from Gillette Stadium in Foxborough Massachusetts it's the cube covering Vita winter warmer 2019 brought to you by silicon angle media hi I'm Stu minimun and this is the cube at V tug winter warmer 2019 at Gillette Stadium home of the New England Patriots the AFC Championship team going to the Super Bowl third year in a row yet again Randall right yeah paying it's my Los Angeles Rams oh so happy to welcome to the program Randall hunt who's a software engineer with AWS did a keynote this morning I believe it was a hundred AWS features in 50 minutes and felt like you we added a couple more than 100 and went a little over 50 minutes but I think we probably hit 57 minutes that was what the slide counter said but yeah I added a couple of the updates since reinvent you know reinvent is not the end of our innovation we continued releasing new stuff after that all right so our program we're not going to be showing JavaScript we're gonna take a deep breath and slow down a little bit because you know our audience absolutely knows Amazon I tell you this show remember like four years ago first time AWS presented me at Microsoft and AWS here and people heard cloud 101 and I was like come on I could have given this presentation and they were walking around like oh my god I just you know found out that you know who you know horseless carriages and I can do that do them and things like this so you know cloud we've been there for a decade but we're still I believe you know day zero day one is what Amazon always likes this is day one it's always day one so there's no way we can shove the entire reinventing keynote into this discussion so you know want to start first Tulsa rent a little bit about yourself your role what you work on and what customers you talk to sure so I studied physics and then I found out physicists don't really make any money so I became a software engineer and I worked at NASA I worked at SpaceX and worked with this company called MongoDB back then it was called Tianjin and then I am an Amazon I was my second time around in Amazon I'm a software engineer there but I'm also a Technical Evangelist and what that means is I get to travel around the world and make make all of the demos and chat with all of our customers and kind of solicit feedback from them and then kind of try to act as the voice of the customer for the service teams whenever I can get them to listen yeah so probably not going to go into open source versus software licensing of things with you because we want to make sure that we can publish I tell you space is one of those things I love it when I've interviewed people that have been in space I've talked to lots of companies that have our code in space Amazon you have I loved you know robotics and space are hard and we make it easy and I kind of laugh cuz I was an engineer as an undergrad I mean I studied a little bit of you know what it takes to break gravity and understand I always love watching you know all the shows about space and track SpaceX would you work for and things like that give me a break you haven't made space easy well I think space as a whole is getting easier this industry is becoming more approachable one of the things that we launched to reinvent this year was a ground station and this is something where if you have an S band or UHF you know satellite and leo which is low Earth orbit or mio which is medium Earth orbit you can basically down stream that data to one of these ground stations which is you know essentially attach to a region you know in this case us East 2 which is in a like Ohio area and you can go and say hey just stream this data into s3 for me or you know let me access this from my V PC which is pretty gnarly if you think about it you know you have a you have an IP address which is a satellite in space yeah I love I worked on replication technology 15 years ago and it was like okay can the application take the ping off the satellite or you know how do we do this so look we're leveraging satellites a little bit more I understand it's a great tagline to make those useful and more readily just you know it's amazing you think about when you think about my availability zones and regions it's now you know that things aren't just on the Terra Firma well I'm looking forward to the first availability zone on the on the moon or on Mars that that'll be you know when we have utopia planitia 1a that'll be the really cool AZ alright we heard the first blue origins working to Mars no well the latency you know if you have 300,000 and fit three hundred fifty thousand kilometers on average between the Earth and the moon so you know you can go around the earth it would speed of light 7.5 times every second to go to the moon is a fool I hang it's like six seven seconds or so so the latency requirements become a little bit harder there I roll more my wrong pin I have I have the Grace Hopper nanosecond which is the wit which is you know curled up and if you follow the white thing it's how long light would take to travel that and it does it in two nanoseconds so you got me I'm a physics lover and love space as does a lot of our audience so bring it down to the thing one of the things that amazon has done really well is I don't need to be a physics geek to be able to use this technology we're having arguments as to you know if I'm starting out or if I want to restart my career today do I go code or heck you know let me just use lambda and all these wonderful things that Amazon have and I might not even need to know traditional coding I mean when I learned programming you know it was you learned logic and wrote lines of code and then when you went to coding it's pulling pieces and modifying things and in the future it's it seems like serverless goes even further along that spectrum I definitely think there's opportunities for folks who have just you know I don't want to say modest coding abilities but people who were kind of you know industry adjacent scientists you know data scientists folks like that who may not necessarily be software engineers or have the they couldn't recite in Big O notation for mergesort and things like that from scratch you know but they know how to write basic code there's a lot of opportunity now for those developers and I'll call them developers to go and write a lambda function and just have it accomplishing a large portion of their business logic for their whole company I think the you know you have a spectrum of compute options you have you know ec2 on the one side and then you have containers and then as you move towards service you get this this you know spectrum between Fargate and lambda and lambda being the the chief level of abstraction but I I think in a couple cases you can you know even go further than that with things like amplify which is a service that well it's an open source project that we launched and it's also a service that we launched and it takes together a bunch of different AWS services things like app sank and kognito and lambda and it merges them all together with one CLI call you can go and say hey spin up a static site for me like a Hugo static site or something and it'll build the code pipeline build all that stuff for you without you having to you know worry about all the stuff and if developers are starting new today you know I remember when I started I really had to go deep on some of the networking stuff you know I had to learn all these different routers and like how to program them and these like the industry router so you know the million dollar ones and having to rack and stack this stuff and the knowledge is not really needed to operate of large-scale enterprise you know if you if you know a Ralph's table and you you you know V pcs you know you can run you know a multi-billion dollar company if you want yeah it's been interesting to watch too and you know I think the last five years the proliferation of services in AWS got to a point where is like oh my gosh if I wanted to kind of configure a server for my datacenter or configure an equivalent something that I wanted at AWS there was more choices in the public cloud than there was there and people like oh my gosh how do I learn it how do I do this but what we start to see is it's more don't need to do that because what do I want to do if there's an application that I can run where services that will help make it easier for me to do that because the whole it's not let me replicate what I was doing here and do it there but I have to kind of start with a clean sheet of paper and say okay well what what's the goal what data do I need what applications do I need to build and start there I'm curious what you see and how do you help companies through that so that this is a really common scenario so I this is a kind of key point here is enterprises and companies have existed since before the cloud was really around so why do we keep seeing so much uptick why do we keep seeing so many customers moving into the cloud and how do we make it easier for customers to get into the cloud with their existing workloads so along that same spectrum if you have greenfield projects if I were running my own company and I were doing everything I would absolutely start in the cloud and I would build everything as kind of cloud native and if you want to migrate these existing workloads that's part of the one of the things that we launched this year in partnership with VMware is VMware kind of interface for AWS so you can use your native vCenter and vSphere kind of control plane to access EBS to access route 53 and ec2 and all the other kind of underlying stuff that you are interested in run it you can even do RDS on VMware in my environment so that line is definitely blurring between my stuff and my stuff somewhere else and when people are talking about migrating workloads right you know you can take the lowest hanging fruit the most orthogonal piece of your infrastructure and you can say hey let me take this piece as an experimental proof of concept workload and what kind of lift and shift it into the cloud and then let me build the accoutrement the glue and all the other stuff that kind of is associated with that workload cloud native and you'll get additional agility your you know 1:1 ops person can manage this whole suite of things across 19 20 regions of AWS and you know there's kind of global availability and all this kind of good stuff that typically comes with the cloud and in addition to that as you keep moving more and more workloads over it's not like it's a static thing you know you can evolve you can adjust the application you can add new features and you can build new stuff as your move these applications over to the cloud yeah and it's interesting because just the dynamics are changing so much so there's been there's still so much movement to the cloud and then oh well some people I'm pulling stuff back and then you see you have a WS outposts so later 2019 we expect to Amazon to have you know footprint in people's environments and then you know Jeff just to make things even more complicated well the whole edge computing IOT and the like which you know everything from snowball and these pieces so the answer is it gets even more complicated but you know your your AWS I know is trying to help simplify this for use right the board I think I can say anything at all about AWS it's that if a customer is asking us to build something we are gonna do our best to make that customer happy we take customer feedback so incredibly seriously in all of our meetings all of our service team meetings you know we that voice of the customer is very strong and so if people are saying hey I want a AWS in my own datacenter you know that's kind of the genesis of outpost and it's this idea that well we have this control plane we have this hardware let's figure out how we can get it to more customers and customers are saying hey I want into my data center I want to just be able to plug in some fiber and plug in some power and I want it to work and that's the idea right we're gonna when I think of every company that I've watched there's usually something that people will gripe about and what I've been very impressed with Amazon Amazon absolutely listens and moves pretty fast to be able to address things and if you see you know if I'm a competitor of Amazon I'm like oh well you know this is the way that we get in there you know where we think we have an advantage chances are that Amazon is addressing it looking to you know move past it and you know absolutely the Amazon of 2019 is sure not the Amazon of 2018 or you know when you thought about it you know 2015 and it's big challenge for people as to because usually I think of something and you never get a second chance to make a first impression but it changes so much right everything changes that you know I need to revisit it it's like oh well this is the way I do things well Amazon has five different ways you can do that now um you know which one fits you best and I think that's important is different applications gonna have different characteristics that you want to be able to pull in and run in different ways yeah you know honestly I'm a huge fan of service I I think service is where a ton of different workloads are going to move into the future and I just see more and more companies migrating their existing you know everything from elastic Beanstalk applications so like vdq you know VMware images into the service environment and I like seeing that kind of uptick and someone recently I I can't remember who it was someone sent me a screenshot of their console with their ec2 instances in 2010 and maybe it was part of this 10-year challenge thing on Twitter where it's 2009 versus 2019 but they sent me you know they're in one large and the screenshot of the console from back then and they sent me a screenshot of 2019 and Wow things really have changed and you don't really notice it as much when you're using it every day but I can imagine you know their their Ops teams where they haven't logged into the console in three years because you know everything is done kind of in an automated fashion they set up their auto scaling group you know three years ago and then the only time they ever log in is to update to new instance types or something for the cost savings and I get messages on Twitter sometimes from people who are like whoa console got an update this is so cool and then sometimes we we get messages from people where you know we changed the EBS volume snapshotting things we had somebody who had it was like 130,000 EBS snapshots or something and they were like hey you removed my ability for me to select multiple snapshots it what it's like well you have a hundred and thirty thousand so we went in into the UI and we added a little icon that works better for large groups of snapshots you know if there's a customer pain point we will do everything we can to address it all right Randall Hunt really appreciate you sharing with us your experience what's going on with customers and absolutely that 10-year challenge we know things change fast we used to measure in decades I say now it's usually more like you know 18 to 24 months before between everything AWS in 2029 it's gonna be crazy and I can't I can't imagine what its gonna look like then all right well the cube we started broadcasting from in 2010 we appreciate you staying with us through 2019 check out the cube net for all of our programming I'm Stu minimun and thanks so much for watching the key

