>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS, and our community partners. >>Hi everyone. Welcome back to the cubes. Virtual coverage of AWS reinvent 2020 virtual. We are the cube virtual I'm John ferry, your host with my coach, Dave Alante for keynote analysis from Swami's machine learning, all things, data huge. Instead of announcements, the first ever machine learning keynote at a re-invent Dave. Great to see you. Thanks Johnny. And from Boston, I'm here in Palo Alto. We're doing the cube remote cube virtual. Great to see you. >>Yeah, good to be here, John, as always. Wall-to-wall love it. So, so, John, um, how about I give you my, my key highlights from the, uh, from the keynote today, I had, I had four kind of curated takeaways. So the first is that AWS is, is really trying to simplify machine learning and use machine intelligence into all applications. And if you think about it, it's good news for organizations because they're not the become machine learning experts have invent machine learning. They can buy it from Amazon. I think the second is they're trying to simplify the data pipeline. The data pipeline today is characterized by a series of hyper specialized individuals. It engineers, data scientists, quality engineers, analysts, developers. These are folks that are largely live in their own swim lane. Uh, and while they collaborate, uh, there's still a fairly linear and complicated data pipeline, uh, that, that a business person or a data product builder has to go through Amazon making some moves to the front of simplify that they're expanding data access to the line of business. I think that's a key point. Is there, there increasingly as people build data products and data services that can monetize, you know, for their business, either cut costs or generate revenue, they can expand that into line of business where there's there's domain context. And I think the last thing is this theme that we talked about the other day, John of extending Amazon, AWS to the edge that we saw that as well in a number of machine learning tools that, uh, Swami talked about. >>Yeah, it was great by the way, we're live here, uh, in Palo Alto in Boston covering the analysis, tons of content on the cube, check out the cube.net and also check out at reinvent. There's a cube section as there's some links to so on demand videos with all the content we've had. Dave, I got to say one of the things that's apparent to me, and this came out of my one-on-one with Andy Jassy and Andy Jassy talked about in his keynote is he kind of teased out this idea of training versus a more value add machine learning. And you saw that today in today's announcement. To me, the big revelation was that the training aspect of machine learning, um, is what can be automated away. And it's under a lot of controversy around it. Recently, a Google paper came out and the person was essentially kind of, kind of let go for this. >>But the idea of doing these training algorithms, some are saying is causes more harm to the environment than it does good because of all the compute power it takes. So you start to see the positioning of training, which can be automated away and served up with, you know, high powered ships and that's, they consider that undifferentiated heavy lifting. In my opinion, they didn't say that, but that's clearly what I see coming out of this announcement. The other thing that I saw Dave that's notable is you saw them clearly taking a three lane approach to this machine, learning the advanced builders, the advanced coders and the developers, and then database and data analysts, three swim lanes of personas of target audience. Clearly that is in line with SageMaker and the embedded stuff. So two big revelations, more horsepower required to process training and modeling. Okay. And to the expansion of the personas that are going to be using machine learning. So clearly this is a, to me, a big trend wave that we're seeing that validates some of the startups and I'll see their SageMaker and some of their products. >>Well, as I was saying at the top, I think Amazon's really trying, working hard on simplifying the whole process. And you mentioned training and, and a lot of times people are starting from scratch when they have to train models and retrain models. And so what they're doing is they're trying to create reusable components, uh, and allow people to, as you pointed out to automate and streamline some of that heavy lifting, uh, and as well, they talked a lot about, uh, doing, doing AI inferencing at the edge. And you're seeing, you know, they, they, uh, Swami talked about several foundational premises and the first being a foundation of frameworks. And you think about that at the, at the lowest level of their S their ML stack. They've got, you know, GPU's different processors, inferential, all these alternative processes, processors, not just the, the Xav six. And so these are very expensive resources and Swami talked a lot about, uh, and his colleagues talked a lot about, well, a lot of times the alternative processor is sitting there, you know, waiting, waiting, waiting. And so they're really trying to drive efficiency and speed. They talked a lot about compressing the time that it takes to, to run these, these models, uh, from, from sometimes weeks down to days, sometimes days down to hours and minutes. >>Yeah. Let's, let's unpack these four areas. Let's stay on the firm foundation because that's their core competency infrastructure as a service. Clearly they're laying that down. You put the processors, but what's interesting is the TensorFlow 92% of tensor flows on Amazon. The other thing is that pie torch surprisingly is back up there, um, with massive adoption and the numbers on pie torch literally is on fire. I was coming in and joke on Twitter. Um, we, a PI torch is telling because that means that TensorFlow is originally part of Google is getting, is getting a little bit diluted with other frameworks, and then you've got MX net, some other things out there. So the fact that you've got PI torch 91% and then TensorFlow 92% on 80 bucks is a huge validation. That means that the majority of most machine learning development and deep learning is happening on AWS. Um, >>Yeah, cloud-based, by the way, just to clarify, that's the 90% of cloud-based cloud, uh, TensorFlow runs on and 91% of cloud-based PI torch runs on ADM is amazingly massive numbers. >>Yeah. And I think that the, the processor has to show that it's not trivial to do the machine learning, but, you know, that's where the infrared internship came in. That's kind of where they want to go lay down that foundation. And they had Tanium, they had trainee, um, they had, um, infrared chow was the chip. And then, you know, just true, you know, distributed training training on SageMaker. So you got the chip and then you've got Sage makers, the middleware games, almost like a machine learning stack. That's what they're putting out there >>And how bad a Gowdy, which was, which is, which is a patrol also for training, which is an Intel based chip. Uh, so that was kind of interesting. So a lot of new chips and, and specialized just, we've been talking about this for awhile, particularly as you get to the edge and do AI inferencing, you need, uh, you know, a different approach than we're used to with the general purpose microbes. >>So what gets your take on tenant? Number two? So tenant number one, clearly infrastructure, a lot of announcements we'll go through those, review them at the end, but tenant number two, that Swami put out there was creating the shortest path to success for builders or machine learning builders. And I think here you lays out the complexity, Dave butts, mostly around methodology, and, you know, the value activities required to execute. And again, this points to the complexity problem that they have. What's your take on this? >>Yeah. Well you think about, again, I'm talking about the pipeline, you collect data, you just data, you prepare that data, you analyze that data. You, you, you make sure that it's it's high quality and then you start the training and then you're iterating. And so they really trying to automate as much as possible and simplify as much as possible. What I really liked about that segment of foundation, number two, if you will, is the example, the customer example of the speaker from the NFL, you know, talked about, uh, you know, the AWS stats that we see in the commercials, uh, next gen stats. Uh, and, and she talked about the ways in which they've, well, we all know they've, they've rearchitected helmets. Uh, they've been, it's really a very much database. It was interesting to see they had the spectrum of the helmets that were, you know, the safest, most safe to the least safe and how they've migrated everybody in the NFL to those that they, she started a 24%. >>It was interesting how she wanted a 24% reduction in reported concussions. You know, you got to give the benefit of the doubt and assume some of that's through, through the data. But you know, some of that could be like, you know, Julian Edelman popping up off the ground. When, you know, we had a concussion, he doesn't want to come out of the game with the new protocol, but no doubt, they're collecting more data on this stuff, and it's not just head injuries. And she talked about ankle injuries, knee injuries. So all this comes from training models and reducing the time it takes to actually go from raw data to insights. >>Yeah. I mean, I think the NFL is a great example. You and I both know how hard it is to get the NFL to come on and do an interview. They're very coy. They don't really put their name on anything much because of the value of the NFL, this a meaningful partnership. You had the, the person onstage virtually really going into some real detail around the depth of the partnership. So to me, it's real, first of all, I love stat cast 11, anything to do with what they do with the stats is phenomenal at this point. So the real world example, Dave, that you starting to see sports as one metaphor, healthcare, and others are going to see those coming in to me, totally a tale sign that Amazon's continued to lead. The thing that got my attention was is that it is an IOT problem, and there's no reason why they shouldn't get to it. I mean, some say that, Oh, concussion, NFL is just covering their butt. They don't have to, this is actually really working. So you got the tech, why not use it? And they are. So that, to me, that's impressive. And I think that's, again, a digital transformation sign that, that, you know, in the NFL is doing it. It's real. Um, because it's just easier. >>I think, look, I think, I think it's easy to criticize the NFL, but the re the reality is, is there anything old days? It was like, Hey, you get your bell rung and get back out there. That's just the way it was a football players, you know, but Ted Johnson was one of the first and, you know, bill Bellacheck was, was, you know, the guy who sent him back out there with a concussion, but, but he was very much outspoken. You've got to give the NFL credit. Uh, it didn't just ignore the problem. Yeah. Maybe it, it took a little while, but you know, these things take some time because, you know, it's generally was generally accepted, you know, back in the day that, okay, Hey, you'd get right back out there, but, but the NFL has made big investments there. And you can say, you got to give him, give him props for that. And especially given that they're collecting all this data. That to me is the most interesting angle here is letting the data inform the actions. >>And next step, after the NFL, they had this data prep data Wrangler news, that they're now integrating snowflakes, Databricks, Mongo DB, into SageMaker, which is a theme there of Redshift S3 and Lake formation into not the other way around. So again, you've been following this pretty closely, uh, specifically the snowflake recent IPO and their success. Um, this is an ecosystem play for Amazon. What does it mean? >>Well, a couple of things, as we, as you well know, John, when you first called me up, I was in Dallas and I flew into New York and an ice storm to get to the one of the early Duke worlds. You know, and back then it was all batch. The big data was this big batch job. And today you want to combine that batch. There's still a lot of need for batch, but when people want real time inferencing and AWS is bringing that together and they're bringing in multiple data sources, you mentioned Databricks and snowflake Mongo. These are three platforms that are doing very well in the market and holding a lot of data in AWS and saying, okay, Hey, we want to be the brain in the middle. You can import data from any of those sources. And I'm sure they're going to add more over time. Uh, and so they talked about 300 pre-configured data transformations, uh, that now come with stage maker of SageMaker studio with essentially, I've talked about this a lot. It's essentially abstracting away the, it complexity, the whole it operations piece. I mean, it's the same old theme that AWS is just pointing. It's its platform and its cloud at non undifferentiated, heavy lifting. And it's moving it up the stack now into the data life cycle and data pipeline, which is one of the biggest blockers to monetizing data. >>Expand on that more. What does that actually mean? I'm an it person translate that into it. Speak. Yeah. >>So today, if you're, if you're a business person and you want, you want the answers, right, and you want say to adjust a new data source, so let's say you want to build a new, new product. Um, let me give an example. Let's say you're like a Spotify, make it up. And, and you do music today, but let's say you want to add, you know, movies, or you want to add podcasts and you want to start monetizing that you want to, you want to identify, who's watching what you want to create new metadata. Well, you need new data sources. So what you do as a business person that wants to create that new data product, let's say for podcasts, you have to knock on the door, get to the front of the data pipeline line and say, okay, Hey, can you please add this data source? >>And then everybody else down the line has to get in line and Hey, this becomes a new data source. And it's this linear process where very specialized individuals have to do their part. And then at the other end, you know, it comes to self-serve capability that somebody can use to either build dashboards or build a data product. In a lot of that middle part is our operational details around deploying infrastructure, deploying, you know, training machine learning models that a lot of Python coding. Yeah. There's SQL queries that have to be done. So a lot of very highly specialized activities, what Amazon is doing, my takeaway is they're really streamlining a lot of those activities, removing what they always call the non undifferentiated, heavy lifting abstracting away that it complexity to me, this is a real positive sign, because it's all about the technology serving the business, as opposed to historically, it's the business begging the technology department to please help me. The technology department obviously evolving from, you know, the, the glass house, if you will, to this new data, data pipeline data, life cycle. >>Yeah. I mean, it's classic agility to take down those. I mean, it's undifferentiated, I guess, but if it actually works, just create a