 From around the globe, it's theCUBE. Covering HPE Discover Virtual Experience. Brought to you by HPE. Hi everybody, you watching theCUBE and this is Dave Vellante in our continuous coverage of the Discover 2020 Virtual Experience HPE's virtual event. theCUBE is here, theCUBE virtual. We're really excited. We had a great session here. We're going to dig deep into machine intelligence and artificial intelligence. Dr. Artie Garg is here. She's the head of advanced AI solutions and technologies at Field of Packard Enterprise. And she's joined by Dr. Soren Kiran, who's the vice president of AI strategy and solutions group at HPE. Folks, great to see you. Welcome to theCUBE. Hi. Hi, nice to meet you. Hello. Dr. Kiran, let's start with you. Maybe talk a little bit about your role. You've had a variety of roles. And maybe what's your current situation at HPE? Hello, hi. So currently at HPE, I'm driving the artificial intelligence strategy and solution group who is currently looking at how do we bring solutions across the HPE portfolio, looking at every business unit but also on the various geos. And at the same time, the team is responsible for building the strategy around AI for the entire company. We're working closely with the field. We're working closely with the teams that are facing the customers every day. And they're also working very, very closely with the various groups in order to make sure that whatever we build holds water for the entire company. Okay, Dr. Garg, maybe you could share with us your focus these days. Yeah, sure. So I'm also part of the AI strategy and solutions team under Soren as our new vice president in that role. And what I'm focused on is really trying to understand what are some of the emerging technologies, whether those be things like new processor architectures or advanced software technologies that could really enhance what we can offer to our customers in terms of AI and exploring what makes sense and how do we bring them to our customers? What are the right ways to package them into solutions? Okay, Soren, everybody's talking about how digital transformation's been accelerated. If you're not digital, you can't transact business. AI infused into every application and now people are realizing, hey, we can't solve all the world's problems with labor. What are you seeing just in terms of AI being accelerated throughout the portfolio and your customers? So that's a very good idea because we've been talking about digital transformation for some time now. And I believe most of our customers believed initially that the one thing that they have is time. Still thinking that, oh, yes, I'm going to somehow at one point apply AI and somehow at one point I'm going to figure out how to build the data strategy or how to use AI in my different line of businesses. What happened with COVID-19 and in this area is that we lost one thing, time. So what we discussed, what they seen our customers is the idea of accelerating their data strategy, accelerating, moving from, let's say, an environment where they were compute-centering models to a data-centering model, trying to understand how do they capture data? How do they accelerate? How do they accelerate the adoption of AI within the various business units? Why? Because they understand that currently, the way they are actually going to do business change completely. They need to understand how to adapt to new business models. They need to understand how to look for value pools where they are none as well. So most of our customers today, while initially they spend a lot of time in an never-ending POC, trying to investigate where do they want to go, currently they want to accelerate the application of AI models, the build-of-data strategies, how then they use all of these data, how do they capture the data to make sure that they look at new business models, new value pools, new customer experience and so forth. So what we've seen in the past, let's say three to six months is that we lost time, but the shift towards an adoption of analytics, AI and data strategies accelerated a lot, simply because customers realize that they need to get ahead of the game. So Dr. Garga, I wonder if you could talk about how HPE is utilizing machine intelligence during this pandemic, maybe helping some of your customers get ahead of it or at least try to track it. How are you applying AI in this context? So I think that, as Soren sort of spoke to, one of the things with adopting AI is it's very transformational for a business. So it changes how you do things, you need to actually adopt new processes to take advantage of it. So what I would say is right now, we're hearing from customers who recognize that the context in which they are doing their work is completely different and they're exploring how AI can help them really meet the challenges of those contexts. So one example might be, how can AI and computer vision be coupled together in a way that makes it easier to reopen stores or ensure that people are distancing appropriately in factories. So I would say that it's the beginning of these conversations as customers, as businesses try to figure out, how do we operate in the new reality that we have? And I think it's a pretty exciting time. And I think just to the point that Soren just made, there's a lot of openness to new technologies that there wasn't before because there's this willingness to change the business processes to really take advantage of the new technologies. Okay, so Dr. Karen, I probably should have started here, but help us understand HPE's overall strategy with regard to AI. I would certainly know that you're using AI to improve IT, the info site, product and capability via the Nimble acquisition, et cetera, and bringing that across the portfolio. But what's the strategy for HPE? So yeah, thank you. That's a good question. So