(electronic music) >> Announcer: From Boston, Massachusetts, it's theCUBE. Covering Cloud Foundry Summit 2018. Brought to you by the Cloud Foundry Foundation. >> I'm Stu Miniman, and this is theCUBE's coverage of Cloud Foundry Summit 2018, here in beautiful Boston, Massachusetts. Happy to welcome to the program first-time guest, Dr. Nic Williams, CEO of Stark and Wayne. Dr. Nic, thanks for joining me >> Thank you very much. I think you must've come to the conference from a different direction than I came. >> I'm a local, and I'm trying to get more people to come to the Boston area. We've been doing theCUBE now for, coming up on our ninth year of doing it, and it's only the third time I've done something in this convention center, so please, more tech shows to this area, Boston, the Hynes Convention Center, and things like that. >> There's plenty of tech people. I was at the Nero Cafe, everyone seemed like they were a tech person. >> Oh no, the Seaport region here is exploding. I've done two interviews today with companies here in Boston or Cambridge. There's a great tech scene. For some reason, you and I were joking, it's like, do we really need another conference in Vegas? I mean really. >> Dr. Nic: Right, no, I like the regional. >> But yeah, the weather here is unseasonably cold. It was snowing and sleeting this morning, which is not the Spring weather. >> It is April, it is mid-April, and it's almost snowing outside. >> Alright, so Dr. Nic, first of all, you get props for the T-shirt. You've got Iron Man and Doctor Doom, and we're saying that there is a connection between the superheroes and Stark and Wayne. >> Right, so Stark and Wayne is founded by two fictional superheroes. The best founders are the fictional ones, they don't go to meetings, they're too busy making, you know, films. >> Yes, but everybody knows that Tony Stark is Iron Man, but nobody's supposed to know that Bruce Wayne was Batman. >> Nic: Right, right. >> But I've heard Stark and Wayne mentioned a number of times by customers here at the conference. So, for our audience that doesn't know, what does Stark and Wayne do, and how are you involved in the Cloud Foundry ecosystem? >> So Stark and Wayne, I first found Bosh, I founded Stark and Wayne. Earlier than that I discovered Bosh, six years ago, when it was first released, became like, I claimed to be the world's first evangelist for Bosh, and still probably the number one evangelist. And so Stark and Wayne came out of that. I was VMWare Pivotal's go-to person for standing things up and then customers grew, and you know. Yeah, people want to know who to go to, and when it comes to running Cloud Foundry, that's us. >> Yeah well, there's always that discussion, right? We've got all these wonderful platforms and these things that go together, but a lot of times there's services and people that help to get those up. Pivotal, just had a great discussion with a Pivotal person, talking about the reason they bought Pivotal Labs originally was like, wow, when people got stuck, that's what Pivotal Labs helps with that whole application development, so you're doing similar things with Bosh? >> Correct. No it's, we have our mental model around what it is to run operations of a platform, where you're running complex software, but you have an end user who expects everything just to work. And they never want to talk to you, and you don't want to talk to them. So it's this new world of IT where they get what they want instantly, that's the platform and it has to keep working. >> Dr Nic, is it an unreasonable thing for people to say that, yeah I want the things to work, and it shouldn't go down, and you know-- >> What is shadow IT? Shadow IT is the rebellion against corporate IT, so we want to bring back, well, we want to bring the wonders of public services to corporate environments. >> Okay, so-- >> That's the Cloud Foundry's story. >> Yeah, so talk to me a little bit about your users. We've watched this ecosystem mature since the early days, you know, things are more mature, but what's working well? What are the challenges? What are some of the prime things that have people calling up your team? >> So our scope, our users, or our customers, are people, they're the GEs and the Fords of the world running either as a service or internally large Cloud Foundry installations. And whilst Cloud Foundry is getting better and better, the security model is better, the upgrades seem to be flawless, it does keep getting more complex. You know, you can't just add container to container networking and it not get more complicated, right? So, yeah, trying to keep up-to-date with not just the core, but even the community of projects going on is part of the novelty, but also it's trying to bring it to customers and be successful. >> Yeah, I go to a number of these shows that are open source and every time you come there, it's like, "Well, here's the main things we're talking about "but here's six other projects that come up." How's that impact some of what you were just talking about? But, maybe elaborate as to how you deal with the pace of change, and those big companies, how are they help integrate those into what they're doing, or do they, you know-- >> So my Twitter is different from your Twitter. So my Twitter is 10 years worth of collecting of people who talk about interesting things, putting in a URL, just referencing an idea they're having, so they tend to be the thought leaders. They might be wrong, or like, let's put Docker into production, like, it doesn't make it wrong, but you've got to be wary of people who are too early. And you just start to peace a picture of what's being built, and you start to know which groups and which individuals are machines, and make great stuff, and you sort of track their work. Like HashiCorp, Mitchell Hashimoto, I knew him before HashiCorp, and he is a monster, and so you tend to track their work. >> So your Twitter and my Twitter might be more alike than you think. >> Nic: No maybe, right. >> I interviewed Armon at the Cube-Con show last year. My Twitter blowing up the show was a bunch of people arguing about whether Serverless was going to eradicate this whole ecosystem. >> Well, we can argue about that if you like, I guess. >> But love, one of the things coming into this show, was, you know, how does the whole Kubernetes discussion fit into Cloud Foundry? We've heard at this show, Microsoft, Google, many others, talking about, look, open source communities, they're going to work together. >> Well Windows is going to track things 'cause they think they need to sell them, right? But then Microsoft has Service Fabric, which they've owned and operated internally for 10 years, and so, I think some really interesting products may be built on top of Service Fabric, because of what it is. Whereas, you know, Kubernetes will run things, Service Fabric may build net new projects. And then Cloud Foundry's a different experience altogether, so some people, it's what problems they experienced, comes to the solution they find, and unless you've tried to run a platform for people, you might not think the solution's a platform. You might think it's Kubernetes, but-- >> Yeah, so one of the things we always look at when we talk about platforms, is what do they get stood up for? How many applications do you get to stand up there? What don't they work for? Maybe you could help give us a little bit of color as to what you see? >> I'm pretty good at jamming anything into Cloud Foundry, so I have a pretty small scope of what doesn't fit, but typically the idea of Cloud Foundry is the assumption the user is a developer who has 10 iterations a day. Alright, so they want to deploy, test, deploy, test, and then layer pipelines on top of that. You also get, you're going to get the backend of long, stable apps, but the value is, for many people, is that the deploy experience. And then, you know, but whilst, you're going to get those apps that live forever, we still get to replace the underlying core of it. So you still maintain a security model even for the things that are relatively unloved. Andthis is really valuable, like the nice, clean separation of the security, the package, CVEs, and the base OS, then the apps is part of the-- >> Yeah, absolutely, there's been an interesting kind of push and pull lately. We need to take some of those old applications, and we may need to lift and shift them. It doesn't mean that I can necessarily take advantage of all the cool stuff, and there are some things that I can't do with them when I get them on to that new platform. But absolutely, you need to worry about security, you know, data's like the center of everything. >> If you're lifting and shifting, there probably is no developer looking after it, so it's more of an operator function, and they can put it anywhere they like. They're looking after it now, whereas the Cloud Foundry experience is that developer-led experience that has an operations backend. If you're lifting and shifting, if it fits in Cloud Foundry, great, if it fits in Kubernetes, great. It's your responsibility. >> Yeah, what interaction do you have with your clients, with some of the kind of cultural and operational changes that they need to go through? So thinking specifically, you've go the developers doing things, you know, the operators, whether they're involved, whether that be devops or not, but I'm curious-- >> So the biggest change when it comes to helping people who are running platforms. And I know many people want to talk about the cloud transformation, but let's talk about the operations transformation, is to become a service-orientated group who are there to provide a service. Yes you're internal, yes they all have the same email address that you do, but you're a service-orientated organization, and that is not technology, that is a mental mode. And if you're not service-orientated, shadow IT occurs, because they can go to Amazon and get a support organization that will respond to them, and so you're competing with Amazon, and Google, and you need to be pretty good. >> Yeah, you mentioned that, you know, your typical client is kind of a large, maybe I'm putting words in your mouth, the Fortune 1000 type companies, does this sort of-- >> We haven't got Berkshire. We haven't got Berkshire, and so if we're going to go Fortune 5, you know, we'd like, I've read my Warren Buffett biography, I reckon the FA are here to meet him I reckon. >> Right, so one of the questions, is this only for the enterprise? Can it be used for smaller businesses, for newer businesses? >> What's interesting is people think about Cloud Foundry as like, "Oh you run it on your infrastructure." Like, I did a talk in 2014, 15, when Docker was starting to be frothy, was, before you think you want to build your own pass, ring me on the hotline. Like, argue with me about why you wouldn't just use Heroku, or Pivotal Web Services, or IBM Cloud, like a public pass. Please, I beg of you, before you go down any path of running on-prem anything, answer solidly the question of why you just wouldn't use a public service. And yeah, so it really starts at that point. It's like, use someone else's, and then if you have to run your own. So, who's really going to have all these rules? It's large organization that have these, "Oh, no, no, we have to run our own." >> Well doctor, one of the things we've said for a while, is there's lots of things that enterprise suck at, that they need to realize that they shouldn't be doing. So start at the most basic level, there's like five companies in the world that are good at building data centers, nobody else should build data centers, if you're using somebody else that can do that. So as you go up and up the stack, you want to get rid of the undifferentiated lifting, things like that, so-- >> I like to joke that every CIO, the moment they get that job, like that's their ticket to get to build their own data center. It's like, what else was the point of becoming a CIO? I want to build my own data center. >> No, not anymore, please-- >> Not anymore, but you know, plus they've been around a little