differentiated product. So, but it's just log it's that it's, you can debate that kind of aspect of it, but I hear what you're saying, just get rid of it and make it simpler. Um, the impact of machine learning is Dave is one came out clear on this, uh, SageMaker clarify announcement, which is a bias decision algorithm. They had an expert, uh, nationally CFUs presented essentially how they're dealing with the, the, the bias piece of it. I thought that was very interesting. What'd you think? >>Well, so humans are biased and so humans build models or models are inherently biased. And so I thought it was, you know, this is a huge problem to big problems in artificial intelligence. One is the inherent bias in the models. And the second is the lack of transparency that, you know, they call it the black box problem, like, okay, I know there was an answer there, but how did it get to that answer and how do I trace it back? Uh, and so Amazon is really trying to attack those, uh, with, with, with clarify. I wasn't sure if it was clarity or clarified, I think it's clarity clarify, um, a lot of entirely certain how it works. So we really have to dig more into that, but it's essentially identifying situations where there is bias flagging those, and then, you know, I believe making recommendations as to how it can be stamped. >>Nope. Yeah. And also some other news deep profiling for debugger. So you could make a debugger, which is a deep profile on neural network training, um, which is very cool again on that same theme of profiling. The other thing that I found >>That remind me, John, if I may interrupt there reminded me of like grammar corrections and, you know, when you're typing, it's like, you know, bug code corrections and automated debugging, try this. >>It wasn't like a better debugger come on. We, first of all, it should be bug free code, but, um, you know, there's always biases of the data is critical. Um, the other news I thought was interesting and then Amazon's claiming this is the first SageMaker pipelines for purpose-built CIC D uh, for machine learning, bringing machine learning into a developer construct. And I think this started bringing in this idea of the edge manager where you have, you know, and they call it the about machine, uh, uh, SageMaker store storing your functions of this idea of managing and monitoring machine learning modules effectively is on the edge. And, and through the development process is interesting and really targeting that developer, Dave, >>Yeah, applying CIC D to the machine learning and machine intelligence has always been very challenging because again, there's so many piece parts. And so, you know, I said it the other day, it's like a lot of the innovations that Amazon comes out with are things that have problems that have come up given the pace of innovation that they're putting forth. And, and it's like the customers drinking from a fire hose. We've talked about this at previous reinvents and the, and the customers keep up with the pace of Amazon. So I see this as Amazon trying to reduce friction, you know, across its entire stack. Most, for example, >>Let me lay it out. A slide ahead, build machine learning, gurus developers, and then database and data analysts, clearly database developers and data analysts are on their radar. This is not the first time we've heard that. But we, as the kind of it is the first time we're starting to see products materialized where you have machine learning for databases, data warehouse, and data lakes, and then BI tools. So again, three different segments, the databases, the data warehouse and data lakes, and then the BI tools, three areas of machine learning, innovation, where you're seeing some product news, your, your take on this natural evolution. >>Well, well, it's what I'm saying up front is that the good news for, for, for our customers is you don't have to be a Google or Amazon or Facebook to be a super expert at AI. Uh, companies like Amazon are going to be providing products that you can then apply to your business. And, and it's allowed you to infuse AI across your entire application portfolio. Amazon Redshift ML was another, um, example of them, abstracting complexity. They're taking, they're taking S3 Redshift and SageMaker complexity and abstracting that and presenting it to the data analysts. So that, that, that individual can worry about, you know, again, getting to the insights, it's injecting ML into the database much in the same way, frankly, the big query has done that. And so that's a huge, huge positive. When you talk to customers, they, they love the fact that when, when ML can be embedded into the, into the database and it simplifies, uh, that, that all that, uh, uh, uh, complexity, they absolutely love it because they can focus on more important things. >>Clearly I'm this tenant, and this is part of the keynote. They were laying out all their announcements, quick excitement and ML insights out of the box, quick, quick site cue available in preview all the announcements. And then they moved on to the next, the fourth tenant day solving real problems end to end, kind of reminds me of the theme we heard at Dell technology worlds last year end to end it. So we are starting to see the, the, the land grab my opinion, Amazon really going after, beyond I, as in pass, they talked about contact content, contact centers, Kendra, uh, lookout for metrics, and that'll maintain men. Then Matt would came on, talk about all the massive disruption on the, in the industries. And he said, literally machine learning will disrupt every industry. They spent a lot of time on that and they went into the computer vision at the edge, which I'm a big fan of. I just loved that product. Clearly, every innovation, I mean, every vertical Dave is up for grabs. That's the key. Dr. Matt would message. >>Yeah. I mean, I totally agree. I mean, I see that machine intelligence as a top layer of, you know, the S the stack. And as I said, it's going to be infused into all areas. It's not some kind of separate thing, you know, like, Coobernetti's, we think it's some separate thing. It's not, it's going to be embedded everywhere. And I really like Amazon's edge strategy. It's this, you, you are the first to sort of write about it and your keynote preview, Andy Jassy said, we see, we see, we want to bring AWS to the edge. And we see data center as just another edge node. And so what they're doing is they're bringing SDKs. They've got a package of sensors. They're bringing appliances. I've said many, many times the developers are going to be, you know, the linchpin to the edge. And so Amazon is bringing its entire, you know, data plane is control plane, it's API APIs to the edge and giving builders or slash developers, the ability to innovate. And I really liked the strategy versus, Hey, here's a box it's, it's got an x86 processor inside on a, throw it over the edge, give it a cool name that has edge in it. And here you go, >>That sounds call it hyper edge. You know, I mean, the thing that's true is the data aspect at the edge. I mean, everything's got a database data warehouse and data lakes are involved in everything. And then, and some sort of BI or tools to get the data and work with the data or the data analyst, data feeds, machine learning, critical piece to all this, Dave, I mean, this is like databases used to be boring, like boring field. Like, you know, if you were a database, I have a degree in a database design, one of my degrees who do science degrees back then no one really cared. If you were a database person. Now it's like, man data, everything. This is a whole new field. This is an opportunity. But also, I mean, are there enough people out there to do all this? >>Well, it's a great point. And I think this is why Amazon is trying to extract some of the abstract. Some of the complexity I sat in on a private session around databases today and listened to a number of customers. And I will say this, you know, some of it I think was NDA. So I can't, I can't say too much, but I will say this Amazon's philosophy of the database. And you address this in your conversation with Andy Jassy across its entire portfolio is to have really, really fine grain access to the deep level API APIs across all their services. And he said, he said this to you. We don't necessarily want to be the abstraction layer per se, because when the market changes, that's harder for us to change. We want to have that fine-grained access. And so you're seeing that with database, whether it's, you know, no sequel, sequel, you know, the, the Aurora the different flavors of Aurora dynamo, DV, uh, red shift, uh, you know, already S on and on and on. There's just a number of data stores. And you're seeing, for instance, Oracle take a completely different approach. Yes, they have my SQL cause they know got that with the sun acquisition. But, but this is they're really about put, is putting as much capability into a single database as possible. Oh, you only need one database only different philosophy. >>Yeah. And then obviously a health Lake. And then that was pretty much the end of the, the announcements big impact to health care. Again, the theme of horizontal data, vertical specialization with data science and software playing out in real time. >>Yeah. Well, so I have asked this question many times in the cube, when is it that machines will be able to make better diagnoses than doctors and you know, that day is coming. If it's not here, uh, you know, I think helped like is really interesting. I've got an interview later on with one of the practitioners in that space. And so, you know, healthcare is something that is an industry that's ripe for disruption. It really hasn't been disruption disrupted. It's a very high, high risk obviously industry. Uh, but look at healthcare as we all know, it's too expensive. It's too slow. It's too cumbersome. It's too long sometimes to get to a diagnosis or be seen, Amazon's trying to attack with its partners, all of those problems. >>Well, Dave, let's, let's summarize our take on Amazon keynote with machine learning, I'll say pretty historic in the sense that there was so much content in first keynote last year with Andy Jassy, he spent like 75 minutes. He told me on machine learning, they had to kind of create their own category Swami, who we interviewed many times on the cube was awesome. But a lot of still a lot more stuff, more, 215 announcements this year, machine learning more capabilities than ever before. Um, moving faster, solving real problems, targeting the builders, um, fraud platform set of things is the Amazon cadence. What's your analysis of the keynote? >>Well, so I think a couple of things, one is, you know, we've said for a while now that the new innovation cocktail is cloud plus data, plus AI, it's really data machine intelligence or AI applied to that data. And the scale at cloud Amazon Naylor obviously has nailed the cloud infrastructure. It's got the data. That's why database is so important and it's gotta be a leader in machine intelligence. And you're seeing this in the, in the spending data, you know, with our partner ETR, you see that, uh, that AI and ML in terms of spending momentum is, is at the highest or, or at the highest, along with automation, uh, and containers. And so in. Why is that? It's because everybody is trying to infuse AI into their application portfolios. They're trying to automate as much as possible. They're trying to get insights that, that the systems can take action on. >>And, and, and actually it's really augmented intelligence in a big way, but, but really driving insights, speeding that time to insight and Amazon, they have to be a leader there that it's Amazon it's, it's, it's Google, it's the Facebook's, it's obviously Microsoft, you know, IBM's Tron trying to get in there. They were kind of first with, with Watson, but with they're far behind, I think, uh, the, the hyper hyper scale guys. Uh, but, but I guess like the key point is you're going to be buying this. Most companies are going to be buying this, not building it. And that's good news for organizations. >>Yeah. I mean, you get 80% there with the product. Why not go that way? The alternative is try to find some machine learning people to build it. They're hard to find. Um, so the seeing the scale of kind of replicating machine learning expertise with SageMaker, then ultimately into databases and tools, and then ultimately built into applications. I think, you know, this is the thing that I think they, my opinion is that Amazon continues to move up the stack, uh, with their capabilities. And I think machine learning is interesting because it's a whole new set of it's kind of its own little monster building block. That's just not one thing it's going to be super important. I think it's going to have an impact on the startup scene and innovation is going, gonna have an impact on incumbent companies that are currently leaders that are under threat from new entrance entering the business. >>So I think it's going to be a very entrepreneurial opportunity. And I think it's going to be interesting to see is how machine learning plays that role. Is it a defining feature that's core to the intellectual property, or is it enabling new intellectual property? So to me, I just don't see how that's going to fall yet. I would bet that today intellectual property will be built on top of Amazon's machine learning, where the new algorithms and the new things will be built separately. If you compete head to head with that scale, you could be on the wrong side of history. Again, this is a bet that the startups and the venture capitals will have to make is who's going to end up being on the right wave here. Because if you make the wrong design choice, you can have a very complex environment with IOT or whatever your app serving. If you can narrow it down and get a wedge in the marketplace, if you're a company, um, I think that's going to be an advantage. This could be great just to see how the impact of the ecosystem this will be. >>Well, I think something you said just now it gives a clue. You talked about, you know, the, the difficulty of finding the skills. And I think that's a big part of what Amazon and others who were innovating in machine learning are trying to do is the gap between those that are qualified to actually do this stuff. The data scientists, the quality engineers, the data engineers, et cetera. And so companies, you know, the last 10 years went out and tried to hire these people. They couldn't find them, they tried to train them. So it's taking too long. And now that I think they're looking toward machine intelligence to really solve that problem, because that scales, as we, as we know, outsourcing to services companies and just, you know, hardcore heavy lifting, does it doesn't scale that well, >>Well, you know what, give me some machine learning, give it to me faster. I want to take the 80% there and allow us to build certainly on the media cloud and the cube virtual that we're doing. Again, every vertical is going to impact a Dave. Great to see you, uh, great stuff. So far week two. So, you know, we're cube live, we're live covering the keynotes tomorrow. We'll be covering the keynotes for the public sector day. That should be chock-full action. That environment is going to impact the most by COVID a lot of innovation, a lot of coverage. I'm John Ferrari. And with Dave Alante, thanks for watching.

