(plane engine roars) (upbeat music) >> They call me Dr. Goh. I'm Senior Vice President and Chief Technology Officer of AI at Hewlett Packard Enterprise. And today I'm in Munich, Germany. Home to one and a half million people. Munich is famous for everything from BMW, to beer, to breathtaking architecture and festive markets. The Bavarian capital is the beating heart of Germany's automobile industry. Over 50,000 of its residents work in automotive engineering, and to date, Munich allocated around 30 million euros to boost electric vehicles and infrastructure for them. (upbeat music) >> Hello, everyone, my name is Dr. Jerome Baudry. I am a professor at the University of Alabama in Huntsville. Our mission is to use a computational resources to accelerate the discovery of drugs that will be useful and efficient against the COVID-19 virus. On the one hand, there is this terrible crisis. And on the other hand, there is this absolutely unique and rare global effort to fight it. And that I think is a is a very positive thing. I am working with the Cray HPE machine called Sentinel. This machine is so amazing that it can actually mimic the screening of hundreds of thousands, almost millions of chemicals a day. What we take weeks, if not months, or years, we can do in a matter of a few days. And it's really the key to accelerating the discovery of new drugs, new pharmaceuticals. We are all in this together, thank you. (upbeat music) >> Hello, everyone. I'm so pleased to be here to interview Dr. Jerome Baudry, of the University of Alabama in Huntsville. >> Hello, Dr. Goh, I'm very happy to be meeting with you here, today. I have a lot of questions for you as well. And I'm looking forward to this conversation between us. >> Yes, yes, and I've got lots of COVID-19 and computational science questions lined up for you too Jerome. Yeah, so let's interview each other, then. >> Absolutely, let's do that, let's interview each other. I've got many questions for you. And , we have a lot in common and yet a lot of things we are addressing from a different point of view. So I'm very much looking forward to your ideas and insights. >> Yeah, especially now, with COVID-19, many of us will have to pivot a lot of our research and development work, to address the most current issues. I watch your video and I've seen that you're very much focused on drug discovery using super computing. The central notebook you did, I'm very excited about that. Can you tell us a bit more about how that works, yeah? >> Yes, I'd be happy to in fact, I watch your video as well manufacturing, and it's actually quite surprisingly close, what we do with drugs, and with what other people do with planes or cars or assembly lanes. we are calculating forces, on molecules, on drug candidates, when they hit parts of the viruses. And we essentially try to identify what small molecules will hit the viruses or its components, the hardest to mess with its function in a way. And that's not very different from what you're doing. What you are describing people in the industry or in the transportation industry are doing. So that's our problem, so to speak, is to deal with a lot of small molecules. Guy creating a lot of forces. That's not a main problem, our main problem is to make intelligent choices about what calculates, what kind of data should we incorporate in our calculations? And what kind of data should we give to the people who are going to do the testing? And that's really something I would like you to do to help us understand better. How do you see artificial intelligence, helping us, putting our hands on the right data to start with, in order to produce the right data and accuracy. >> Yeah, that's that's a great question. And it is a question that we've been pondering in our strategy as a company a lot recently. Because more and more now we realize that the data is being generated at the far out edge. By edge. I mean, something that's outside of the cloud and data center, right? Like, for example, a more recent COVID-19 work, doing a lot of cryo electron microscope work, right? To try and get high resolution pictures of the virus and at different angles, so creating lots of movies under electron microscope to try and create a 3D model of the virus. And we realize that's the edge, right, because that's where the microscope is, away from the data center. And massive amounts of data is generated, terabytes and terabytes of data per day generated. And we had to develop means, a workflow means to get that data off the microscope and provide pre-processing and processing, so that they can achieve results without delay. So we learned quite a few lessons there, right, especially trying to get the edge to be more intelligent, to deal with the onslaught of data coming in, from these devices. >> That's fantastic that you're saying that and that you're using this very example of cryo-EM, because that's the kind of data that feeds our computations. And indeed, we have found that it is very, very difficult to get the right cryo-EM data to us. Now we've been working with HPE supercomputer Sentinel, as you may know, for our COVID-19 work. So we have a lot of computational power. But we will be even faster and better, frankly, if we knew what kind of cryo-EM data to focus on. In fact, most of our discussions are based on not so much how to compute the forces of the molecules, which we do quite well on an HP supercomputer. But again, what cryo-EM 3D dimensional space to look at. And it's becoming almost a bottleneck. >> Have access to that. >> And we spend a lot of time, do you envision a point where AI will be able to help us, to make this kind of code almost live or at least as close to live as possible, as that that comes from the edge? How to pack it and not triage it, but prioritize it for the best possible computations on supercomputers? >> What a visionary question and desire, right? Like exactly the vision we have, right? Of course, the ultimate vision, you aim for the best, and that will be a real time stream of processed data coming off the microscope straight, providing your need, right? We are not there. Before this, we are far from there, right? But that's the aim, the ability to push more and more intelligence forward, so that by the time the data reaches you, it is what you need, right, without any further processing. And a lot of AI is applied there, particularly in cryo-EM where they do particle picking, right, they do a lot of active pictures and movies of the virus. And then what they do is, they rotate the virus a little bit, right? And then to try and figure out in all the different images in the movies, to try and pick the particles in there. And this is very much image processing that AI is very good at. So many different stages, application is made. The key thing, is to deal with the data that is flowing at this at this speed, and to get the data to you in the right form, that in time. So yes, that's the desire, right? >> It will be a game changer, really. You'll be able to get things in a matter of weeks, instead of a matter of years to the colleague who will be doing the best day. If the AI can help me learn from a calculation that didn't exactly turn out the way we want it to be, that will be very, very helpful. I can see, I can envision AI being able to, live AI to be able to really revolutionize all the process, not only from the discovery, but all the way to the clinical, to the patient, to the hospital. >> Well, that's a great point. In fact, I caught on to your term live AI. That's actually what we are trying to achieve. Although I have not used that term before. Perhaps I'll borrow it for next time. >> Oh please, by all means. >> You see, yes, we have done, I've been doing also recent work on gene expression data. So a vaccine, clinical trial, they have the blood, they get the blood from the volunteers after the first day. And then to run very, very fast AI analytics on the gene expression data that the one, the transcription data, before translation to emit amino acid. The transcription data is enormous. We're talking 30,000, 60,000 different items, transcripts, and how to use that high dimensional data to predict on day one, whether this volunteer will get an adverse event or will have a good antibody outcome, right? For efficacy. So yes, how to do it so quickly, right? To get the blood, go through an SA, right, get the transcript, and then run the analytics and AI to produce an outcome. So that's exactly what we're trying to achieve, yeah. Yes, I always emphasize that, ultimately, the doctor makes that decision. Yeah, AI only suggests based on the data, this is the likely outcome based on all the previous data that the machine has learned from, yeah. >> Oh, I agree, we wouldn't want the machine to decide the fate of the patient, but to assist the doctor or nurse making the decision that will be invaluable? And are you aware of any kind of industry that already is using this kind of live AI? And then, is there anything in, I don't know in sport or crowd control? Or is there any kind of industry? I will be curious to see who is ahead of us in terms of making this kind of a minute based decisions using AI? Yes, in fact, this is very pertinent question. We as In fact, COVID-19, lots of effort working on it, right? But now, industries and different countries are starting to work on returning to work, right, returning to their offices, returning to the factories, returning to the manufacturing plants, but yet, the employers need to reassure the employees that things, appropriate measures are taken for safety, but yet maintain privacy, right? So our Aruba organization actually developed a solution called contact location tracing inside buildings, inside factories, right? Why they built this, and needed a lot of machine learning methods in there to do very, very well, as you say, live AI right? To offer a solution? Well, let me describe the problem. The problem is, in certain countries, and certain states, certain cities where regulations require that, if someone is ill, right, you actually have to go in and disinfect the area person has been to, is a requirement. But if you don't know precisely where the ill person has been to, you actually disinfect the whole factory. And if you have that, if you do that, it becomes impractical and cost prohibitive for the company to keep operating profitably. So what they are doing today with Aruba is, that they carry this Bluetooth Low Energy tag, which is a quarter size, right? The reason they do that is, so that they extract the tag from the person, and then the system tracks, everybody, all the employees. We have one company, there's 10,000 employees, right? Tracks everybody with the tag. And if there is a person ill, immediately a floor plan is brought up with hotspots. And then you just targeted the cleaning services there. The same thing, contact tracing is also produced automatically, you could say, anybody that is come in contact with this person within two meters, and more than 15 minutes, right? It comes up the list. And we, privacy is our focused here. There's a separation between the tech and the person, on only restricted people are allowed to see the association. And then things like washrooms and all that are not tracked here. So yes, live AI, trying to make very, very quick decisions, right, because this affects people. >> Another question I have for you, if you have a minute, actually has to be the same thing. Though, it's more a question about hardware, about computer hardware purify may. We're having, we're spending a lot of time computing on number crunching giant machines, like Sentinel, for instance, which is a dream to use, but it's very good at something but when we pulled it off, also spent a lot of time moving back and forth, so data from clouds from storage, from AI processing, to the computing cycles back and forth, back and forth, did you envision an architecture, that will kind of, combine the hardware needed for a massively parallel calculations, kind of we are doing. And also very large storage, fast IO to be more AI friendly, so to speak. You see on the horizon, some kind of, I would say you need some machine, maybe it's to be determined, to be ambitious at times but something that, when the AI ahead plan in terms of passing the vector to the massively parallel side, yeah, that makes sense? >> Makes a lot of sense. And you ask it I know, because it is a tough problem to solve, as we always say, computation, right, is growing capability enormously. But bandwidth, you have to pay for, latency you sweat for, right? >> That's a very good >> So moving data is ultimately going to be the problem. >> It is. >> Yeah, and we've move the data a lot of times, right, >> You move back and forth, so many times >> Back and forth, back and forth, from the edge that's where you try to pre-process it, before you put it in storage, yeah. But then once it arrives in storage, you move it to memory to do some work and bring it back and move it memory again, right, and then that's what HPC, and then you put it back into storage, and then the AI comes in you, you do the learning, the other way around also. So lots of back and forth, right. So tough problem to solve. But more and more, we are looking at a new architecture, right? Currently, this architecture was built for the AI side first, but we're now looking and see how we can expand that. And this is that's the reason why we announced HPE Ezmeral Data Fabric. What it does is that, it takes care of the data, all the way from the edge point of view, the minute it is ingested at the edge, it is incorporated in the global namespace. So that eventually where the data arrives, lands at geographically one, or lands at, temperature, hot data, warm data or cold data, regardless of eventually where it lands at, this Data Fabric checks everything, from in a global namespace, in a unified way. So that's the first step. So that data is not seen as in different places, different pieces, it is a unified view of all the data, the minute that it does, Just start from the edge. >> I think it's important that we communicate that AI is purposed for good, A lot of sci-fi movies, unfortunately, showcase some psychotic computers or teams of evil scientists who want to take over the world. But how can we communicate better that it's a tool for a change, a tool for good? >> So key differences are I always point out is that, at least we have still judgment relative to the machine. And part of the reason we still have judgment is because our brain, logical center is automatically connected to our emotional center. So whatever our logic say is tempered by emotion, and whatever our emotion wants to act, wants to do, right, is tempered by our logic, right? But then AI machine is, many call them, artificial specific intelligence. They are just focused on that decision making and are not connected to other more culturally sensitive or emotionally sensitive type networks. They are focus networks. Although there are people trying to build them, right. That's this power, reason why with judgment, I always use the phrase, right, what's correct, is not always the right thing to do. There is a difference, right? We need to be there to be the last Judge of what's right, right? >> Yeah. >> So that says one of the the big thing, the other one, I bring up is that humans are different from machines, generally, in a sense that, we are highly subtractive. We, filter, right? Well, machine is highly accumulative today. So an AI machine they accumulate to bring in lots of data and tune the network, but our brains a few people realize, we've been working with brain researchers in our work, right? Between three and 30 years old, our brain actually goes through a pruning process of our connections. So for those of us like me after 30 it's done right. (laughs) >> Wait till you reach my age. >> Keep the brain active, because it prunes away connections you don't use, to try and conserve energy, right? I always say, remind our engineers about this point, about prunings because of energy efficiency, right? A slice of pizza drives our brain