intel changed all that IBM started to buy software companies and bought lots of them so they became a services company with a collection of software assets and the main mainframe and you know the power they have a storage business and you know Finance I'd be a global finance business etc etc so my my point is I'm not sure Jim Whitehurst would want to run that you know it's it's kind of messy now what you need run that is somebody who really understands finance knows how to turn the knobs and that's why I think you know Martin Schroeder is actually an excellent pick for that to keep the cash flow going to keep the dividend going to keep the stock buybacks going it's still in my view not a growth play I think there's certainly near-term growth that can be had by modernizing applications but I don't look at IBM as a growth company I look at IBM as a portfolio company that throws off a lot of cash and if and when the market stops rewarding growth and profit list growth a company like IBM will become more favorable to investors yeah and the question at the end of the day is after spending thirty four billion dollars for red hat does IBM help weather the storm of what is happening with the phenomenal growth of AWS the changes happening in Microsoft build more of a relationship than they've already had with Google and help position themselves for this next wave of IT there's IBM helped create a lot of the waves that you know happen in IT well the pure play cloud players are in it for the long game you know you know Amazon's philosophy is give tools to builders and allow them to disrupt the you know traditional old guard whether it's old guard technology companies or old guard industry players and you've seen the stat of how many Fortune 1000 companies or you know have gone out of business in the last 20 or 30 years or whatever it is that's going to continue and Amazon and and certainly Google and Microsoft want to support that disruption by providing cloud tooling and put the data in the hands of people that allows them to create new business models now that doesn't mean everybody's gonna throw up there mainframes it's it's not gonna happen it's certainly not gonna happen overnight and probably will never happen but I just don't see how IBM becomes a growth company in that scenario the growth is going to be continue to be with the cloud well but Dave we had seen IBM I'd say struggle a little bit when it comes to the the developers these days and the Red Hat acquisition is definitely going to be a boon to them in this space because Red Hat all about the developers that that's what you know that their customers are so you know that that's such a huge community that they've already tapped into so Ginny has said this hybrid multi-cloud is a chapter two with a trillion dollar opportunity so who else is going after that trillion dollar opportunity let's let's lay it out there who are the multi cloud players VMware obviously IBM Red Hat with open shift is in there Google with anthos Cisco is coming at it from a network perspective so they have coming at it from their position of strength even though you know you know they're relatively new entrants well ever everybody wants to be the new management layer in this multi cloud environment what VMware had done is had you know vCenter became you know the console for everyone as they were consolidating all of their silos and when I go to a multi cloud environment right where do I live you know Microsoft has a strong play there that's the other you know VMware IBM Red Hat anthos Google Mentos Cisco and Microsoft yeah and of course the one that while they won't say that they are multi cloud you can't talk about multi cloud without talking about Amazon because Amazon is a piece of everyone's cloud environment we were seeing what they're doing with outpost there so they are the kind of Spectre looming over this entire multi-cloud discuss yeah right on I think you got to put Amazon into that mix they will be an entrance into this multi cloud play and it's not gonna be a winner-take-all deal I could say cisco is coming at it from a position of networking strength Microsoft has its software estate and it's gonna do very well there IBM Red Hat coming at it from a standpoint of modernizing applications and there's a services could play and services component there and VMware of course coming at it from the the infrastructure operating system I don't see Oracle as interested in that market there may be some smaller players like turbo anomic you know who probably get gobbled up by one of these guys that we just mentioned but that really is the landscape and this is you know five six companies a trillion dollars there's plenty to go around all right Stu final thoughts on on the the Red Hat news the IBM news that they've finalized the Red Hat acquisition yes so you know what you want to look for is you know first of all you know what's happening organizationally you know if open shift is the primary you know the the tip of the sphere what we're talking about here for this you know cloud native multi-cloud world you know what does you know the IBM Cloud messaging looked like they're gonna have an analyst event here in a couple of weeks that you know that they've invited all the analysts to going into what does that cloud portfolio looks like how do they sort through all of the kubernetes options that they've had today do they try to elevate IBM cloud to be a stronger player or will they let Red Hat continue to play across all of the cloud environments that they have so you know organization and product positioning of the two things that I'm looking at the most Tom Siebel said publicly yesterday that IBM is a great company national international treasure but they miss cloud and they missed a I I wouldn't agree totally they didn't miss cloud they were late