Sand Hill Road to the heart of Silicon Valley it's the cute presenting the people first Network insights from entrepreneurs and tech leaders when I'm John Ferrari with the cube I'm the co-host also the founder of Silicon angle me we are here on Sand Hill Road at Mayfield for the people first conversations I'm John furry with the cube weird Allen being global CTO and IT of innovation at Procter & Gamble formerly the same position at coca-cola has done a lot of innovations over the years also a reference account back in the day for web methods when they call on the financing of that one of the most famous IPOs which set the groundwork for web services and has a lot of history going back to the 80s we were just talking about it welcome this conversation on people first network thank you for inviting me so the people first network is all about people and it's great to have these conversations you're old school you were doing some stuff back on the 80s talking about doing RPA 3270 you've been old school here yeah I go back to APL as my first programming language went through the the third generation languages and of course the old 30 to 70 emulation which is what we know today is our PA one of the cool things I was excited to hear some of your background around your history web methods you were a reference call for venture financing of web methods which was financed on the credit card for the two founders husband and wife probably one of the most successful I appeals but more importantly at the beginning of the massive wave that we now see with web services this is early days this was very early days when I was at DHL we were looking at what we're gonna do for the future and in fact we built one of the first object-oriented frameworks in C++ at the time because that was all that was available to us or the best was available we rejected Corbis and we said look if we're gonna go this direction and one of my developers found web methods found philip merrick it was literally at the time working out of his garage and had this technology that was going to allow us to start moving into this object-oriented approach and I remember the day Robin Vasan form a field called and said hey I'm thinking about investing in web methods what do you think about it and not only was it one of the first startups that I ever worked with but it's actually the first time I met anybody in the venture community way back in nineteen I think 1997 is what had happened and that was a computing time in computer science and then the rest is history and then XML became what it became lingua franca for the web web services now Amazon Web Services you see in cloud computing micro services kubernetes service meshes this is a new stack that's being developed in the cloud and this is the new generation you've seen many waves and at Procter & Gamble formerly coca-cola you're the same role you have to navigate this so what's different now what's different say 15 20 years ago how are you looking at this market how you implementing some of the IT and infrastructure and software development environments I think what's change is you know when we got into the the early 2000s Nicolas car came out and said IT doesn't matter and I think anybody that was an IT had this very objectionable response initially but when you step back and you looked at it what she realised was in many cases IT didn't matter and those were those areas that were non-competitive those things that could be commoditized and it was completely right the reality is IT has always mattered that technology does give you a competitive advantage in certain markets and certain capabilities for a company but back then we had to go out and we had to purchase equipment we had to configure the equipment there was a lot of heavy lifting in corporations just did not want to invest the capital so they outsource the stuff wholesale I think General Motors was the first one that just out sourced everything and was followed by other companies including Procter & Gamble the decision at that time was probably right but as we go forward and we see what's happened with corporations we see the valuations of corporations the amount of return on equity based on the on the capital that's being invested we can see that data is important we can see that agility flexibility is key to competing in the future and therefore what's changing is we are now moving into an age of away from ERP so we're moving into an age away from these outsource providers on a wholesale basis and using it selectively to drive down costs and allowing us to free up money in order to invest in those things that are most important to the company so you're saying is that the folks naturally the server consolidation they've bought all this gear all this software over you know 18-month rollouts before they even see the first implementation those are the glory days of gravy trains for the vendor's yeah not good for the practitioners but you're saying that the folks who reinvested are investing in IT as a core competency are seeing a competitive advantage they certainly are you know I think I made the statement front of a number of the vendors and a few years ago and people were not comfortable with it but what I said was like you gone are the ears of these 10 20 million dollar deals gone are the ears of the million two million dollar deals we're in the ear of throwaway technology I need to be able to use and invest in technology for a specific purpose for a specific period of time and be able to move on to the next one it's the perfect time for startups but startups shouldn't be looking at the big picture they should be looking at the tail on these investments let me try things let me get out in the market let me have a competitive advantage in marketing which is most important to me or in supply chain those are the areas that I can make a difference with my consumers and my customers and that's where the investments have to go so just in constant of throwaway technology and you know you'd also be said of you know being more agile though interesting to look at the cloud SAS business model if Amazon for us I think that's the gold standard where they actually lower prices on a per unit basis and increase more services and value but in the aggregate you're still paying more but you have more flexibility and that's kind of a good tell sign so that you're seeing that ability to reuse either the infrastructure that's commoditized to shift the value this is are people having a hard time understanding this so I want to get your reaction to how should I tea leaders understand that the wave of cloud the wave of machine learning what a I can bring to the table these new trends how how should leaders figure this out is there a playbook as there are things that you've learned that you could share you know that there's really a playbook it's still early on everyone's looking for one cloud fits all the reality is whether it's Google whether it's Amazon whether it's Microsoft whether it's IBM all clouds are different all clouds have our special are purpose-built for different solutions and I think as an IT leader you have to understand you're not going to take everything and lift and shift that's what we used to do we're now in the position where we have to deconstruct our business we have to understand the services the capabilities that we want to bring to market and not lock ourselves in its building blocks its Legos we're in the period of Legos putting these things together in different manners in order to create new solutions if we try to lock ourselves in the past of how we've always financed things how we've always built things then we're not going to be any better off in the new world than we were in the old alan i want to get your reaction to to two words our PA and containers well as i said earlier our PA is 3270 emulation from the 1980s and for those of us that are old enough to remember that i I still remember scraping the the old green screens and and putting a little process around it it what's nice though is that we have moved forward machine learning and AI and other other capabilities are now present so that we can do this I actually played around with neural nets probably back in 1985 with an Apollo computer so that tells you how far back I go but technologies change processing speeds change everything the technology trends are allowing us to now to do these things the question that we have is also a moral dilemma is are we trying to replace people or are we trying to make improvements and I think that you don't look at our PA as a way simply to replace work it's a way to enhance what we're doing in order to create new value for the customer or for the consumer in our case I think in the in the area of containers you know again been around for a while been around for a while it's just another another approach that we're not we don't want lock in we don't want to be dependent on specific vendors we want the portability we want the flexibility and I think as we start moving containers out to the edge that's where we're gonna start seeing more value as the business processes and the capabilities are spread out again the idea of centralized cloud computing is very good however it doesn't need to be distributed what's interesting I find about the conversation here is that you mentioned a couple things earlier you mentioned the vendors locking you in and saying here's the ERP buy this and with this you have to have a certain process because this is our technology you got to use it this way and you were slave to their their tech on your process serve their tech with containers and say orchestration you now the ability to manage workloads differently and so an interesting time there's that does that change the notion of rip and replace lift and shift because if I a container I could just put a container around it and not have to worry about killing the old to bring in the new this is on the fundamental kind of debate going on do you have to kill the old to bring in the new well you need to kill the old sometimes just because it's old it's time to go other times you do need to repackage it and other times I hate to say it you do need to lift and shift if you're a legacy organization they have a long history such as most of the manufacturing companies in the world today we can't get rid of old things that quickly we can't afford to a lot of the processes are still valid as we're looking to the future we certainly are breaking these things down into services we're looking to containerize these things we're looking to move them into areas where we can compute where we want to when we want to at the right price we're just at the beginning of that journey in the industry I still think there's about five to seven years to go to get there now I'll talk about the role of the edge role of cloud computing as it increases the surface area of IT potentially combined with the fact that IT is a competitive advantage bring those two notions together what's the role of the people because you used to have people that would just manage the rack and stack I'm provisioning some storage I'm doing this as those stovepipes start to be broken down when the service area of IT is bigger how does that change the relationship of the people involved you know you win with people at the end of the day you don't win with technology you know a company of such as Proctor and Gamble and I think what's happened if you look at historically the ERP vendors came out probably 99 2000 and it used to be and remember these I'm old to be honest with you but I remember that we used to have to worry about the amount of memory we were managing we had to be able to tune databases in all of this and the vendors went ahead and they started automating all those processes with the idea that we can do it better than a human and a lot of people a lot of the technology talent then started leaving the organizations and organizations were left with people that we're focusing on process and people a process excuse me process and the the the business which is very good because you need the subject matter experts going forward we have to reinvest in people our people have the subject matter expertise they have some technology skills that they've developed over the years and they've enhanced it on their own but we're in this huge change right now where we have to think different we have to act different and we have to behave differently so doubling down on people is the best thing that you can do and the old outsource model of outsourcing everything kind of reduces the core competency of the people yeah now you got to build it back up again exactly I mean we when we left at P&G 15 years ago about 5,000 people left the organization when we outsource them when we outsource the technology to our partner at that time now it's time we're starting to bring it back in we've brought the network team back in and stood up our own sock in our own NOC for the first time in years just this past year we're doing the same thing by moving things out to the cloud more and more is moving to the cloud we're setting up our own cloud operations and DevOps capabilities I can tell you having been on both sides of it it's a lot harder to be able to bring it back in than it is to take it out and you know interesting proctoring games well known as being a very intimate with the data very data-driven company the data is valuable and having that infrastructure NIT to support the data that's important what's your vision on the data future of the data in the world well I think data is has a value to itself but when you tie it to products you tie it to your customers and consumers it's even more valuable and we're in the process now of things that we used to do completely internally with our own technology or technology partners we're now moving all of that out into the cloud now and I must say cloud its clouds plural again going back to certain clouds are better for certain things so you're seeing a dramatic shift we have a number of projects underway that are in the cloud space but for customers and consumers number of cloud projects in the way for our own internal employees it's all about collecting the data processing the data protecting that data because we take that very seriously and being able to use it to make better decisions I want to get your reaction on two points and two quite lines of questioning here because I think it's very relevant on the enterprise side you're a big account for the big whales the old ERP so the big cloud providers so people want to sell you stuff at the same time you're also running IT innovation so you want to play with the new shiny new toys and experiments start up so if startups want to get your attention and big vendors want to sell to you the tables have kind of turned it's been good this is a good it's a good buyers market right now in my opinion so what's your thoughts on