for three hours. (laughs) That's why, sometimes when I get need to get my engineers to work longer, I just offer them pizza, three more hours, >> Pizza is universal solution to our problems, absolutely. Food Indeed, indeed. There is always a need for a human consciousness. It's not just a logic, it's not like Mr. Spock in "Star Trek," who always speaks about logic but forgets the humanity aspect of it. >> Yes, yes, The connection between the the logic centers and emotional centers, >> You said it very well. Yeah, yeah and the thing is, sleep researchers are saying that when you don't get enough REM sleep, this connection is weakened. Therefore, therefore your decision making gets affected if you don't get enough sleep. So I was thinking, people do alcohol test breathalyzer test before they are allowed to operate sensitive or make sensitive decisions. Perhaps in the future, you have to check whether you have enough REM sleep before, >> It is. This COVID-19 crisis obviously problematic, and I wish it never happened, but there is something that I never experienced before is, how people are talking to each other, people like you and me, we have a lot in common. But I hear more about the industry outside of my field. And I talk a lot to people, like cryo-EM people or gene expression people, I would have gotten the data before and process it. Now, we have a dialogue across the board in all aspects of industry, science, and society. And I think that could be something wonderful that we should keep after we finally fix this bug. >> Yes. yes, yes. >> Right? >> Yes, that's that's a great point. In fact, it's something I've been thinking about, right, for employees, things have changed, because of COVID-19. But very likely, the change will continue, yeah? >> Right. Yes, yes, because there are a few positive outcomes. COVID-19 is a tough outcome. But there positive side of things, like communicating in this way, effectively. So we were part of the consortium that developed a natural language processing system in AI system that would allow you scientists to do, I can say, with the link to that website, allows you to do a query. So say, tell me the latest on the binding energy between the Sasko B2 virus like protein and the AC receptor. And then you will, it will give you a list of 10 answers, yeah? And give you a link to the papers that say, they say those answers. If you key that in today to NLP, you see 315 points -13.7 kcal per mole, which is right, I think the general consensus answer, and see a few that are highly out of out of range, right? And then when you go further, you realize those are the earlier papers. So I think this NLP system will be useful. (both chattering) I'm sorry, I didn't mean to interrupt, but I mentioned yesterday about it, because I have used that, and it's a game changer indeed, it is amazing, indeed. Many times by using this kind of intelligent conceptual, analyzes a very direct use, that indeed you guys are developing, I have found connections between facts, between clinical or pharmaceutical aspects of COVID-19. That I wasn't really aware of. So a it's a tool for creativity as well, I find it, it builds something. It just doesn't analyze what has been done, but it creates the connections, it creates a network of knowledge and intelligence. >> That's why three to 30 years old, when it stops pruning. >> I know, I know. (laughs) But our children are amazing, in that respect, they see things that we don't see anymore. they make connections that we don't necessarily think of, because we're used to seeing a certain way. And the eyes of a child, are bringing always something new, which I think is what AI could potentially bring here. So look, this is fascinating, really. >> Yes, yes, difference between filtering subtractive and the machine being accumulative. That's why I believe, the two working together, can have a stronger outcome if used properly. >> Absolutely. And I think that's how AI will be a force for good indeed. Obviously see, seems that we would have missed that would end up being very important. Well, we are very interested in or in our quest for drug discovery against COVID-19, we have been quite successful so far. We have accelerated the process by an order of magnitude. So we're having molecules that are being tested against the virus, otherwise, it would have taken maybe three or four years to get to that point. So first thing, we have been very fast. But we are very interested in natural products, that chemicals that come from plants, essentially. We found a way to mine, I don't want to say explore it, but leverage, that knowledge of hundreds of years of people documenting in a very historical way of what plants do against what diseases in different parts of the world. So that really has been a, not only very useful in our work, but a fantastic bridge to our common human history, basically. And second, yes, plants have chemicals. And of course we love chemicals. Every living cell has chemicals. The chemicals that are in plants, have been fine tuned by evolution to actually have some biological function. They are not there just to look good. They have a role in the cell. And if we're trying to come up with a new growth from scratch, which is also something we want to do, of course, then we have to engineer a function that evolution hasn't already found a solution to, for in plants, so in a way, it's also artificial intelligence. We have natural solutions to our problems, why don't we try to find them and see their work in ourselves, we're going to, and this is certainly have to reinvent the wheel each time. >> Hundreds of millions of years of evolution, >> Hundreds of millions of years. >> Many iterations, >> Yes, ending millions of different plants with all kinds of chemical diversity. So we have a lot of that, at our disposal here. If only we find the right way to analyze them, and bring them to our supercomputers, then we will, we will really leverage this humongus amount of knowledge. Instead of having to reinvent the wheel each time we want to take a car, we'll find that there are cars whose wheels already that we should be borrowing instead of, building one each time. Most of the keys are out there, if we can find them, They' re at our disposal. >> Yeah, nature has done the work after hundreds of millions of years. >> Yes. (chattering) Is to figure out, which is it, yeah? Exactly, exactly hence the importance of biodiversity. >> Yeah, I think this is related to the Knowledge Graph, right? Where, yes, to objects and the linking parameter, right? And then you have hundreds of millions of these right? A chemical to an outcome and the link to it, right? >> Yes, that's exactly what it is, absolutely the kind of things we're pursuing very much, so absolutely. >> Not only only building the graph, but building the dynamics of the graph, In the future, if you eat too much Creme Brulee, or if you don't run enough, or if you sleep, well, then your cells, will have different connections on this graph of the ages, will interact with that molecule in a different way than if you had more sleep or didn't eat that much Creme Brulee or exercise a bit more, >> So insightful, Dr. Baudry. Your, span of knowledge, right, impressed me. And it's such fascinating talking to you. (chattering) Hopefully next time, when we get together, we'll have a bit of Creme Brulee together. >> Yes, let's find out scientifically what it does, we have to do double blind and try three times to make sure we get the right statistics. >> Three phases, three clinical trial phases, right? >> It's been a pleasure talking to you. I like we agreed, you knows this, for all that COVID-19 problems, the way that people talk to each other is, I think the things that I want to keep in this in our post COVID-19 world. I appreciate very much your insight and it's very encouraging the way you see things. So let's make it happen. >> We will work together Dr.Baudry, hope to see you soon, in person. >> Indeed in person, yes. Thank you. >> Thank you, good talking to you.

>>Yeah. Hello and welcome to the Cubes Presentation of Women in text. Global event Celebrating International Women's Day I'm John for a host of the Cube were with Sally E. Senior Policy Advisor Global Foundation for Cyber Studies and Research. Sally, great to see you. Thanks for coming on the cue for International Women's Day. Appreciate it. >>Pleasure, John. Great speech again. >>Love your title. Global Foundation for Cyber Studies. Um, global is a big part of the theme this year. Uh, cyber studies. We're seeing a lot of cyber activity all around the world, networks, communities coming together, the role of data. I mean, everything is touching our lives. There are no boundaries anymore. What does it all mean? There's so much to talk about your in the middle of it before we get into it. Tell us about your career and your history. How you got interested in tech and what you're working on. >>Absolutely. I love it. Kind of this age of convergence coming together right now, isn't it? That's how I would describe it. And that's kind of a bit like my career. I think in many ways as well. So for the audience, really great to be here and share about that today, and I kind of say, three main palace, so one would be emergent technologies. So, you know, I started off right through from coding to advisory to CTO type roles as well also change management. And now I'm more advisors right across from a I to five G to to Iot and security, for example as well. Also passionate about education checking education for me. They always go hand in hand, some a professor at a number of universities and in my non for profit, we really do a lot of outreach around educational opportunities as well. And that third pillar opponent hinted at it already will be social impact. So really passionate about how we can use tech as a force for good things around sustainability right at the heart of that, but also around diversity equity and inclusion. So we do a lot of pro project your locally and globally around kind of reframing what a tech career looks like, giving people more democratised access. Those tech opportunities outside of that a bit like yourself, you know, podcast host and writer and speaker and things as well, so very much going to building that community around key tech topics. >>Well, folks watching should check it out on Twitter. She's that great content you mentioned Mobile World Congress. Before we get on camera, you mentioned convergence. I mean, we're at a time now. I got to ask you while I got you here before we get into the whole schools and career tech thing, we've seen this movie before, but never at this scale. The convergence and the confluence of education and scale of cloud computing, the ability to level up and get, um, I won't say democratised. That's kind of overused. But I'm just talking about like with cloud computing could be educated and in market with a job instantly. Um, the barriers just seem to be moving away because of the the openings and the roles are changing. So, more than ever, this whole new tech scene comes together in a way. Can you share your thoughts and vision because to me, we're seeing this happening at such a scale unprecedented in my career? >>It is. And that's one of those words that the part had been overused, unprecedented, but right now it really, really is. It's not just a speed of change. I think it's a scale of change as well. You know, I think previously we've talked about disciplines in silos to a certain extent. Haven't we know in terms of like, an AI special is, um or five g one or other disciplines as well? But really, now that convergence about what one tech enables another, it really is that smart technology coming together for more and more different use cases, but that residents around how important education is alongside that alongside process alongside culture and shared values as well it really is. It's kind of holistic integration of everything that matters at the moment. And it's evolving business models as well. You know, shared values rights centre stage around that MWC just come back from that, And the key topics there weren't just by G, it was the importance of ecosystem collaboration. For example, there are less tracks that were isolated on one technology. It was more this conflation of these different technologies coming together and what we can achieve from that from business but also for society so really exciting focus areas now things that maybe once or a few years ago, more than periphery. They're now absolutely centre stage. So it's good to see that progress in that area. And I love to advocate around that. >>And the education piece is so important, and we always stay here in Cuba. It's a data problem, right? Everything's a data problem when you look at schools and education is structured and unstructured data kind of our our systems right, So structured as schools, institutions, those kinds of career paths or education pathways. And then you haven't structured freeform communities, seeing a lot more education going on within groups. Um, off structured environments like schools, Can you and you do a lot with schools? Can you share more how you're doing? Um uh, work with schools specifically on the structured side to get girls into careers faster and tech? And then can you also comment on the other side? What's going on in the communities because it's it's kind of going on in parallel, but they're not mutually exclusive. >>No, absolutely community, absolutely key word that I love that, and I think when we're talking about diversity and technology, it's not just what we're doing now with what we're looking at is looking ahead, but also looking at future pipeline as well. So for me, I use this express a little bit. But change the narrative. That's what springs to mind for me when we're talking about that, and particularly for girls going into technology but also more broadly, diversity of experience. More broadly, we do have these drop offs, so UK is one example, but it is really representative of the global trends that we're seeing. Now. We get a drop off of girls in particular, taking ice subjects at GCSE level so kind of that subject choice choice at 12 to 14, that kind of area. We get the same thing at a level that's equivalent of 16 to 18 and then even safer university or even apprenticeships, whichever both equally valid. But even if people are taking those types of skills, they're not then choosing to apply them in their careers. So we're seeing these kind of three pillars where we need to intervene earlier. So for me, the more that we can do things you know from dedicated educational offers, but equally partnering with tech companies to do outreach around this area. We need to go in younger and younger is so important to address that. Why? Why are people thinking they can't? Why is his career not for me, for example, so addressing that is huge. And that's one of the things we do with my nonprofit that's called aspirational futures. We go into schools and two universities, but equally do things with older adults and re Skilling and up Skilling as well. Because again, we can't leave that behind either. There's something for all different kind of age groups and backgrounds here, but specifically, I think, in terms of getting people interested in this career, curiosity matters. You know, I think it's an underrated skills. So it's changing the narrative again. And what the tech career actually is, what skills are valid? You know, I mentioned, I have a coding background as a starter. But not all tech careers involve coding, particularly the rise of low code or no code, for example as well. So really valued skill. But so many other skills are valid as well, you know, creativity or emotional intelligence problem solving skills. So for me, I like to drive forward. All those skills can make a difference as an individual, as a team, so your you know your tech career. All those skills are valid and you can make a huge difference. And I also think, you know, just kind of really bringing to the fore what different types of projects you can be involved in in