you obviously, you started with a couple of our acquisition in the past because obviously Nimble and then we talked a lot about our efforts to bring info site across the portfolio. But currently in the past couple of months, let's say close to a year, we've been announcing a lot about the acquisitions and we've been talking about the data and we've been talking about the title, we've been talking about Cray and so on and so forth. And now what we are doing at HPE is to bring all of this IP together into one place and try to help our customers within the AI journey. If you're looking at what, for example, what did you actually get when we acquired Cray was not only the HPE C part, but we also acquired and we also have a lot of software and a lot of IP around optimization and so on and so forth. Also within our own labs, we've been investigating AI around like, for example, swarm learning or accelerators or a lot of other activity. So right now what we are trying to help our customers with is to understand how do they leap, how do they leap from the production state in from the POC state in the production state. So if I look at what we are trying to do, is we are trying to accelerate their adoption of AI. So simply starting from an optimized platform infrastructure up to the solutions they are actually going to apply or to use to solve their business problems and wrapping all of that around with services either consumed on-prem as a service and so on. So practically what we want to do is we want to help our customers optimize, orchestrate and operationalize AI because the problem for our customers is not to start in POC. The problem is how do I then take everything that I've been developing or working on and then put that in production at the edge, right? And then keep it maintaining in production in order to get insights and then actually take actions that are helping the enterprise. So basically we want to be data-driven, edge-setting, cloud-enabled and we want to help our customers move from POC into production. Artie, you work with obviously a lot of data folks, companies are data-driven, data scientists, you are hands-on practitioners in this regard. One of the challenges that I hear a lot from customers is trying to operationalize AI, put AI into production. They have data in silos, they spend all their time munging data. You guys have made a number of acquisitions, not the least of which is Cray, obviously MapR from Data Specialist, my friend, my Kumar's company, Blue Data. So what do you see as HP's role in terms of helping companies operationalize AI? So I think that a big part of operationalizing AI, moving away from the POC to really integrate AI into the business processes you have and also the sort of pre-existing IT infrastructure you talked about, you might already have siloed data, that's sort of something we know very well at HPE. We understand a lot of the IT that enterprises already have, the incumbent IT and those systems. And we also understand how to put together systems and integrated systems that include a lot of different types of computing infrastructure. So whether that be different types of servers and different types of storage, we have the ability to bring all of that together and then we also have the software that allows you to talk to all of these different components and build applications that can be deployed in the real world in a way that's easy to maintain and scale and grow as your AI applications will almost invariably get more complex, involve more outputs, involve more input. And so one of the important things as customers try to operationalize AI is knowing that it's not just solving the problem you're currently solving, it's not just operationalizing the solution you have today, it's ensuring that you can continue to operationalize new things or additional capabilities in the future. I want to talk a little bit about AI for good. Everybody talks about AI taking away jobs, but the reality is when you look at the productivity data, for instance, in the United States and Europe, it's declining and it has for the last several decades. And so I guess my point is that we're not going to be able to solve some of the world problems in the coming decades without machine intelligence. I mean, you think about healthcare, you think about feeding populations, you think about obviously things like pandemics, climate change, energy alternatives, et cetera, et cetera, productivity is coming down, machines are a potential opportunity. So there's an automation imperative and do you feel, Dr. Kieran, that people are sort of beyond that machines replacing humans issue? Is that still an item or has the pandemic sort of changed that? So I believe it is. So it used to be a very big guide to me, right? And every time we were speaking at the conference and every time you're actually looking at the features of AI, two scenarios are coming into place, right? The first one where machines are here to actually take our work and then the second one is even a darker version where terminator is coming and so forth, right? So basically these are the two, is the lesser and the greater equivalence and so forth. So and we still see that recurrence theme coming over and over again. And I believe that 2019 was the year of reckoning where people are trying to realize that not only we can actually create responsible AI but we can actually create an AI that is trustworthy and AI that is fair and so on so forth and that we also understood in 2019 it was highly debated everywhere which part of our jobs are going to be replaced like the part that are mundane that can actually be easily automated and so on so. With the COVID-19, what happened is that people are starting to look at AI differently. Why? They are starting to look at data differently and looking at data differently. How do I