to cloud they had to buy software they're in cloud just like Oracle's in cloud not as competitive as the AWS cloud but they're they've got a cloud yeah HP doesn't have a cloud Dell doesn't have a cloud these these two companies that I just mentioned do AI yeah they're not sound of generalized AI like what Google and Amazon and Facebook and Microsoft are doing IBM's trying to solve you know big chewy problems iBM is a services company as they said so you know Watson you see a lot of negative stories about Watson but Watson requires a lot of services to make it work and it's as they say solving different problems so they're a player in AI multi cloud is new and this move the acquisition of red hat yes thirty four billion dollars expensive it's not gonna be pretty on the balance sheet but they get good cash flow so they'll deal with that over time it puts them right in the mix as a leader in multi cloud so thanks to for breaking down the the acquisition and thank you for watching this is Dave Volante what's do min and then we'll see you next time

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is >> a cute conversation. Hey, welcome back. Get ready. Geoffrey here with the Cube. We're gonna rip out the studios for acute conversation. It's the middle of the summer, the conference season to slow down a little bit. So we get a chance to do more cute conversation, which is always great. Excited of our next guest. He's Ridge, IP, Ops Statik. He's a VP and GM from key. Cite, Reject. Great to see you. >> Thank you for hosting us. >> Yeah. So we've had Marie on a couple of times. We had Bethany on a long time ago before the for the acquisition. But for people that aren't familiar with key site, give us kind of a quick overview. >> Sure, sure. So I'm within the excess solutions group Exhale really started was founded back in 97. It I peered around 2000 really started as a test and measurement company quickly after the I poet became the number one vendor in the space, quickly grew around 2012 and 2013 and acquired two companies Net optics and an ooey and net optics and I knew we were in the visibility or monitoring space selling taps, bypass witches and network packet brokers. So that formed the Visibility Group with a nice Xia. And then around 2017 key cite acquired Xia and we became I S G or extra Solutions group. Now, key site is also a very large test and measurement company. It is the actual original HB startup that started in Palo Alto many years ago. An HB, of course, grew, um it also started as a test and measurement company. Then later on it, it became a get a gun to printers and servers. HB spun off as agile in't, agile in't became the test and measurement. And then around 2014 I would say, or 15 agile in't spun off the test and measurement portion that became key site agile in't continued as a life and life sciences organization. And so key sites really got the name around 2014 after spinning off and they acquired Xia in 2017. So more joy of the business is testing measurement. But we do have that visibility and monitoring organization to >> Okay, so you do the test of measurement really on devices and kind of pre production and master these things up to speed. And then you're actually did in doing the monitoring in life production? Yes, systems. >> Mostly. The only thing that I would add is that now we are getting into live network testing to we see that mostly in the service provider space. Before you turn on the service, you need to make sure that all the devices and all the service has come up correctly. But also we're seeing it in enterprises to, particularly with security assessments. So reach assessment attacks. Security is your eye to organization really protecting the network? So we're seeing that become more and more important than they're pulling in test, particularly for security in that area to so as you. As you say, it's mostly device testing. But then that's going to network infrastructure and security networks, >> Right? So you've been in the industry for a while, you're it. Until you've been through a couple acquisitions, you've seen a lot of trends, so there's a lot of big macro things happening right now in the industry. It's exciting times and one of the ones. Actually, you just talked about it at Cisco alive a couple weeks ago is EJ Computer. There's a lot of talk about edges. Ej the new cloud. You know how much compute can move to the edge? What do you do in a crazy oilfield? With hot temperatures and no powers? I wonder if you can share some of the observations about EJ. You're kind of point of view as to where we're heading. And what should people be thinking about when they're considering? Yeah, what does EJ mean to my business? >> Absolutely, absolutely. So when I say it's computing, I typically include Io TI agent. It works is along with remote and branch offices, and obviously we can see the impact of Io TI security cameras, thermal starts, smart homes, automation, factory automation, hospital animation. Even planes have sensors on their engines right now for monitoring purposes and diagnostics. So that's one group. But then we know in our everyday lives, enterprises are growing very quickly, and they have remote and branch offices. More people are working from remotely. More people were working from home, so that means that more data is being generated at the edge. What it's with coyote sensors, each computing we see with oil and gas companies, and so it doesn't really make sense to generate all that data. Then you know, just imagine a self driving car. You need to capture a lot of data and you need to process. It just got really just send it to the cloud. Expect a decision to mate and then come back and so that you turn left or right, you need to actually process all that data, right? We're at the edge where the source of the data is, and