tech as well. And I found really resonating when you can talk about tech for good projects and show how you're making a difference about some of those big challenges. Um, that's kind of really kind of resonating responsible people as well. So again, the more we can show tangible projects where you can make a difference and the whole range of skills that are involved in that it really helps people to think differently and gain that skills confidence. So it's like, >>Well, that's awesome insight. I want to just double click on that for a second, because one the drop off. Can you just repeat the ages where you see the drop off with the drop offs are >>absolutely yeah, no problem, John. So it's kind of when you're making your first choices around your first kind of qualifications. Between that 12 to 14 age group, 16 to 18 and then 18 to 21 I think we've really got to tackle that So again the earlier we can go in the better and again supporting people within organisations as well. So I do a lot of work like internally, with organisations as well people looking to up skill and re skill. You mentioned about data and the importance of data literacy earlier on in the conversation as well. For example, going into organisations and really helping to support people in all roles, not just tech facing roles develop that skills, confidence as well. So for me it's access to skills really bringing forward the difference. You can make that holistic range of skills that makes a difference, but also the confidence to apply them as well. You know, we talk about agility, of organisations, a lot areas, one of those kind of words in the last 12 months. But maybe we don't talk about personal agility and team agility as well. So I kind of talked about it. This little toolbox, if we can give people more and more things to draw from it, the only constant is this rate of change. If you've got more things in your armoury to cope with that and be an agile to that. It takes that fear away about what happens next because you feel you've got more skills to dip into it and to apply. So for me, it's that that confidence, not just the access to the skills >>and the other thing, too, I thought was insightful. I want to just reiterate and bring to the surface again as skills, right? So you don't have to be a coder. And I see I have two daughters just with my family. Yeah, I do python. They kind of put their toe in the water cause it's cool. Maybe that's a path, and they kind of don't like, maybe get into it. But it's not about coding anymore because you said low code, no code. Certainly. Maybe AI writes the code. We all see that happening. It's problem solving. It's you could be in health care and you could be nerd native, as we say, as on some of the other interviews of that year at the problem, solving the aperture of skills is much broader now. Can >>you share more than >>more than because with your with your programme and your nonprofit, I know you're in the middle of it, and this is important to get that out there. >>Absolutely so skills. You know, I think we need to change the focus on what skills make a difference if you see what I mean. I think you're absolutely right. There's some misconceptions about, you know, you want to go into tech, you need to be a coda. And you're right with the upscale around low Skilling. Sorry, Low code and the code opportunities. Um, I think the niches around being a specialist. Koda. We're gonna get more roles in that area, but in other areas, we need to look at different skills gap. So I'm advising people to look at where the gaps are now. So cyber security is a key example of that testing architecture. Those gaps are getting bigger. Their amazing skills, opportunities. They're so focused on a particular discipline. But it's all those skills that surround that that make a difference as well. So as I mentioned, you know, e Q creativity, communication skills, because it's not just about having the skills to build the future, knew that imagination to refocus about what that could even be. You know, that was one of the MWC 20 to refrain, reimagine and I love to kind of galvanise that spirit and people that you can be part of that, you know, wherever you are now. And I actually run a little series called 365, and you mentioned something right at the start of our conversation about International Women's Day being such an important focus area. But also we need to think about this beyond that as well. So hence that's the title of the series that I run because it's a focus on that every single day of the year. You know, I interviewed people that could be a C suite roles, but equally I've had some amazing interviews with 12 to 14 year olds, even younger, the youngest of the seven year old. He's doing like an amazing project in their kitchen with a three D printer working with local school or a hospice doing something around Ukraine. Another project we're doing at the moment, actually, and it's so resonating it's trying to show people wherever you are now, wherever you want to be, there's somebody relatable that you can make. You can see whatever sector, in whatever age, whatever background, and I think it's to give that inspiration. Hey, you know what I can do that that can be me. So visibility of role models, it really matters. And to really broaden out what role model looks like, you know? >>And then I think people out there you see yourself. I mean, this is what we been >>proven right? >>It's proven I want to get into the aspirational futures thing that you have going on, and I know this is important to you, but also something else you said was, is that there's more jobs open and say cybersecurity than ever before. And you're seeing this trend where all these new roles are emerging because of the tech that weren't around years ago, right? And so we've been having conversations in the Cube saying, Hey, all these roles are new, but also problems are new to these New new problems are surfacing because of the this new environment we're in. So these new roles still have to solve problems, so we need people to solve those problems. This is the future. This is the conversation that people are trying to get zero in on misinformation, cybersecurity, you name it. Society is changing with >>new. You >>have new new problems and new opportunities. Could you share your aspirational future? How you vector into that? >>Yeah, absolutely. And for me it's just again that we're convergence around people in technology and partnership, and that's what we aim to do. We do projects at a very local level, but equally we do them at national and international level as well. And one of our kind of people assume I'm talking pillars a lot, but I like it as a framework. So one of those esteem learning. So putting an equal value on the arts as well as science, technology, engineering, mathematics because I think they are. You know, as I mentioned before, hand that imagination, creativity, curiosity, collaboration, skills. They're equally valid as a different types of tech skills as well. We need an equal value and all of them. I think that's hugely important, important today. I think over the last 5 to 10 years, maybe there's been less of a focus within curriculums on the arts area than the other areas. So for me, putting that equal focus back is hugely important to navigate change, you know, I think that's that's that's absolutely key. So we focus on that area and we do a whole range of tech for good projects, and that's the way we help people to learn, you know, for example, data 90% at the moment of data isn't touched again when it's archived after three months. How can we turn that into a learning opportunity? For example? Some of the projects we use some of this is not going to be used again. We do it in a very safe, secure way, but we use that as one of our training aids, and then we apply them for local projects. We have initiatives from hackathons and ideation right through to very tangible hubs that we've actually built out where people can go, learn up skill and kind of learn through play and experimentation as well. Because again, I think that sometimes under explored that type of value and that freedom to be able to do that. And we also do things, change management skills. We talk about agile learning, agile technology need agile change management as well. So it's a very holistic skills. Look at what you need to navigate that future and have the confidence to apply them. So steam is very much our focus, applying them for tech for good projects and doing that externally, but also within organisations as well. So that very much is shared value approach to good business, but good for society as well. So yes, that this toolbox, that technology I applied earlier we really try and give people that support. To be able to do that, to move forward with confidence and optimism. >>I think adding the aid to stem really for steam is really smart because entrepreneurship or any problem solving creativity is the spark of innovation. >>And that's a super >>important skill. And we've seen it, whether it's startup or in a big company or in society, so super, super insightful. So I got to ask you, as a policy senior policy advisor on cyber studies globally, what are the core issues you're looking at right now? What are you shutting the light on and what's the most important thing you're working on? And then what's the most important thing you're working that people aren't talking about, that people should pay attention to >>Absolutely so. One of my key roles of the foundation is is kind of share of global trust. Essentially, um, and again trust is that one of the key issues of our time? One thing that people are talking about so much that relates with that actually is there's there's research from a group called The Woman. They've been looking at this for about 17 years or so. The research that came out most recently and I've got some original research that kind of support this as well is that for the first time ever, consumers are looking at organisations like tech organisations and other large organisations, in particular the enterprise level, really, as the bastions of trust to a bigger extent than NGOs or even governments. And that's the first time we've seen it at that level. So trust really really matters. It's one of the biggest differentiators of our time, so we're trying to help people. How do you establish trust? How do you build transparency, commitment and accountability, particularly in areas where there's currently confusion, so as one example going back Security zero Trust That phrase is used an awful lot, isn't it? But it's sometimes causing some confusion. Actually, it against what it's trying to deliver if you see what to me. So now I just do something recently with SMB s in particular and there is a confusion that effectively, you know, you could You could buy off the shelf and it's once and done. Um, And then we're sorted for the zero Trust security. And obviously it's not like that. It's an ongoing journey, and there's so many different constituent parts. So there's some things I'm seeing at the moment in the market with there's confusion around around certain language, for example. So again it goes back to backing things up with the technology but also research and awareness so we can see where those skills gaps are. You can see where there's awareness gaps are we can help to fill them. So that's an important part of that particular role bringing the technology in the culture and the education hand in hand together. So it's something I'm really passionate about, and for me sort of related to this, Um, I do a lot of work around S G, um, to the sustainable development goals. In particular, environmental and social governance is something that's becoming much more of a bigger kind of centre stage conversation. I'm an action point in a moment which is fantastic because this is something I've been involved in kind as long as I can remember. So I work directly with organisations like, um Unesco, lots of different professional bodies. It's kind of a huge driver for me. So one thing to kind of look out for that's coming very soon. I'm seeing an issue around around measurement in this area. You know, we're seeing consumers becoming more and more conscious and employees, you know you want to work for by from advocate organisations that have that same value alignment that you have personally and professionally, hugely important. We're seeing some great reports coming out around better e S g measurement. But it can be hard to compare between different organisations, so we are getting more transparency. But it's difficult sometimes to make fare comparisons. Um, so what I'm trying to do a lot of work on at the moment is how you go beyond that transparency to commitment to accountability and that deeper level and that comparability. So I would say kind of to the audience moment, Look out for a bit of a new index. It's going to help people, I think, make those conscious choices make informed choices. So it's something I'm super, super passionate about. I want to try and take that to next level in terms of its actualisation. >>That's awesome. And certainly we'll link to it on our site. All the work you're doing on interviews will put links there as well. We'll make sure we'll follow up on that. Great to have you on. You're such an inspiration. Amazing work, cutting edge work. And I'm I'm super impressed with the cyber studies, and I think this is really important. I have to ask you a final question because you're in the middle of it again with covid and the unfortunate situations we've been living with Covid. And now, obviously with this Ukraine situation that the cyber has been pulled to the front of the agenda and you're seeing a cultural shift. You certainly got Web three. Cyber is now part of everyone's life, and they can see it. They've been seeing it living it. Everything's been pulled forward as a cultural shift happening, okay, and and it's really interesting right now, and I want to get your thoughts because this now people are now aware what cyberwar means cyber security cyber. At home, I have remote work. Cyber has become front and centre or digital. However you want to call it in our lives pulled forward. >>So I'm not even sure in some >>cases, maybe rightfully so, and others. What's your view on this whole cultural cyber being pulled forward? >>It is. It's really, really interesting. And so one of the things I do is I am now ready to a Cyber Insights magazine as well. So we're developing a lot of content pieces around this and lots of things I'm seeing here. So your covid point, I think one of the most interesting things there is around literacy. For example, you remember when we went back to 18 months ago? We're having daily briefings, whether that's from from UK Parliament or the U. S. Equivalent. And different phrases were coming into everyday language driven by the curve or driven by the data. And they're coming into everyday life and people family kitchen table. It was something that hasn't been spoken about before, but suddenly it was driving everyday decision making and what you could and couldn't do. And that's raised awareness. And I think it helped people to ask better questions and to challenge things that they're seeing. And where has that data come from? How has it been presented to have seen that there? I think similarly, where we're having that same understanding and raise of questioning around what we're hearing around cyber as well. You're looking at where that source has come from, and how can we look at that in a different way? So again, I think it's raising that awareness, which is really, really crucial, >>the >>other thing as well around cyber security in particular. And again, I don't think this is talked about as much. When we talk about aspects around inclusion, we talk about diversity equity. Um, I'll see inclusion. I talk about belonging a lot as well. I think there's other aspects around sustainability that Inter relate as well, because when we find, for example, communities that are not included, they tend to be more adversely affected by, for example, climate factors as well. There's an interrelation. They're equally We find that people that haven't got, for example, the same level of cybersecurity protection are also in that same. There's an interrelation across all those elements were not talking about that either. So that's the other thing. I want to kind of bring attention to their again. They aren't separate conversations is a huge crossover between these different conversations and actions that we can do to make a difference. So there's some positive aspects about things that have happened over the last period of time and also some challenges that if we're aware of them, we can work together again, that collaboration piece to be able to overcome them. You know, I've got I've got a book coming out, all for charity called Tech for Good and one of my kind of tag lines. There is around contagion of positive change. Again, let's reframe the language around what's been happening. And let's kind of put that together is something that's far more positive. >>Language is super important, great >>content here. So >>thanks so much for coming. I really appreciate all the great insight and taking the time out of your busy day to to join us here in the Cube. Women in tech Global Event. Thank you so much. >>My absolute pleasure. Thank you. Thank you all for watching. >>Okay. The cubes presentation of women in text. Global event Celebrating International Women's Day. I'm John for a host of the Cube. Thanks for watching