longer than-- >> So, what is that line? What should companies be able to consume a platform, versus where do they add the value, and do you help customers kind of understand that that-- >> By the time they're talking to us, they're pretty far along having convinced themselves about what they're doing. And they have their rules. They have their isolation rules, their data-ownership rules, and they'll have their level of comfort. So they might be comfortable on Amazon, Google, Azure, or they might still not be comfortable with public cloud, and they want the vSphere, but they still have that notion of we're going to run this ourselves. And most of them it's not running one, because that idea of we need our own, propagates throughout the entire organization, and they'll start wanting their own Cloud Foundry-- >> Look, I find that when I talk to users, we, the vendors, and those that watch the industry, always try to come up with these multi-cloud hybrid cloud-type discussion. Users, have a cloud strategy, and it's usually often siloed just like everything else, and right, they're using-- >> Developers-- >> I have some data service, and it's running on Google-- >> Developers just want to have a nice life. >> Microsoft apps. >> They just want to get their work done. They want to feel like, "Alright this is a great job, "like, I'm respected, I get interesting work, "we get to ship it, it actually goes into production." I think if you haven't ever had a project you've worked on that didn't go into production, you haven't worked long enough. Many of us work on something for it not to be shipped. Get it into production as quick as possible and-- >> So, do you have your, you know, utopian ideal world though as to, this is the step-- >> Oh, absolutely-- >> And this is how it'll be simple. >> Tell developers what the business problems are. Get them as close to the business problems, and give them responsibility to solve them. Don't put them behind layers of product managers, and IT support-- >> But Dr. Nic, the developers, they don't have the budget-- >> Speak for utopian-- >> How do we sort through that, because, right, the developer says they want to do this, but they're not tied to the person that has the budget, or they're not working with the operators, I mean, how do we sort through that? >> How do we get to utopia? >> Stu: Yeah. Well, Facebook, Google, Microsoft, they all solved utopia, right? So, this is, think more like them, and perhaps the CEO of the company shouldn't come from sales, perhaps it should be an IT person. >> Well, yeah, what's the T-shirt for the show? It was like running at scale, when you reach a certain point of scale, you either need to solve some of these things, or you will break? >> Right, alright look, hire great sales organizations, but if you don't have empathy for what your company needs to look like in five years time, you're probably not going to allow your organization to become that. The power games, alright? If everyone assumes that the marketing department becomes the top of the organization, or the, you know, then the good people are going to leave to go to organizations where they might be become CEO one day. >> Alright, Dr. Nic, want to give you the final word. For the people that haven't been able to come to the sessions, check out the environment, what are they missing at this show? What is exciting you the most in this ecosystem? >> Like any conference you go to, you come, the learning is all put online. Your show is put online, or every session is put online. You don't come just to learn. You get the energy. I live in Australia, I work from a coffee shop, my staff are all in America, and so to come and just to get the energy that you're doing the right thing, that you get surrounded by a group of people, and certainly no one walks away from a CF Summit feeling like they're in the wrong career. >> Excellent. Well, Dr. Nic, appreciate you helping us understand the infinity wars of cloud environments here. Stark and Wayne, thanks so much for joining us. I'm Stu Miniman, and you're watching theCUBE. >> Dr. Nic: Thanks Stu. (electronic music)

>> Announcer: From Boston, Massachusetts, it's the Cube. Covering Cloud Foundry Summit 2018. Brought to you by The Cloud Foundry Foundation, >> Hi I'm Stu Miniman and this is the Cube's coverage of the Cloud Foundry Summit 2018 here in Boston, Massachusetts. Happy to welcome back one of our earliest and favorite guests of the Cube Chad Sakac Who's at Pivotal now and he handles PKS and Dell technologies. Chad, great to see you, thanks for joining us, welcome to the Boston area, you come through this area a lot but it's great to see you. >> It's good to see you too. This is, by the way, my first CF summit. So it's interesting, you and I have talked together at Dell Technologies World, Dell EMC World, and EMC World for years. >> Stu: VMWorld. >> And VMWorld. This is a different scene. >> Alright Chad, this is my third time doing this show. I was at the first one back in 2014, last year we did the Cube there; every year it's like 'oh wait, there's this cool new technology; containers, maybe, how's Pivotal going to deal with that? This year, wait, Kubernetes, cloud natives everywhere. Maybe give us your point of view, as to how this fits in. >> So I feel like I'm a kid in a candy store. My job inside Pivotal is to drive PKS. Pivotal Container Service, that's built on top of Kubernetes. And there's a lot of Kubernetes action occurring here. If I had to net it out, I'd say a couple things. Number one, we've moved past the early hype cycle, and actually went through several hype cycles that blew up, so Docker is going to take over the world, not correct. What turned out to be correct is Docker would become the container standard, right? >> It's Mobi now, right? >> Right. Then, we went in to the battles of different cluster container managers. It's Swarm, it's Mesos Marathon, it's Kubernetes and there were lots of others, and then you get through that early hype period and things settle down to the point where they're actually productive, and everyone now kind of agrees, that Kubernetes is the standard container cluster manager for broad sets of workloads, great. Now the debate is Cloud Foundry, the structured PaaS-World, right? The structured platform opinionated, versus the little more wild west and open eco system of Kubernetes, and then early stage Kubernetes projects, like Istio and others, right? I think this has two chapters now, in front of us. Number one, and this is my focus I think for the next few years, is how do we make Kubernetes simple enough, easy enough, and frankly, enterprise ready. Not that it's not ready today, but a lot of Kubernetes projects that our customers are all over the map, difficult to sustain. We want to bring a lot of the lessons learned over the years of Cloud Foundry to Kubernetes. And I'm happy to say, that just a couple days ago, we released PKS 1.O.2 and 1.1, which we haven't announced the date but we've always said that we're going to be in constant compatibility with GKE, and the core Kubernetes. Since GKE shortly will have Kubernetes 1.10 support you can expect a 1.1 of PKS. So mission number one is make Kubernetes a great platform, and I am determined and stubborn, and will make PKS the best enterprise platform for customers that are putting workloads on Kubernetes. That said, Kubernetes isn't steady still and neither is the ecosystem. And you can see that there's a lot of discussion over what is the intersection between Cloud Foundry and Kubernetes? I think that over time it's inevitable that these things come together more. But again, I think that's going to occur over years. Not in a heartbeat. >> And even, I've been at the Kubernetes show and have been at this show a few times, it's not a monolithic stack, we're building distributed, lots of different pieces. You go to the Cloud Foundry, I'm sorry, the show that's Kub-Con, there's so many different projects there, I mean Istio was all the buzz, talk about the service national, there's all these little pieces there. And at this show, we're talking about Zip Car came and talked about they love everything in this eco system. They don't use some of the core components, but they use all these other pieces. As you and I've talked many times, Chad, people go read, Chad writes a little bit about some of these things to give you all the details there, but this stuff's pretty complicated. There's some in the Kubernetes community that's like it's never going to get simple. Remember when we thought Cloud computing was simple? And if you've been to any Amazon show and you go through, it is more complicated to configure a compute instance at Amazon, than it is to buy a Dell server these days. Because there's more options out there. Look, customers need options, many of them want things to be packaged and serviced and buy it as a service, but some love to put those pieces together and it's a spectrum and I loved at this show, Google and Microsoft up on stage, talking, 'hey, open communities, collaborating together'. Maybe not merging everything, but working together, understanding where things fit and it's not one or the other, it's many customers will choose both. >> You and I are both nerds at heart, I hope you don't take offense to that. >> I've already been doing Star Wars quotes this week. >> I wear it with pride. I'm always fascinated by the technology itself, but one thing that's been really cool about my experience alongside, and now inside Pivotal, and you can see it here at the CF Summit, is that the Pivotal obsession, is about the customer and the outcome. We build a platform that is an essential part of that, but teaching the world how to build better software is a noble mission. And the thing that's the most exciting for me is actually when the customers talk. So if you went to any of the customer discussions, did you see any of them, did you see the T-Mobile one? >> I saw T-Mobile up on the key note, I actually did an interview with T-Mobile. Had an interview with US Air Force. >> The Air Force One is amazing. >> Awesome. >> It's fascinating, from a technological standpoint, to say how do you use these tools? But it's the story of what you do with it, that actually matters so much more. I'll leave the, no, I won't leave the customer name out of it. So in talking with the T-Mobile crew, they love the Pivotal application service. So they are using it, it's an essential part of how T-Mobile works. They talked about it on stage, that's why I don't mind talking about it. And if you ask them, it's not an or. They also have massive projects, massive application workloads, that don't fit in PaaS, but are Docker images, they're currently doing some strange stuff with Swarm, and blah blah. And they're like 'Man, if you guys can basically deliver a great platform that we can consume instead of trying to construct and maintain, we trust you, you iterate with us, you work with us, we'll be able to focus more on the outcome. The thing that I'm actually going to be the most curious to hear feedback from customers over the next couple of years, is how do they navigate what workloads are best put into Kubernetes, how does Kubernetes sets of ecosystems start to not calcify, but firm up, right? It's going to be loose. But it will start to align more over time. >> Yeah our research team actually calls it, we need to get to a place where it's plastic. It should be not just scalable up and down but side to side a little bit more too. Once you have it, you can be able to go. >> Figuring out over time, and helping, with customers, figure out 'Hey, this is a Kafka or Crunchy data.' Post grass instance, or it's an ISV stack, or it's an application they've home grown, but they don't want it fully compartmentalized and put on paths, and they decide that they want to put it on Kubernetes, awesome. What is the value and the return of doing further work on that app to really make it Cloud Native, pull out all config, turn it into sets of small micro services, and then it's better fit for the PaaS part of PCF. Figuring out that formula over the next few years is going to be really cool. >> You mentioned culture. And that's been something you and I, Chad, lived through. It was the server vs the storage vs the network and the virtualization admin, and then the cloud admin. I talked to the US Air Force guy, and he was like, 'We actually have the people take off their uniforms, because rank would have a certain meaning inside there.' But you've got the Devs, you've got OPS, you've got still the infrastructure pieces on tub, what are you seeing from the customers you're talking to; what are some of the big challenges that are slowing people back from reaching this Utopia of fast, fast, fast, agile, inter-operable, wonderful times? >> How do I answer that one? That's a loaded question, brother. The biggest impediment is human nature. It's these damn humans, if we could just get all the humans out. >> Well everybody's mine, mine, mine. >> We'll go to low code, no code, eliminate all the humans, it'll be dreamy. >> I did one of those interviews today, too. Absolutely, you don't need all programmers, the business people can do it. >> The human tendency for control, and the need for control, I think it's probably deep seated in our, we're living in a world where we know intellectually that we don't have control over everything, but we hate that. Because we want to create control in our lives, that basically is the thing that sets up boundaries between people, and they get really hung up on their function. That's not new, the word's changed, like you said. Used to be server people vs storage people. Then it was virtualization teams vs the silo teams. And now it's the intersection of the DEV team and the DevOps team, the