that means pushing more of that computer infrastructure closer to the source. That also means running business critical applications closer to the source. And that means, you know, um, it's it's more of, ah, madness, massively distributed computer architecture. Um, what happens is that you have to then reliably connect all these devices so connectivity becomes important. But as you distribute, compute as well as applications, your attack surface increases right. Because all of these devices are very vulnerable. We're probably adding about 5,000,000 I ot devices every day to our network, So that's a lot of I O T. Devices or age devices that we connect many of these devices. You know, we don't really properly test. You probably know from your own home when you can just buy something and could easily connect it to your wife. I Similarly, people buy something, go to their work and connect to their WiFi. Not that device is connected to your entire network. So vulnerabilities in any of these devices exposes the entire network to that same vulnerability. So our attack surfaces increasing, so connection reliability as well as security for all these devices is a challenge. So we enjoy each computing coyote branch on road officers. But it does pose those challenges. And that's what we're here to do with our tech partners. Toe sold these issues >> right? It's just instinct to me on the edge because you still have kind of the three big um, the three big, you know, computer things. You got the networking right, which is just gonna be addressed by five g and a lot better band with and connectivity. But you still have store and you still have compute. You got to get those things Power s o a cz. You're thinking about the distribution of that computer and store at the edge versus in the cloud and you've got the Leighton see issue. It seems like a pretty delicate balancing act that people are gonna have to tune these systems to figure out how much to allocate where, and you will have physical limitations at this. You know the G power plant with the sure by now the middle of nowhere. >> It's It's a great point, and you typically get agility at the edge. Obviously, don't have power because these devices are small. Even if you take a room order branch office with 52 2 100 employees, there's only so much compute that you have. But you mean you need to be able to make decisions quickly. They're so agility is there. But obviously the vast amounts of computer and storage is more in your centralized data center, whether it's in your private cloud or your public cloud. So how do you do the compromise? When do you run applications at the edge when you were in applications in the cloud or private or public? Is that in fact, a compromise and year You might have to balance it, and it might change all the time, just as you know, if you look at our traditional history off compute. He had the mainframes which were centralized, and then it became distributed, centralized, distributed. So this changes all the time and you have toe make decisions, which which brings up the issue off. I would say hybrid, I t. You know, they have the same issue. A lot of enterprises have more of a, um, hybrid I t strategy or multi cloud. Where do you run the applications? Even if you forget about the age even on, do you run an on Prem? Do you run in the public cloud? Do you move it between class service providers? Even that is a small optimization problem. It's now even Matt bigger with H computer. >> Right? So the other thing that we've seen time and time again a huge trend, right? It's software to find, um, we've seen it in the networking space to compete based. It's offered to find us such a big write such a big deal now and you've seen that. So when you look at it from a test a measurement and when people are building out these devices, you know, obviously aton of great functional capability is suddenly available to people, but in terms of challenges and in terms of what you're thinking about in software defined from from you guys, because you're testing and measuring all this stuff, what's the goodness with the badness house for people, you really think about the challenges of software defined to take advantage of the tremendous opportunity. >> That's a really good point. I would say that with so far defined it working What we're really seeing is this aggregation typically had these monolithic devices that you would purchase from one vendor. That wonder vendor would guarantee that everything just works perfectly. What software defined it working, allows or has created is this desegregated model. Now you have. You can take that monolithic application and whether it's a server or a hardware infrastructure, then maybe you have a hyper visor or so software layer hardware, abstraction, layers and many, many layers. Well, if you're trying to get that toe work reliably, this means that now, in a way, the responsibility is on you to make sure that you test every all of these. Make sure that everything just works together because now we have choice. Which software packages should I install from which Bender This is always a slight differences. Which net Nick Bender should I use? If PJ smart Nick Regular Nick, you go up to the layer of what kind of ax elation should I use? D. P. D K. There's so many options you are responsible so that with S T N, you do get the advantage of opportunity off choice, just like on our servers and our PCs. But this means that you do have to test everything, make sure that everything works. So this means more testing at the device level, more testing at the service being up. So that's the predeployment stage and wants to deploy the service. Now you have to continually monitor it to make sure that it's working as you expected. So you get more choice, more diversity. And, of course, with segregation, you