>> From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. (intense music) >> Hi, everybody, this is Dave Vellante in theCUBE, and as you know, I've been doing a CEO series, and welcome to the isolation economy. We're here at theCUBE's remote studio, and really pleased to have Charlie Giancarlo, who is the CEO of PureStorage. Charlie, I wish we were face-to-face at Pure Accelerate, but this'll have to do. Thanks for coming on. >> You know, Dave, it's always fun to be face-to-face with you. At Pure Accelerate when we do it in person is great fun, but we do what we have to do, and actually, this has been a great event for us, so appreciate you coming on air with me. >> Yeah, and we're going to chat about that, but I want to start off with this meme that's been going around the internet. I was going to use the wrecking ball. I don't know if you've seen that. It's got the people, the executives in the office building saying, "Eh, digital transformation; "not in my lifetime," complacency, and then this big wrecking ball, the COVID-19. You've probably seen it, but as you can see here, somebody created a survey, Who's leading the digital transformation at your company? The CEO, the CTO, or of course circled is COVID-19, and so we've seen that, right? You had no choice but to be a digital company. >> Well, there's that, and there's also the fact that the CEOs who've been wanting to push a digital transformation against a team that wants to stick with the status quo, it gives the CEO now, and even within our own company in Pure, to drive towards that digital transformation when people didn't really take up the mantle. So no, it's a great opportunity for digital transformation, and of course, the companies that have been doing it all along have been getting ahead during this crisis, and the ones that haven't are having some real trouble. And you and I have had some really interesting conversations. Again, that's, I think, the thing I miss most, not only having you in theCUBE, but the side conversations at the cocktail parties, et cetera. And we've talked about IP, and China, and the history of the US, and all kinds of interesting things there, but one of the things I want to put forth, and I know you guys, Kix especially, has done a lot of work on Tech For Good, but the narrative pre-COVID, PC I guess we'd call it, was really a lot of vitriol toward big tech especially, but you know what? That tech lash... Without tech, where would we be right now? >> Well, just think about it, right? Where would we be without videoconferencing, without the internet, right? We'd be sheltered in place with literally nothing to do, and all business would stop, and of course many businesses that require in-person have, but thank God you can still get goods at your home. You can still get food, you can still get all these things that today is enabled by technology. We've seen this ourselves, in terms of having to make emergency shipments during our first quarter to critical infrastructure to keep things going. It's been quite a quarter. I was saying to my team recently that we had just gotten everyone together in February for our sales kickoff for the year, and it felt like a full year since I had seen them all. >> Well, I had interviewed, I think, is it Mike Fitzgerald, your head of supply chain. >> Yes. >> In March, and he was saying, "No. "We have no disruptions. "We're delivering for clients," and we certainly saw that in your results in the quarter. >> Yeah, no, we're very fortunate, but we had been planning for doing our normal business continuity disaster planning, and actually, once we saw COVID in Asia in January we started exercising all those muscles, including pre-shipping product around to depos around the world in case transportation got clogged, which it in fact did. So we were well-prepared, but we're also, I think, very fortunate in terms of the fact that we had a very distributed supply chain. >> Yeah, I mean you guys obviously did a good job. You saw in Dell's earnings they held pretty firm. HPE, on the other hand, really saw some disruption, so congratulations to you and the team on that. So as we think about exiting this isolation economy, we've done work that shows about 44% of CIOs see a U-shaped recovery, but it's very fragmented. It varies by industry. It varies by how digital the organizations are. Are they able to provide physical distancing? How essential are these organizations? And so I'm sure you're seeing that in your customer base as well. How are you thinking about exiting this isolation economy? >> Well, I've certainly resisted trying to predict a U- or a V-shape, because I think there are many more unknowns than there are knowns, and in particular, we don't know if there's a second wave. If there is a second wave, is it going to be more or less lethal than the first wave? And as you know, maybe some of your audience knows, I contracted COVID in March. So I've done a lot of reading on not just COVID, but also on the Spanish flu of 1918-1919. It's going to take a while before this settles down, and we don't know what it's going to look like the rest of the year or next year. So a lot of the recovery is going to depend on that. What we can do, however, is make sure that we're prepared to work from home, work in the office, that we make sure that our team out in the field is well-placed to be able to support our customers in the environment, and the way that we're incenting our overall team now has less to do with the macro than it does with our specific segment, and what I mean by that is we're incenting our team to continue to build market share, and to continue to outperform our competition as we go forward, and also on our customer satisfaction figure, which you know is our Net Promoter Score, which is the highest in the industry. So that's how we're incenting our team. >> Yeah, and we're going to talk about that, and by the way, yes, I did know, and it's great to see you healthy, and I'd be remiss if I didn't also express my condolences, Matt, the loss of Matt Danziger, your head of IR, terrible tragedy. Of course Matt had some roots in Boston, went to school in Maine. >> Yeah. >> Loved Cape Cod, and so really sad loss, I'm sure, for all of the Puritans. >> It's affected us all very personally, because Matt was just an incredible team member, a great friend, and so young and vital. When someone that young dies for almost unexplainable reasons. It turned out to be a congenital heart condition that nobody knew about, but it just breaks... It just breaks everyone's heart, so thank you for your condolences. I appreciate it. >> You're welcome. Okay, so let's get into the earnings a little bit. I want to just pull up one of the charts that shows roughly, I have approximately Q1 because some companies like NetApp, Dell, HPE, are sort of staggered, but the latest results you saw IBM growing at 19%. Now we know that was mainframe-driven in a very easy compare. Pure plus 12, and then everybody else in the negative. Dell, minus five, so actually doing pretty well relative to NetApp and HPE, who, as I said, had some challenges with deliveries. But let's talk about your quarter. You continue to be the one sort of shining star in the storage business. Let's get into it. What are your big takeaways that you want us to know about? >> Well, of course I'd rather see everybody in the black, right, everybody in the positive, but we continue to take market share and continue to grow 20 to 30% faster than the rest of the industry combined, and it's quarter after quarter. It's not just a peak in one quarter and then behind in another quarter. Every quarter we're ahead of the rest of the industry, and I think the reasoning is really quite straightforward. We're the one company that invests in storage as if it's high technology. You do hear quite often, and even among some customers, that storage is commoditized, and all of our competitors invest in it, or don't invest in it, as if it's a commoditized market. Our view is quite straightforward. The science and the engineering of computing and data centers continues to evolve, continues to advance, has to advance if we continue down this path of becoming more of a digital economy. As we all know, processors advance in speed and capability. Networking advances in terms of speed and capability. Well, data storage is a third of data center spend, and if it doesn't continue to advance at the same pace or faster than everything else, it becomes a major bottleneck. We've been the innovator. If you look at a number of different studies, year after year, now over six or seven years, we are the leader in innovation in the data storage market, and we're being rewarded for that by penetrating more and more of the customer base. >> All right, let's talk about that. And you mentioned in your keynote at Accelerate that you guys spend more on R&D as a percentage of revenue than anybody, and so I want to throw out some stats. I'm sorry, folks, I don't have a slide on this. HPE spends about 1.8 billion a year on R&D, about 6% of revenues. IBM, I've reported on IBM and how it's spending the last 10 years, spent a huge amount on dividends and stock buybacks, and they spent six billion perpetually on R&D, which is now 8% of revenue. Dell at five billion. Of course Dell used to spend well under a billion before the EMC acquisition. That's about 6% of revenue. And NetApp, 800 million, much higher. They're a pure play, about 13%. Pure spends 430 million last year on R&D, which is over 30% of revenue on R&D, to your point. >> Yeah, yeah, well, as I said, we treat it like it's high technology, which it is, right? If you're not spending at an appropriate level you're going to fall behind, and so we continue to advance. I will say that you mentioned big numbers by the other players, but I was part of a big organization as well with a huge R&D budget, but what matters is what percent of the revenue of a specific area are you spending, right? You mentioned Dell and VMware. A very large fraction of their spend is on VMware. Great product and great company, but very little is being spent in the area of storage. >> Well, and the same thing's true for IBM, and I've made this point. In fact, I made this point about Snowflake last week in my breaking analysis. How is Snowflake able to compete with all these big whales? And the same thing for you guys. Every dime you spend on R&D goes to making your storage products better for your customers. Your go-to-market, same thing. Your partner ecosystem, same thing, and so you're the much more focused play. >> Right, well I think it boils down to one very simple thing, right? Most of our competitors are, you might call them one-stop shops, so the shopping mall of IT gear, right? The Best Buy, if you will, of information technology. We're really the sole best of breed player in data storage, right, and if you're a company that wants two vendors, you might choose one that's a one-stop shop. If you have the one-stop shop, the next one you want is a best of breed player, right? And we fill that role for our customers. >> Look it, this business is a technology business, and technology and innovation is driven by research and development, period, the end. But I want to ask you, so the storage business generally, look, you're kind of the one-eyed man in the land of the blind here. I mean the storage business has been somewhat on the back burner. In part it's your fault because you put so much flash into the data center, gave so much headroom that organizations didn't have to buy spindles anymore to get to performance, the cloud has also been a factor. But look, last decade was a better decade for storage than the previous decade when you look at the exits that you guys had and escape velocity, Nutanix, if you can kind of put them in there, too. Much larger than say the Compellents or 3PARs. They didn't make it to a billion. So my question is storage businesses, is it going to come back as a growth business? Like you said, you wish everybody were in the black here. >> Right, well a lot of what's being measured, of course, is enterprise on-prem storage, right? If we add on-prem and cloud, it actually continues to be a big growth business, because data is not shrinking. In fact, data is still growing faster than the price reduction of the media underneath, right, so it's still growing. And as you know, more recently we've introduced what we call Pure as-a-Service and Cloud Block Store. So now we have our same software, which we call Purity, that runs on our on-prem arrays, also running on AWS, and currently in beta on Azure. So from our point of view this is a... First of all, it's a big market, about $30 to $40 billion total. If you add in cloud, it's another $10 to $15 billion, which is a new opportunity for us. Last year we were about 1.65 billion. We're still less than, as you know, less than 10% of the overall market. So the opportunity for us to grow is just tremendous out there, and whether or not total storage grows, for us it's less important right now than the market share that we pick up. >> Right, okay, so I want to stay on that for a minute and talk about... I love talking about the competition. So what I'm showing here with this kind of wheel slide is data from our data partner ETR, and they go out every quarter. They have a very simple methodology. It's like Net Promoter Score, and it's very consistent. They say relative to last year, are you adopting the platform, that's the lime green, and so this is Pure's data. Are you increasing spend by 6% or more? That's the 32%, the forest green. Is spending going to be flat? Is it going to decrease by more than 6%? That's the 9%. And then are you replacing the platform, 2%. Now this was taken at the height of the US lockdown. This last survey. >> Wow. >> So you can see the vast majority of customers are either keeping spending the same, or they're spending more. >> Yeah. >> So that's very, very strong. And I want to just bring up another data point, which is we like to plot that Net Score here on the vertical axis, and then what we call market share. It's not like IDC market share, but it's pervasiveness in the survey. And you can see here, to your point, Pure is really the only, and I've cited the other vendors on the right hand, that box there, you're the only company in the green with a 40% Net Score, and you can see everybody else is well below the line in the red, but to your point, you got a long way to go in terms of gaining market share. >> Exactly, right, and the reason... I think the reason why you're seeing that is really our fundamental and basic value is that our