operations team. How do they intersect? The places where they're the most successful, is that they don't get hung up on that and the people blend the roles. Now the trick is, how do you do that in a big company? I wrote a blog, I'm not trying to advertise, virtualgeek.io I wrote a blog on this which was a synthesis of all the customer dialogues I've been having over the last few years. And the pattern I've seen that is most successful, is actually to recognize that there are stacks, and the stacks, I don't mean this particular technology choice, but the way that the whole stack driven by the business and the application and then the abstraction it sits on, and then you have to build your actual operations team underneath that. That creates a whole operational model which in itself is a stack, and just so it doesn't sound like I'm describing something that's nonsensical, a stack can be in big enterprises, there's a main frame based app, that's running on a main frame, that's being supported by a main frame operations team, and then right beside it there's another stack, which is all X86 workloads that are static. So they don't need an IAS they just need to run on a kernel mode VM abstraction. And then under that you've got the team that supports. Then you've got the workload that can be containerized, and don't need a full blown PaaS. And then you've got another one, which is a full blown application service model. Each one of those stacks ends up with different people, processes and tools, because they're mapped to the cultural operational model of that stack. And the thing that I'm trying to guide customers when I'm talking to them is, don't reject that; that's actually reality. Yes you should move as much as you can to the highest order abstraction you can. That's goodness and it pays dividends all the way down the stack. But don't go and say, that this workload, by definition has to go there. Or because you operate this way in this stack and this group operates this way, that by definition you're stupid and they're smart. The other rule is that- >> Chad, the answer to everything is server-less. >> By the way, I should have said that's another abstraction even to the right of the application service model. So the thing I've found, is a key kind of pattern of good, is that between the stacks, people and process are not allowed to transverse them, because the process is linked to how you operate. The only thing that goes between them, because in the end, for any customer, the stuff that touches all of those, is to become religious about one thing, which is that API's and data, and how those transit, those different stacks, that you have to be very clear on. Do you know what I mean? On the blog I drew a picture, but it was terrible. It was a terrible drawing. >> I've done whiteboards with you, Chad, I understand. Great, so. Sound's like you've got your hands full. Lots of us read the S1, so Pivotal's marching towards an IPO. You've only been there a very short time, you've know Pivotal since the beginning and all the pieces since Greenplum's part of the MC, Cloud Foundry part of VMware. Anything that you've learned since you've been inside Pivotal now that there's misconceptions? One of the things I always find is, we always learn about something the first time and then don't think it changes. >> It's funny actually, that's an insightful question. Having joined the team, it's weird because to many of them, I'm new, I'm a new Pivot. But to many of them they know that I've always been there. And I was reminding some of the originals, the crazy tortured path that we've taken to get to today. The original effort was hey, people are doing new things data's at the core of it. And that was the trigger for the Greenplum acquisition. And several of the people who are the senior leaders of Pivotal now came in through that. And then Paul Maritz was the CEO of VMware at the time, hey, I'm seeing people build new apps in new ways, by the way there's this crazy team inside VMware working on this thing called Cloud Foundry. And they were like a red headed stepchild. That's not PC, but like a black sheep? Or I don't know what metaphor you want to use, but basically they were working on something that had nothing to do with kernel mode virtualization at its core. >> Yeah it was a Cloud native peg in a VM square. >> And at the time, VMware isn't what they are now too. And then people forget this but I wrote a blog about it, so it's on the internet permanently. There was a Greenplum project, which was a great idea, that says people want to collaborate with data sets, and data scientists want to work together and it's really hard. Let's build a thing, which is like a social media portal, for Greenplum which was called Chorus. And the Chorus project was completely sideways. And they were like we don't know how we're going to get this thing on track on time, and they asked around the Valley, and people said hey, you should go talk to these guys, Pivotal Labs, up in San Francisco. What they do is they help people when they're stuck. They went, and I remember when Bill Cook and Scott Yara came back to Hoppington and said 'This was awesome, they've changed the way we think about how we build software, we think we should buy them.' And that got added, I remember when Paul Maritz said 'Spring is available.' it's like the most widely used modern JAVA framework, and that was also stuff in Spring Rif. All of these weird bits, in essence became the essence of Pivotal. You know what I've learned through that? Is these journeys are not in a straight line. Everyone's. >> Like our careers, Chad. >> Like our careers man. That's the first part, the second thing is, and this is going to be a challenge for Pivotal, honest, if we're very transparent as always, is Pivotal's brand is now so linked with Pivotal Cloud Foundry. And that's a good thing, like those customers raving about the business outcomes that they are getting. But inside Pivotal, the strategic change, the strategic pivot ha ha ha, to do a full embrace of Kubernetes versus the traditional opinionated versus plastic debates, I wouldn't say that we have 100% of the company fully embracing it yet, because companies are themselves, organic. But across the vast majority of the company it is something understood that it is an imperative for us. If we want to help the customers and the world build better software, we've got to do it for stuff that fits into PaaS, and stuff that doesn't. And so I've learned over the last few weeks about how many people share that passion that I have, and I think we can make something awesome with PKS. >> Alright, well with that Chad, we'll have to leave it there for now, looking forward to seeing you at more events. Congrats on the new role, I'm sure if people haven't already, Chad does have a new site for his blog, virtualgeek.io instead of the previous one. Chad, always a pleasure. Got the Cube here at Cloud Foundry Summit, I'm Stu Miniman, thanks for watching the Cube. (upbeat tempo)

>> Welcome everyone. Thank you for coming to the Intel AI lounge and joining us here for this economist world event. My name is Jack. I'm the chief architect of our autonomist driving solutions at Intel and I'm very happy to be here and to be joined by an esteemed panel of colleagues who are joining to, I hope, engage you all in a frayed dialogue and discussion. There will be time for questions as well, so keep your questions in mind. Jot them down so you ask them to us later. So first, let me introduce the panel. Next to me we have Michelle, who's the co-founder and CEO of Fine Mind. She just did an interview here shortly. Fine Mind is a company that provides a technology platform for retailers and brands that uses artificial intelligence as the heart of the experiences that her company's technology provides. Joe from Intel is the head of partnerships and acquisitions for artificial intelligence and software technologies. He participated in the recent acquisition of Movidius, a computer vision company that Intel recently acquired and is involved in a lot of smart city activities as well. And then finally, Sarush, who is data scientist by training, but now has JDA labs, which is researching emerging technologies and their application in the supply chain worldwide. So at the end of the day, the internet things that artificial intelligence really promises to improve our lives in quite incredible ways and change the way that we live and work. Often times the first thing that we think about when we think about AI is Skynet, but we at Intel believe in AI for good and that there's a lot of things that can happen to improve the way people live, work, and enjoy life. So as things in the Internet, as things become connected, smart, and automated, artificial intelligence is really going to be at the heart of those new experiences. So as I said my role is the architect for autonomous driving. It's a common place when people think about artificial intelligence, because what we're trying to do is replace a human brain with a machine brain, which means we need to endow that machine with intelligent thoughts, contexts, experiences. All of these things that sort of make us human. So computer vision is the space, obviously, with cameras in your car that people often think about, but it's actually more complicated than that. How many of us have been in a situation on a two lane road, maybe there's a car coming towards us, there's a road off to the right, and you sort of sense, "You know what? That car might turn in front of me." There's no signal. There's no real physical cue, but just something about what that driver's doing where they're looking tells us. So what do we do? We take our foot off the accelerator. We maybe hover it over the brake, just in case, right? But that's intelligence that we take for granted through years and years and years of driving experience that tells us something interesting is happening there. And so that's the challenge that we face in terms of how to bring that level of human intelligence into machines to make our lives better and richer. So enough about automated vehicles though, let's talk to our panelists about some of the areas in which they have expertise. So first for Michelle, I'll ask... Many of us probably buy stuff online everyday, every week, every hour, hourly delivery now. So a lot has been written about the death of traditional retail experiences. How will artificial intelligence and the technology that your company has rejuvenate that retail experience, whether it be online or in the traditional brick and mortar store? >> Yeah, excuse me. So one of the things that I think is a common misconception. You hear about the death of the brick and mortar store, the growth of e-commerce. It's really that e-commerce is beating brick and mortar in growth only and there's still over 90% of the world's commerce is done in physical brick and mortar store. So e-commerce, while it has the growth, has a really long way to go and I think one of the things that's going to be really hard to replace is the very human element of interaction and connection that you get by going to a store. So just because a robot named Pepper comes up to you and asks you some questions, they might get you the answer you need faster and maybe more efficiently, but I think as humans we crave interaction and shopping for certain products especially, is an experience better enjoyed in person with other people, whether that's an associate in the store or people you come with to the store to enjoy that experience with you. So I think artificial intelligence can help it be a more frictionless experience, whether you're in store or online to get you from point A to buying the thing you need faster, but I don't think that it's going to ever completely replace the joy that we get by physically going out into the world and interacting with other people to buy products. >> You said something really profound. You said that the real revolution for artificial intelligence in retail will be invisible. What did you mean by that? >> Yeah, so right now I think that most of the artificial intelligence that's being applied in the retail space is actually not something that shoppers like you and I see when we're on a website or when we're in the store. It's actually happening behind the scenes. It's happening to dynamically change the webpage to show you different stuff. It's happening further up the supply chain, right? With how the products are getting manufactured, put together, packaged, shipped, delivered to you, and that efficiency is just helping retailers be smarter and more effective with their budgets. And so, as they can save money in the supply chain, as they can sell more product with less work, they can reinvest in experience, they can reinvest in the brand, they can reinvest in the quality of the products, so we might start noticing those things change, but you won't actually know that that has anything to do with artificial intelligence, because not always in a robot that's rolling up to you in an aisle. >> So you mentioned the supply chain. That's something that we hear about a lot, but frankly for most of us, I think it's very hard to understand what exactly that means, so could you educate us a bit on what exactly is the supply chain and how is artificial intelligence being implied to improve it? >> Sure, sure. So for a lot of us, supply chain is the term that we picked up when we went to school or we read about it every so often, but we're not that far away from it. It is in fact a key part of what Michelle calls the invisible part of one's experience. So when you go to a store and you're buying a pair of shoes or you're picking up a box of cereal, how often do we think about, "How did it ever make it's way here?" We're