actually create this core of data which is trusted, secure and so forth? And they are trying to understand that if the data is trusted and secure somehow AI will be trusted and secure as well. Now, if I actually shift it forward, as you said and then I try to understand for example in the manufacturing floor, how do I add more machines or how do I replace humans with machines simply because I need to make sure that I am able to stay in production and so on so forth. From that perspective, I don't believe that the view of how people are actually looking at AI from the job market perspective changed a lot. The view that actually changes how AI is helping us, better certain crisis how AI is helping us for example in healthcare but the idea of AI actually taking part of the jobs or automating part of the jobs we are not actually passed yet. Even if 2018 and even more so in 2019 it was the year also where actually AI through automation replaced the number of jobs but at the same time it was as I was saying the first year where AI created more jobs because once you're displacing in one place they're actually creating more opportunities in other places as well. So, but still I don't believe the feeling changed but we realize that AI is a lot more valuable and it can actually help us to our some of our darkest hours but also allow us get better and faster insights as well. Well, machines have always replaced humans and now for the first time in history it's doing so in a really cognitive functions in a big way. But I want to ask you guys, I'll start with Dr. Gardner, a series of questions that I think underscore the impact of AI and the central role that it plays in companies digital transformations. We talk about that a lot but the questions that I want to ask you I think we'll hit home just in terms of some hardcore examples and if you have others I'd love to hear them but I'm going to start with Artie. So, when do you think doctor or machines will be able to make better diagnoses than doctors? We actually there today already? So I think it depends a little bit on how you define that and I'm just going to practice this by saying both of my parents are physicians so I have a little bit of bias in this space but I think that humans can bring creativity and a certain type of intelligence that it's not clear to me we even know how to model with the computer. And so diagnoses have sometimes two components one is recognizing patterns and being able to say I'm going to diagnose this disease that I've seen before I think that we are getting to the place where there are certain examples just starting to happen where you might be able to take the data that you need to make a diagnosis as well understood a machine may be able to recognize those subtle patterns better but there's another component of doing diagnoses is when it's not obvious what you're looking for you're trying to figure out what is the actual set of diseases I might be looking at and I think that's where we don't really know how to model that type of inspiration and creativity that humans still bring to things that they do including medical diagnoses. Okay so Dr. Kieran my next question is when do you think that owning and driving your own vehicle will become largely obsolete? So well I believe my son is six years old now and I believe I'm working with a lot of companies to make sure that he will not get his driving license with his 18 right? So depending who you're asking and depending the level of autonomy that you're looking at but you just mentioned level five most likely so there are a lot of dates out there so some people actually say 20, 30 I believe that my son in most of the cities in US but also most of the cities in Europe by the time he's 18 in let's say 20, 35 I'll try to make sure that I'm working with the right companies not to allow him to get the driving license. Okay my next question is for maybe both of you can answer do you think the traditional banks will lose control of payment system? So that's an interesting question because I think it's broader than an AI question right? I think that it goes into some other emerging technologies including distributed ledgers and sort of the more secure forms of blockchain. I think that's a challenging question to my mind because it's bigger than the technology it's got economic and policy implications that I'm not sure I can answer. Well that's a great answer because I agree with you Artie I think that governments and banks have a partnership and it's an important partnership for social stability You know similar we've seen now Dr. Kiran in retail you know obviously the COVID-19 has affected retail in a major major way especially physical retail do you think the large retail stores are going to go away? I mean we've seen many in chapter 11 to Artie's point how much of that is machine intelligence versus just social change versus digital transformation it's an interesting question isn't it? So I think most of the right now the retailers are here to stay for the next I guess for the next couple of years but moving forward I think their capacity of adapting to stores like to walking stores or to stores where basically you're just going and there are no shop assistants and you don't even need a credit card to pay you're actually being able to pay either with your face or with your phone or with your small chip and so forth so I believe currently in the next couple of years obviously they are here to stay moving forward and looking at artificial intelligence or robotics applied everywhere in the store and so forth most likely their capacity of adapting to the new normal which is placing AI everywhere and optimizing the working through predicting when and how to guide the customers through the shop and so forth would allow them to actually survive I don't believe that everything is