product and our company is easy to do business with and easy to operate, and it's such a pleasure to use versus the competition that customers really appreciate the product and the company. We do have a Net Promoter Score of over 80, which I think you'd be hard-pressed to find another company in any industry with Net Promoter Scores that high. >> Yeah, so I want to stay on the R&D thing for a minute, because you guys bet the company from day one on simplicity, and that's really where you put a lot of effort. So the cloud is vital here, and I want to get your perspective on it. You mentioned your Cloud Block Store, which I like that, it's native to AWS. I think you're adding other platforms. I think you're adding Azure as well, and I'm sure you'll do Google. >> Azure, Azure's in beta, yes. >> Yeah, Google's just a matter of time. Alibaba, you'll get them all, but the key here is that you're taking advantage of the native services, and let's take AWS as an example. You're using EC2, and high priority instances of EC2, as an example, to essentially improve block storage on Amazon. Amazon loves it because it sells Compute. Maybe the storage guys in Amazon don't love it so much, but it's all about the customer, and so the native cloud services are critical. I'm sure you're going to do the same thing for Azure and other clouds, and that takes a lot of investment, but I heard George Kurian today addressing some analysts, talking about they're the only company doing kind of that cloud native approach. Where are you placing your bets? How much of it is cloud versus kind of on-prem, if you will? >> Yeah, well... So first of all, an increasing fraction is cloud, as you might imagine, right? We started off with a few dozen developers, and now we're at many more than that. Of course the majority of our revenue still comes from on-prem, but the value is the following in our case, which is that we literally have the same software operating, from a customer and from a application standpoint. It is the same software operating on-prem as in the cloud, which means that the customer doesn't have to refactor their application to move it into the cloud, and we're the one vendor that's focused on block. What NetApp is doing is great, but it's a file-based system. It's really designed for smaller workloads and low performance workloads. Our system's designed for high performance enterprise workloads, Tier 1 workloads in the cloud. To say that they're both cloud sort of washes over the fact that they're almost going after two completely separate markets. >> Well, I think it's interesting that you're both really emphasizing cloud native, which I think is very important. I think that some of the others have some catching up to do in that regard, and again, that takes a big investment in not just wrapping your stack, and shoving it in the cloud, and hosting it in the cloud. You're actually taking advantage of the local services. >> Well, I mean one thing I'll mention was Amazon gave us an award, which they give to very few vendors. It's called the Well-Architected AWS Award, because we've designed it not to operate, let's say, in a virtualized environment on AWS. We really make use of the native AWS EC2 services. It is designed like a web service on EC2. >> And the reason why this is so important is just, again, to share with our audience is because when you start talking about multi-cloud and hybrid cloud, you want the same exact experience on-prem as you do in the cloud, whether it's hybrid or across clouds, and the key is if you're using cloud native services, you have the most efficient, the highest performance, lowest latency, and lowest cost solution. That is going to be... That's going to be a determinate of the winner. >> Yes, I believe so. Customers don't want to be doing... Be working with software that is going to change, fundamentally change and cause them to have to refactor their applications. If it's not designed natively to the cloud, then when Amazon upgrades it may cause a real problem with the software or with the environment, and so customers don't want that. They want to know they're cloud native. >> Well, your task over the next 10 years is something. Look it, it's very challenging to grow a company the size of Pure, period, but let's face it, you guys caught EMC off-guard. You were driving a truck through the Symmetrics base and the VNX base. Not that that was easy. (chuckling) And they certainly didn't make it easy for ya. But now we've got this sort of next chapter, and I want to talk a little bit about this. You guys call it the Modern Data Experience. You laid it out last Accelerate, kind of your vision. You talked about it more at this year's Accelerate. I wonder if you could tell us the key takeaways from your conference this year. >> Right, the key takeaway... So let me talk about both. I'll start with Modern Data Experience and then key takeaways from this Accelerate. So Modern Data Experience, for those that are not yet familiar with it, is the idea that an on-prem experience would look very similar, if not identical, to a cloud experience. That is to say that applications and orchestrators just use APIs to be able to call upon and have delivered the storage environment that they want to see instantaneously over a high speed network. The amazing thing about storage, even today, is that it's highly mechanical, it's highly hardware-oriented to where if you have a new application and you want storage, you actually have to buy an array and connect it. It's physical. Where we want to be is just like in the cloud. If you have a new application and you want storage or you want data services, you just write a few APIs in your application and it's delivered immediately and automatically, and that's what we're delivering on-prem with the Modern Data Experience. What we're also doing, though, is extending that to the cloud, and with Cloud Block Store as part of this, with that set of interfaces and management system exactly the same as on-prem, you now have that cloud experience across all the clouds without having to refactor applications in one or the other. So that's our Modern Data Experience. That's the vision that drives us. We've delivered more and more against it starting at the last Accelerate, but even more now. Part of this is being able to deliver storage that is flexible and able to be delivered by API. On this Accelerate we delivered our Purity 6.0 for Flash Array, which adds not only greater resiliency characteristics, but now file for the first time in a Flash Array environment, and so now the same Flash Array can deliver both file and block. Which is a unified experience, but all delivered by API and simple to operate. We've also delivered, more recently, Flash Array 3.0... I'm sorry, Purity 3.0 on FlashBlade that delivers the ability for FlashBlade now to have very high resiliency characteristics, and to be able to even better deliver the ability to restore applications when there's been a failure of their data systems very, very rapidly, something that we call Rapid Restore. So these are huge benefits. And the last one I'll mention, Pure as-a-Service allows a customer today to be able to contract for storage as a service on-prem and in the cloud with one unified subscription. So they only pay for what they use. They only pay for what they use when they use it, and they only pay for it, regardless of where it's used, on-prem or in the cloud, and it's a true subscription model. It's owned and operated by Pure, but the customer gets the benefit of only paying for what they use, regardless of where they use it. >> Awesome, thanks for that run through. And a couple other notes that I had, I mean you obviously talked about the support for the work from home and remote capabilities. Automation came up a lot. >> Yep. >> You and I, I said, we have these great conversations, and one of the ones I would have with you if we were having a drink somewhere would be if you look at productivity stats in US and Europe, they're declining-- >> Yes. >> Pretty dramatically. And if you think about the grand challenges we have, the global challenges, whether it's pandemics, or healthcare, or feeding people, et cetera, we're not going to be able to meet those challenges without automation. I mean people, for years, have been afraid of automation. "Oh, we're going to lose jobs." We don't have enough people to solve all these problems, and so I think that's behind us, right-- >> Yeah, I agree. >> The fear of automation. So that came up. Yeah, go ahead, please. >> I once met with Alan Greenspan. You may remember him. >> Of course. >> This is after he was the chairman, and he said, "Look, I've studied the economies now "for the last 100 years, "and the fact of the matter is "that wealth follows productivity." The more productive you are as a society, that means the greater the wealth that exists for every individual, right? The standard of living follows productivity, and without productivity there's no wealth creation for society. So to your point, yeah, if we don't become more productive, more efficient, people don't live better, right? >> Yeah, I knew you'd have some good thoughts on that, and of course, speaking of Greenspan, we're seeing a little bit of rational exuberance maybe in the market. (chuckling) Pretty amazing. But you also talked about containers, and persisting containers, and Kubernetes, the importance of Kubernetes. That seems to be a big trend that you guys are hopping on as well. >> You bet. It is the wave of the future. Now, like all waves of the future, it's going to take time. Containers work entirely differently from VMs and from machines in terms of how they utilize resources inside a data center environment, and they are extraordinarily dynamic. They require the ability to build up, tear down connections to storage, and create storage, and spin it down at very, very rapid rates, and again, it's all API-driven. It's all responsive, not to human operators, but it's got to be responsive to the application itself and to the orchestration environment. And again, I'll go back to what we talked about with our Modern Data Experience. It's exactly the kind of experience that our customers want to be able to be that responsive to this new environment. >> My last question is from John Furrier. He asked me, "Hey, Charlie knows a lot about networking." We were talking about multi-cloud. Obviously cross-cloud networks are going to become increasingly important. People are trying to get rid of their MPLS networks, really moving to an SD-WAN environment. Your thoughts on the evolution of networking over the next decade. >> Well, I'll tell you. I'm a big believer that even SD-WANs, over time, are going to become obsolete. Another way to phrase it is the new private network is the internet. I mean look at it now. What does SD-WAN mean when nobody's in the local office, right? No one's in the remote office; they're all at home. And so now we need to think about the fact... Sometimes it's called Zero Trust. I don't like that term. Nobody wants to talk about zero anything. What it really is about is that there is no internal network anymore. The fact of the matter is even for... Let's say I'm inside my own company's network. Well, do they trust my machine? Maybe not. They may trust me but not my machine, and so what we need to have is going to a cloud model where all communication to all servers goes through a giant, call it a firewall or a proxy service, where everything is cleaned before it's delivered. People, individuals only get, and applications, only get access to the applications that they're authorized to use, not to a network, because once they're in the network they can get anywhere. So they should only get access to the applications they're able to use. So my personal opinion is the internet is the future private network, and that requires a very different methodology for authentication for security and so forth, and if we think that we protect ourselves now by firewalls, we have to rethink that. >> Great perspectives. And by the way, you're seeing more than glimpses of that. You look at Zscaler's results recently, and that's kind of the security cloud, and I'm glad you mentioned that you don't like that sort of Zero Trust. You guys, even today, talked about near zero RPO. That's an honest statement-- >> Right. >> Because there's no such thing as zero RPO. (chuckling) >> Right, yeah. >> Charlie, great to have you on. Thanks so much for coming back in theCUBE. Great to see you again. >> Dave, always a pleasure. Thank you so much, and hopefully next time in person. >> I hope so. All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (smooth music)

(upbeat music) >> Announcer: Live from San Diego, California, it's theCUBE, covering KubeCon and CloudNativeCon. Brought to you by Red Hat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Welcome back, this is theCUBE's coverage of KubeCon, CloudNativeCon 2019. And a special segment, we're actually going to doing our 2020 predictions. I am Stu Miniman, joining me, my two co-hosts of the week. To my left is Justin Warren, who I believe's been to, you went to the first one? >> I've been to all four, yeah. >> All four of the North America shows. >> Yep. >> I personally have been now to three of the North American, as well as one in the Barcelona. And we have a first time KubeConner, but long time host of theCUBE and things, John Troyer to my right. Gentlemen, thanks so much for joining us. So first thing, the rapid fire. 12,000 in attendance. Last year 8,000, the year before 4,000. So, my math says that it will be 16,000 when we come next year to beautiful November in Boston, Massachusetts, which I can drive to. We've had snow in Austin, rain in San Diego. So, I'm predicting 60 to 70 degree weather in Boston, 'cause that never happens in Boston. Number of attendees next year, Justin? >> Well, it was doubling and now they have dropped it to 50%, so I reckon another 50%, I'll reckon 18 to 20,000. >> Stu: Oh, John? >> Yeah, I'll go higher. That many plus one. >> Okay, I feel like we'll do, I bet $1, $1. But, okay-- >> We have not hit peak Kubernetes yet. >> No. >> We definitely have not hit peak Kubernetes. One of the things, I keep looking for the theme of the show, and one of the things, we've been talking in some of the segments, is there needs to be simplification. When we talk about where we're at with cloud adoption, when we talk about some of these environments, there is a broad ecosystem. So, there needs to be some winnowing down of the technologies. We've seen some areas where things like MicroK8s and K3s to be able to be able to put Kubernetes at the edge. It's not that, that will replace Kubernetes, but things need to get simpler in some environments. Justin, I'll throw it to you first. Is simplification the theme of the show, is there something else that's grabbing you? >> The theme for me is that the money has arrived. We saw a little bit of that last year but this year it is definitely just the number of sponsors that we have here, the number of startups that we have here, the ecosystem, the number of parties, the VCs are here. This feels like a lot of other technology shows that we've been to before in their hay day. We are right here in the hay day of Kubernetes. So, I can see it getting bigger. Will there be consolidation? Yes, I think there will. But I think that this is going to broaden out further first. I don't think that we're quite at the point where things need to start collapsing in. I think we're still going to be exploring all the different options that we have. I think the theme is simplification, yes, I agree. But it's now going to be people trying to solve that problem by creating these higher-level services, managed-Kubernetes offerings. A lot of the different component projects that are there, we're going to see a lot of options where they try to manage that for you and make it easier to consume. But there will be several different attempts at that and not all of them are going to survive. >> Yeah, I'll go with you. Simplification's going to be an issue. Has to happen, we