the constituent components. They probably came from multiple countries and so they had to be manufactured. They had to be assembled in these plants. They had to then be moved, either through an ocean vessel or through trucks. They probably have gone through multiple warehouses and distribution centers and then finally into the store. And what do we see? We want to make sure that when I go to pick up my favorite brand of cereal, it better be there. And so, one of the things where AI is going to help and we're doing a lot of active work in this, is in the notion of the self learning supply chain. And what that means is really bringing in these various assets and actors of the supply chain. First of all, through IOT and others, generating the data, obviously connecting them, and through AI driving the intelligence, so that I can dynamically figure out the fact that the ocean vessel that left China on it's way to Long Beach has been delayed by 24 hours. What does that mean when you go to a Foot Locker to buy your new pair of shoes? Can I come up with alternate sourcing decisions, so it's not just predicting. It's prescribing and recommending as well. So behind the scenes, bringing in a lot of the, generating a lot of the data, connecting a lot of these actors and then really deriving the smarts. That's what the self learning supply chain is all about. >> Are supply chains always international or can they be local as well? >> Definitely local as well. I think what we've seen over the last decades, it's kind of gotten more and more global, but a lot of the supply chain can really just be within the store as well. You'd be surprised at how often retailers do not know where their product is. Even is it in the front of the store? Is it in the back of the store? Is it in the fitting room? Even that local information is not really available. So to have sensors to discover where things are and to really provide that efficiency, which right now doesn't exist, is a key part of what we're doing. >> So Joe, as you look at companies out there to partner or potentially acquire, do you tend to see technologies that are very domain specific for retail or supply chain or do you see technologies that could bridge multiple different domains in terms of the experiences we could enjoy? >> Yeah, definitely. So both. A lot of infant technologies start out in very niched use cases, but then there are technologies that are pervasive across multiple geographies and multiple markets. So, smart cities is a good way to look at that. So let's level set really quick on smart cities and how we think about that. I have a little sheet here to help me. Alright, so, if anybody here played Sim City before, you have your little city that's a real world that sits here, okay? So this is reality and you have little buildings and cars and they all travel around and you have people walking around with cell phones. And what's happening is as we develop smart cities, we're putting sensors everywhere. We're putting them around utilities, energies, water. They're in our phones. We have cameras and we have audio sensors in our phones. We're placing these on light poles, which is existing sustaining power points around the city. So we have all these different sensors and they're not just cameras and microphones, but they're particulate sensors. They're able to do environmental monitoring and things like that. And so, what we have is we have this physical world with all these sensors here. And then what we have is we've created basically this virtual world that has a great memory because it has all the data from all the sensors and those sensors really act as ties, if you think of it like a quilt, trying a quilt together. You bring it down together and everywhere you have a stitch, you're stitching that virtual world on top of the physical world and that just enables incredible amounts of innovation and creation for developers, for entrepreneurs, to do whatever they want to do to create and solve specific problems. So what really makes that possible is communications, connectivity. So that's where 5G comes in. So with 5G it's not just a faster form of connectivity. It's new infrastructure. It's new communication. It includes multiple types of communication and connectivity. And what it allows it to do is all those little sensors can talk to each other again. So the camera on the light pole can talk to the vehicle driving by or the sensor on the light pole. And so you start to connect everything and that's really where artificial intelligence can now come in and sense what's going on. It can then reason, which is neat, to have computer or some sort of algorithm that actually reasons based on a situation that's happening real time. And it acts on that, but then you can iterate on that or you can adapt that in the future. So if we think of an actual use case, we'll think of a camera on a light post that observes an accident. Well it's programmed to automatically notify emergency services that there's been an accident. But it knows the difference between a fender bender and an actual major crash where we need to send an ambulance or maybe multiple firetrucks. And then you can create iterations and that learns to become more smart. Let's say there was a vehicle that was in the accident that had a little yellow placard on it that said hazard. You're going to want to send different types of emergency services out there. So you can iterate on what it actually does and that's a fantastic world to be in and that's where I see AI really playing. >> That's a great example of what it's all about in terms of making things smart, connective, and autonomous. So Michelle as somebody who has founded the company and the space with technology that's trying to bring some of these experiences to market, there may be folks in the audience who have aspirations to do the same. So what have you learned over the course of starting your company and developing the technology that you're now deploying to market? >> Yeah, I think because AI is such a buzz word. You can get a dot AI domain now, doesn't mean that you should use it for everything. Maybe 7, 10, 15 years ago... These trends have happened before. In the late 90s, it was technology and there was technology companies and they sat over here and there was everybody else. Well that not true anymore. Every company uses technology. Then fast forward a little bit, there was social media was a thing. Social media was these companies over here and then there was everybody else and now every company needs to use social media or actually maybe not. Maybe it's a really bad idea for you to spend a ton of money on social media and you have to make that choice for yourself. So the same thing is true with artificial intelligence and what I tell... I did a panel on AI for Adventure Capitalists last week, trying to help them figure out when to invest and how to evaluate and all that kind of stuff. And what I would tell other aspiring entrepreneurs is "AI is means to an end. "It's not an end in itself." So unless you're a PH.D in machine learning and you want to start an AI as a service business, you're probably not going to start an AI only company. You're going to start a company for a specific purpose, to solve a problem, and you're going to use AI as a means to an end, maybe, if it makes sense to get there, to make it more efficient and all that stuff. But if you wouldn't get up everyday for ten years to do this business that's going to solve whatever problem you're solving or if you wouldn't invest in it if AI didn't exist, then adding dot AI at the end of a domain is not going to work. So don't think that that will help you make a better business. >> That's great advice. Thank you. Surash, as you talked about the automation then of the supply chain, what about people? What about the workers whose jobs may be lost or displaced because of the introduction of this automation? What's your perspective on that? >> Well, that's a great question. It's one that I'm asked quite a bit. So if you think about the supply chain with a lot of the manufacturing plants, with a lot of the distribution centers, a lot of the transportation, not only are we talking about driverless cars as in cars that you and I own, but we're talking about driverless delivery vehicles. We're talking about drones and all of these on the surface appears like it's going to displace human beings. What humans used to do, now machines will do and potentially do better. So what are the implications around human beings. So I'm asked that question quite a bit, especially from our customers and my general perception on this is that I'm actually cautiously optimistic that human beings will continue to do things that are strategic. Human beings will continue to do things that are creative and human being will probably continue to do things that are truly catastrophic, that machines simply have not been able to learn because it doesn't happen very often. One thing that comes to mind is when ATM machines came about several years ago before my time, that displaced a lot of teller jobs in the banking industry, but the banking industry did not go belly up. They found other things to do. If anything, they offered more services. They were more branches that were closed and if I were to ask any of you now if you would go back and not have 24/7 access to cash, you would probably laugh at me. So the thing is, this is AI for good. I think these things might have temporary impact in terms of what it will do to labor and to human beings but I think we as human beings will find bigger, better, different things to do and that's just in the nature of the human journey. >> Yeah, there's definitely a social acceptance angle to this technology, right? Many of us technologists in the room, it's easier for us to understand what the technology is, how it works, how it was created, but for many of our friends and family, they don't. So there's a social acceptance angle to this. So Michelle as you see this technology deployed in retail environments, which is a space where almost every person in every country goes, how do you think about making it feel comfortable for people to interact with this kind of technology and not be afraid of the robots or the machines behind the curtain. >> Yeah, that's a great question. I think that user experience always has to come first, so if you're using AI for AI's sake or for the cool factor, the wow factor, you're already doing it wrong. Again, it needs to solve a problem and what I tend to tell people who are like, "Oh my God. AI sounds so scary. "We can't let this happen." I'm like, "It's already happening "and you're already liking it. "You just don't know "because it's invisible in a lot of ways." So if you can point of those scenarios where AI has already benefited you and it wasn't scary because it was a friendly kind of interaction, you might not even have realized it was there versus something that looks so different and... Like panic driving. I think that's why the driverless car thing is a big deal because you're so used to seeing, in America at least, someone on the left side of the car in the front seat. And not seeing that is like, woah, crazy. So I think that it starts with the experience and making it an acceptable kind of interface or format that doesn't give you that, "Oh my God. Something is wrong here," kind of feeling. >> Yeah, that's a great answer. In fact, it reminds me there was this really amazing study by a Professor Nicholas Eppily that was published in the journal of social psychology and the name of this study was called A Mind In A Machine. And what he did was he took subjects and had a fully functional automated vehicle and then a second identical fully functional automated vehicle, but this one had a name and it had a voice and it had sort of a personality. So it had human anthropomorphics characteristics. And he took people through these two different scenarios and in both scenarios he's evil and introduced a crash in the scenario where it was unavoidable. There was nothing going to happen. You were going to get into an accident in these cars. And then afterwards, he pulled the subjects and said, "Well, what did you feel about that accident? "First, what did you feel about the car?" They were more comfortable in the one that had anthropomorphic features. They felt it was safer and they'd be more willing to get into it, which is not terribly surprising, but the kicker was the accident. In the vehicle that had a voice and a name, they actually didn't blame the self-driving car they were in. They blamed the other car. But in the car that didn't have anthropomorphic features, they blamed the machine. They said there's something wrong with that car. So it's one of my favorite studies because I think it does illustrate that we have to remember the human element to these experiences and as artificial intelligence begins to replace humans, or some of us even, we need to remember that we are still social beings and how we interact with other things, whether they be human or non-human, is important. So, Joe, you talk about evaluating companies. Michelle started a company. She's gotten funding. As you go out and look at new companies that are starting up, there's just so much activity, companies that just add dot AI to the name as Michelle said, how do you cut through the noise and try to get to the heart of is there any value in a technology that a company's bringing or not? >> Definitely. Well, each company has it's unique, special sauce, right? And so, just to reiterate what Michelle was talking about, we look for companies that are really good at doing what they do best, whatever that may be, whatever that problem that they're solving that a customer's willing to pay for, we