that so you know start with the big companies what do they got to do to win you over well they got to look like how they got to engage and for startups how do they get your attention I think the biggest thing for either startup or large companies understanding the company you're dealing with whether it's Procter & Gamble whether it's coca-cola whether it was DHL if you understand how I operate if you understand how decisions are made if you understand how I'm organized that's gonna give you an a competitive advantage now the large corporations understand this because they've been around through the entire journey of computing with these large corporations the startups need to step back and take a look and see where do I add that competitive advantage many times when you're selling to a large corporate you're not selling to a large corporate you're selling two divisions you're selling two functions and that's how you get in I've been working with startups as I said back since web methods and it was just a two-person company but we brought them in for a very specific capability I then took web methods with me when I left DHL I took them to GE when I left GE I took them to ing because I trusted them and they matured along the way I think finding that right individual that has the right need is the key and working it slowly don't think you're gonna close the deal fast if you're start-up know it's gonna take some time and decide if that's in your best interest or not slow things down focus don't try to boil the ocean over too many of them try to boy you're right Jimmy people try to boil the ocean get that win one win will get you another one which will get you another win and that's the best way to succeed get that beachhead Ellen so if you could go back and knowing what you know now and you're breaking into the IT leadership's position looking forward what would you do differently can do a mulligan hey what would you do differently well you know I think one of the one of the dangers of being an innovator in IT is that you really are risk taker and taking risks is counterculture to corporations so I think I would probably try to get by in a little bit more I mean someone once told me that you know you see the force through the trees before anybody else does your problem is you don't bring people along with you so I think I would probably slow down a little bit not in the adoption of technology but I'd probably take more time to build the case to bring people along a lot faster so that they can see it and they can take credit for it and they can move that needle as well yeah always sometimes early adopters and pioneers had the arrows on the back as they say I've had my share now thanks for sharing your experience what's next for you what's the next mountain you're going to climb well I think that as we're looking forward latency is still an issue you know we have to find a way to defeat latency we're not going to do it through basic physics so we're gonna have to change our business models change our technology distribution change everything that we're doing consumers and customers are demanding instant access to enhanced information through AI and m/l right at the point where they want it and that means we're now dealing with milliseconds and nanoseconds of having to make decisions so I'm very interested in looking at how are we going to change consumer behavior and customer behavior by combining a lot of the new technology trends that are underway and we have to do it also with the security in mind now before we security was secondary now as we're seeing with all of the hacks and the malware and everything that's going on in the world we have to go in and think a little bit different about how we're gonna do that so I'm very much engaged in working with a lot of startups I live here in the Silicon Valley I commute to Cincinnati for Procter & Gamble I'm spending time and just flew in from tel-aviv literally an hour ago I'm in the middle of all the technology hotspots trying to find that next big thing and it's a global it's global innovation happens everywhere and anywhere the venture community if you look at the amount of funds it used to be invested out of the Silicon Valley versus the rest of the world it continues to be on a downward trend not because the funding isn't here in the Silicon Valley but because everyone is recognizing that innovation and technology is developed everywhere in the world Alan Bain was the CTO global CTO and IT innovator there at the cube conversation here in San Hill Road I'm John for a year thanks for watching you

hello everyone I'm Jean Faria we are reporting on the ground near Puerto Rico for blockchain unbound exclusive conversations at coinage end of covering all the action restart week of ten of events cryptocurrency blockchain all the people are here with the local ecosystem the cube is here it's great to have you on thanks for joining blockchain innovation is today global this is a revolution way bigger than the Internet itself programmable money programmable contracts that wipes out finance it wipes out legal it wipes out governance in many ways there's no central authority you have access to open source software it's fully connected so now is the time to make it translate we've all heard about the steam digital transformation its businesses that if they don't evolve and adopt blockchain AI all these other things they have a threat of being put out of business it is extremely competitive a new set of stakeholders investors global players governments are it's happening now you have a chance to be a part of an economy without a permission of a centralized organization have to pay 200 people in 40 countries and it's an unholy mess with withholding taxes and concerns around money transfer costs a hassle it's a nightmare like all currency control so you're only allowed to move a certain amount of capital out the country legally so what happens in all your backups our currency and you can effectively invest in assets around the world this is making it much easier to contribute to help people to get healthy and you don't have to go to school there's a very big influx of young and talented minds at that right and this is really changing the revolution landscape you've got the radical Burning Man hippie guy all the way to a three-piece suit yeah and that diversity is very very rich a lot of people are scared I like whoa hold on slow down we're not gonna prove it the other half saying no this is the future so you have two competing forces colliding for some reason crypto really pokes at people's biases you know why does it have any value and I go well why does the United States dollar have any value I mean you've got Full Faith and Credit of the government that's in debt by 20 trillion dollars you know is that a good idea most people that come here sorry with the what the how and people are scared but the young people are like yo this is happening this is not a moment this is a movement is definitely oh say 1996-97 of the internet bubble it's just starting people know there's something really magical they don't quite know what you know America really grew because you're abused to have all the controls and so the capital by sea left Europe and away in America and now it's happening 300 years later as America has all the controls and the capital starting to go away so a new Liberation's happening incredible resources are now being poured in problems that were ignored for many many and what is beautiful is that block Candy's doing it open-source is accelerating the tech these ideas are being freely shared whereas before there's bottlenecks in the collaboration aspect if we're able to write a contract in a thousand people be able to verify that contract and we're able to transfer money from one person to another without the two parties being involved we've got a perfect scenario security and speed and fairness all at the same time you can create these chains of trust and that can happen anywhere in the world you're on a level playing field if you have 4G connectivity now you can compete globally and be a part of the global economy so if you're someone who's in the emerging developing world and you want to begin to build wealth and you'd like to own a piece of first world real estate and today the minimum is about a thousand dollars but by implementing the Plott chain further they won't eventually get down to one dollar you can buy a piece of real estate and enjoy the returns on that I want to solve the wealth gap and I truly believe we can do it when we can allow anyone anywhere to invest in good quality assets a conduit with the current system there's too many friction costs the killer app right is money it's paying people that is the killer app of the block type right now let's say that money is software and it is software so if you buy something with a credit card what do you think's happening it's all software and what has happened is open-source software has always eventually won with respect to close source software so proprietary money is probably back on its heels because open-source money's coming in something like that will give liquidity to a lot of small business owners America is a country of small business owners across the globe it supports small business owners it's an interesting model yeah you don't have to give up any equity you don't have to give up any poor seats yeah right it's much leaner my super if you're an investor you gotta get a pound of flesh somewhere is it's just getting it on the discounted tokens is there a little liquidity going on when you think about you know private sale presale is 99% a token deal right although equities coming in because a lot of more venture capital is coming in and they're demanding a piece of the action from a company and equity perspective its equity might be future revenue sometimes as dividends or the opportunity get dividends so it's a combination of you have a preference you care you know at the other day equity is I was always preferable there is a provision in the 1934 Securities Act called section 12 G it allows us Spacely to go public by telling the SEC we're doing it without having to delay it to wait for their permission after 60 days it's a derivative so we'll continue to clear comments but but the thing is with tokens who knows how long that'll take I mean is the SEC gonna Shepherd something through with crypto 1 or do they gonna make it take 5 years I don't know [Music] all over the island this is the new Oliver field the world is moving too fast today for a big country to keep up it's all gonna happen now in this next century at the city level and so we work a lot with four smaller countries or small countries because I know estonia armenia baja rains got you know dubai envy so i mean every country wants to be the crypto country multiple small countries are going to come into the space which they know now they can get the capital flowing into that company and they're gonna allow their rules to be lacs they're gonna let capital flow through and then us will have to change or maybe UK will have to change orders against us will have to change in the first world a lot of what we're talking about is a nice-to-have it's it's sort of a bit of a game and if i can participate but where I come from an emerging war that's a necessity they are no other solutions so if you live in South Africa or China or India and you want to get your money into a first world country like England Australia America it's very very difficult and virtually no one can do it but it's a major problem because you want wealth preservation you want but Plan B you want your children to be able to go to a first world university etc etc etc Puerto Rico being a free associated States of the United States of America is like the best place to actually test this possibly some push for that for infrastructure for you know internet for all sorts of different things in terms of building the best infrastructure the new newest best-in-class for your business it's four percent corporate taxes and individual it's zero percent now that's what you got to move here you gotta move here okay but you don't have to give you deliver your US citizenship no taxes are great at the same time they fall in love with the islands so it's amazing because to me Puerto Rico is a combination of LA's whether San Francisco's open-mindedness and Barcelona's you know deep European history it's just a really beautiful place and it's US territory so it's a short hop and a jump to the States if you need to most people in America mainland sort of think they're going to a foreign country because it's treated that way by our government how do I come to Puerto Rico do it right not offend the culture in abil them together what's your experience with the play ball stay good friends lost their relocation services for their business and themselves so they write a big check to you guys for the service but it's you guide them through the entire process and there's real energy here because there's a social movement underneath the entire cryptocurrency movement and that's to basically help your fellow man or women all these activity is really going to give a a shot in the arm to the Puerto Rican economy and we're bringing our funds and we're bringing our advisory the radar Thank You exponent there the hurricane was a horrible atrocity that happened and now we have this blank canvas to create a vision for Puerto Rico so what we're doing is we're connecting every single University on the island to work on open source projects to like make solutions for the private sector they know that if they can buy power on a cellphone like they're already doing for other goods and services now we've got a game-changer this is restart week and one of the other things that we've done is help all of the conference's come together collaborate rather than compete so go into the same week and put all of these satellite groups around it and then we blanket it a week around it so that we had one place for people to go and look for all of the events and then also for some for them to understand a movement about the education piece it's very difficult for people that kind of get caught up to speed because there's some technical things that need to understand to really apply this technology into the business world the other day we had an event where we talked 50 people how to create a smart contract from scratch those are 50 people who are not the same anymore ecosystems developing yet entrepreneurs you got projects you got funding coming in but as it's gonna be a fight for the ecosystem because you can't have zillion ecosystems there are definitely some you know the galaxies and you know regulatory aspects that you know put some concerns and a lot of you know people's mind since its inception you've seen people and media and mainstream media in particular target Bitcoin and they're just adopting the