saw a lot of different stacks here at the show, if you go out on the show floor. A lot of people are trying to give you a generic platform. A general-purpose platform, maybe it has its own opinionated view of networking, or storage, or management, or security. But at the end of the day we need things on top of the platform. So, I'm hoping next year we see more things on top of the platform, more applications. We saw some big data applications this year. But people are still building engines and I want them to build cars, because not everybody can build the engine. >> Justin: Yes! >> Well, and actually, Justin, a question for you is when we talk about Kubernetes, there's so many people I interview here and they're like, "Well, no, "we know how to build it better than others "and when you want to go across all environments "we should do it." Is that, are we still going to see that for awhile? Or, can we all hold hands, and talk about open source and be able to just manage across all of these environments? >> Well, one of the key founding principles of Kubernetes is that you can operate it the same everywhere. If it's certified Kubernetes, it should function the same, no matter who's build of it it is. So, that just provides us a common platform that we then build on top of. So, I think the main differentiation's going to be on things like the tooling and the services that allow you to operate that base layer of Kubernetes. But that base layer of Kubernetes is about interesting as Ethernet. It's extremely pluggable and it's just ubiquitous, but no one really cares which brand of Ethernet you happen to be giving me. I care about all the stuff that I run on it. And that's what I think that we're going to see a lot more, I'm with you, John. We're going to see a lot more of those services. I'm seeing a bunch of startups at this show that are starting on that journey, they're providing a lot of things like database services, very highly-tuned monitoring and measurement telemetry systems. There's a big push to make sure that there is a certain amount of interoperability between these different services. Things like having open telemetry be the standard for sending telemetry information around. Because everyone knows that if we all build to Ethernet we're all going to have a much better time of it, than if we all start trying to come up with our own version of it and call it Banyan VINES, and FidoNet, and God knows what. >> Okay, I'm glad you brought up the example of Ethernet. First of all, I have no problem watching a 45-minute discussion of what 400 Gig's going to look like, and the challenge and the opportunities. And if you are talking Ethernet in someone's data center, for the most part they're going to run that on a single vendor because while there is interoperability, it's not until I go to the Internet, because layer two, I want to keep it single vendor, when I go layer three I want to do that. Is that, maybe it's not the best analogy but Kubernetes-- >> No, I think that's reasonable. And if you're trying to operate something across different environments then it's much easier if the two environments can talk to each other. Simple example that people tend to forget about is M&A. If one company goes and buys another one and I run Banyan VINES and you run, I don't know, FinLand or something, then we can't talk to each other, and integrating those two companies becomes impossible. But at least if we both have, you might have Juniper, I might have Cicso, those two network sets can still talk to each other. You might be running, I don't know ,Mesosphere, and someone else might be running Mirantis or Rantia, and that's their system for operating Kubernetes. Turns out, actually if you can operate it much the same, one of you can decide, you know what, we're going to operate everything with Rantia, 'cause we think that that's going to be the best thing for the holistic company. You may keep them separate. As long as you get the same outcome then it doesn't really matter. >> Yeah, that's why I think we aren't yet at peak Kubernetes. Those Kubernetes skills that are in high demand from a job market that people are being upskilled on, they're actually still going to be useful. Now, these stacks that these opinions that people are doing. I mean, they want us to talk about people over projects, right? That's a great philosophy, this is a very friendly community, it's very open source. But, cynically, I think, and sometimes people swap your company T-shirt for your project T-shirt that your company is the one that's behind. And that's kind of a, that's a little bit of a bait and switch. Yes, it's an open source stack. Yes, all the major vendors have open source, 100% open source stacks around Kubernetes. But they're all with different projects and they all pick their own projects. So, I think that is yet to be resolved. >> Well, it's interesting 'cause the thing that I heard is it used to be open source was something that people contribute to it. Now, the majority of people that contribute to open source do it as part of their job. So, there is some of that. Yes, I'm paid by company X, but my job is to participate in the community. There is a large company that got bought by $34 billion. They have a lot of contributors out there. Their job is open source, they are on those projects, they might switch from one project to another. We had Kelsey Hightower on today, he's like, "Hey, right, "but we need to think of people above project. "It's okay for them to move from one to the other "between projects or between companies." But, right, it is very much often companies that are behind the scenes and pushing people and dollars into these projects. One thing I like about the CNCF here is we do have, there's 129 end-user companies participating here, so we've reached a certain maturity level that they are driving it, not just companies driving it for the dollars. So, I guess the thing I want to ask though is, there's so many companies here, we started off the conversation this week, John, talking about Docker. And the cautionary tale of how many companies, when I asked, "What is your business model, what do you do?" Is, I created some cool new project. What does that mean? You look at the business model. You live right with Silicon Valley there. What are you seeing as you look forward? What do you expecting to see consistently? >> Oh sure, I mean, half the logos will be gone but they'll be swapped out for other logos, so that's all fine, right? If you have a point solution, as I was kind of pointing out, things are kind of stackifying. So, things need to consolidate from a buyer's perspective. A lot of the sessions here were about custom projects that people did, either in-house or for a customer. So, I think that's okay, that's the natural, it's the natural Cambrian explosion and then die off. >> Yep, creative destruction. (John laughing) That's the general point of how we do things. There's a lot of things that are basically a feature and you can't really build a company behind a feature. They're hoping that they will find some sort of pathway to money, we've seen some big acquisitions where they didn't really find a good route to money. That's fine, people will figure that out. And how you fund this development, Stu, I mean that's the perennial problem. At the moment it's possibly not the perfect solution but it's a pretty good one, in that we have developers are employed by a company that pays them to develop open source software. So, anyone can go and grab that software and then use it. So, we don't actually really depend on that company sticking around. >> And enterprise sales, it's still very expensive to have even a small booth here, and three or four people and nice T-shirts, and all of your swag, and you flew them here. And fly them all around the country to company after company, conference room after conference room. That is an expensive model to sell things. I mean, you need to have a fair amount of revenue. >> All right, so, Justin, a lot of progress, a lot of projects. >> Yeah. >> What's missing? Look out for 2020, is there an area or a space that needs to mature or needs work? What's your advice for this ecosystem? >> Well, for me it's all about the data. So, we've seen a lot of evolution in stateful sets and being able to manage state-based data within the Kubernetes ecosystem, a lot of progress on that, but there's still a long, long, long way to go. Also, just on the general operational tooling. So, the things that we are used to and have taken for granted in other traditional, like vSphere, or we've come from the VMware ecosystem. Simple things like higher availability. So, I need my data to always be available and I need to be able to have this managed. There's a lot of stuff in there but there's still a lot more stuff that needs to happen. Service mesh and that service discovery and making that easy enough for normal mortal humans to deal with, that still really isn't there. You kind of have to be a bit of a super genius to configure that and get it working and operating. So, there's still a lot of very hard work on these quite hard problems, to then make it look simple. >> Yeah, so, John, the one I want to throw to you is Dan Kohn came out on the keynote stage yesterday and he said, "Kubernetes has crossed the chasm, "yet most enterprises are still worried "about software failure." We know many people that are coming in new and shell-shocked when they come to look. What does the industry as a whole and this ecosystem, specifically, need to do to make sure that we don't come a year from now and say, "Wow, things slowed down "because we kind of couldn't get "the vast majority of people on board?" >> Well, I mean, we're going back to, I guess then the same thing, things have to be simpler. In times of uncertainty people either stop or they go to a trusted provider. There is, probably, although there's a high value on Kubernetes skills right now, that also means there's not enough folks. So, if you can't get the engineers. That was a problem in previous generations of some of these stacks, in that if you couldn't get enough engineers, or if the stack, if everybody had their own snowflake version of it and the skills were not transferable you could not move forward. So, I'm hoping we'll see more managed service providers. I'm hoping that we'll see more startups and services built on top of these existing infrastructures, I think we're seeing more of those. I see a lot of stuff in the operations space and kind of the SRE space, the incident management space. Kind of all the tooling you'll need to actually run these things in day two and beyond. And then, hopefully, the industry keeps pounding on digital transformation and process transformation. One project at a time, you start with one, you start small, you start tooling, you start tooling up, you get some small things under your belt and start to learn. But that's enterprise timeline. So, at a certain speed. >> All right, last thing, any aha moments, surprises, cool things as you've been going around the show? Justin? >> Oh, just walking into the show surprised me. Just how big it has gotten and how much energy there is here. It's amazing to me and I can just only see it getting bigger and, I hope, better. I am surprised by the reaction from people who haven't come into the Kubernetes ecosystem, I think. There's still a lot of people out there for whom this is a big surprise. That it's as big a show as this is, there are lots and lots of people out there who can't actually spell Kubernetes. So, there's a lot of work for us to go and do to figure out how we get those people to come into this ecosystem in a way that doesn't shock them and scare them away. >> Yeah, absolutely. Welcome to the party, those of you that had been joined. John? >> Hey, the thing that surprised me was this is both a multicloud show and a non-cloud show. This is the only show where people working in multiple public clouds can come together. So, that's one of the systemic forces causing it to grow. On the other hand, this is not a public cloud-only show. Over and over again, we talk to people here on theCUBE, I talk to people on the show floor, and most of their workloads, or many of their workloads, are on-premises, right? Kubernetes is fully functional and fully up to speed in private cloud, in people's data centers because it is useful. And they're starting to do that process tooling and process re-engineering, even on-site. And then they may be using a portfolio of different clouds. So, I think that was one of the surprising things to me is this was not 100% public cloud show. >> Yeah, and a little bit of caution I'll give there is we want to make sure we don't become complacent and say, oh, well, we could just kind of slide in what we were doing before and not make some change because the driver here, we've been talking about for decades now, was really kind of that application modernization. And Kubernetes and this whole, it is about cloud-native. It's not the Kubernetes, it's the cloud-native piece. >> You know what I didn't hear? I did not hear putting legacy apps on Kubernetes as much this year. Much quieter this year. >> So, and I'll just say, I'll highlight, we did an interview yesterday with the American Red Cross. Tech For Good, it's something that we've been highlighting, John, for especially helping lead the charge and make sure we highlight that. The Microsoft show, they very much talked about that this year. American Red Cross is saying, hey, we always want your dollars but we'd also love your skillset. So, if this community, and specifically Kubernetes, cloud-native ecosystem makes it easier. There's common tooling, something that I've been hearing a lot this year is when I go through that modernization I can hire the next-generation workforce. There's too many of those, oh, I'm doing it the old way. If I don't have somebody with 30 or 40 years experience in the industry, you won't understand our systems and we need that next generation of workforce to be able to get involved. So, love future jobs, Tech For Good, all good things. This community's always been strong on diversity and inclusion. And so, I guess final word I'll say, big shout-out to, of course, the CNCF, this event, they have a large menagerie that they need to take in here and manage, and they're doing a good job. There's always things to work on. They are listening and open. We have really appreciated the partnership. A huge shout-out, of course, to our sponsors that make it possible for us to do this. So, for Justin Warren, for John Troyer, I'm Stu Miniman, thanks so much. We definitely are excited for one more day. Tomorrow, as well as next year in 2020, Amsterdam and Boston. Please reach out always if you have any questions. And thank you so much for watching theCUBE. (upbeat music)