can take advantage of improvements on the hardware layer of the software layer. So there's that the segregation advantage. But it means more work on test as well as monitoring. So you know there's there's always a compromise >> trade off. Yeah, so different topic is security. Um, weird Arcee. This year we're in the four scout booth at a great chat with Michael the Caesars Yo there. And he talked about, you know, you talk a little bit about increasing surface area for attack, and then, you know, we all know the statistics of how long it takes people to know that they've been reach its center center. But Mike is funny. He you know, they have very simple sales pitch. They basically put their sniffer on your network and tell you that you got eight times more devices on the network than you thought. Because people are connecting all right, all types of things. So when you look at, you know, kind of monitoring test, especially with these increased surface area of all these, Iet devices, especially with bring your own devices. And it's funny, the H v A c seemed to be a really great place for bad guys to get in. And I heard the other day a casino at a casino, uh, connected thermometer in a fish tank in the lobby was the access point. How is just kind of changing your guys world, you know, how do you think about security? Because it seems like in the end, everyone seems to be getting he breached at some point in time. So it's almost Maur. How fast can you catch it? How do you minimize the damage? How do you take care of it versus this assumption that you can stop the reaches? You >> know, that was a really good point that you mentioned at the end, which is it's just better to assume that you will be breached at some point. And how quickly can you detect that? Because, on average, I think, according to research, it takes enterprise about six months. Of course, they're enterprise that are takes about a couple of years before they realize. And, you know, we hear this on the news about millions of records exposed billions of dollars of market cap loss. Four. Scout. It's a very close take partner, and we typically use deploy solutions together with these technology partners, whether it's a PM in P. M. But very importantly, security, and if you think about it, there's terabytes of data in the network. Typically, many of these tools look at the packet data, but you can't really just take those terabytes of data and just through it at all the tools, it just becomes a financially impossible toe provide security and deploy such tools in a very large network. So where this is where we come in and we were the taps, we access the data where the package workers was essentially groom it, filtering down to maybe tens or hundreds of gigs that that's really, really important. And then we feed it, feed it to our take partners such as Four Scout and many of the others. That way they can. They can focus on providing security by looking at the packets that really matter. For example, you know some some solutions only. Look, I need to look at the package header. You don't really need to see the send the payload. So if somebody is streaming Netflix or YouTube, maybe you just need to send the first mega byte of data not the whole hundreds of gigs over that to our video, so that allows them to. It allows us or helps us increase the efficiency of that tool. So the end customer can actually get a good R Y on that on that investment, and it allows for Scott to really look at or any of the tech partners to look at what's really important let me do a better job of investigating. Hey, have I been hacked? And of course, it has to be state full, meaning that it's not just looking at flow on one data flow on one side, looking at the whole communication. So you can understand What is this? A malicious application that is now done downloading other malicious applications and infiltrating my system? Is that a DDOS attack? Is it a hack? It's, Ah, there's a hole, equal system off attacks. And that's where we have so many companies in this in this space, many startups. >> It's interesting We had Tom Siebel on a little while ago actually had a W s event and his his explanation of what big data means is that there's no sampling air. And we often hear that, you know, we used to kind of prior to big day, two days we would take a sample of data after the fact and then tried to to do someone understanding where now the more popular is now we have a real time streaming engines. So now we're getting all the data basically instantaneously in making decisions. But what you just bring out is you don't necessarily want all the data all the time because it could. It can overwhelm its stress to Syria. That needs to be a much better management approach to that. And as I look at some of the notes, you know, you guys were now deploying 400 gigabit. That's right, which is bananas, because it seems like only yesterday that 100 gigabyte Ethan, that was a big deal a little bit about, you know, kind of the just hard core technology changes that are impacting data centers and deployments. And as this band with goes through the ceiling, what people are physically having to do, do it. >> Sure, sure, it's amazing how it took some time to go from 1 to 10 gig and then turning into 40 gig, but that that time frame is getting shorter and shorter from 48 2 108 100 to 400. I don't even know how we're going to get to the next phase because the demand is there and the demand is coming from a number of Trans really wants five G or the preparation for five G. A lot of service providers are started to do trials and they're up to upgrading that infrastructure because five G is gonna make it easier to access state of age quickly invest amounts of data. Whenever you make something easy for the consumer, they will consume it more. So that's one aspect of