government narrative saying oh everyone in this industry is corrupt Oh everyone in this industry is an ICS camera Oh everyone in this industry is a a drug runner and they have all selling drugs on the dark web and and it's like you know what like you can do some research and don't get better than that traditional media they want to take down everybody that they don't consider you know like a birds of the same feather there actually are a lot of scammers and a lot of like dark forces inside of the cryptocurrency movement so that's why I think we welcome kind of more regulatory influence because you know none of us want to see bad actors in the space we've seen folks go out raise you know really big about to capital with no product roadmap no business talking roadmap no real way to get from zero to X what are they trying to shoehorn a regular business onto the blockchain and just assume that by adding crypto at the end of you know toilet paper they're gonna get something I had another founder tell me that you know Mike tokens are worth 100 million humming yep you don't have a user you just have a product you're tokens I've hiked if you ask me it's it's what little I can tell my house is 100 million dollars it's only worth as much as the top buyer how much we really need hardcore reputation systems in our industry and in the for the world I think 2018 is going to be the year of clarity on regulation and I think that's where Puerto Rico comes in and plays a major role just to see the thousands of people who have come here to support these several conferences has been amazing my most surprising thing though is the amount of people that have told me that they bought a one-way ticket and have no intention of going home so to make Puerto Rico your home I think is a really amazing first step when I go to the supermarket and where I go it's full of American and people from outside and when you ask them where you're from and they will tell you from Puerto Rico this is gonna become the epicenter of this multi-billion dollar market we need to have people prepared for this you have to create the transparency the beauty of the transparency is there's actually privacy baked in and that's what I love about blockchain is it has all of the good things all communities need to evolve in my opinion between technology communities open networks of governance where we have peer-to-peer distribution of finance and of resources in a way that allows people to aggregate around the marketplaces that are actually benefitting the way that they believe the world should work we're going to be tools that far surpassed what's currently available in terms of the messages the websites all these things for 20 years the Internet has been free it's a really beautiful thing for consumption and open-source is the absolute right methodology for software when it comes to your own content a reward it makes sense everybody is going to get to play together across every device the developers are going to get rewarded for creating content people are going to be rewarded for creating things inside the games and the players are going to get rewarded for getting to the top levels of all the games and we're going to reward them through our cryptocurrency if we begin to own ourself sovereign identity then when we're owning our data that's the foundation for universal basic income communications completely frictionless payment completely frictionless and governance completely frictionless and we have to put this all together who wins here the average citizen entrepreneur that is leveraged citizen player that wants to start something whether it's a banking a service provider of some sort an entrepreneur or a new financial instrument or firm you all have greenfield opportunity here the first thing I would tell found us is to reach out ok this community is very very supportive like you can reach out to me you can reach out to other guys LinkedIn Facebook or come to these events and say your idea and you need help because you will need help you cannot run this alone ok you are running a company you're running your team have a good team that's the first thing you got to be vigilant and you keeping your money in a hard wallet not keeping your private keys on your computer if you're using a centralized system those centralized systems are really easily exploitable strategic partnerships Advisors founding team and then show the idea to the people explain yourself frankly and honestly and I think the community will reward you to go and find it ring whether you're a fortune 500 company or a startup it's all about building the community and I believe that whether it's utility Target or security or combination of the two it provides an incredible vehicle to ultimately be the catalyst to your community and if you the to community adding value then you're going to build a company event it's always gonna be led by the business model because you need something to act as the power pull to pull the thing along right and you can continuously pump capital into something but if the model is wrong it's just going to drain and it's going to go to inefficient systems and in the end maybe do some help but but a very small percentage of the capacity of what it could do then the advice would be to entrepreneurs don't fret about the infrastructure just nail your business models right and because the switching cost might not be as high as you think that's right we're in the old days when we grew up yeah you made a bad technology decision you're out of business yeah but the first advice that I give my clients is to stomp this is this business that's too much formal in it yeah right if you're missing out so no just because everybody's out there Nico you should be doing an SEO right yeah 46% of I SEOs have already failed already failed start with the business gather this in the counties down right so free cash flow unique value proposition Prada market fit what sits under business think about the token model right the token model has to go in handy now with your business model and revenue model and once you figure out that business and took the models now it's time to think about compliance I'm gonna raise money in the US and abroad I've decided to go to security choking hypothetical instance absolute what do I do is there for you an incentive mechanism or is a fundraising mechanism or both who's gonna be my user who's gonna use this token right there aren't gonna be moms dads hospitals they was my target and then how they're gonna use it and are they gonna hold it I'm gonna sell it are they gonna trade it so all these different things define that oh c'mon once you get your token actually authenticated realized everything's transparent and it gets on that secondary market it's better to use that to invest in anything you need investment get everybody incentivized around your token all your employees all your vendors everybody incentivize around that token it's a thousand percent more powerful than a dollar so the dollar doesn't go up in value in your token your token can go up and down and as soon as you find just one spark it blows up everybody boats rise equal it's pasta Sara Lee the time to crack open the champagne you still have to demonstrate product market fit you have to help build a market in our particular case so there's a lot of hard work launch it's a start line it's just like it's only a step along the whole process you know what made people get it you showed them the money yeah you showed them the money sometimes people don't you can explain these concepts that are world-changing super high level or whatever people were not actually gonna get it until it's useful to them average business people and senior business people who have typically been shut off to the idea of blockchain are now seeing this as very real and here to stay momentum is just beginning it's gonna be amazing what these guys come up with that's one of the things I love about doing this thing right I'm an old guy and I get to hang around these smart young people makes me feel young again yeah but the other thing that we have and I think you should share it as well as we have to offer to these young guys experience thing we just invented a new category in the ico category an advisor token and a you have to have the stomach for it and I think you just have to be as educated and as you can what government entity can resist for the long term something that's actually trying to provide a better and better and better financial infrastructure you should be able to participate in many different nations who have many different economies that are all really cooperating interdependently to create the best possible life for all human good one dollar will not change your life but if you change your habits you'll change your financial destiny and so my philosophy is get it to a dollar so that every single person can participate and once you start to learn good habits around money and wealth the rest it's a formula like it's a flywheel instead the world will become a better place we'll have better companies positive impact is not counter to profit they go hand in hand the Puerto Rico movement it's a movement while Czech entrepreneurs capital investors the pioneers in the blockchain decentralized Internet are all here this is like the Silicon Valley of the crypto right I think they're calling it crypto island yes TV show we should be honest like it's not lost its crypto island exclusive coverage for Puerto Rico's - Cuba I'm John Ferrari getting the signal here out of all the noise in the market this is what we do this is the cube mission great strip we start week Point agenda open content community thanks for watching [Music]

>>The cute presents on the ground. Here's your host, John furrier. >>Hello, I'm John foray with Silicon angle media, the cube, and we are here for an Inn at the Ritz Carlton in San Francisco for the special exclusive press event with Andy Jassy. And the special announcement was Pat Gelsinger, CEO of VMware announcing what, in my opinion is probably the biggest, most historic announcement in the industry. And certainly for VMware as the future migration to the cloud migration of the next generation infrastructure continues. Uh, and so big, significant as exclusive. I'm having a one-on-one interview with Andy and Pat shortly, but I had a chance to grab the chief architect of this deal. One of the many that the lead EVP and general manager. So I don't think it's an, a Ragu Ragu Ragu around welcome, uh, to see, great to see you. Thanks for spending the time to see you. Thanks. So Ragu you're, you're an old timer VMware, but now you're also architecting. What looks to be the bridge to the future for VMware? Um, this relationship with AWS, Amazon web services puts VMware in the cloud the best, the best, most functional best, biggest public cloud, and most robust capabilities immediately in Amazon available mid 2017. But this is a path instantly for all of the and where customers, um, what's when did this all start and what motivated you to architect this? >>Yeah, I mean, um, as you recall, the past VMware, we announced our cross-cloud architecture and the idea that customers, enterprise customers want choice with control, right? The legwork for that was done, um, over a year ago, right? When we internally, we finalized our strategy to enable our platform to run in multiple different, uh, clouds, such as our weekend partner network and IBM and now AWS. So that's when we all started around this. But the key idea here is for customers that are increasingly putting a variety of workloads from the, in their private cloud, in their public cloud, you want to have a consistent way of running and managing and securing and operating these applications. And as you just pointed out, one of the biggest cloud providers for our customer is AWS. And so this was a natural partnership from that point of view. >>So one of my favorite tweets out there for us from, you know, obviously Dave Alante co-host of the cube, he said, um, please allow me to translate. He was translating from a customer, went help our customer impact one. You've squeezed the blood from the data center stone with virtualization. You've done all you can. This is my customer translation, too. You have, um, a legacy amount of VMware processes and procedures and software, AKA VMware, three year Jones, and for the agility and innovation of AWS, come on in the water's nice and warm. So essentially it's kind of tongue in cheek, but you know, the data center is, has been maxed out. So data center consolidation, certainly people don't want to be in the data center business, but they want the benefits of a data center with the cloud. You guys are not providing that. What is the impact to customers because they are jonesing for innovation that Jones and from microservices, they're jonesing for cloud native, that Jones and for the, some of the goodness that Amazon has shown works, but yet it's a huge migration nightmare and they want a SAS business model. They want a SAS company. This is the digital transformation. What is the impact of customers? >>Yeah, I mean, it's ultimately comes down to simplicity and agility, right? And the, there is two big transformations going on. One is there's a huge data center transformation going on, driven by simplicity, driven by software. And that is the whole software defined data center while you're absolutely right. Many of our customers have maxed out the server virtualization, but their network is inefficient and the storage is efficient, et cetera, et cetera. So the software defined data centers, one of the moves they're making now at the same time, like you said, they're jonesing for all these advanced services, uh, for their new applications. Uh, they want some way to bridge both environments. And that's where this service, uh, hits the sweet spot. If you will, right now, without replatforming, without changing your operational models, like your quote that you, the tweet that you quoted without changing any of our operational models, you can have an agile on demand of VMware data center. And what's running in that VMware data center is the full software defined data center stack, all of the great security and manageability capabilities of networking, of NSX, of virtual San, of vSphere at the same time, connecting to all these great services that AWS provides. It's really a best of both worlds story. >>So look from a customer standpoint, if I get this right, there's a big breathing out. Oh, finally, he got there, right? It's I don't have to do all this heavy lifting to move my VMware to the cloud. One, two in the demo that we show in V center. So specifically under the hood, what is running in the full stack? I mentioned V motion. I heard V motion mentioned. Is it all, all of the entire VMware stack running on the cloud? >>Yes. So the stack that's powering that, that you saw in the demo is a virtual