>> Live from Las Vegas, it's theCUBE covering Informatica World 2019 brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World. I am your host, Rebecca Knight, along with my co-host, John Furrier. We are joined by Amit Walia, President - Product and Marketing here at Informatica. Thank you for coming back on theCUBE. So we're here at Informatica World, there's a lot of buzz, a lot of energy, obviously CLAIRE is a big story, your company got great press yesterday from The Wall Street Journal teaming up with Google to tame the data. One of the themes we keep hearing is that data needs AI, but AI needs data. Elaborate on that a little bit. >> That's a great point, in fact I would extend that and say I believe, and I will talk about that today in the closing keynote, is the language that AI needs or speaks is data. Because to be honest, without data, there's no great AI. And I think something that we've known all this while, but now that AI is really becoming pervasive and has skill, you really, really need to give it relevant, good, contextual data for a Siri or a Cortana or Alexa to make some contextual decisions, right? And we see that happening a lot in the world of enterprise now. Finally enterprises are arriving at the point where they want to use AI for P-to-P use cases, not just consumer use cases that you and me are used to. And then, to your other question, AI is a part of everything that we do in data. Because, to be honest, it really helps improve productivity, automate mundane tasks. And I think we were talking before this, there is a massive skills gap. And I think you look around, the economy's kind of fully saturated with jobs, and there's still so much more work to be done with more data, different data, so AI's helping making some of those mundane activities become a lot more easier or autonomous, if I may. >> What's the use cases for CLAIRE in AI around as it grows? Because, you know, the data world, you guys have been doing it for 25 years at Informatica, private for 4 so, innovating on the products side, but it used to be, here's the data department, they handle it. The data warehousing in the fenced out area in the company, now it's strategically part of everything, right? So you guys have the MDM, you've got the Catalog, you've got all kinds of solutions. How is that role changing within your customer base? And what are some of those use cases? Because now they have to think end-to-end, you've got Cloud and On-premise, these are challenges and opportunities. But the role of data and the data teams is expanding rapidly. >> In a significant way. A significant way. I think I kind of was joking with our practitioners yesterday that they were all becoming, they were going from heroes to superheroes, if you are enjoying the Avengers movies, and that analogy. But genuinely, because if you think about it, right, I think what we are seeing in this world, we call it the data three data where the data is becoming a platform of a sort. It is getting decoupled from the data bases, from the applications, from the infrastructure, because to truly be able to leverage AI, and build applications on top, you cannot let it be siloed and be hostage to its individual infrastructure components. So we're seeing that fundamental change happening where data as a platform is coming along, and in that context the catalog becomes a very, very pivotal start, because you want to get a full view of everything. And look, you're not going to be able to move all your data in one place, it's impossible. But understanding that through metadata is where enterprises are going, and then from there, John, as Rebecca's talked about, you can have a customer experience journey with MDM. You can have a analytics journey in the Cloud with an AWS or (inaudible) or a JCP. Or you can have a complete governance and security and privacy journey understanding anomalous activity. >> So before I go any further I just want to ask you about this one point because you guys made a big bet with the Catalog >> Okay, and it's looking good. A lot of good bets. You know, AI, Catalog, Cloud, early on the Cloud, but one of the things I hear a lot is that data's at the blood stream, you want the blood flowing around the system, the body. People looking at data like an operating system kind of architecture where you got to have the data free flowing. So the Catalog seems to be a big bet there. How is that helping the AI peeps because if you can have the data flowing -- >> Yep. No I think -- >> You're going to have feeding the machine learning >> Absolutely. >> The machine learning feeds the application of AI, you got to have the data, the data's not flowing, you can't just inject it at certain times. >> The way we think about it is, you're exactly right. I would just, in fact it's so ah, interesting, the analogy I use is that data is everywhere. It's like the blood flowing through your body, right? You're not going to get all the data in one place to do any kind of analytics, right? You're going to let it be there. So we say metadata is the new OS. Bring the metadata, which is data about the data in one place. And from there let AI run on it. And what we think about AI is that, think about this. LinkedIn is a beautiful place where they leveraged the machine learning algorithm to create and social graph about you and me. So if I'm connected with John, I know now that I can be connected with you. The same thing can happen to the data layer. So when I'm doing analytics, and I'm basically searching for some report, I don't know, through that same machine learning algorithm at the catalog level, now we can tell you, you know what? This is another table. This is another report. This is another user. And so on. And we can give you back ratings within that environment for you to do what I call analytics on your fingertips at enterprise scale. So that's an extremely powerful use case of taking analytics which is the most commonly done activity in an enterprise and make it accurate at an enterprise scale. >> Well the LinkedIn example, you know, of course I have a different opinion on that. They're a siloed platform. They don't have any API's, it's only within LinkedIn. But it begs the question, since you're both that kind of consumer, look at a company like Slack, going public, very successful, their numbers are off the charts in terms of adoption, usage, a simple utility in IRC message chat room that has a great UI on it. But their success came when they integrated. >> Sure. >> Integration was a big part of their success. They wanted to have API's and let customers use the software, SAS software, with a lot of data. So they were really open. >> Yes. >> How were you guys from a business standpoint taking that concept of SAS openness connecting with other apps because I might have, bring my own app to the table as data, and integrate that piece into Informatica. How does that work? >> Very similarly. So the way we've done it is that our whole platform is fully API based. So we have opened up the API's, any application can hook on to that. So we believe that we are the Switzerland of data. So you may have any underlying infrastructure stack. On-prem, in the Cloud, multi-Cloud, whatever it is. Different applications, different Cloud applications, right? So our goal is that at the layer which is the metadata layer on which CLAIRE runs, we've opened up the API's, we've hooked to everything, and so we can consume the metadata, and there we truly provide a true data platform to our organization. So if you are running a Server Snap, a Salesforce.com, Adobe, Google, AWS, you can still bring all that stuff together and make contextual business decisions. >> One of the things you had talked about on the main stage is how the Millennials that you're hiring have higher expectations in their personal lives from the technology that they're using, and that's really pushing you to deliver different kinds of products and services that have the same level of innovation and high touch. Can you talk a little bit about that and how, and how this new generation of the workforce, and there's obviously Gen Y coming right behind it, is really pushing innovation in your company. >> Well you know, I have a fourteen-year-old, so I get a taste of that every day at home. (laughing) So you know, what they want to experience, so I, you know, I use this word, experiences are changing. And by the way they are pushing the boundary for us too. We grew up in the infrastructure software world which you know, twenty-five years ago was all, you can go down to the command line interface. Not any more. You really really have to make it simple. I think users today don't want to waste their time what I call doing mundane activities. They want to get to value fast. That's pushing the boundary for us. In fact that's where we're leveraging AI in our products to make sure we can remove the mundane clutter activities for them, for them to do value added activities. For example, I want to discover data to do some analysis. I don't want to go around discovering. Discover it for me. So that's where CLAIRE comes in and the catalog, right? Discover it for me. You know what? I don't want to figure out whether this data is accurate or not accurate. Tell me. So we are taking that philosophy, really really pushing the boundary for us, but in a good way. Because definitely those users want what I call very simplified and value added experiences. >> And that's really what SAS and consumer applications have shown us, and that's proven to be hard in the enterprise. So I got to ask you as you take this data concept to the infrastructure, a lot of enterprises are re-architecting, you hear words like multi-Cloud, hybrid Cloud, public Cloud, and you start to see a holistic new kind of persona, a Cloud architect. >> Yes. >> They're re-architecting their infrastructure to be SAS-like, to take advantage of data. >> Correct. >> That's kind of known out there, it's been reported on, we've been reporting on it. So the question is, that isn't alignment, that's not just the data people, it's data meets infrastructure. >> Absolutely. >> What's your advice to the companies out there that are doing this, because you guys have Cloud, Google, Amazon, Azure, Cloud, On-premise. You can work anywhere. What's you're advice? >> Yeah, no, I think it's a very good, it's a very topical question. Because I do think that the infra, the old days of separating different layers of the stack are are gone. Especially the old infrastructure all the way to platform as a server stack has to be very well though out together. To your point, customers running a hybrid multi-cloud world, right? So think about it, if you're in the world of improving customer experiences, I may have my marketing cloud running somewhere, I may have my sales cloud running somewhere, and a service cloud running somewhere. But to give a great experience I have to bring it all together. So you have to think about the infrastructure and the data together for enterprises to give a better experience to their customers. And I see innovative customers of companies truly think through that one and succeed. And the ones that are still lagging behind are still looking at that in silos. And then be able to have the data layer for hyper scale. Well these are all hyper scale platforms. You cannot run a little experiment over here. So we've invested in that whole concept of hyperscale, multi-cloud, hybrid cloud, and make sure it touches everything through API's. >> So we've been covering you guys for four years here at Informatica World. It's great to see the journey, nothing's really changed on the messaging and the strategy, you say you're going to do something and you keep doing it, and some little course corrections here, and acquisitions here and there to kind of accelerate it. But when we talk to your customers we hear a couple of different things. We hear platform, Informatica, when describing Informatica. You guys win the whole data thing, you're there, it's the business you're in. In the data business. But I'm hearing new words, platform. Scale. These are kind of new signals we're hearing from your customer base and some of the people here at the show. Talk about that impact, how you guys are investing in the platform, what it means for customers, and what does scale mean for your business and customers? >> No, we've heard that from our customers too. Customers said look, they all recognize that they have to invest in data as a platform. But you know, it's not like an original platform so they want it because we serve the broader state of management needs, so they want us to be like a platform. So we've invested that, couple of years ago we went completely ground-up, re-built everything, micro-services based. All API driven. Containerized. Modular. So the idea is that nobody is buying a monolithic platform. Nobody buying a platform, it just builds by itself. And they can compartmentize it, I want this now, I want that later, so like a Lego block it builds. And, you know what, through an API it also hooks into any of the existing infrastructure they have, or anything new that they want to bring in. So that really pushed the boundary for us. We invested in that. By the way, that platform today, in the Cloud, which you call IICS, runs eight trillion transactions a month. Eight trillion transactions a month. And by the way, last Informatica World, it was running two-and-a-half trillion transactions. So in one year it's gone from two-and-a-half to eight. So we are seeing that really hyper scale. >> And you, and I'm going to ask you if you believe, just, and you can answer yes or no or maybe, or answer on your own, do you believe that data is critical for SAS success? >> Oh absolutely. No doubt about it. I have not met a single customer who ever said anything different. In fact, the thing that I see is like, it's becoming more and more and more a sea-level conversation. That hey, what are we going to do with our data? How do we bring that data together to make decisions? How do we leverage AI and data together? It's truly in our sea-level discussion, whereas it was never a sea-level discussion years ago, it was more about what application am I going to use? What infrastructure am I going to use? Now they're all about, how do I manage this data? >> I wanted to talk about ethics (laughs) and this is, because recently had published a paper about Tech for Good, and it's about this idea of using AI and machine learning to help society achieve better outcomes, and then also to help us measure it's impact on our welfare beyond GDP. Because think about the value that technology brings to our lives. What's your take on this? I mean how much value do you think AI brings to the enterprise in terms of this Tech for Good idea? >> No, so, by the way one of Informatica's values is "Do good". And we are firm believers in that look, there is an economic value to everything in life. But then we all have something to give back to the society. There is something to create value out there which is outside the realm of just pure economics which is the point you were asking. And we are firm believers in that. I do think that by the way, there is a very high bar for all of us in the industry to make sure that not only, it's not just about ethics of AI also at the same time, because we cannot abuse the data. We're collecting a lot of information. You and me as consumers are giving a lot of information and I talked about that yesterday as well, that we believe that the ethics of AI are going to play a fundamental and differentiating role going forward. I think the Millennials we're talking about, they are very aware of that one. They are very purposeful. So they'll look back and say, who actually has a values system to take this technology innovation and do something better with it, not just creating money out of it. And I think I totally agree, and by the way in the very early stages, industry has to still learn that, and internalize that, then do something about it. >> Well Amit, yeah I think you're right on, early days, and I can give you an anecdotal example is that this year, University of California, Berkeley, graduated its first inaugural class of data science analytics. First! First ever class for them. They're a pioneer, they're usually having protests and doing things with revolutionary things. That shows it's so early. So the question I got to ask you is, you've got your fourteen-year-old, you know I have kids, we follow each other on Facebook. I'm always asked the question and I want to get this exposed. People are really discovering new ways to learn. Not just in school, you got YouTube videos, you've got CUBE videos, you got all kinds of great things out there. But really people are trying to figure out where to double down on, what dials to turn, what classes to take, what disciplines are going to help me. It used to be oh, go into computer science, you'll get a great job. And certainly that's still true. But there's now new opportunities for people, data's now grown from you know, programming deeply to ethics. And you don't need to have a CS degree to get in and be successful to fill the job openings or contribute to society. So what are those areas that you see that people who are watching might say hey you know what? I'm good at that, I'm good at art, I'm good at society or philosophy or I'm really good at math or, what skills do you, should people think about if they want to be successful in data? >> You know, I think it's a very foundational question. I think you're right, I think programming has become a lot easier. So I think if I'd stepped back to the days we graduated, right? It's become a lot easier so I don't think that necessarily learning programming is a differentiating, I do think that back where you were going, people who'd generally think about what to do with that. I think there is analytical skills that we all need, but I think the soft skills I believe in the society, we are kind of leaving behind, right? A little bit of the psychology of how users want to use something. Design thinking. By the way I still think that design thinking is not yet completely out there. Um, the ability to marry what I call the left brain to the right brain, I mean, I think that's key. And I do think that we cannot run away completely to the right brain, as much as I am an analytical person myself. I think marrying the left and the right, I do believe, like I, as I said I have a fourteen-year-old. My advice to all those who say, he wants to do Computer Science, is to take enough psychology or design classes to kind of have that balance. So my encouragement would be have the balance. We cannot all just be hyper-analytical. We have to kind of have the balance to see ... >> I think just be smart, balance, I mean again, I have not found one, well I guess the answers are stats and math, have the check, that's easy to say, but ... >> The emotional skills. But you need more of those, I think a little bit more of those left-brain skills also to complement them. >> Well and also for the experience, study art, music, what delights people. What inspires the passion? >> I agree with that. >> Yeah. Absolutely. Amit, always a pleasure to see you. Thank you so much. >> Thank you very much. Always a pleasure to be here. >> Great conversation. Good insight. >> I'm Rebecca Knight for John Furrier, stay tuned at theCUBE's live coverage at Informatica World. (Upbeat music)