actually going to be done online especially from the retailer perspective most of the we've seen a big shift to COVID-19 but what I was eating the other day especially in France where the counter has opened again we've seen a very quick pickup in the retailers of people that actually visiting the stores as well so it's going to be something interesting five to 10 years and then most of the companies that have adapted to the digital transformation and to the new normal I think they are here to stay some of them obviously are going to step aside I mean I think it's an interesting question too that you're really sort of triggering in my mind is when you think about the framework for how companies are going to come back and come out of this it's not just digital oh that's a big piece of it like how digital the business is can they physically distance I mean I don't know how sports arenas are going to be able to physically distance that's going to be interesting to see how essential is the business and if you think about the different industries it really is quite different across those industries and obviously digital plays a big factor there but maybe we could end on that your final thoughts and maybe any other things you'd like to share with our audience so I think one of the things that's interesting anytime you talk about adopting a new technology and right now we're happening to see this sort of huge uptick in AI adoption happening right at the same time that this is sort of massive shift in how we live our lives is happening and sort of an acceptance I think that can't just go back to the way things work as you mentioned they'll probably be continued sort of desire to maintain social distancing I think that it's going to force us to sort of rethink you know why we do things the way we do now a lot you know the retail environment that we have the transportation solutions that we have they were adapted you know in many cases you know in a very different context in terms of you know what people need to do on a day-to-day basis within their life and then what were the sort of state of art technologies available we're sort of being stressed and forced to reckon with like what is it I really need to do to live my life and then what are the technologies I have available to me to answer that and I think you know it's really difficult to predict right now what people will think is important about a retail experience I wouldn't be surprised if you start to find in-person retail actually be much less you know technologically aided and much more about having the ability to talk to a human being and get their opinion and you know maybe the tactile sense of being able to like you know touch new clothes or whatever it is and so it's really difficult I think right now to predict what things are gonna look like maybe even a year or two from now from that perspective I think that what I feel fairly confident is is that people are really starting to understand and engage with new technologies and they are gonna be really open to thinking about what those new technologies enable them to do in this sort of new way of living that we're gonna probably be entering pretty soon. Excellent. All right, Soren bring us home we'll give you the last word on this topic. No, so I wanted to, I agree with Artie because what these three months of staying at home and of busy shutting down allowed us to do was to actually have a very big reset so let's say a great reset but basically we realize that all the things we've taken from granted like our freedom of move of movement, our technology, our interactions with each other and also for sudden you realize that everything needs to change and the only one thing that we actually kept doing is interacting with each other remotely interacting with each other with our peers in the house and so on and so forth but the one thing that stayed was generating data and data was here to stay because we actually leave trails of data everywhere we go we leave trails of data when we put our watch on where we're actually playing with our phone where we consume digital and so on and so forth so what these three months reinforced for me personally but also for some of our customers was that the data is here to stay and even if the world shut down for three months we did not generate less data data was there on the contrary in some cases more data so the data is the main enabler for the new norm of it is going to pick up and the data will actually allow us to understand how to increase customer experience in the new normal most likely using AI how as I was saying at the beginning how do I actually operate new business model how do I find who do I partner with how do I actually go to market together how do I make collaborations more security and so forth and finally where do I actually find new value force for example how do I actually still enjoy for having a beer in a pub right because suddenly during the COVID-19 that was not possible I have a very nice place around the corner is actually shipping stuff I'm not talking about beer here but in general I mean so the experience is different the pools of data that were the pools for more actually getting values are different as well so data is here to stay and the AI definitely is going to be accelerated because it used to use data to allow us to adapt the new normal and the digital transformation. Yeah a lot of unknowns but certainly machines and data are going to play a big role in the coming decade I want to thank Dr. Artigard and Dr. Soren here and for coming on theCUBE it was great to have you thank you for a wonderful conversation really appreciate it. Thank you very much. Thanks so much. All right and thank you for watching everybody this is Dave Vellante for theCUBE and the HPE 2020 virtual experience we'll be right back for this short break.