sun watch lies in the storage underneath, um, NSX, providing the network virtualization. And of course, vSphere that's the core infrastructure stack. And in order to manage an ESX nodes for the hypervisor in order to manage ESX and control these resource pools and so on, you have the vSphere functionality built into V-Center. And that was a key requirement. Design requirement for this service is customers are very, very familiar with V-Center. They've been operating it for 15 years and have that as a huge ecosystem of tools, operational tools, backup dual security tools, you name it built around V-Center and all of that had to work seamlessly in the cloud. And that's why we sent her is so important. >>And certainly got a lot helps with the storage side of it. You mentioned networking, how does the Amazon relationship and the co-located if you want cold locating, but running managed in AWS help on the networking because in the demo, it was very cool besides the pay by credit card and pay by VMware account was the fact that you can pick a global footprint instantly, which means from what I took away, was it, I can be up and running in a geography with networking in the cloud, but not just Amazon's networking, you're networking. Absolutely. That's that accurate? You got it. Right. >>So, um, Amazon obviously has got a global network fabric that powers their services. And so you can stand up these clusters of the STDC hardware, if you will, on any one of their data centers in the fullness of time, maybe not on day one. And NSX already has the capability to connect across STDC clusters across different data centers. So now we can stretch a logical network, um, and have literally applications in the Portland data center of AWS and, uh, applications at the Virginia data center of AWS and applications in their London data center, all tied together, biological network. >>All right. So I'm going to ask some hard questions down so densely, by the way. So here's the hard question. So here's the hard question. So Paul Moritz and Joe Tucci no longer involved Maritz, retired, Tucci, retired, he wanted to own the enterprise. The private cloud was the original thing. Amazon was just kind of getting strong lift at that time. The world has gone all hybrids. There's a lot of hybrid cloud going around. So the world is different from them. So I want to get your comments on where the private cloud has came from to this reality and to comment to the naysayers out that I've heard some tweets like, Oh, rip VM-ware, they rang the bell, they tapped out, they capitulated talk about those two dynamics, private cloud, that vision, uh, from Mauritson Gelsey, uh, to cheek. And how do you answer the critics to say, Oh, they capitulated VMware's toast. >>Yeah. So, um, what the, uh, I would say are significantly incorrect views of how you look at this. The private cloud is still very strong, right? And you've got customers deploying the private cloud, literally every large enterprise that we talked to and we've got the leading share when it comes to private cloud deployments. And along with pivotal cloud Foundry, we can offer not just the infrastructure services of a private cloud, but also the application platform services of the private cloud or the private cloud exists for lots of different reasons can be regular. >>It's not done. The cloud is not going away anytime soon. What >>This allows customers to do is really get a hybrid that combines the best of a VMware environment or the best of an AWS. And that's really, what's unique. And what is in the service is the full VMware stack. And you've got to remember that 95% of our customers are still largely on vSphere. They've just started deploying and adopting NSX and virtual sand by adopting this service, they automatically get upgraded to the full power of network virtualization and storage virtualization. >>Of course. So you see this as an expansion of the business model, not anything I see complete expansion of the business model, that's going to come from SAS apps or, yep. >>So the whole service is a mad at service. So customers are not have to learn how to sort of rearchitect their data center. They can just get a rearchitected data center on demand wherever they want, or they can build the rearchitecture data center by themselves and connect it all up. Right. >>Okay. Final question. I'll see. Um, I'd love to chat more about what it's like cut this deal with Amazon fan of both of you guys. Um, actually we use Amazon work customer. Um, talk about your relationship with other clauses comes up with the press. People who are, you know, not as deep on, on the, on the industry they talk about IBM, Oh, it was IBM and Azure Azure. We can see that as competitive thing. I don't want to want to go there because we're going to do a whole blog post on the impact of Microsoft, which I think is the big competitor for us, for customers. But you guys have an open cloud strategy. And I think the IBM thing is let them compete. Now they have soft layer. Now some would argue Amazon, Andy talked about the relationship with them, the soft layer and how they compete. But ultimately IBM is deep with you guys. They're adding 20,000 developers. I think million people, which 4 million people trained highly integrated with VMware. So your strategy with them is the same, right? But primarily as a service operating on Amazon, are you guys going to be operating on soft layer and blue mix as well in a similar fashion? >>So, um, the service that we announced, uh, last month with IBM is a service that IBM is managing and operating, right? And we have worked very closely with them, the VMware cloud foundation, >>Just their business model. They're going to operate that you guys will operate the AWS cloud. >>We operate the VMware and IBM operates that service, but we go to market together with IBM on their service, right. And we work very closely with them. >>So this is a choice thing for you guys, as nothing to do with picking a better part, I'll even use the word primary. Okay. >>I mean, like Pat talked about, uh, the QA session, we've had lots of customers that are customers of AWS and for them, the first choice might be the VMware cloud on AWS. We equally got a lot of customers that are customers of IBM and for them and software and for them, uh, the choice would be running their on the IBM cloud with the cloud. >>Thanks for taking the time to speak with us. I'll give you the final word, not on the business side, cause it's pretty obvious. It's a good win-win on the business side. What is the coolest technical under the hood thing about this deal that people should know about? >>I think what AWS has engineered to build a service and how we are taking advantage of it for Delaware and elastic data centers across the globe is going to be very, very cool. Once you can talk more about it in a public domain >>Raku he's he had a, vice-president great to see you, a chief architect of this deal among many other things at VM-ware well-known within the industry legend in the, uh, VMware community. Thanks for joining us here on the non live Q, but we're here in San Francisco for the exclusive announcement of the AWS VMware relationship partnership integration. A lot of glad of goodness there. I'm John Ferrari. Thanks for watching.

>>From Las Vegas, it's the cube cuddle EMC world 2016, brought to you by EMC. Now your host, John furrier. Welcome >>Back everyone. We are here, live in Las Vegas for EMC world 2012. I'm John Ferrari, the founder of Silicon angle and host of the cube. And we are extracting the signal from noise. And one of our traditions at EMC world is to do a conversation and panel discussion around women of the world with Stella Lowe, who is VP of global communications for EMC and Susan Carter, Nico, who's the founder and CEO of authentic leadership. Stella. Every year we do this as one of my favorite things. As we wrap up EMC world, soon, it may be Dell world or Dell EMC, whatever that kind of turns into. Yeah, I wish you can't comment. Cause your communications is, is to talk about kind of the human side of what's going on. And the theme for EMC was modernization of enterprise, you know, infrastructure, speed, performance, scalability. And you've taken this theme this year with women of the world to modernizing your career in an era of change. And tell me about what that was this year. >>Yeah, absolutely. John. So yeah, we were in this, um, tech industry is changing all the time, but right now we're in this kind of unprecedented change. Um, you, this, this is gonna be a lot of consolidations is the thinking over the next two years, a lot of people find a lot of companies finding their dance partners. In some ways we've already found our dance partner, which is Dell, but there's gonna be a lot of that going on. And um, and there's definitely a lot of change happening here at EMC. So we wanted to make sure that we were focusing on how to own modernize and direct your career within this sea of tremendous James. >>So Susan, I want to get your take on this because we are living as the theme of the show is, is a transformation happening, which means there are certainly change and there's big bets being made in the business that requires people process and technology transformation. People is a big part of it. And people have to be bold. There's some gambling, there's some bets and with that will come maybe some missteps or some failures and how you can overcome that will define ultimately your success to take maybe little failures, not big failures, but like, but this is part of the evolution of innovation. How does that affect people, specifically women, as they're in this now converge workforce, male, men and women coming together. What's your thoughts on this? >>Well, men and women alike change is hard, right? So as industries converge as merchants and acquisitions happen, you know, the industry itself is in such a massive transformation mode. It's requiring people of all of all levels and in all fields, but particularly in the world of technology to completely redefine their skillsets, their relevance, the way they're going to actually help sort of step into this new era of digital technology. So it's causing, you know, ripple effects of reinvention and change all over the place. You know, we all to change as human beings at a very personal level. What does it mean for me? And so a big part of what we discussed today at the conference was just, how do you sort of lean into that change and how can you begin to look at your own potential and your own skillsets from, with a different lens? >>You know, um, we tend to box ourselves in as far as our potential goes and we say, okay, I've been in this functional area for all of my career. So I guess my opportunities sit squarely in this box. And we talked a lot about the value of sort of reinventing and taking a hard look at our transferable skill sets. So the attributes that we have as, as human beings that could let be leveraged into other roles or expanded roles and the skill sets that have made us so successful in what we're doing today. So how might we bust that open and find new opportunities in this world of change? And it's pretty important that we do it now. I mean, there was a, um, it was announced just a few days ago that in 2015, there were 359 new CEOs announced, uh, in the top two and a half thousand companies around the world. Only 10 were women, John 10, 10 out of 359. It's shocking. So if we're going to change, reverse that trend, we've got to start reversing that rate from that >>Consistent though across all industry, even venture capital, which has really highlighted in Silicon Valley where we live and that's obvious a male dominate, but now there's no women VCs. Now cowboy ventures is a bunch of them that are coming together and Hey, we can play ball each other. >>What does it surprise you that there's less women learning about tech now learning, you know, in tech education now than there was in the eighties? I mean, so, so we've already got to grapple with this and, and, and change the course of this. And, and women have got to start taking responsibility for their own careers and their own direction. >>What are some of the stories that you've heard this week at, at your event, as you guys talk with each other, what are some of the common patterns and stories that you're hearing? >>So we're certainly hearing from the women in the room, but they see that the impending change as exciting as an opportunity, but they're also, there's also some things anxiety around that change. There's definitely fear there and that's what we're seeing. Um, you know, and, and, um, you know, they need, people need to take that fair and use it as a catalyst for positive things. Right, right. I mean, 10 people tend to shut down when they're in environments of fear. And one of the things that we talked a great deal about was how do you sort of turn that around and, um, use that as a catalyst to take stock in not only sort of what your inherent capabilities are, but your vision for your life and the values that you hold dear and say, okay. So if my job serves my life, then what is my end game and what steps in choices can I make, you know, putting myself back in the driver's seat versus letting this this change. That's sort of at the, both of my macro level and the micro level, like sweet meander and, and, and create a, of a victim mentality. We talked a lot about sort of that empowerment and the accountability to sort of take charge of your own desks. >>It's interesting. You mentioned leaned in earlier. So Sheryl Sandberg's in my community in Palo Alto, Facebook friend, you know, where I'm involved a lot with some Facebook stuff. And I put, I've been following her lean in and I want to bring this up is you mentioned the word fearless. Um, you know, I've been called fearless, fearless. That's a guy thing, right. Guys can be fearless. Is it okay for women to be fearless and is lean in a fearless kind of vibes? It's not so much, I don't wanna get semantically tied on views, but this brings up a point that people get stuck on the semantics, but that kind of is a bias thing. Be more fearless and you'll get ahead versus lean in is a guess could be construed as a female version of fearless, the words matter. But at the same day, how does a woman become fearless? It doesn't matter. Yeah. >>So the other speaker that we had on the panel today, we were very lucky also to have Rashma, um, uh Rashma Sudani uh, and she, she, um, has the company, uh, founded the company, girls who code, and she says that women were brought up to be, uh, perfect. Whereas boys were brought up to be brave. So it's okay for a boy to climb a tree and go to the top. But with girls were like, no, no, sit in the chair, look pretty, be nice, you know, but be perfect. Um, and so women are very scared to go into areas that don't know because they're worried about making mistakes. And what we