>> Hey, welcome back everybody Jeff Frick here with theCUBE, we're downtown San Francisco, the Hotel Nikko, it's International Women's Day, March 8th, there's stuff going on all around the world, but we're excited to be here at the Accenture event, about 400 people, a lot of great panels, some familiar faces, some new faces, and one of those familiar faces joins us in the next segment. He's Marc Carrel, from Accenture, great to see you. >> Great to see you too. >> And a new face, Mary Hamilton, managing director also from Accenture Labs. Mary, great to see you. >> Great to see you too. >> So, first things, just kind of impressions of this event. I don't know if you did it last year, we weren't here, you know, there's a lot of energy, kind of, initial takeaways from some of the early panels. >> I mean, the energy is there, I mean, definitely last year we were here, I mean we do that every year for sure, and last year it was amazing as well, but I think this year is even bigger than we had last year. We have a kind of a hub and spokesmen of our organization where we have also our top leadership to go from different cities and then we celebrate all over the world. So this year the hub is here, and that's the reason why there's so much buzz and so much excitement. So that's pretty cool. >> Yeah, all of our leadership is here, and just phenomenal guests, um, from, yeah, we really aim for diversity, even not just gender diversity but diversity across all of our different panelists, you know, kind of thing they're thinking about, the way they're thinking about diversity, um, and you know, for me just some of those takeaways, you know, Vivian Ming, her point was when she showed up um, and, is there a difference between how men and women are treated? When she showed up as herself, as she is today, as a woman, she said she's never been asked a math question since. And that just blew me away that it's so black and white and they're really you know, from someone who's lived on both sides, there really is a difference. >> Right, right. So what are the topics? You guys are involved in Labs, is innovation, right? So there's digital transformation, yeah yeah yeah yeah yeah, but really innovation is kind of a more concrete thing that people are trying to achieve. And you guys are a big part of that at Labs, diversity is a big part of being more innovative. >> It's critical. >> So how do you guys see it in your customer base, and how do you see it within the work that you guys do within your own department at the Labs group? >> Well, I'll start, just, you know, you think about innovation that taps diversity is stronger innovation. Right? Our clients are delivering products and services to a diverse audience. And as we serve our clients and try to help them transform and be more digital, we have to reflect, the consumers or the buyers, for their products. And if we don't have that diversity, we're not going to deliver the right kinds of innovation. >> Right. >> I think Mary is absolutely right. And then what's very important to us is that we absolutely demonstrate that through numbers. So, you know, we have like seven labs, two of our leaders are women from those labs, we have five research domains, out of the five research domains, three out of the five are lead by women. >> Right. >> And I think that's pretty amazing. Now you see that from an organization's perspective. But I think if you look at who are the researchers, the most prolific that we have in the labs, from the few hundred people that we have, they're women. Hands down. And I'm going to give you some numbers which is again amazing, we are again publishing about 2,000 patents. I mean from the labs, since we exist. More than thirty eight percent have been driven by women. And then our most prolific labber is a woman. She has many of her, 124 applications and patents. How about that? I mean, she's amazing. >> Well drive is such an important piece, which is one of my favorite quotes. "In God we trust, but everybody else better bring data." Right? So if you don't apply data, if you don't measure the data, and you don't actually put in processes to specifically address the problem, it's just conversation, right? It's just interesting words. >> Absolutely, Jeff. And I think Mary will share with you, I mean also we're putting a process and an approach, a culture that is really changing the mind. >> Yeah. We focus on programs, not just at the junior level of recruiting, we do spend a lot of time and effort on getting out where women are, so we do things like Grace Hopper. We invest a lot to go to Grace Hopper and meet those technical women, we do things with women who code, with girls who code, what's the pipeline going to look like? But then once we have them in, how do we retain them? And so we've created a community and a network where we do a number of things. We mentor them, we create external networks, we create internal networks, we create kind of a social space, a safe social space, where you can bring up questions like "what should I wear to International Women's Day?", without having to feel awkward about asking those kind of things. We create a community that empowers and makes people feel comfortable. >> And do the clients get now that for whatever good, bad or otherwise they just need more good people. I mean we can't just not pull from the greatest population of good people that you can pull from. >> Absolutely, you're absolutely right. And I think another aspect from what I see what's happening in the lab, and I think Mary is a great example of that, we're looking at raw morals. Like, amazing woman like Mary, that is going to be driving, basically striving, and showing our people that you can really have a fantastic capacity as a technology person in the lab and in the Accenture organization overall. And that is very, very important for us. >> Yeah, and for me I'm not just a technologist but I'm also a mother of three small kids and I try to bring that to work, right? I try to show people, you know, I'm not just taking the hardcore path, I'm balancing a family I'm doing all these things that probably the rest of you are trying to do too and I let it show. Right? This is hard, how can I help you, here's what I'm going through, here are the challenges I'm facing, and try to bring others along too. >> So funny I did an interview years ago at an IBM event and there was a great women who was from an HR kind of consultative background, and she said, "You know, we spent all this time trying to find these great people, that have all these great attributes, and then we bring them in and then we just like give them the compliance manual, now you need to not be you, the mom, you've just got to be this little machine." And that's really not the way anymore, not at all. >> And credit to our leadership, to Marc, to Paul, Ellen, all the way up, right? There's true support for being truly human, bringing yourself to the workplace, and they do support it, they encourage it, right? And I think that that culturally seeps in to how we bring diversity to innovation too, right? It's bring your whole self to how you think about innovation. When we're hiring, I mean, I have a great example, I had a client come visit us, and he's been a strong supporter of us within his client space, and he came in and we were talking about you know, his work, and then I took him out to meet the team that was building the proof of concept for him, some tangential areas, and he met people from not just men and women, you know, diverse, but also different backgrounds, engineers, researchers, businessfolks, he met people from all kinds of backgrounds around the world. And he was able to have conversations about sports science, cricket, extended reality, and bring all those conversations back and at the end of his meeting he said "I was just floored at how many engaged conversations I was able to have with different people and the diversity of your workforce." And it's not just male female, right? You need that broad spectrum diversity to fuel innovation. >> Right. >> So -- >> Go ahead. >> Go ahead, Mark. Oh, I was just going to say, so, you know obviously it's a feel-good day today, it's feel-good place right here, but what are some of the significant, is it just execution or are there still some big hurdles that we have to overcome? Let's see, Mary, from your perspective. Marc's got it all figured out so we don't have to worry about him. >> Well, yeah, I mean there absolutely are, right? There is a pipeline problem, there is pipeline problem both from girls in STEM, coming up, right, what culturally we're telling girls and then there's a pipeline problem for, you know, we need to hire today. And I'm actually on the board of Women Who Code because I'm so passionate about their mission is, let's get women to understand that technology is approachable. That it is for all of us. >> Right. >> There's so many, the spectrum of what you can do with technology is so broad and so really if you think about it it's so appealing to so many women if you hit the right focus for them, then I think we can bring more women into tech even now, right? We don't have to wait for the pipe, we have to work on the pipeline, but we don't have to wait for it. We can start now. >> It's great, we do stuff with girls in tech and girls who code and obviously your Grace Hopper too. So you saw, just basing on her name, the gal that got the keynote, from uh, from the UK, who was basically, you know, at her last nickel with her kids, the poorest, homeless, and she learned how to code. And I dunno how old she was but she wasn't -- >> And we have so many stories of women who code. It turns their life around. And maybe the Tech For Good. >> Yeah, I think that's interesting, I mean also the nature of some of the projects we're doing also are driving women to be involved in this project. Do you know what is Tech For Good? I think I discussed that with you for some of these interviews. >> Yes. >> Where we're using technology and innovation to bring change to the world and the society and everything. We really believe, and we're not the only ones who believe that, you know, I mean, there are CEOs from other organizations that believe that, like, women are really on track today to build solutions or projects, with meaningful projects that really have purpose. That are meaningful to the society. And so Tech For Good, that we have launched, first of all got an incredible success, not only within the firm but outside of the firm, and the second thing is that it attracted tons of women talents. They love these kind of things. And then because they loved that, they want to stick with Accenture, and they, you couldn't describe it. >> Yeah, I mean, you get both sides of the coin. You're doing things that are empowering women in many cases, a lot of the projects we're doing. >> Right, right. And then that's also attracting women because we're excited about betterment of society and humanity and -- >> It's interesting, you know I got to give a lot of credit to kind of the younger generation coming up in terms of the prioritization of purpose within their hierarchy in deciding what to do, what companies to work for, how to spend their time, you know, it's very different than when we were, we didn't think about purpose, was trying to get a good job. Pay off the mortgage and then get a car. They don't want a car, they don't want a mortgage, they just want to do good. >> Absolutely, and I'll tell you something Jeff, I mean it's just like the Tech For Good I was just discussing with Mike Sutcliff before that, our chief officer of Accenture, and I was telling him that Tech For Good, the reason why we decided to do the Tech For Good and lab, talking to my leaders and everything is just like because my kids come to me and say "Hey Dad, you have the best job in the firm now, I mean, you need to do something with it." And so obviously we had to do some Tech For Good things. That's it. >> I love it. Alright, we're running out of time so I'll give you the last word, if when we come back a year from now, I'll probably see you in a month since I see you all the time. But a year from now at International Women's Day what are you working on, what are your priorities, how does this integrate into what you guys are doing at Labs, in your brand new space, by the way. >> Yeah, yeah. I mean part of the mission in that brand new space is to create these accidental collisions, right? >> Accidental collisions? >> Collaborative collisions I should say. (laughter) >> I was like, I love that term. >> No, we're not just colliding with each other. We're collaborating in these collisions. >> When atoms collide big things happen, right? >> Exactly. >> I'm sorry, knocked your train of thought. >> No, no, no, that's perfect. Um, and I think that whole mission is about how to create that diversity of thought. How do we bring people together that wouldn't have collaborated in the past? So my mission as we're moving into that new space, is to get my labbers, who are, you know, we're on our own little floor doing our own little thing, to expand our horizons, right? To think about diversity across the spectrum, how are we going to work with other groups, how are we going to bring different pieces to the innovation? So I hope we can reflect than even as we come back next year to this program. >> Great, alright. >> And my job is really to, I mean, as a, to pile on what Mary says, like, I'm going to continue stretching the limit of others' research. Because I think that there's nothing better than to do that hard research to solve that hard problem to elevate our people. And to be honest whether it's woman or man, they're all labbers, they're all part of our family, and there's no better, basically, reward for you to see these people, basically shining and explaining their passion to our clients, changes society and everything. That's what we got to do. >> Love the passion Marc, Mary, it's always great to catch up. >> It's great to see you. (soft music)