want to make sure that that company's doing that. No one wants a company that just has AI in the name. So we look for that number one and the other thing we do is once we establish that we have a need or we're looking at a company based on either talent or intellectual property, we'll go in and we'll have to do a vetting process and it takes a whole. It's a very long process and there's legal involved but at the end of the day, the most important thing for the start up to remember is to continue doing what they do best and continue to build upon their special sauce and make sure that it's very valuable to their customer. And if someone else wants to look at them for acquisition so be it, but you need to be meniacally focused on your own customer. That's my two cents. >> I'm thinking again about this concept of embedding human intelligence, but humans have biases right? And sometimes those biases aren't always good. So how do we as technologists in this industry try to create AI for good and not unintentionally put some of our own human biases into models that we train about what's socially acceptable or not? Anyone have any thoughts on that? >> I actually think that the hype about AI taking over and destroying humanity, it's possible and I don't want to disagree with Steven Hawking as he's way smarter than I am. But he kind of recognizes it could go both ways and so right now, we're in a world where we're still feeding the machine. And so, there's a bunch of different issues that came up with humans feeding the machine with their foibles of racism and hatred and bias and humans experience shame which causes them to lash out and what to put somebody else down. And so we saw that with Tay, the Microsoft chatbot. We saw that with even Google's fake news. They're like picking sources now to answer the question in the top box that might be the wrong source. Ads that Google serves often show men high paying jobs, $200,000 a year jobs, and women don't get those same ones. So if you trace that back, it's always coming back to the inputs and the lens that humans are coming at it from. So I actually think that we could be in a way better place after this singularity happens and the machines are smarter than us and they take over and they become our overlords. Because when we think about the future, it's a very common tendency for humans to fill in the blanks of what you don't know in the future with what's true today. And I was talking to you guys at lunch. We were talking about this harbored psychology professor who wrote a book and in the book he was talking about how 1950s, they were imagining the future and all these scifi stories and they have flying cars and hovercrafts and they're living in space, but the woman still stays at home and everyone's white. So they forgot to extrapolate the social things to paint the picture in, but I think when we're extrapolating into the future where the computers are our overlords, we're painting them with our current reality, which is where humans are kind of terrible (laughs). And maybe computers won't be and they'll actually create this Utopia for us. So it could be positive. >> That's a very positive view. >> Thanks. >> That's great. So do we have this all figured out? Are there any big challenges that remain in our industries? >> I want to add a little bit more to the learning because I'm a data scientist by training and a lot of times, I run into folks who think that everything's been figured out. Everything is done. This is so cool. We're good to go and one of the things that I share with them is something that I'm sure everyone here can relate to. So if a kindergartner goes to school and starts to spell profanity, that's not because the kid knows anything good or bad. That is what the kid has learned at home. Likewise, if we don't train machines well, it's training will in fact be biased to your point. So one of the things that we have to kep in mind when we talk about this is we have to be careful as well because we're the ones doing the training. It doesn't automatically know what is good or bad unless that set of data is also fed to it. So I just wanted to kind of add to your... >> Good. Thank you. So why don't we open it up a little bit for questions. Any questions in the audience for our panelists? There's one there looks like (laughs). Emily, we'll get to you soon. >> I had a question for Sarush based on what you just said about us training or you all training these models and teaching them things. So when you deploy these models to the public with them being machine learning and AI based, is it possible for us to retrain them and how do you build in redundancies for the public like throwing off your model and things like that? What are some of the considerations that go into that? >> Well, one thing for sure is training is continuous. So no system should be trained once, deployed, and then forgotten. So that is something that we as AI professionals need to absolutely, because... Trends change as well. What was optimal two years ago is no longer optimal. So that part needs to continue to happen and we're the where the whole IOT space is so important is it will continue to generate relevant consumable data that these machines can continuously learn. >> So how do you decide what data though, is good or bad, as you retrain and evolve that data over time? As a data scientist, how do you do selection on data? >> So, and I want to piggyback on what Michelle said because she's spot on. What is the problem that you're trying to solve? It always starts from there because we have folks who come in to CIOs, "Oh look. "When big data was hot, we started to collect "a lot of the data, but nothing has happened." But data by itself doesn't automatically do magic for you, so we ask, "What kind of problem are you trying to solve? "Are you trying to figure out "what kinds of products to sell? "Are you trying to figure out "the optimal assortment mix for you? "Are you trying to find the shortest path "in order to get to your stores?" And then the question is, "Do you now have the right data "to solve that problem?" A lot of times we put the science and I'm a data scientist by training. I would love to talk about the science, but really, it's the problem first. The data and the science, they come after. >> Thanks, good advice. Any other questions in the audience? Yes, one right up here. (laughing) >> Test, test. Can you hear me? >> Yep. >> So with AI machinery becoming more commonplace and becoming more accessible to developers and visionaries and thinkers alike rather than being just a giant warehouse of a ton of machines and you get one tiny machine learning, do you foresee more governance coming into play in terms of what AI is allowed to do and the decisions of what training data is allowed to be fed to Ais in terms of influence? You talk about data determining if AI will become good or bad, but humans being the ones responsible for the training in the first place, obviously, they can use that data to influence as they, just the governance and the influence. >> Jack: Who wants to take that one? >> I'll take a quick stab at it. So, yes, it's going to be an open discussion. It's going to have to take place, because really, they're just machines. It's machine learning. We teach it. We teach it what to do, how to act. It's just an extension of us and in fact, I think you had a really great conversation or a statement at lunch where you talked about your product being an extension of a designer because, and we can get into that a little bit, but really, it's just going to do what we tell it to do. So there's definitely going to have to be discussions about what type of data we feed. It's all going to be centered around the use case and what that solves the use case. But I imagine that that will be a topic of discussion for a long time about what we're going to decide to do. >> Jack: Michelle do you want to comment on this thought of taking a designer's brain and putting it into a model somehow? >> Well, actually, what I wanted to say was that I think that the regulation and the governance around it is going to be self imposed by the the developer and data science community first, because I feel like even experts who have been doing this for a long time don't rally have their arms fully around what we're dealing with here. And so to expect our senators, our congressmen, women, to actually make regulation around it is a lot, because they're not technologists by training. They have a lot of other stuff going on. If the community that's already doing the work doesn't quite know what we're dealing with, then how can we expect them to get there? So I feel like that's going to be a long way off, but I think that the people who touch and feel and deal with models and with data sets and stuff everyday are the kind of people who are going to get together and self-regulate for a while, if they're good hearted people. And we talk about AI for good. Some people are bad. Those people won't respect those convenance that we come up with, but I think that's the place we have to start. >> So really you're saying, I think, for data scientists and those of us working in this space, we have a social, ethical, or moral obligation to humanity to ensure that our work is used for good. >> Michelle: No pressure. (laughing) >> None taken. Any other questions? Anything else? >> I just wanted to talk about the second part of what she said. We've been working with a company that builds robots for the store, a store associate if you will. And one of their very interesting findings was that the greatest acceptance of it right now has been at car dealerships because when someone goes to the car dealer and we all have had terrible experiences doing that. That's why we try to buy it online, but just this perception that a robot would be unbiased, that it will give you the information without trying to push me one way or the other. >> The hard sell. >> So there's that perception side of it too that, it isn't that the governance part of your question, but more the biased perception side of what you said. I think it's fascinating how we're already trained to think that this is going to have an unbiased opinion, whether or not that true. >> That's fascinating. Very cool. Thank you Sarush. Any other questions in the audience? No, okay. Michelle, could I ask, you've got a station over there that talks a little bit more about your company, but for those that haven't seen it yet, could you tell us a little bit about what is the experience like or how is the shopping experience different for someone that's using your company's technology than what it was before? >> Oh, free advertising. I would love to. No, but actually, I started this company because as a consumer I found myself going back to the user experience piece, just constantly frustrated with the user experience of buying products one at a time and then getting zero help. And then here I am having to google how to wear a white blazer to not look like an idiot in the morning when I get dressed with my white blazer that I just bought and I was excited about. And it's a really simple thing, which is how do I use the product that I'm buying and that really simple thing has been just abysmally handled in the retail industry, because the only tool that the retailers have right now are manual. So in fashion, some of our fashion customers like John Varvatos is an example we have over there, it's like a designer for high-end men's clothing, and John Varvatos is a person, it's not just the name of the company. He's an actual person and he has a vision for what he wants his products to look like and the aesthetic and the style and there's a rockstar vibe and to get that information into the organization, he would share it verbally with PDFs, thing like that. And then his team of merchandisers would literally go manually and make outfits on one page and then go make an outfit on another page with the same exact items and then products would go out of stock and they'd go around in circles and that's a terrible, terrible job. So to the conversation earlier about people losing jobs because of artificial intelligence. I hope people do lose jobs and I hope they're the terrible jobs that no one wanted to do in the first place, because the merchandisers that we help, like the one form John Varvatos, literally said she was weeks away from quitting and she got a new boss and said, "If you don't ix this part of my job, I'm out of here." And he had heard about us. He knew about us and so he brought us in to solve that problem. So I don't think it's always a bad thing, because if we can take that route, boring, repetitive task off of human's plates, what more amazing things can we do with our brain that is only human and very unique to us and how much more can we advance ourselves and our society by giving the boring work to a robot or a machine. >> Well, that's fantastic. So Joe, when you talk about Smart Cities, it seems like people have been talking about Smart Cities for decades and often people cite funding issues, regulatory environment or a host of other reasons why these things haven't happened. Do you think we're on the cusp of breaking through there or what challenges still remain for fulfilling that vision of a smart city? >> I do, I do think we're on the cusp. I think a lot of it has to do, largely actually, with 5G and connectivity, the ability to process and send all this data that needs to be shared across the system. I also think that we're getting closer and more conscientious about security, which is a major issue with IOT, making sure that our in devices or our edge devices, those things out there sensing, are secure. And I think interocular ability is something that we need to champion as well and make