were trying to get over today was imperfection is okay, it's okay to make mistakes. It's okay to, you know, and you've got to get kind of get over that fear to do that. >>And it's the attributes Susan. So a woman and a man, they have different attributes. So maybe fearless my, Oh, he's feeling at the top of the tree, but every attribute in a diverse environment can contribute to a common outcome that makes it better. I mean, that's kind of the theme that I'm seeing. >>It's true. Um, fearlessness in you say words matter, uh, concept is kind of the same. We talked a lot about self con self-confidence and the, the contrast in the sexes, uh, when it comes to self-confidence and then so many women seem to sort of stop short of having that self confidence to step out and you say, be fearless to take risk to just sort of seize that moment and say, you know, what, if it doesn't work out, I can choose again. There's we just seem to stop short of being able to do that, where guys seem to be a little bit more comfortable. And part of it is the way we're raised, you know, women to be perfect. And we tend to be very, very quiet about those failures. And so it kind of sends that message. Like, I really need to set a stay away from those arenas where I just, I might not be a stunning success. >>So there was some discussion around men versus women in the imposter syndrome, which tends to afflict a lot of women, particularly women in business, where we kind of doubt our own worth as, as a leader, as a professional. And there's this fear that, you know, at some point we're going to be found out that we're really not as good as others around us think we are. And that drives a certain kind of behavior in the workplace. So, you know, um, workaholism, perfectionism, procrastination, just so afraid to make a mistake and be found out. So, you know, that seems to be, um, more characteristic of females than males. Um, there are just a lot of, there's a lot of complexity around >>The guys that are faking it, that good will be found out. It may be, maybe there's a thing there, but modernizing your career though. That's the theme? What is the pattern that, what does that mean? I mean, how, how do you talk to that? Because everyone wants, I mean, who doesn't want to be modern, right. And we're in the modern era, we want to be happy. We want to be cool when advance, okay. Advancement means you're climbing the ladder or you're, you're trying something new, which means you will fall and stumble. We all stumble when we learn is that part of the modernization is dealing with the environment and the change and the failure. >>Yeah, it is. In fact, um, the first thing that we talked about was the need to be incredibly strategic in this environment, we're business people. And when facing any business challenge, you tend to do scenario planning, right? And you say, well, if this happens, here's my strategy. Uh, if that happens, here's my strategy. So you say worst case, best case likely case. And, and when you start to develop strategies around how you're going to navigate those things, it gives you additional power and confidence to sort of move forward in your redefinition. So that's sort of that the first step in modernizing your career, we also talked a bit a bit ago about, um, understanding where you might have some self limiting beliefs about where you might play, you know, the, what arena, where you might, you might sit and so starting to sort of broaden your horizons. >>Um, yeah, definitely. I mean, uh, women will look at a job spec, um, and have a completely different perspective from men. So men will look at it and they'll say, well, I can do about 38% of this. So I'm going to go for this job. Um, women will look at it unless they can do 85% of it, or they've done that they have experienced in 85% of it. They won't even go for the job. So we have to start to really broaden our view of the types of jobs we can go for the types of opportunities we can go for and start to think more, well, much more openly. So be >>More aggressive on the job. Applicants was one was >>One. Yeah. Broaden your horizons. Think about this, the transferable skill sets that you have, that you can take into other areas. And, and don't be, don't be fair fearful of things that you haven't done before. >>So I had a public failure startup that was very funded and then the public failure and it's traumatizing. And I dealt with that and you know, this whole failure is rewarded in Silicon Valley. That's BS, in my opinion, people tolerate failure, but they loved the comeback. That's part of learning is coming back. And, but, you know, and so I had to deal with that until I was in my own way as a guy, but there's a post in Silicon Valley going around today, around a woman who failed. And she didn't know whether she should be vulnerable or just be that what'd you call it the imposter syndrome, fake it till you make it. And she was saying, no, I want to be vulnerable. Because what she found is by being vulnerable, people were helping her. So that brings up the concept of vulnerability, male, female, and two in the modern world. We have social networks now. So lean is a great example of some gravity around peer groups. Can you guys talk about that? Does that come up at all on your radar, in terms of the dynamic there around men versus women being vulnerable versus being strong and also the notion of networks and how that could be? >>Well, I think vulnerability is often tied to shame and that fear of shame causes people to hold back in sharing their real stories. You said something very important and that's that people care about what you've learned along the way. They don't necessarily care about what, you know, they care about what you've learned. Most people are comfortable talking about what they've learned when they're on the other side of that. So it's not in the, in the middle of that trail here, when you are just feeling horrible, you're feeling horrible. You're feeling like a failure. You're feeling embarrassed, you're feeling shame. So the ability to kind of step up to that is it's a tall order. Now you talked about social networks in this environment of social media. Authenticity is so important, right? So it's that happy balance. If you're not all that comfortable with being completely naked in that vulnerability, maybe there's a happy medium where you can share some of the challenges and things that you've been facing while not necessarily going all the way down to the, you know, to the bare nub of it. Um, I think we're right. >>So authenticity will track the right alchemy of, of help or it relationship as a way to signal to people. I mean, I guess, and that's just me. I love this concept. I mean, I feel like I should get you guys with my life coach. This is my lifestyle. So this is the next one. So, okay. So that's cool. I love that theme. I love this topic because that really helps you get through to the other side and gain to the other side. You're on the comeback. That's a learning what you've learned and applying what you've learned is a growth mindset. Now there's a lot of women, my age, I'm 50 that I've grown through the ranks and they get up to the top. And you mentioned the numbers, aren't that significant on the seat level of women it's lonely yet. They're being asked to be mentors down to the new generation of ladies coming up or women. And, but they're lonely at the top. How do they deal with that? As you're moving closer to the top, have they talked about that >>Only at the top? And I would like still, I was a senior executive at a big company and found that loneliness to be quite palpable. Right? Um, it's part of the choice you make to be in that arena, stepping up to that position of leadership. It often means that you're distancing yourself. You're being more, you're more concerned with being respected than you are being liked. And you know, there there's a, there's a new game, right? New parameters around your relationships like CEO's, um, who find solace in their peer relationships. I think that same goes for women. You know, you, you need to actively cultivate your formal and informal networks and they may be with, with, uh, peers outside of your company, outside of your functional area. Those relationships though are so important because you can become isolated and insulated. Um, people may not always come to you with the, with the truth. >>And so, you know, making sure that you keep those lines of communication and mutual support open is really pivotal. Now you mentioned mentorship. Um, I think it is incumbent on senior women to reach down and find opportunities to mentor other women and sponsor other women. You know, there's mentorship and sponsorship, and both are crucial in terms of sort of direct feedback and developmental advice on the mentorship side, but then sponsorship literally actively opening doors for other women and, and reaching a hand and helping them come up to because that's often where we find a gap. People think I had to claw my way up. It was a lot of work. So I'm just going to sort of protect myself and hang out and let everybody else kind of go on their own journey. We talked a lot today about the need to sort of reach down and help other women. >>So the takeaway there is develop your formal informal networks. That's a foundational really critical linchpin to the whole success. Um, what about now, as we look at the progression going forward, um, the skill development, you mentioned the job applications, a lot of these jobs that are going to come with the next industrial revolution as Michael Dell was pointing out, don't even exist today. So there might be an opportunity here as we look to the future. Did that come up at all on the radar of your sessions? >>Well, we talked, I think it comes back to really transferable skill sets. You need to take a look at what, what you do and who you are, bring it up a level because I got to tell you if you can manage well in ambiguity, if you can lead and motivate people. I mean, if you, there, there are certain attributes that, that pick the job. Yeah. If you have those, if you have those attributes and those skills, you can learn a discipline, but those inherent leadership skills are going to pay off the big time as this industry continues to redefine. And as you say, jobs that we don't even know exist yet, suddenly come onto the table. >>What surprises you the most in this, in the conversation around modernization, as you talk with folks out there, what's a trend that surprised you that you kind of knew about, but, Oh my God, this is really more acute or more explosive than in a good way, or in bad way. Anything you can share, like the literally like, wow, this is really more pressing than I thought, or this is actually more amazing than I thought. >>Yeah. Um, one of the things the Rushman talked about is women supporting other women. I mean, sometimes we are the worst critics of other women and, uh, you know, female bosses can be harder on female employees and so on. And I think there's got to be that kind of sisterhood, um, uh, around, uh, all of us have been bring women up as, as, um, Susan has said, support other women, uh, make sure that you are their back and they are watching yours. And, uh, it will help with the loneliness factor, but it also helps to, to bring women forward. And I think that's always a surprise to me that women don't want to do that. And they, and they don't want to get involved in that. We should be paying that back and paying it. >>So is there anything that surprised you looking back at, and then the constitution here? >>I think I would echo what Stella said. It's, um, it's important to understand the role you may be playing in the plight that faces you. So, you know, we talk about women sometimes being their own worst enemy and trying to, to again, modernize and redefine what that relationship looks like and what that success looks like and how accountable we each are for, you know, moving forward and pushing the envelope. >>Okay. Final question. If you guys could each answer, this would be great. What advice would you give the people watching here live, and then on demand things that they could do to modernize their career in this change, uh, advice that you can surface and share insight around their opportunity, things that they could do differently or new, or, >>Yeah, I'll let Susan have the last word on this. Cause you'll have some fabulous advice, but you know, one thing I would say is, is, uh, be comfortable in your imperfection. You don't have to be perfect. You'd go for it, widen your spear of opportunities and, uh, you know, Matt Mo uh, Charlotte, your way and, and dream bigger and he dreamed bigger. You might, you know, you'll get somewhere bigger. Very good. Um, I would say first and foremost, one of the best things that you can do is challenge some of the beliefs that you might hold about what your potential next steps or career path might be, um, get clear on what your end game is for your life and what your values are, because that becomes a very important lens through which to view future opportunity, get, get really clear that you can always choose. >>Again. I think this fear of making a mistake and that you talked about fearlessness, um, you know, I think people tend to, to limit their opportunities because they think, wow, if I make this choice and it's mistake, then I'm done, but you can just turn around and make a new choice and begin again. And there are limitless choices that you can make. So a lot of this I find is mindset related. You know, we're heading into a, we are in a highly turbulent time. It's going to continue. We need to be agile in our thinking part of that is getting grounded in who we are and what are our potential could be getting clear on what we want because our jobs serve our life, not the, not the other way around and really sort of getting into the driver's seat versus letting whatever the change is, whether it's up here, the industry consolidation level, or whether it's down in, whether we're in the middle of a merger, or we've just gotten a new boss that we don't particularly click with, we can default to a victim mentality. So part of this is just saying, you know what, I am going to pick this thing up and I am going to manage to the change myself >>And we are living in a world where there's great opportunities, women of the world. Great segment. Thank you so much, Stella. We thank you so much, Susan, really great to have you guys sharing your insight here on the cube. Um, congratulations again, always my favorite conversation. I learned a lot, um, and I love, I feel like I'm learning so much and this is a world of diversity and it's great. And the outcome is diversity is fantastic. And I think that's what everyone's seeing. So congratulations on the great work. This is the queue here at EMC world 2016. I'm John for a, you're watching the cube >>Looking back at the history of it.