it. The preparation for five GS increasing the need for band with an infrastructure overhaul. The other piece is that we're with the neutralization. We're generating more Eastern West traffic, but because we're distributed with its computing, that East West traffic can still traverse data centers and geography. So this means that it's not just contained within a server or within Iraq. It actually just go to different locations. That also means your data center into interconnect has to support 400 gig. So a lot of network of hitmen manufacturers were typically call them. Names are are releasing are about to release 400 devices. So on the test side, they use our solutions to test these devices, obviously, because they want to release it based the standards to make sure that it works on. So that's the pre deployment phase. But once these foreign jiggy devices are deployed and typically service providers, but we're start slowly starting to see large enterprises deploy it as a mention because because of visualization and computing, then the question is, how do you make sure that your 400 gig infrastructure is operating at the capacity that you want in P. M. A. P M. As well as you're providing security? So there's a pre deployment phase that we help on the test side and then post deployment monitoring face. But five G is a big one, even though we're not. Actually we haven't turned on five year service is there's tremendous investment going on. In fact, key site. The larger organization is helping with a lot of these device testing, too. So it's not just Xia but key site. It's consume a lot of all of our time just because we're having a lot of engagements on the cellphone side. Uh, you know, decide endpoint side. It's a very interesting time that we're living in because the changes are becoming more and more frequent and it's very hot, so adapt and make sure that you're leading that leading that wave. >> In preparing for this, I saw you in another video camera. Which one it was, but your quote was you know, they didn't create electricity by improving candles. Every line I'm gonna steal it. I'll give you credit. But as you look back, I mean, I don't think most people really grown to the step function. Five g, you know, and they talk about five senior fun. It's not about your phone. It says this is the first kind of network built four machines. That's right. Machine data, the speed machine data and the quantity of Mr Sheen data. As you sit back, What kind of reflectively Again? You've been in this business for a while and you look at five G. You're sitting around talking to your to your friends at a party. So maybe some family members aren't in the business. How do you How do you tell them what this means? I mean, what are people not really seeing when they're just thinking it's just gonna be a handset upgrade there, completely missing the boat? >> Yeah, I think for the for the regular consumer, they just think it's another handset. You know, I went from three G's to 40 year. I got I saw bump in speed, and, you know, uh, some handset manufacturers are actually advertising five G capable handsets. So I'm just going to be out by another cell phone behind the curtain under the hurt. There's this massive infrastructure overhaul that a lot of service providers are going through. And it's scary because I would say that a lot of them are not necessarily prepared. The investment that's pouring in is staggering. The help that they need is one area that we're trying to accommodate because the end cell towers are being replaced. The end devices are being replaced. The data centers are being upgraded. Small South sites, you know, Um, there's there's, uh how do you provide coverage? What is the killer use case? Most likely is probably gonna be manufacturing just because it's, as you said mission to make mission machine learning Well, that's your machine to mission communication. That's where the connected hospitals connected. Manufacturing will come into play, and it's just all this machine machine communication, um, generating vast amounts of data and that goes ties back to that each computing where the edge is generating the data. But you then send some of that data not all of it, but some of that data to a centralized cloud and you develop essentially machine learning algorithms, which you then push back to the edge. The edge becomes a more intelligent and we get better productivity. But it's all machine to machine communication that, you know, I would say that more of the most of the five communication is gonna be much information communication. Some small portion will be the consumers just face timing or messaging and streaming. But that's gonna be there exactly. Exactly. That's going to change. I'm of course, we'll see other changes in our day to day lives. You know, a couple of companies attempted live gaming on the cloud in the >> past. It didn't really work out just because the network latency was not there. But we'll see that, too, and was seeing some of the products coming out from the lecture of Google into the company's where they're trying to push gaming to be in the cloud. It's something that we were not really successful in the past, so those are things that I think consumers will see Maur in their day to day lives. But the bigger impact is gonna be for the for the enterprise >> or jet. Thanks for ah, for taking some time and sharing your insight. You know, you guys get to see a lot of stuff. You've been in the industry for a while. You get to test all the new equipment that they're building. So you guys have a really interesting captaincy toe watches developments. Really exciting times. >> Thank you for inviting us. Great to be here. >> All right, Easier. Jeff. Jeff, you're watching the Cube. Where? Cube studios and fellow out there. Thanks for watching. We'll see you next time.