sure that we basically work together to enable these systems. So very, very difficult to create little, tiny walled gardens of solutions in a smart city. You may corner a certain part of the market, but you're definitely not going to have that ubiquitous benefit to society if you establish those little walled gardens, so those are the areas I think we need to focus on and I think we are making serious progress in all of them. >> Very good. Michelle, you mentioned earlier that artificial intelligence was all around us in lots of places and things that we do on a daily basis, but we probably don't realize it. Could you share a couple examples? >> Yeah, so I think everything you do online for the most part, literally anything you might do, whether that's googling something or you go to some article, the ads might be dynamically picked for you using machine learning models that have decided what is appropriate based on you and your treasure trove of data that you have out there that you're giving up all the time and not really understanding you're giving up >> The shoes that follow you around the internet right? >> Yeah, exactly. So that's basically anything online. I'm trying to give in the real-world. I think that, to your point earlier about he supply chain, just picking a box of cereal off the shelf and taking it home, there's not artificial intelligence in that at all, but the supply chain behind it. So the supply chain behind pretty much everything we do even in television, like how media gets to us and get consumed. At some point in the supply chain, there's artificial intelligence playing in there as well. >> So to start us in the supply chain where we can get the same day even within the hour delivery. How do you get better than that? What's coming that's innovative in the supply chain that will be new in the future? >> Well, so that is one example of it, but you'd be surprised at how inefficient the supply chain is, even with all the advances that have already gone in, whether it's physical advances around building modern warehouses and modern manufacturing plants, whether it's through software and others that really help schedule things and optimize things. What has happened in the supply chain just given how they've evolved is they're very siloed, so a lot of times the manufacturing plant does things that the distribution folks do not know. The distribution folks do things that the transportation folks don't know and then the store folks know nothing other than when the trucks pulls up, that's the first time they find out about things. So where the great opportunity in my mind is, in the space that I'm in, is really the generation of data, the connection of data, and finally, deriving the smarts that really help us improve efficiency. There's huge opportunity there. And again, we don't know it because it's all invisible to us. >> Good. Let me pause and see if there's any questions in the audience. There, we got one there. >> Thank you. Hi guys, you alright? I just had a question about ethics and the teaching of ethics. As you were saying, we feed the artificial intelligence, whereas in a scenario which is probably a little bit more attuned to automated driving, in a car crash scenario between do we crash these two people or three people? I would be choosing two, whereas the scenario may be it's actually better to just crash the car and kill myself. That thought would never go through my mind, because I'm human. My rule number one is self preservation. So how do we teach the computer this sort of side of it? Is there actually the AI ethic going to be better than our own ethics? How do we start? >> Yeah, that's a great question. I think the opportunity is there as Michelle was talking earlier about maybe when you cross that chasm and you get this new singularity, maybe the AI ethics will be better than human ethics because the machine will be able to think about greater concerns perhaps other than ourselves. But I think just from my point of view, working in the space of automated vehicles, I think it is going to have to be something that the industry, and societies are different, different geographies, and different countries. We have different ways of looking at the world. Cultures value different things and so I think technologists in those spaces are going to have to get together and agree amongst the community from a social contract theory standpoint perhaps in a way that's going to be acceptable to everyone who lives in that environment. I don't think we can come up with a uniform model that would apply to all spaces, but it's got to be something though that we all, as members of a community, can accept. And so yeah, that would be the right thing to do in that situation and that's not going to be an easy task by any means, which is, I think, one of the reasons why you'll continue to see humans have an important role to play in automated vehicles so that the human could take over in exactly that kind of scenario, because the machines perhaps aren't quite smart enough to do it or maybe it's not the smarts or the processing capability. It's maybe that we haven't as technologists and ethicists gotten together long enough to figure out what are those moral and ethical frameworks that we could use to apply to those situations. Any other thoughts? >> Yeah, I wanted to jump in there real quick. Absolutely questions that need to be answered, but let's come together and make a solution that needs to have those questions answered. So let's come together first and fix the problems that need to be fixed now so that we can build out those types of scenarios. We can now put our brainpower to work to decide what to do next. There was a quote I believe by Andrew Ningh Bidou and he was saying in concerning deep questions about what's going to happen in the future with AI. Are we going to have AI overlords or anything like that? And it's kind of like worrying about overpopulation at the point of Mars. Because maybe we're going to get there someday and maybe we're going to send people there and maybe we're going to establish a human population on Mars and then maybe it will get too big and then maybe we'll have problems on Mars, but right now we haven't landed on the planet and I thought that really does a good job of putting in perspective that that overall concern about AI taking over. >> So when you think about AI being applied for good and Michelle you talked about don't do AI just for AI's sake, have a problem to solve, I'll open it up to any of the three of you, what's a problem in your life or in your work experience that you'd love somebody out here would go solve with AI? >> I have one. Sorry, I wanted to do this real quick. There's roads blocked off and it's raining and I have to walk a mile to find a taxi in the rain right now after this to go home. I would love for us to have some sort of ability to manage parking spaces and determine when and who can come in to which parts of the city and when there's a spot downtown, I want my autonomous vehicle to know which one's available and go directly to that spot and I want it to be cued in a certain manner to where I'm next in line and I know. And so I would love for someone to go solve that problem. There's been some development on the infrastructure side for that kind of solution. We have a partnership Intel does with GE and we're putting sensors that have, it's an IOT sensor basically. It's called City IQ. It has environmental monitoring, audio, visual sensors and it allows this type of use case to take place. So I would love to see iterations on that. I would love to see, sorry there's another one that I'm particular about. Growing up I lived in Southern California right against the hills, a housing development, because the hills and there was not a factory, but a bunch of oil derricks back there. I would love to have sensor that senses the particulate in the air to see if there was too many fumes coming from that oil field into my yard growing up as a little kid. I would love for us to solve problems like that, so that's the type of thing that we'll be able to solve. Those are the types of innovations that will be able to take place once we have these sensors in place, so I'm going to sit down on that one and let someone else take over. >> I'm really glad you said the second one because I was thinking, "What I'm about to say is totally going to "trivialize Joe's pain and I don't want to do that." But cancer is my answer, because there's so much data in health and all these patterns are there waiting to be recognized. There's so many things you don't know about cancer and so many indicators that we could capture if we just were able to unmask the data and take a look, but I knew a brilliant company that was using artificial intelligence specifically around image processing to look at CAT scans and figure out what the leading indicators might be in a cancerous scenario. And they pivoted to some way more trivial problem which is still a problem and not to trivialize parking an whatnot, but it's not cancer. And they pivoted away from this amazing opportunity because of the privacy and the issues with HIPPA around health data. And I understand there's a ton of concern with it getting into the wrong hands and hacking and all of this stuff. I get that, but the opportunity in my mind far outweighs the risk and the fact that they had to change their business model and change their company essentially broke my heart because they were really onto something. >> Yeah that's a shame and it's funny you mention that. Intel has an effort that we're calling the cancer cloud and what we're trying to do is provide some infrastructure to help with that problem and the way cancer treatments work today is if you go to a university hospital let's say here in Texas, how you interpret that scan and how you respond and apply treatment, that knowledge is basically just kept within that hospital and within that staff. And so on the other side of the country, somebody could go in and get a scan and maybe that scan brand new to that facility and so they don't know how to treat it, but if you had an opportunity with machine learning to be able to compare scans from people, not only just in this country, but around the world and understand globally, all of the hundreds of different treatment pads that were applied to that particular kind of cancer, think how many lives could be saved, because then you're sharing knowledge with what courses of treatment worked. But it's one of those things like you say, sometimes it's the regulatory environment or it's other factors that hold us back from applying this technology to do some really good things, so it's a great example. Okay, any other questions in the audience? >> I have one. >> Good Emily. >> So this goes off of the HIPPA question, which is, and you were talking about just dynamically displaying ads earlier. What does privacy look like in a fully autonomous world? Anybody can answer that one. Are we still private citizens? What does it look like? >> How about from a supply chain standpoint? You can learn a lot about somebody in terms of the products that they buy and I think to all of us, we sort of know maybe somebody's tracking what we're buying but it's still creepy when we think about how people could potentially use that against us. So, how do you from a supply chain standpoint approach that problem? >> Yeah and it's something that comes up in my life almost every day because one of the thing's we'd like to do is to understand consumer behavior. How often am I buying? What kinds of products am I buying? What am I returning? And so for that you need transactional data. You really get to understand the individual. That then starts to get into this area of privacy. Do you know too much about me? And so a lot of times what we do is data is clearly anonymized so all we know is customer A has this tendency, customer B has this tendency. And that then helps the retailers offer the right products to these customers, but to your point, there are those privacy concerns and I think issues around governance, issues around ethics, issues around privacy, these will continue to be ironed out. I don't think there's a solid answer for any of these just yet. >> And it's largely a reflection of society. How comfortable are we with how much privacy? Right now I believe we put the individual in control of as much information as possible that they are able to release or not. And so a lot of what you said, everyone's anonymizing everything at the moment, but that may change as society's values change slightly and we'll be able to adapt to what's necessary. >> Why don't we try to stump the panel. Anyone have any ideas on things in your life you'd like to be solved with AI for good? Any suggestions out there that we could then hear from our data scientist and technologist and folks here? Any ideas? No? Alright good. Alright, well, thank you everyone. Really appreciate your time. Thank you for joining Intel here at the AI lounge at Autonomous World. We hope you've enjoyed the panel and we wish you a great rest of your event here at South by Southwest. (audience clapping) (bright music)