>>The cube at IBM. Impact 2014 is brought to you by headline sponsor. IBM. Here are your hosts, John furrier and Paul Gillin. Okay, welcome back. Everyone live in Las Vegas at IBM impact. This is the cube, our flagship program. We go out to the events, instruct us to live in the noise. I'm John Ferrari, the founder of SiliconANGLE Joe, my close Paul Gillen. And our next special guest is great bushes as a legend in the software development community. And then she went to st this school in Santa Barbara. My son goes there, he's a freshman, but there's a whole nother conversation. Um, welcome to the cube. Thank you. Uh, one of the things we really exciting about when we get all the IBM guys get the messaging out, you know, the IBM talk, but the groundbreaking work around, um, computer software where hardware is now exploding and capability, big data's instrumentation of data. >>Um, take us to a conversation around cognitive computing, the future of humanity, society, the societal changes that are happening. There's a huge, uh, intersection between computer science and social science. Something that's our tagline for Silicon angle. And so we are passionate about. So I want to, I just want to get your take on that and, and tell about some of the work you're doing at IBM. Um, what does all this, where's all this leading to? Where is this unlimited compute capacity, the mainframe in the cloud, big data instrumentation, indexing, human thought, um, fit, Fitbit's wearable computers, um, the sensors, internet of things. This all taking us in the direction. What's your vision? There are three things that I think are inevitable and they're irreversible, that have unintended consequences, consequences that, you know, we can't, we have to attend to and they will be in our face eventually. >>The first of these is the growth of computational power in ways we've only begun to see. The second is the development of systems that never forget with storage beyond even our expectations now. And the third is a pervasive connectivity such that we see the foundations for not just millions of devices, but billions upon billions of devices. Those three trends appear to be where technology is heading. And yet if you follow those trends out, one has to ask. The question is you begin to, what are the implications for us as humans? Um, I think that the net of those is an interesting question indeed to put in a personal blog. My wife and I are developing a documentary or the computer history with the computer history museum for public television on that very topic, looking at how computing intersects with the human experience. So we're seeing those changes in every aspect of it too, that I'll dwell upon here, which I think are germane to this particular conference are some of the ethical and moral implications. >>And second, what the implications are for cognitive systems. On the latter case we saw on the news, I guess it was today or yesterday, there's a foundation led by the Gates foundation. It's been looking at collecting data for kids in various schools. A number of States set up for it. But as they begin to realize what the implications of aggregating that information were for the privacy of that child, the parents became, became cognizant of the fact that, wow, we're disclosing things for which there can be identification of the kid in ways that maybe we wouldn't want to do that. So I think the explosion of big data and explosion of computational power has a lot of us as a society to begin asking those questions, what are the limits of ownership and the rights of that kind of information. And that's a dialogue that will continue on in the cognitive space. >>It kind of follows on because one of the problems of big data, and it's not just you know, big, big data, but like you see in at CERN and the like, but also these problems of aggregation of data, there are, there are such an accumulation information at such a speed in ways that an individual human cannot begin to reason about it in reasonable ways. Thus was born. What we did with Watson a few years ago, Watson jeopardy. I think the most important thing that the Watson jeopardy experience led us to realize is that theory is an architectural framework upon which we can do many interesting reasoning things. And now that Watson has moved from research into the Watson group, we're seeing that expand out in so many domains. So the journey is really just beginning as we take what we can know to do in reason with automated systems and apply it to these large data systems. >>It's going to be a conversation we're going to have for a few generations. You were beginning to see, I mean computing has moved beyond the, the, the role of automate or of automating rote manual tasks. We're seeing, uh, it's been, uh, I've seen forecast of these. Most of the jobs that will be automated out of existence in the next 20 years will be, will be, uh, knowledge jobs and uh, even one journalism professor of forecasting, the 80% of journalism jobs will go away and be replaced by computer, uh, over the next couple of decades. Is this something for people to fear? I'm not certain fear will do us any good, especially if the change like that is inevitable. Fear doesn't help. But I think that what will help is an understanding as to where those kinds of software systems will impact various jobs and how we as individuals should relate to them. >>We as a society, we as individuals in many ways are slowly surrendering ourselves to computing technology. And what describe is one particular domain for that. There's been tremendous debate in the economic and business community as to whether or not computing has impacted the jobs market. I'm not an economist, I'm a computer scientist, but I can certainly say from my input inside perspective, I see that transformational shift and I see that what we're doing is radically going to change the job market. There was, you know, if you'd go back to the Victorian age where people were, were looking for a future in which they had more leisure time because we'd have these devices to give us, you know, free us up for the mundane. We're there. And yet the reality is that we now have so many things that required our time before. It means yours in a way, not enough work to go around. >>And that's a very different shift than I think what anyone anticipated back to the beginnings of the industrial age. We're coming to grips with that. Therefore, I say this, don't fear it, but begin to understand those areas where we as humans provide unique value that the automated systems never will. And then ask ourselves the question, where can we as individuals continue to add that creativity and value because there and then we can view these machines as our companions in that journey. Great. You want to, I want to ask you about, um, the role, I mean the humans is great message. I mean that's the, they're driving the car here, but I want to talk about something around the humanization piece. You mentioned, um, there's a lot of conversations around computer science does a discipline which, um, the old generation when a hundred computer science school was, it was code architecture. >>But now computer science is literally mainstreams. There's general interest, hence why we built this cube operation to share signal from the noise around computer science. So there's also been a discussion around women in tech tolerance and different opinions and views, freedom of speech, if you will, and sensors if everything's measured, politically correctness. All of this is now kind of being fully transparent, so, so let's say the women in tech issue and also kids growing up who have an affinity towards computer science but may not know us. I want to ask you the question. With all that kind of as backdrop, computer science as a discipline, how is it going to evolve in this space? What are some of those things for the future generation? For the, my son who's in sixth grade, my son's a freshman in college and then in between. Is it just traditional sciences? >>What are some of the things that you see and it's not just so much coding and running Java or objective C? I wish you'd asked me some questions about some really deep topics. I mean, gosh, these are, these are, I'm sorry. It's about the kids. In the early days of the telephone, phone, telephones were a very special thing. Not everybody had them and it was predicted that as the telephone networks grew, we were going to need to have many, many more telephone operators. What happened is that we all became, so the very nature of telephony changed so that now I as an individual have the power to reach out and do the connection that had to be done by a human. A similar phenomenon I think is happening in computing that it is moved itself into the interstitial spaces of our world such that it's no longer a special thing out there. We used to speak of the programming priesthood in the 60s where I lost my thing here. Hang on. >>Here we go. I think we're good. We're good. I'm a software guy. I don't do hardware so my body rejects hardware. So we're moving in a place where computing very much is, is part of the interstitial spaces of our world. This has led to where I think the generation after us, cause our, our median age is, let me check. It's probably above 20, just guessing here. Uh, a seven. I think you're still seven. Uh, we're moving to a stage where the notion of computational thinking becomes an important skill that everyone must have. My wife loves to take pictures of people along the beach, beautiful sunset, whales jumping and the family's sitting there and it did it again. My body's rejecting this device. Clearly I have the wrong shape. i-Ready got it. Yeah. There we go. Uh, taking pictures of families who are seeing all these things and they're, they're very, with their heads in their iPhones and their tablets and they're so wedded to that technology. >>We often see, you know, kids going by and in strollers and they've got an iPad in front of them looking at something. So we have a generation that's growing up, uh, knowing how to swipe and knowing how to use these devices. It's part of their very world. It's, it's difficult for me to relate to that cause I didn't grow up in that kind of environment. But that's the environment after us. So the question I think you're generally asking is what does one need to know to live in that kind of world? And I think it says notions of computational thinking. It's an idea that's come out of uh, the folks at Carnegie Mellon university, which asks the question, what are some of the basic skills we need to know? Well, you need to know some things about what an algorithm is and a little bit behind, you know, behind the screen itself. >>One of the things we're trying to do with the documentary is opening the curtain behind just the windows you say and ask the question, how do these things actually work because some degree of understanding to that will be essential for anyone moving into, into, into life. Um, you talked about women in tech in particular. It is an important question and I think that, uh, I worked with many women side by side in the things that I do. And you know, frankly it saddens me to see the way our educational system in a way back to middle school produces a bias that pushes young women out of this society. So I'm not certain that it's a bias, it's built into computing, but it's a bias built in to culture. It's bias built into our educational system. And that obviously has to change because computing, you know, knows no gender or religious or sexual orientation boundaries. >>It's just part of our society. Now. I do want to, everyone needs to contribute. I'm sorry. I do want to ask you about software development since you're devoted your career to a couple of things about to defining, uh, architectures and disciplines and software development. We're seeing software development now as epitomized by Facebook, perhaps moving to much more of a fail fast mentality. Uh, try it. Put it out there. If it breaks, it's okay. No lives were lost. Uh, pull it back in and we'll try it again. Is this, is there a risk in, in this new approach to software? So many things here are first, is it a new approach? No, it's part of the agile process that we've been talking about for well over a decade, if not 15 years or so. You must remember that it's dangerous to generalize upon a particular development paradigm that's applied in one space that apply to all others. >>With Facebook in general, nobody, no one's life depends upon it. And so there are things that one can do that are simplifying assumptions. If I apply that same technique to the dialysis machine, to the avionics of a triple seven, a simple fly, you know, so one must be careful to generalize those kinds of approaches to every place. It depends upon the domain, depends upon the development culture. Ultimately depends upon the risk profile that would lead you to high ceremony or low ceremony approaches. Do you have greater confidence in the software that you see being developed for mission critical applications today than you did 10 years ago? Absolutely. In fact, I'll tell you a quick story and I to know we need to wind down. I had an elective open heart surgery or a few years ago elective because every male in my family died of an aneurysm. They are an aneurism. >>So I went in and got checked and indeed I had an aneurysm developing as well. So we had, you know, hi my heart ripped open and then dealt with before it would burst on me. I remember laying there in the, in the, uh, in the CT scan machine looking up and saying, this looks familiar. Oh my God, I know the people that wrote the software where this thing and they use the UML and I realized, Oh this is a good thing. Which is your creation. Yes. Yes. So it's a good thing because I felt confidence in the software that was there because I knew it was intentionally engineered. Great. I want to ask you some society questions around it. And computing. I see green as key and data centers take up a lot of space, right? So obviously we want to get to a smarter data center environment. >>And how do you see the role of software? I see with the cognitive all things you talked about helping businesses build a physical plant, if you will. And is it a shared plan is a Terminus, you seeing open power systems here from IBM, you hear him about the open sources source. Um, what, what does that future look like from your standpoint? May I borrow that cup of tea or coffee? I want to use it as a aid. Let's presume, Oh, it's still warm. Let's say that this is some tea and roughly the energy costs to boil water for a cup of tea is roughly equivalent to the energy costs needed to do a single Google search. Now imagine if I multiply that by a few billion times and you can begin to see the energy costs of some of the infrastructure, which for many are largely invisible. >>Some studies suggest that computing is grown to the place releasing the United States. It's consuming about 10% of our electrical energy production. So by no means is it something we can sweep under the rug. Um, you address I think a fundamental question, which is the hidden costs of computing, which believe people are becoming aware of the meaning. Ask the question also. Where can cognitive systems help us in that regard? Um, we live in, in Maui and there's an interesting phenomenon coming on where there are so many people using solar power, putting into the power grid that the electrical grid companies are losing money because we're generating so much power there. And yet you realize if you begin to instrument the way that people are actually using power down to the level of the homes themselves, then power generation companies can start making much more intelligent decisions about day to day, almost minute to minute power production. >>And that's something that black box analytics would help. But also cognitive systems, which are not really black box analytic systems, they're more learn systems, learning systems can then predict what that might mean for the energy production company. So we're seeing even in those places, the potential of using cognitive systems for, for uh, attending to energy costs in that regard. The future is a lot of possibilities. I know you've got to go, we're getting the hook here big time cause you gotta well we really appreciate it. These are important future decisions that are, we're on track to, to help solve and I really appreciate it. Looking for the documentary anytime table on that, uh, sometime before I die. Great. Thanks for coming on the, we really appreciate this. This SiliconANGLE's we'll be right back with our next guest at to nature. I break.