>> Voiceover: From Orlando, Florida, it's theCUBE. (upbeat music) Covering Sapphire Now. Headlines sponsored by SAP HANA Cloud, the leader in platform as a service, with support from Console, Inc., the cloud internet company. Now, here's your host, Peter Burris. >> Welcome back to theCUBE. I'm Peter Burris, and theCUBE is, once again, our flagship platform for bringing what's happening in big events to the community. Today, we're here at SAP Sapphire and I'm being joined by Tom Roberts, who's the Global Vice President of Third-Party Software Solutions. Tom, we're going to spend some time talkin' about how you're working with the ecosystem at SAP to fill in some of those crucial gaps that customers face as they try to create those new outcomes with SAP-related technologies. Tell us a little bit about what your team does. >> Great, Peter, and thanks, appreciate you havin' us here. You know, Peter, one of the key things that Third-Party Solutions does, and what my team does, is we really help complete the solution. Right? So, it's a complex world. We've got customers out there trying to solve some very challenging problems and, of course, SAP brings the bulk of the solution there, but there's going to be some gaps. We've created unique relationships in our ecosystems in order to help fill that and deliver a complete solution. So, for example, you'll hear the name out in the marketplace, Solution Extensions, and that's our external branding. These are solutions that SAP sells on its paper, that have been tested and are supported by SAP, same as our own products, so the customer can buy with confidence and help get that total solution in place. >> So, it's your almost SAP-compliant additional software. >> Yeah, that's right. >> Excellent. That's a really interesting perspective. You know, it's interesting. Over the course of our two days here at Sapphire, and we'll be here tomorrow as well, two things have popped out that are a little bit different from SAP. First off, the tension between whether or not SAP was an applications company or platform company seems to have totally gone away. >> Yes. >> You're a platform company. >> That's correct. >> The second thing that I find very interesting is that SAP has always been the company that kind of, was a little bit more neutral, stood back. When a customer needed us, we'll show up and we'll do it. You're now being a little bit more aggressive about going after business, after some other companies' customers. How are you utilizing this extensions approach to more rapidly create a solutions fabric that can bring, that can rapidly grab new customers for SAP, and your partners? >> Well, Peter, you're right on the money. You know, it's no doubt that the industry has moved rapidly to the cloud. In fact, everybody said it would happen faster and it's happened even faster than they said it would. Everyone is, when they see results, they're always surprised, and cloud growth was even faster than we thought it would be. Now, what a lot of people haven't figured out, but I think SAP has, is that, in a cloud-based solution world, the expectation is that, one, it's seamlessly integrated, and, two, the experience of buying it is seamlessly integrated, and, three, it's supported in a seamlessly integrated way and that's what Solution Extensions delivers in the cloud. So, you take an example of the success we've had with the acquisition of SuccessFactors, growing great, growin' well in the industry, but they have a lot of needs in order to mature the solution and meet the customer's entire wishlist. One example that we use is we've got a relationship with WorkForce Software for time and attendance, so it wasn't something that SAP developed, but it's something that the customers needed and provides high ROI. But, if you go and you look at that solution, you'll look and see that it's directly embedded inside employee central, right on the drop down, so, for the customers, a completely seamless experience, and they can buy that from their SAP account executive. >> So, SAP is installed in a lot of companies, 300 thousand across all industries. >> Right. >> As we move to a digital world, a lot of your customers, a lot of your SAP customers themselves, are starting to envision how software becomes part of their delivery mechanism. >> Right. >> And they're looking at the customers that they serve and saying, I wonder if I can use this software better. Are you startin' to see non-traditional software companies starting to come to you and saying, how can we be part of this program so that we can plug into, or we can enhance, that broad set of solutions for our customers. >> Right. So, look at, everyone likes to talk about Internet of Things, right? So you take a historical business that's asset heavy and, by that I mean, think of like an oil and gas company. You know, traditionally the guys would work out in the field and they didn't carry devices with them. They carried wrenches, (giggles), right? They didn't carry mobile devices that were digitally connected. >> And flasks. (laughter) >> Sometimes. I hope not too often. That's a dangerous line of work. But, if you think about it, now that's changed. Right? They now use the Internet of Things not only to get information back from the field, but they also use it so that when they have to go out and do those repairs, they're getting digital assets that they can see. Now, we have created some relationships, and I'll give you two examples. You'll hear about a relationship that SAP has with OSIsoft, right. They have a well-known reputation for being able to draw that information off Internet of Things, and we've created a link between that and the HANA platform. So that now, you can do that analysis in real-time, because, as you know, HANA is made for the real-time and, if you're going to do Internet of Things, that's the only platform you can really go with. You can't go with, it's not the old batch then analyze later; you need that information happening in real time. That's one example. The other example that I'll give you is you'll see here a Sapphire, you'll see a company called, Utopia. You say, well, alright, I've never heard of this company but they do a unique thing. It's a direct add in into he SAP platform, a solution extension, that allows you to do master data governance around your enterprise assets. And you say, wow, that sounds really complicated. Okay, what is that? This is the ability to look at those documents in a digital way while you're out in the field to understand hey, that bolt there, that needs to be made out of steel, not aluminum, or you're going to have a chemical reaction, for example. That's the kind of thing that can safe lives, save time, and also make the job out in the field easier. And you can't do that just with SAP's software by itself, we need the partners to contribute into that ecosystem and bring that richness there. >> You talked about the rapid adoption of the cloud, in many respects, almost surprising adoption of the cloud. 'Cause you're right, we all knew it was going to happen, many of us didn't necessarily know how fast it was going to be. SAP has a very on-premise and a lot of the programs that SAP put together were initially optimized for that on-premise orientation. >> That's right. >> Are your clients today, when they become part of the SAP extension, or the Solutions Extension program, are they automatically part of both worlds? First off, let me start there. >> Yeah, I mean, it's true that we live in a hybrid world already today. Hybrid happens so quickly. You saw SAP move aggressively forward and acquire some leading cloud companies. >> Yep. >> Right. (mumbles) >> And you did a great job of integrating them, by the way. >> Thank you. I think we did. And I'm really impressed with these properties. I think you saw in the keynote yesterday, a really great representation of some of the leaders of those businesses up there and how tightly they've become part of the SAP family. Now, when you look at Solution Extensions, it mirrors that. We have solutions across all five of the major pillars of the business which, of course, include these cloud properties, and the areas we're seeing the fastest growth, or the most rapid adoption, are in these cloud properties. Because we all went through the era of the best-of-breed became the suite, and then we had the era of the cloud. And if you noticed, when the cloud companies were launched, they were best-of-breed companies and now we're in that period where people want things to move back to the suite because they want integration. >> Or a least at a platform level. >> Sure, because they want efficiency. Efficiency comes from that integration and they get the first round of benefits by moving to the new application in the cloud and they get out of the business of having to operate it themselves. But, then, they want to get back to the business of having that seamlessly integrated with their core operations. So, we live in a hybrid world today but it's clear that the pendulum is moving directly to cloud. >> So are you suggesting to companies that want to be part of the extensions program, that they focus on the cloud first and then everything else second? >> Yes, I would, and here's why. All conversations with customers start with cloud. And they'll look to see if they can do something in the cloud first and it's the default. So, we've really moved past that world where the first conversation's around on-prem and then look to cloud. That changed maybe two to three years ago and today, every conversation starts with the cloud. >> So, I want to go back to that notion of non-traditional software companies creating solutions within the SAP ecosystem for their customers. Do you have companies like that in the extensions program today? >> Well, I think many of these companies are evolving, just like SAP. Now, I tend to deal with the ISVs, so I tend to deal with companies that are in the business of that. But, I will tell you this, what we're seeing with HANA Cloud Platform is exactly what you're talking about. It's that intersection of SAP, our ISV ecosystem, and those non-traditional customers that are, themselves, moving into the digital, and it's that intersection, and you'll see that happen on HCP, where they'll develop applications unique to their own business. I like to remind people this, when we first rolled out our three and then we went to the business suite, companies wrote billions of lines of custom ABAP code to get that system the way they wanted it, in each of these individual companies. Well, as we move to S4, companies are going to revisit what they did to make those systems special and perform just the way they want it to. But they're not going to do that in ABAP, likely. They're likely they're going to do that on HCP, and they're going to build in that platform because that's where they're going to get the integration, that's where they're going to get the benefit of where our ISV ecosystem is headed and tap into the richness of that. So, I think this is why you hear this rebirth of innovation at SAP and it's because it's driven by the customers. That's why we have so many people turn out at Sapphire this week, so much so that even the SAP employees are like, wow, this is really an impressive turnout. >> It's 60,000 plus people, it's one of the most, without question, this is one of most energetic and packed trade shows that I've ever been to. Or customer shows I've ever been to. >> Yes, it's impressive. We're lookin' around here right now and you just, all these, just, bodies. It's incredible. >> Yeah, absolutely. So, if I envision the next couple of years for you, every, we had a partner on yesterday, in fact, and we asked him a couple of pointed questions, as we're asking you, and we asked him, what do you want to see from SAP, as a partner? What would make SAP an even better partner so that you would be that much more willing to tie into the ecosystem? And what they said was, we want to see better road maps to, so that we can see how, where our responsibilities and SAP's responsibilities, our roles and SAP's roles, end. We're still concerned about the platform mentality rolling us. How are you assuaging those ISV concerns about your roadmap as you try to bring even more integrated value into the platform? >> You know, SAP has a brand of trust. And, when you get to road maps, you have to have trust with your partners- who's going to do what. Very clear and transparent conversations. I've seen a lot of maturity from SAP really in the last six to eight months being much more diligent in how they're planning their road maps and how they're involving partners in those road maps. I'll give you an example. You know, Wieland Schriener, who really leads some of the development around S4, in particular, as it relates to initiative that we work on with open text. That's one of our largest partners inside Solution Extensions. We have, right now, about 19 million users who have purchased that through SAP so, really, an incredible relationship, unique in the industry, that we have with them. As they, as we launch S4 and as we push it out into the marketplace, we've seamlessly integrated the open-text capabilities around unstructured content into S4. And, that's happened through the leadership of our development team. By making commitments like that. Weiland presented that on the partner summit on Monday to all the partners in there, really as a message out to them to say, this is how SAP is going to do business in the future with our ISVs and our partners. And it, and we're moving at such a pace it requires that level of coordination. Right? We can't just let it to chance. Or, we can't let it be ambiguous. We have to be clear about we're going to build this and we're expecting our partners to step up here, so that that dance happens the way it should happen. I do respect though, that the partners have that concern, 'cause it's a legacy. >> They're always going to have the concern, but a big piece of it is going to be how well do you share and how well do you work together. >> Yeah. >> Hey, Tom, thank you very much. Tom Roberts, Global Vice President, SAP Solutions Extension program. Thank you very much for being here as part of this great show, talkin' about partnerships and the evolution of the SAP platform and SAP the company. 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